Bob Muglia, George Gilbert & Tristan Handy | How Supercloud will Support a new Class of Data Apps
(upbeat music) >> Hello, everybody. This is Dave Vellante. Welcome back to Supercloud2, where we're exploring the intersection of data analytics and the future of cloud. In this segment, we're going to look at how the Supercloud will support a new class of applications, not just work that runs on multiple clouds, but rather a new breed of apps that can orchestrate things in the real world. Think Uber for many types of businesses. These applications, they're not about codifying forms or business processes. They're about orchestrating people, places, and things in a business ecosystem. And I'm pleased to welcome my colleague and friend, George Gilbert, former Gartner Analyst, Wiki Bond market analyst, former equities analyst as my co-host. And we're thrilled to have Tristan Handy, who's the founder and CEO of DBT Labs and Bob Muglia, who's the former President of Microsoft's Enterprise business and former CEO of Snowflake. Welcome all, gentlemen. Thank you for coming on the program. >> Good to be here. >> Thanks for having us. >> Hey, look, I'm going to start actually with the SuperCloud because both Tristan and Bob, you've read the definition. Thank you for doing that. And Bob, you have some really good input, some thoughts on maybe some of the drawbacks and how we can advance this. So what are your thoughts in reading that definition around SuperCloud? >> Well, I thought first of all that you did a very good job of laying out all of the characteristics of it and helping to define it overall. But I do think it can be tightened a bit, and I think it's helpful to do it in as short a way as possible. And so in the last day I've spent a little time thinking about how to take it and write a crisp definition. And here's my go at it. This is one day old, so gimme a break if it's going to change. And of course we have to follow the industry, and so that, and whatever the industry decides, but let's give this a try. So in the way I think you're defining it, what I would say is a SuperCloud is a platform that provides programmatically consistent services hosted on heterogeneous cloud providers. >> Boom. Nice. Okay, great. I'm going to go back and read the script on that one and tighten that up a bit. Thank you for spending the time thinking about that. Tristan, would you add anything to that or what are your thoughts on the whole SuperCloud concept? >> So as I read through this, I fully realize that we need a word for this thing because I have experienced the inability to talk about it as well. But for many of us who have been living in the Confluence, Snowflake, you know, this world of like new infrastructure, this seems fairly uncontroversial. Like I read through this, and I'm just like, yeah, this is like the world I've been living in for years now. And I noticed that you called out Snowflake for being an example of this, but I think that there are like many folks, myself included, for whom this world like fully exists today. >> Yeah, I think that's a fair, I dunno if it's criticism, but people observe, well, what's the big deal here? It's just kind of what we're living in today. It reminds me of, you know, Tim Burns Lee saying, well, this is what the internet was supposed to be. It was supposed to be Web 2.0, so maybe this is what multi-cloud was supposed to be. Let's turn our attention to apps. Bob first and then go to Tristan. Bob, what are data apps to you? When people talk about data products, is that what they mean? Are we talking about something more, different? What are data apps to you? >> Well, to understand data apps, it's useful to contrast them to something, and I just use the simple term people apps. I know that's a little bit awkward, but it's clear. And almost everything we work with, almost every application that we're familiar with, be it email or Salesforce or any consumer app, those are applications that are targeted at responding to people. You know, in contrast, a data application reacts to changes in data and uses some set of analytic services to autonomously take action. So where applications that we're familiar with respond to people, data apps respond to changes in data. And they both do something, but they do it for different reasons. >> Got it. You know, George, you and I were talking about, you know, it comes back to SuperCloud, broad definition, narrow definition. Tristan, how do you see it? Do you see it the same way? Do you have a different take on data apps? >> Oh, geez. This is like a conversation that I don't know has an end. It's like been, I write a substack, and there's like this little community of people who all write substack. We argue with each other about these kinds of things. Like, you know, as many different takes on this question as you can find, but the way that I think about it is that data products are atomic units of functionality that are fundamentally data driven in nature. So a data product can be as simple as an interactive dashboard that is like actually had design thinking put into it and serves a particular user group and has like actually gone through kind of a product development life cycle. And then a data app or data application is a kind of cohesive end-to-end experience that often encompasses like many different data products. So from my perspective there, this is very, very related to the way that these things are produced, the kinds of experiences that they're provided, that like data innovates every product that we've been building in, you know, software engineering for, you know, as long as there have been computers. >> You know, Jamak Dagani oftentimes uses the, you know, she doesn't name Spotify, but I think it's Spotify as that kind of example she uses. But I wonder if we can maybe try to take some examples. If you take, like George, if you take a CRM system today, you're inputting leads, you got opportunities, it's driven by humans, they're really inputting the data, and then you got this system that kind of orchestrates the business process, like runs a forecast. But in this data driven future, are we talking about the app itself pulling data in and automatically looking at data from the transaction systems, the call center, the supply chain and then actually building a plan? George, is that how you see it? >> I go back to the example of Uber, may not be the most sophisticated data app that we build now, but it was like one of the first where you do have users interacting with their devices as riders trying to call a car or driver. But the app then looks at the location of all the drivers in proximity, and it matches a driver to a rider. It calculates an ETA to the rider. It calculates an ETA then to the destination, and it calculates a price. Those are all activities that are done sort of autonomously that don't require a human to type something into a form. The application is using changes in data to calculate an analytic product and then to operationalize that, to assign the driver to, you know, calculate a price. Those are, that's an example of what I would think of as a data app. And my question then I guess for Tristan is if we don't have all the pieces in place for sort of mainstream companies to build those sorts of apps easily yet, like how would we get started? What's the role of a semantic layer in making that easier for mainstream companies to build? And how do we get started, you know, say with metrics? How does that, how does that take us down that path? >> So what we've seen in the past, I dunno, decade or so, is that one of the most successful business models in infrastructure is taking hard things and rolling 'em up behind APIs. You take messaging, you take payments, and you all of a sudden increase the capability of kind of your median application developer. And you say, you know, previously you were spending all your time being focused on how do you accept credit cards, how do you send SMS payments, and now you can focus on your business logic, and just create the thing. One of, interestingly, one of the things that we still don't know how to API-ify is concepts that live inside of your data warehouse, inside of your data lake. These are core concepts that, you know, you would imagine that the business would be able to create applications around very easily, but in fact that's not the case. It's actually quite challenging to, and involves a lot of data engineering pipeline and all this work to make these available. And so if you really want to make it very easy to create some of these data experiences for users, you need to have an ability to describe these metrics and then to turn them into APIs to make them accessible to application developers who have literally no idea how they're calculated behind the scenes, and they don't need to. >> So how rich can that API layer grow if you start with metric definitions that you've defined? And DBT has, you know, the metric, the dimensions, the time grain, things like that, that's a well scoped sort of API that people can work within. How much can you extend that to say non-calculated business rules or governance information like data reliability rules, things like that, or even, you know, features for an AIML feature store. In other words, it starts, you started pragmatically, but how far can you grow? >> Bob is waiting with bated breath to answer this question. I'm, just really quickly, I think that we as a company and DBT as a product tend to be very pragmatic. We try to release the simplest possible version of a thing, get it out there, and see if people use it. But the idea that, the concept of a metric is really just a first landing pad. The really, there is a physical manifestation of the data and then there's a logical manifestation of the data. And what we're trying to do here is make it very easy to access the logical manifestation of the data, and metric is a way to look at that. Maybe an entity, a customer, a user is another way to look at that. And I'm sure that there will be more kind of logical structures as well. >> So, Bob, chime in on this. You know, what's your thoughts on the right architecture behind this, and how do we get there? >> Yeah, well first of all, I think one of the ways we get there is by what companies like DBT Labs and Tristan is doing, which is incrementally taking and building on the modern data stack and extending that to add a semantic layer that describes the data. Now the way I tend to think about this is a fairly major shift in the way we think about writing applications, which is today a code first approach to moving to a world that is model driven. And I think that's what the big change will be is that where today we think about data, we think about writing code, and we use that to produce APIs as Tristan said, which encapsulates those things together in some form of services that are useful for organizations. And that idea of that encapsulation is never going to go away. It's very, that concept of an API is incredibly useful and will exist well into the future. But what I think will happen is that in the next 10 years, we're going to move to a world where organizations are defining models first of their data, but then ultimately of their business process, their entire business process. Now the concept of a model driven world is a very old concept. I mean, I first started thinking about this and playing around with some early model driven tools, probably before Tristan was born in the early 1980s. And those tools didn't work because the semantics associated with executing the model were too complex to be written in anything other than a procedural language. We're now reaching a time where that is changing, and you see it everywhere. You see it first of all in the world of machine learning and machine learning models, which are taking over more and more of what applications are doing. And I think that's an incredibly important step. And learned models are an important part of what people will do. But if you look at the world today, I will claim that we've always been modeling. Modeling has existed in computers since there have been integrated circuits and any form of computers. But what we do is what I would call implicit modeling, which means that it's the model is written on a whiteboard. It's in a bunch of Slack messages. It's on a set of napkins in conversations that happen and during Zoom. That's where the model gets defined today. It's implicit. There is one in the system. It is hard coded inside application logic that exists across many applications with humans being the glue that connects those models together. And really there is no central place you can go to understand the full attributes of the business, all of the business rules, all of the business logic, the business data. That's going to change in the next 10 years. And we'll start to have a world where we can define models about what we're doing. Now in the short run, the most important models to build are data models and to describe all of the attributes of the data and their relationships. And that's work that DBT Labs is doing. A number of other companies are doing that. We're taking steps along that way with catalogs. People are trying to build more complete ontologies associated with that. The underlying infrastructure is still super, super nascent. But what I think we'll see is this infrastructure that exists today that's building learned models in the form of machine learning programs. You know, some of these incredible machine learning programs in foundation models like GPT and DALL-E and all of the things that are happening in these global scale models, but also all of that needs to get applied to the domains that are appropriate for a business. And I think we'll see the infrastructure developing for that, that can take this concept of learned models and put it together with more explicitly defined models. And this is where the concept of knowledge graphs come in and then the technology that underlies that to actually implement and execute that, which I believe are relational knowledge graphs. >> Oh, oh wow. There's a lot to unpack there. So let me ask the Colombo question, Tristan, we've been making fun of your youth. We're just, we're just jealous. Colombo, I'll explain it offline maybe. >> I watch Colombo. >> Okay. All right, good. So but today if you think about the application stack and the data stack, which is largely an analytics pipeline. They're separate. Do they, those worlds, do they have to come together in order to achieve Bob's vision? When I talk to practitioners about that, they're like, well, I don't want to complexify the application stack cause the data stack today is so, you know, hard to manage. But but do those worlds have to come together? And you know, through that model, I guess abstraction or translation that Bob was just describing, how do you guys think about that? Who wants to take that? >> I think it's inevitable that data and AI are going to become closer together? I think that the infrastructure there has been moving in that direction for a long time. Whether you want to use the Lakehouse portmanteau or not. There's also, there's a next generation of data tech that is still in the like early stage of being developed. There's a company that I love that is essentially Cross Cloud Lambda, and it's just a wonderful abstraction for computing. So I think that, you know, people have been predicting that these worlds are going to come together for awhile. A16Z wrote a great post on this back in I think 2020, predicting this, and I've been predicting this since since 2020. But what's not clear is the timeline, but I think that this is still just as inevitable as it's been. >> Who's that that does Cross Cloud? >> Let me follow up on. >> Who's that, Tristan, that does Cross Cloud Lambda? Can you name names? >> Oh, they're called Modal Labs. >> Modal Labs, yeah, of course. All right, go ahead, George. >> Let me ask about this vision of trying to put the semantics or the code that represents the business with the data. It gets us to a world that's sort of more data centric, where data's not locked inside or behind the APIs of different applications so that we don't have silos. But at the same time, Bob, I've heard you talk about building the semantics gradually on top of, into a knowledge graph that maybe grows out of a data catalog. And the vision of getting to that point, essentially the enterprise's metadata and then the semantics you're going to add onto it are really stored in something that's separate from the underlying operational and analytic data. So at the same time then why couldn't we gradually build semantics beyond the metric definitions that DBT has today? In other words, you build more and more of the semantics in some layer that DBT defines and that sits above the data management layer, but any requests for data have to go through the DBT layer. Is that a workable alternative? Or where, what type of limitations would you face? >> Well, I think that it is the way the world will evolve is to start with the modern data stack and, you know, which is operational applications going through a data pipeline into some form of data lake, data warehouse, the Lakehouse, whatever you want to call it. And then, you know, this wide variety of analytics services that are built together. To the point that Tristan made about machine learning and data coming together, you see that in every major data cloud provider. Snowflake certainly now supports Python and Java. Databricks is of course building their data warehouse. Certainly Google, Microsoft and Amazon are doing very, very similar things in terms of building complete solutions that bring together an analytics stack that typically supports languages like Python together with the data stack and the data warehouse. I mean, all of those things are going to evolve, and they're not going to go away because that infrastructure is relatively new. It's just being deployed by companies, and it solves the problem of working with petabytes of data if you need to work with petabytes of data, and nothing will do that for a long time. What's missing is a layer that understands and can model the semantics of all of this. And if you need to, if you want to model all, if you want to talk about all the semantics of even data, you need to think about all of the relationships. You need to think about how these things connect together. And unfortunately, there really is no platform today. None of our existing platforms are ultimately sufficient for this. It was interesting, I was just talking to a customer yesterday, you know, a large financial organization that is building out these semantic layers. They're further along than many companies are. And you know, I asked what they're building it on, and you know, it's not surprising they're using a, they're using combinations of some form of search together with, you know, textual based search together with a document oriented database. In this case it was Cosmos. And that really is kind of the state of the art right now. And yet those products were not built for this. They don't really, they can't manage the complicated relationships that are required. They can't issue the queries that are required. And so a new generation of database needs to be developed. And fortunately, you know, that is happening. The world is developing a new set of relational algorithms that will be able to work with hundreds of different relations. If you look at a SQL database like Snowflake or a big query, you know, you get tens of different joins coming together, and that query is going to take a really long time. Well, fortunately, technology is evolving, and it's possible with new join algorithms, worst case, optimal join algorithms they're called, where you can join hundreds of different relations together and run semantic queries that you simply couldn't run. Now that technology is nascent, but it's really important, and I think that will be a requirement to have this semantically reach its full potential. In the meantime, Tristan can do a lot of great things by building up on what he's got today and solve some problems that are very real. But in the long run I think we'll see a new set of databases to support these models. >> So Tristan, you got to respond to that, right? You got to, so take the example of Snowflake. We know it doesn't deal well with complex joins, but they're, they've got big aspirations. They're building an ecosystem to really solve some of these problems. Tristan, you guys are part of that ecosystem, and others, but please, your thoughts on what Bob just shared. >> Bob, I'm curious if, I would have no idea what you were talking about except that you introduced me to somebody who gave me a demo of a thing and do you not want to go there right now? >> No, I can talk about it. I mean, we can talk about it. Look, the company I've been working with is Relational AI, and they're doing this work to actually first of all work across the industry with academics and research, you know, across many, many different, over 20 different research institutions across the world to develop this new set of algorithms. They're all fully published, just like SQL, the underlying algorithms that are used by SQL databases are. If you look today, every single SQL database uses a similar set of relational algorithms underneath that. And those algorithms actually go back to system R and what IBM developed in the 1970s. We're just, there's an opportunity for us to build something new that allows you to take, for example, instead of taking data and grouping it together in tables, treat all data as individual relations, you know, a key and a set of values and then be able to perform purely relational operations on it. If you go back to what, to Codd, and what he wrote, he defined two things. He defined a relational calculus and relational algebra. And essentially SQL is a query language that is translated by the query processor into relational algebra. But however, the calculus of SQL is not even close to the full semantics of the relational mathematics. And it's possible to have systems that can do everything and that can store all of the attributes of the data model or ultimately the business model in a form that is much more natural to work with. >> So here's like my short answer to this. I think that we're dealing in different time scales. I think that there is actually a tremendous amount of work to do in the semantic layer using the kind of technology that we have on the ground today. And I think that there's, I don't know, let's say five years of like really solid work that there is to do for the entire industry, if not more. But the wonderful thing about DBT is that it's independent of what the compute substrate is beneath it. And so if we develop new platforms, new capabilities to describe semantic models in more fine grain detail, more procedural, then we're going to support that too. And so I'm excited about all of it. >> Yeah, so interpreting that short answer, you're basically saying, cause Bob was just kind of pointing to you as incremental, but you're saying, yeah, okay, we're applying it for incremental use cases today, but we can accommodate a much broader set of examples in the future. Is that correct, Tristan? >> I think you're using the word incremental as if it's not good, but I think that incremental is great. We have always been about applying incremental improvement on top of what exists today, but allowing practitioners to like use different workflows to actually make use of that technology. So yeah, yeah, we are a very incremental company. We're going to continue being that way. >> Well, I think Bob was using incremental as a pejorative. I mean, I, but to your point, a lot. >> No, I don't think so. I want to stop that. No, I don't think it's pejorative at all. I think incremental, incremental is usually the most successful path. >> Yes, of course. >> In my experience. >> We agree, we agree on that. >> Having tried many, many moonshot things in my Microsoft days, I can tell you that being incremental is a good thing. And I'm a very big believer that that's the way the world's going to go. I just think that there is a need for us to build something new and that ultimately that will be the solution. Now you can argue whether it's two years, three years, five years, or 10 years, but I'd be shocked if it didn't happen in 10 years. >> Yeah, so we all agree that incremental is less disruptive. Boom, but Tristan, you're, I think I'm inferring that you believe you have the architecture to accommodate Bob's vision, and then Bob, and I'm inferring from Bob's comments that maybe you don't think that's the case, but please. >> No, no, no. I think that, so Bob, let me put words into your mouth and you tell me if you disagree, DBT is completely useless in a world where a large scale cloud data warehouse doesn't exist. We were not able to bring the power of Python to our users until these platforms started supporting Python. Like DBT is a layer on top of large scale computing platforms. And to the extent that those platforms extend their functionality to bring more capabilities, we will also service those capabilities. >> Let me try and bridge the two. >> Yeah, yeah, so Bob, Bob, Bob, do you concur with what Tristan just said? >> Absolutely, I mean there's nothing to argue with in what Tristan just said. >> I wanted. >> And it's what he's doing. It'll continue to, I believe he'll continue to do it, and I think it's a very good thing for the industry. You know, I'm just simply saying that on top of that, I would like to provide Tristan and all of those who are following similar paths to him with a new type of database that can actually solve these problems in a much more architected way. And when I talk about Cosmos with something like Mongo or Cosmos together with Elastic, you're using Elastic as the join engine, okay. That's the purpose of it. It becomes a poor man's join engine. And I kind of go, I know there's a better answer than that. I know there is, but that's kind of where we are state of the art right now. >> George, we got to wrap it. So give us the last word here. Go ahead, George. >> Okay, I just, I think there's a way to tie together what Tristan and Bob are both talking about, and I want them to validate it, which is for five years we're going to be adding or some number of years more and more semantics to the operational and analytic data that we have, starting with metric definitions. My question is for Bob, as DBT accumulates more and more of those semantics for different enterprises, can that layer not run on top of a relational knowledge graph? And what would we lose by not having, by having the knowledge graph store sort of the joins, all the complex relationships among the data, but having the semantics in the DBT layer? >> Well, I think this, okay, I think first of all that DBT will be an environment where many of these semantics are defined. The question we're asking is how are they stored and how are they processed? And what I predict will happen is that over time, as companies like DBT begin to build more and more richness into their semantic layer, they will begin to experience challenges that customers want to run queries, they want to ask questions, they want to use this for things where the underlying infrastructure becomes an obstacle. I mean, this has happened in always in the history, right? I mean, you see major advances in computer science when the data model changes. And I think we're on the verge of a very significant change in the way data is stored and structured, or at least metadata is stored and structured. Again, I'm not saying that anytime in the next 10 years, SQL is going to go away. In fact, more SQL will be written in the future than has been written in the past. And those platforms will mature to become the engines, the slicer dicers of data. I mean that's what they are today. They're incredibly powerful at working with large amounts of data, and that infrastructure is maturing very rapidly. What is not maturing is the infrastructure to handle all of the metadata and the semantics that that requires. And that's where I say knowledge graphs are what I believe will be the solution to that. >> But Tristan, bring us home here. It sounds like, let me put pause at this, is that whatever happens in the future, we're going to leverage the vast system that has become cloud that we're talking about a supercloud, sort of where data lives irrespective of physical location. We're going to have to tap that data. It's not necessarily going to be in one place, but give us your final thoughts, please. >> 100% agree. I think that the data is going to live everywhere. It is the responsibility for both the metadata systems and the data processing engines themselves to make sure that we can join data across cloud providers, that we can join data across different physical regions and that we as practitioners are going to kind of start forgetting about details like that. And we're going to start thinking more about how we want to arrange our teams, how does the tooling that we use support our team structures? And that's when data mesh I think really starts to get very, very critical as a concept. >> Guys, great conversation. It was really awesome to have you. I can't thank you enough for spending time with us. Really appreciate it. >> Thanks a lot. >> All right. This is Dave Vellante for George Gilbert, John Furrier, and the entire Cube community. Keep it right there for more content. You're watching SuperCloud2. (upbeat music)
SUMMARY :
and the future of cloud. And Bob, you have some really and I think it's helpful to do it I'm going to go back and And I noticed that you is that what they mean? that we're familiar with, you know, it comes back to SuperCloud, is that data products are George, is that how you see it? that don't require a human to is that one of the most And DBT has, you know, the And I'm sure that there will be more on the right architecture is that in the next 10 years, So let me ask the Colombo and the data stack, which is that is still in the like Modal Labs, yeah, of course. and that sits above the and that query is going to So Tristan, you got to and that can store all of the that there is to do for the pointing to you as incremental, but allowing practitioners to I mean, I, but to your point, a lot. the most successful path. that that's the way the that you believe you have the architecture and you tell me if you disagree, there's nothing to argue with And I kind of go, I know there's George, we got to wrap it. and more of those semantics and the semantics that that requires. is that whatever happens in the future, and that we as practitioners I can't thank you enough John Furrier, and the
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Breaking Analysis: Snowflake caught in the storm clouds
>> 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. >> A better than expected earnings report in late August got people excited about Snowflake again, but the negative sentiment in the market is weighed heavily on virtually all growth tech stocks and Snowflake is no exception. As we've stressed many times the company's management is on a long term mission to dramatically simplify the way organizations use data. Snowflake is tapping into a multi hundred billion dollar total available market and continues to grow at a rapid pace. In our view, Snowflake is embarking on its third major wave of innovation data apps, while its first and second waves are still bearing significant fruit. Now for short term traders focused on the next 90 or 180 days, that probably doesn't matter. But those taking a longer view are asking, "Should we still be optimistic about the future of this high flyer or is it just another over hyped tech play?" Hello and welcome to this week's Wiki Bond Cube Insights powered by ETR. Snowflake's Quarter just ended. And in this breaking analysis we take a look at the most recent survey data from ETR to see what clues and nuggets we can extract to predict the near term future in the long term outlook for Snowflake which is going to announce its earnings at the end of this month. Okay, so you know the story. If you've been investor in Snowflake this year, it's been painful. We said at IPO, "If you really want to own this stock on day one, just hold your nose and buy it." But like most IPOs we said there will be likely a better entry point in the future, and not surprisingly that's been the case. Snowflake IPOed a price of 120, which you couldn't touch on day one unless you got into a friends and family Delio. And if you did, you're still up 5% or so. So congratulations. But at one point last year you were up well over 200%. That's been the nature of this volatile stock, and I certainly can't help you with the timing of the market. But longer term Snowflake is targeting 10 billion in revenue for fiscal year 2028. A big number. Is it achievable? Is it big enough? Tell you what, let's come back to that. Now shorter term, our expert trader and breaking analysis contributor Chip Simonton said he got out of the stock a while ago after having taken a shot at what turned out to be a bear market rally. He pointed out that the stock had been bouncing around the 150 level for the last few months and broke that to the downside last Friday. So he'd expect 150 is where the stock is going to find resistance on the way back up, but there's no sign of support right now. He said maybe at 120, which was the July low and of course the IPO price that we just talked about. Now, perhaps earnings will be a catalyst, when Snowflake announces on November 30th, but until the mentality toward growth tech changes, nothing's likely to change dramatically according to Simonton. So now that we have that out of the way, let's take a look at the spending data for Snowflake in the ETR survey. Here's a chart that shows the time series breakdown of snowflake's net score going back to the October, 2021 survey. Now at that time, Snowflake's net score stood at a robust 77%. And remember, net score is a measure of spending velocity. It's a proprietary network, and ETR derives it from a quarterly survey of IT buyers and asks the respondents, "Are you adopting the platform new? Are you spending 6% or more? Is you're spending flat? Is you're spending down 6% or worse? Or are you leaving the platform decommissioning?" You subtract the percent of customers that are spending less or churning from those that are spending more and adopting or adopting and you get a net score. And that's expressed as a percentage of customers responding. In this chart we show Snowflake's in out of the total survey which ranges... The total survey ranges between 1,200 and 1,400 each quarter. And the very last column... Oh sorry, very last row, we show the number of Snowflake respondents that are coming in the survey from the Fortune 500 and the Global 2000. Those are two very important Snowflake constituencies. Now what this data tells us is that Snowflake exited 2021 with very strong momentum in a net score of 82%, which is off the charts and it was actually accelerating from the previous survey. Now by April that sentiment had flipped and Snowflake came down to earth with a 68% net score. Still highly elevated relative to its peers, but meaningfully down. Why was that? Because we saw a drop in new ads and an increase in flat spend. Then into the July and most recent October surveys, you saw a significant drop in the percentage of customers that were spending more. Now, notably, the percentage of customers who are contemplating adding the platform is actually staying pretty strong, but it is off a bit this past survey. And combined with a slight uptick in planned churn, net score is now down to 60%. That uptick from 0% and 1% and then 3%, it's still small, but that net score at 60% is still 20 percentage points higher than our highly elevated benchmark of 40% as you recall from listening to earlier breaking analysis. That 40% range is we consider a milestone. Anything above that is actually quite strong. But again, Snowflake is down and coming back to churn, while 3% churn is very low, in previous quarters we've seen Snowflake 0% or 1% decommissions. Now the last thing to note in this chart is the meaningful uptick in survey respondents that are citing, they're using the Snowflake platform. That's up to 212 in the survey. So look, it's hard to imagine that Snowflake doesn't feel the softening in the market like everyone else. Snowflake is guiding for around 60% growth in product revenue against the tough compare from a year ago with a 2% operating margin. So like every company, the reaction of the street is going to come down to how accurate or conservative the guide is from their CFO. Now, earlier this year, Snowflake acquired a company called Streamlit for around $800 million. Streamlit is an open source Python library and it makes it easier to build data apps with machine learning, obviously a huge trend. And like Snowflake, generally its focus is on simplifying the complex, in this case making data science easier to integrate into data apps that business people can use. So we were excited this summer in the July ETR survey to see that they added some nice data and pick on Streamlit, which we're showing here in comparison to Snowflake's core business on the left hand side. That's the data warehousing, the Streamlit pieces on the right hand side. And we show again net score over time from the previous survey for Snowflake's core database and data warehouse offering again on the left as compared to a Streamlit on the right. Snowflake's core product had 194 responses in the October, 22 survey, Streamlit had an end of 73, which is up from 52 in the July survey. So significant uptick of people responding that they're doing business in adopting Streamlit. That was pretty impressive to us. And it's hard to see, but the net scores stayed pretty constant for Streamlit at 51%. It was 52% I think in the previous quarter, well over that magic 40% mark. But when you blend it with Snowflake, it does sort of bring things down a little bit. Now there are two key points here. One is that the acquisition seems to have gained exposure right out of the gate as evidenced by the large number of responses. And two, the spending momentum. Again while it's lower than Snowflake overall, and when you blend it with Snowflake it does pull it down, it's very healthy and steady. Now let's do a little pure comparison with some of our favorite names in this space. This chart shows net score or spending velocity in the Y-axis, an overlap or presence, pervasiveness if you will, in the data set on the X-axis. That red dotted line again is that 40% highly elevated net score that we like to talk about. And that table inserted informs us as to how the companies are plotted, where the dots set up, the net score, the ins. And we're comparing a number of database players, although just a caution, Oracle includes all of Oracle including its apps. But we just put it in there for reference because it is the leader in database. Right off the bat, Snowflake jumps out with a net score of 64%. The 60% from the earlier chart, again included Streamlit. So you can see its core database, data warehouse business actually is higher than the total company average that we showed you before 'cause the Streamlit is blended in. So when you separate it out, Streamlit is right on top of data bricks. Isn't that ironic? Only Snowflake and Databricks in this selection of names are above the 40% level. You see Mongo and Couchbase, they know they're solid and Teradata cloud actually showing pretty well compared to some of the earlier survey results. Now let's isolate on the database data platform sector and see how that shapes up. And for this analysis, same XY dimensions, we've added the big giants, AWS and Microsoft and Google. And notice that those three plus Snowflake are just at or above the 40% line. Snowflake continues to lead by a significant margin in spending momentum and it keeps creeping to the right. That's that end that we talked about earlier. Now here's an interesting tidbit. Snowflake is often asked, and I've asked them myself many times, "How are you faring relative to AWS, Microsoft and Google, these big whales with Redshift and Synapse and Big Query?" And Snowflake has been telling folks that 80% of its business comes from AWS. And when Microsoft heard that, they said, "Whoa, wait a minute, Snowflake, let's partner up." 'Cause Microsoft is smart, and they understand that the market is enormous. And if they could do better with Snowflake, one, they may steal some business from AWS. And two, even if Snowflake is winning against some of the Microsoft database products, if it wins on Azure, Microsoft is going to sell more compute and more storage, more AI tools, more other stuff to these customers. Now AWS is really aggressive from a partnering standpoint with Snowflake. They're openly negotiating, not openly, but they're negotiating better prices. They're realizing that when it comes to data, the cheaper that you make the offering, the more people are going to consume. At scale economies and operating leverage are really powerful things at volume that kick in. Now Microsoft, they're coming along, they obviously get it, but Google is seemingly resistant to that type of go to market partnership. Rather than lean into Snowflake as a great partner Google's field force is kind of fighting fashion. Google itself at Cloud next heavily messaged what they call the open data cloud, which is a direct rip off of Snowflake. So what can we say about Google? They continue to be kind of behind the curve when it comes to go to market. Now just a brief aside on the competitive posture. I've seen Slootman, Frank Slootman, CEO of Snowflake in action with his prior companies and how he depositioned the competition. At Data Domain, he eviscerated a company called Avamar with their, what he called their expensive and slow post process architecture. I think he actually called it garbage, if I recall at one conference I heard him speak at. And that sort of destroyed BMC when he was at ServiceNow, kind of positioning them as the equivalent of the department of motor vehicles. And so it's interesting to hear how Snowflake openly talks about the data platforms of AWS, Microsoft, Google, and data bricks. I'll give you this sort of short bumper sticker. Redshift is just an on-prem database that AWS morphed to the cloud, which by the way is kind of true. They actually did a brilliant job of it, but it's basically a fact. Microsoft Excel, a collection of legacy databases, which also kind of morphed to run in the cloud. And even Big Query, which is considered cloud native by many if not most, is being positioned by Snowflake as originally an on-prem database to support Google's ad business, maybe. And data bricks is for those people smart enough to get it to Berkeley that love complexity. And now Snowflake doesn't, they don't mention Berkeley as far as I know. That's my addition. But you get the point. And the interesting thing about Databricks and Snowflake is a while ago in the cube I said that there was a new workload type emerging around data where you have AWS cloud, Snowflake obviously for the cloud database and Databricks data for the data science and EML, you bring those things together and there's this new workload emerging that's going to be very powerful in the future. And it's interesting to see now the aspirations of all three of these platforms are colliding. That's quite a dynamic, especially when you see both Snowflake and Databricks putting venture money and getting their hooks into the loyalties of the same companies like DBT labs and Calibra. Anyway, Snowflake's posture is that we are the pioneer in cloud native data warehouse, data sharing and now data apps. And our platform is designed for business people that want simplicity. The other guys, yes, they're formidable, but we Snowflake have an architectural lead and of course we run in multiple clouds. So it's pretty strong positioning or depositioning, you have to admit. Now I'm not sure I agree with the big query knockoffs completely. I think that's a bit of a stretch, but snowflake, as we see in the ETR survey data is winning. So in thinking about the longer term future, let's talk about what's different with Snowflake, where it's headed and what the opportunities are for the company. Snowflake put itself on the map by focusing on simplifying data analytics. What's interesting about that is the company's founders are as you probably know from Oracle. And rather than focusing on transactional data, which is Oracle's sweet spot, the stuff they worked on when they were at Oracle, the founder said, "We're going to go somewhere else. We're going to attack the data warehousing problem and the data analytics problem." And they completely re-imagined the database and how it could be applied to solve those challenges and reimagine what was possible if you had virtually unlimited compute and storage capacity. And of course Snowflake became famous for separating the compute from storage and being able to completely shut down compute so you didn't have to pay for it when you're not using it. And the ability to have multiple clusters hit the same data without making endless copies and a consumption/cloud pricing model. And then of course everyone on the planet realized, "Wow, that's a pretty good idea." Every venture capitalist in Silicon Valley has been funding companies to copy that move. And that today has pretty much become mainstream in table stakes. But I would argue that Snowflake not only had the lead, but when you look at how others are approaching this problem, it's not necessarily as clean and as elegant. Some of the startups, the early startups I think get it and maybe had an advantage of starting later, which can be a disadvantage too. But AWS is a good example of what I'm saying here. Is its version of separating compute from storage was an afterthought and it's good, it's... Given what they had it was actually quite clever and customers like it, but it's more of a, "Okay, we're going to tier to storage to lower cost, we're going to sort of dial down the compute not completely, we're not going to shut it off, we're going to minimize the compute required." It's really not true as separation is like for instance Snowflake has. But having said that, we're talking about competitors with lots of resources and cohort offerings. And so I don't want to make this necessarily all about the product, but all things being equal architecture matters, okay? So that's the cloud S-curve, the first one we're showing. Snowflake's still on that S-curve, and in and of itself it's got legs, but it's not what's going to power the company to 10 billion. The next S-curve we denote is the multi-cloud in the middle. And now while 80% of Snowflake's revenue is AWS, Microsoft is ramping up and Google, well, we'll see. But the interesting part of that curve is data sharing, and this idea of data clean rooms. I mean it really should be called the data sharing curve, but I have my reasons for calling it multi-cloud. And this is all about network effects and data gravity, and you're seeing this play out today, especially in industries like financial services and healthcare and government that are highly regulated verticals where folks are super paranoid about compliance. There not going to share data if they're going to get sued for it, if they're going to be in the front page of the Wall Street Journal for some kind of privacy breach. And what Snowflake has done is said, "Put all the data in our cloud." Now, of course now that triggers a lot of people because it's a walled garden, okay? It is. That's the trade off. It's not the Wild West, it's not Windows, it's Mac, it's more controlled. But the idea is that as different parts of the organization or even partners begin to share data that they need, it's got to be governed, it's got to be secure, it's got to be compliant, it's got to be trusted. So Snowflake introduced the idea of, they call these things stable edges. I think that's the term that they use. And they track a metric around stable edges. And so a stable edge, or think of it as a persistent edge is an ongoing relationship between two parties that last for some period of time, more than a month. It's not just a one shot deal, one a done type of, "Oh guys shared it for a day, done." It sent you an FTP, it's done. No, it's got to have trajectory over time. Four weeks or six weeks or some period of time that's meaningful. And that metric is growing. Now I think sort of a different metric that they track. I think around 20% of Snowflake customers are actively sharing data today and then they track the number of those edge relationships that exist. So that's something that's unique. Because again, most data sharing is all about making copies of data. That's great for storage companies, it's bad for auditors, and it's bad for compliance officers. And that trend is just starting out, that middle S-curve, it's going to kind of hit the base of that steep part of the S-curve and it's going to have legs through this decade we think. And then finally the third wave that we show here is what we call super cloud. That's why I called it multi-cloud before, so it could invoke super cloud. The idea that you've built a PAS layer that is purpose built for a specific objective, and in this case it's building data apps that are cloud native, shareable and governed. And is a long-term trend that's going to take some time to develop. I mean, application development platforms can take five to 10 years to mature and gain significant adoption, but this one's unique. This is a critical play for Snowflake. If it's going to compete with the big cloud players, it has to have an app development framework like Snowpark. It has to accommodate new data types like transactional data. That's why it announced this thing called UniStore last June, Snowflake a summit. And the pattern that's forming here is Snowflake is building layer upon layer with its architecture at the core. It's not currently anyway, it's not going out and saying, "All right, we're going to buy a company that's got to another billion dollars in revenue and that's how we're going to get to 10 billion." So it's not buying its way into new markets through revenue. It's actually buying smaller companies that can complement Snowflake and that it can turn into revenue for growth that fit in to the data cloud. Now as to the 10 billion by fiscal year 28, is that achievable? That's the question. Yeah, I think so. Would the momentum resources go to market product and management prowess that Snowflake has? Yes, it's definitely achievable. And one could argue to $10 billion is too conservative. Indeed, Snowflake CFO, Mike Scarpelli will fully admit his forecaster built on existing offerings. He's not including revenue as I understand it from all the new stuff that's in the pipeline because he doesn't know what it's going to look like. He doesn't know what the adoption is going to look like. He doesn't have data on that adoption, not just yet anyway. And now of course things can change quite dramatically. It's possible that is forecast for existing businesses don't materialize or competition picks them off or a company like Databricks actually is able in the longer term replicate the functionality of Snowflake with open source technologies, which would be a very competitive source of innovation. But in our view, there's plenty of room for growth, the market is enormous and the real key is, can and will Snowflake deliver on the promises of simplifying data? Of course we've heard this before from data warehouse, the data mars and data legs and master data management and ETLs and data movers and data copiers and Hadoop and a raft of technologies that have not lived up to expectations. And we've also, by the way, seen some tremendous successes in the software business with the likes of ServiceNow and Salesforce. So will Snowflake be the next great software name and hit that 10 billion magic mark? I think so. Let's reconnect in 2028 and see. Okay, we'll leave it there today. I want to thank Chip Simonton for his input to today's episode. Thanks to Alex Myerson who's on production and manages the podcast. Ken Schiffman as well. Kristin Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hove is our Editor in Chief over at Silicon Angle. He does some great editing for us. Check it out for all the news. Remember all these episodes are available as podcasts. Wherever you listen, just search Breaking Analysis podcast. I publish each week on wikibon.com and siliconangle.com. Or you can email me to get in touch David.vallante@siliconangle.com. DM me @dvellante or comment on our LinkedIn post. And please do check out etr.ai, they've got the best survey data in the enterprise tech business. This is Dave Vellante for the CUBE Insights, powered by ETR. Thanks for watching, thanks for listening and we'll see you next time on breaking analysis. (upbeat music)
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Breaking Analysis: Even the Cloud Is Not Immune to the Seesaw Economy
>>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 Ante. >>Have you ever been driving on the highway and traffic suddenly slows way down and then after a little while it picks up again and you're cruising along and you're thinking, Okay, hey, that was weird. But it's clear sailing now. Off we go, only to find out in a bit that the traffic is building up ahead again, forcing you to pump the brakes as the traffic pattern ebbs and flows well. Welcome to the Seesaw economy. The fed induced fire that prompted an unprecedented rally in tech is being purposefully extinguished now by that same fed. And virtually every sector of the tech industry is having to reset its expectations, including the cloud segment. Hello and welcome to this week's Wikibon Cube Insights powered by etr. In this breaking analysis will review the implications of the earnings announcements from the big three cloud players, Amazon, Microsoft, and Google who announced this week. >>And we'll update you on our quarterly IAS forecast and share the latest from ETR with a focus on cloud computing. Now, before we get into the new data, we wanna review something we shared with you on October 14th, just a couple weeks back, this is sort of a, we told you it was coming slide. It's an XY graph that shows ET R'S proprietary net score methodology on the vertical axis. That's a measure of spending momentum, spending velocity, and an overlap or presence in the dataset that's on the X axis. That's really a measure of pervasiveness. In the survey, the table, you see that table insert there that shows Wiki Bond's Q2 estimates of IAS revenue for the big four hyperscalers with their year on year growth rates. Now we told you at the time, this is data from the July TW 22 ETR survey and the ETR hadn't released its October survey results at that time. >>This was just a couple weeks ago. And while we couldn't share the specific data from the October survey, we were able to get a glimpse and we depicted the slowdown that we saw in the October data with those dotted arrows kind of down into the right, we said at the time that we were seeing and across the board slowdown even for the big three cloud vendors. Now, fast forward to this past week and we saw earnings releases from Alphabet, Microsoft, and just last night Amazon. Now you may be thinking, okay, big deal. The ETR survey data didn't really tell us anything we didn't already know. But judging from the negative reaction in the stock market to these earnings announcements, the degree of softness surprised a lot of investors. Now, at the time we didn't update our forecast, it doesn't make sense for us to do that when we're that close to earning season. >>And now that all the big three ha with all the big four with the exception of Alibaba have announced we've, we've updated. And so here's that data. This chart lays out our view of the IS and PAs worldwide revenue. Basically it's cloud infrastructure with an attempt to exclude any SaaS revenue so we can make an apples to apples comparison across all the clouds. Now the reason that actual is in quotes is because Microsoft and Google don't report IAS revenue, but they do give us clues and kind of directional commentary, which we then triangulate with other data that we have from the channel and ETR surveys and just our own intelligence. Now the second column there after the vendor name shows our previous estimates for q3, and then next to that we show our actuals. Same with the growth rates. And then we round out the chart with that lighter blue color highlights, the full year estimates for revenue and growth. >>So the key takeaways are that we shaved about $4 billion in revenue and roughly 300 basis points of growth off of our full year estimates. AWS had a strong July but exited Q3 in the mid 20% growth rate year over year. So we're using that guidance, you know, for our Q4 estimates. Azure came in below our earlier estimates, but Google actually exceeded our expectations. Now the compression in the numbers is in our view of function of the macro demand climate, we've made every attempt to adjust for constant currency. So FX should not be a factor in this data, but it's sure you know that that ma the the, the currency effects are weighing on those companies income statements. And so look, this is the fundamental dynamic of a cloud model where you can dial down consumption when you need to and dial it up when you need to. >>Now you may be thinking that many big cloud customers have a committed level of spending in order to get better discounts. And that's true. But what's happening we think is they'll reallocate that spend toward, let's say for example, lower cost storage tiers or they may take advantage of better price performance processors like Graviton for example. That is a clear trend that we're seeing and smaller companies that were perhaps paying by the drink just on demand, they're moving to reserve instance models to lower their monthly bill. So instead of taking the easy way out and just spending more companies are reallocating their reserve capacity toward lower cost. So those sort of lower cost services, so they're spending time and effort optimizing to get more for, for less whereas, or get more for the same is really how we should, should, should phrase it. Whereas during the pandemic, many companies were, you know, they perhaps were not as focused on doing that because business was booming and they had a response. >>So they just, you know, spend more dial it up. So in general, as they say, customers are are doing more with, with the same. Now let's look at the growth dynamic and spend some time on that. I think this is important. This data shows worldwide quarterly revenue growth rates back to Q1 2019 for the big four. So a couple of interesting things. The data tells us during the pandemic, you saw both AWS and Azure, but the law of large numbers and actually accelerate growth. AWS especially saw progressively increasing growth rates throughout 2021 for each quarter. Now that trend, as you can see is reversed in 2022 for aws. Now we saw Azure come down a bit, but it's still in the low forties in terms of percentage growth. While Google actually saw an uptick in growth this last quarter for GCP by our estimates as GCP is becoming an increasingly large portion of Google's overall cloud business. >>Now, unfortunately Google Cloud continues to lose north of 850 million per quarter, whereas AWS and Azure are profitable cloud businesses even though Alibaba is suffering its woes from China. And we'll see how they come in when they report in mid-November. The overall hyperscale market grew at 32% in Q3 in terms of worldwide revenue. So the slowdown isn't due to the repatriation or competition from on-prem vendors in our view, it's a macro related trend. And cloud will continue to significantly outperform other sectors despite its massive size. You know, on the repatriation point, it just still doesn't show up in the data. The A 16 Z article from Sarah Wong and Martin Martin Kasa claiming that repatriation was inevitable as a means to lower cost of good sold for SaaS companies. You know, while that was thought provoking, it hasn't shown up in the numbers. And if you read the financial statements of both AWS and its partners like Snowflake and you dig into the, to the, to the quarterly reports, you'll see little notes and comments with their ongoing negotiations to lower cloud costs for customers. >>AWS and no doubt execs at Azure and GCP understand that the lifetime value of a customer is worth much more than near term gross margin. And you can expect the cloud vendors to strike a balance between profitability, near term profitability anyway and customer attention. Now, even though Google Cloud platform saw accelerated growth, we need to put that in context for you. So GCP, by our estimate, has now crossed over the $3 billion for quarter market actually did so last quarter, but its growth rate accelerated to 42% this quarter. And so that's a good sign in our view. But let's do a quick little comparison with when AWS and Azure crossed the $3 billion mark and compare their growth rates at the time. So if you go back to to Q2 2016, as we're showing in this chart, that's around the time that AWS hit 3 billion per quarter and at the same time was growing at 58%. >>Azure by our estimates crossed that mark in Q4 2018 and at that time was growing at 67%. Again, compare that to Google's 42%. So one would expect Google's growth rate would be higher than its competitors at this point in the MO in the maturity of its cloud, which it's, you know, it's really not when you compared to to Azure. I mean they're kind of con, you know, comparable now but today, but, but you'll go back, you know, to that $3 billion mark. But more so looking at history, you'd like to see its growth rate at this point of a maturity model at least over 50%, which we don't believe it is. And one other point on this topic, you know, my business friend Matt Baker from Dell often says it's not a zero sum game, meaning there's plenty of opportunity exists to build value on top of hyperscalers. >>And I would totally agree it's not a dollar for dollar swap if you can continue to innovate. But history will show that the first company in makes the most money. Number two can do really well and number three tends to break even. Now maybe cloud is different because you have Microsoft software estate and the power behind that and that's driving its IAS business and Google ads are funding technology buildouts for, for for Google and gcp. So you know, we'll see how that plays out. But right now by this one measurement, Google is four years behind Microsoft in six years behind aws. Now to the point that cloud will continue to outpace other markets, let's, let's break this down a bit in spending terms and see why this claim holds water. This is data from ET r's latest October survey that shows the granularity of its net score or spending velocity metric. >>The lime green is new adoptions, so they're adding the platform, the forest green is spending more 6% or more. The gray bars spending is flat plus or minus, you know, 5%. The pinkish colors represent spending less down 6% or worse. And the bright red shows defections or churn of the platform. You subtract the reds from the greens and you get what's called net score, which is that blue dot that you can see on each of the bars. So what you see in the table insert is that all three have net scores above 40%, which is a highly elevated measure. Microsoft's net scores above 60% AWS well into the fifties and GCP in the mid forties. So all good. Now what's happening with all three is more customers are keep keeping their spending flat. So a higher percentage of customers are saying, our spending is now flat than it was in previous quarters and that's what's accounting for the compression. >>But the churn of all three, even gcp, which we reported, you know, last quarter from last quarter survey was was five x. The other two is actually very low in the single digits. So that might have been an anomaly. So that's a very good sign in our view. You know, again, customers aren't repatriating in droves, it's just not a trend that we would bet on, maybe makes for a FUD or you know, good marketing head, but it's just not a big deal. And you can't help but be impressed with both Microsoft and AWS's performance in the survey. And as we mentioned before, these companies aren't going to give up customers to try and preserve a little bit of gross margin. They'll do what it takes to keep people on their platforms cuz they'll make up for it over time with added services and improved offerings. >>Now, once these companies acquire a customer, they'll be very aggressive about keeping them. So customers take note, you have negotiating leverage, so use it. Okay, let's look at another cut at the cloud market from the ETR data set. Here's the two dimensional view, again, it's back, it's one of our favorites. Net score or spending momentum plotted against presence. And the data set, that's the x axis net score on the, on the vertical axis, this is a view of et r's cloud computing sector sector. You can see we put that magic 40% dotted red line in the table showing and, and then that the table inserts shows how the data are plotted with net score against presence. I e n in the survey, notably only the big three are above the 40% line of the names that we're showing here. The oth there, there are others. >>I mean if you put Snowflake on there, it'd be higher than any of these names, but we'll dig into that name in a later breaking analysis episode. Now this is just another way of quantifying the dominance of AWS and Azure, not only relative to Google, but the other cloud platforms out there. So we've, we've taken the opportunity here to plot IBM and Oracle, which both own a public cloud. Their performance is largely a reflection of them migrating their install bases to their respective public clouds and or hybrid clouds. And you know, that's fine, they're in the game. That's a point that we've made, you know, a number of times they're able to make it through the cloud, not whole and they at least have one, but they simply don't have the business momentum of AWS and Azure, which is actually quite impressive because AWS and Azure are now as large or larger than IBM and Oracle. >>And to show this type of continued growth that that that Azure and AWS show at their size is quite remarkable and customers are starting to recognize the viability of on-prem hi, you know, hybrid clouds like HPE GreenLake and Dell's apex. You know, you may say, well that's not cloud, but if the customer thinks it is and it was reporting in the survey that it is, we're gonna continue to report this view. You know, I don't know what's happening with H P E, They had a big down tick this quarter and I, and I don't read too much into that because their end is still pretty small at 53. So big fluctuations are not uncommon with those types of smaller ends, but it's over 50. So, you know, we did notice a a a negative within a giant public and private sector, which is often a, a bellwether giant public private is big public companies and large private companies like, like a Mars for example. >>So it, you know, it looks like for HPE it could be an outlier. We saw within the Fortune 1000 HPE E'S cloud looked actually really good and it had good spending momentum in that sector. When you di dig into the industry data within ETR dataset, obviously we're not showing that here, but we'll continue to monitor that. Okay, so where's this Leave us. Well look, this is really a tactical story of currency and macro headwinds as you can see. You know, we've laid out some of the points on this slide. The action in the stock market today, which is Friday after some of the soft earnings reports is really robust. You know, we'll see how it ends up in the day. So maybe this is a sign that the worst is over, but we don't think so. The visibility from tech companies is murky right now as most are guiding down, which indicates that their conservative outlook last quarter was still too optimistic. >>But as it relates to cloud, that platform is not going anywhere anytime soon. Sure, there are potential disruptors on the horizon, especially at the edge, but we're still a long ways off from, from the possibility that a new economic model emerges from the edge to disrupt the cloud and the opportunities in the cloud remain strong. I mean, what other path is there? Really private cloud. It was kind of a bandaid until the on-prem guys could get their a as a service models rolled out, which is just now happening. The hybrid thing is real, but it's, you know, defensive for the incumbents until they can get their super cloud investments going. Super cloud implying, capturing value above the hyperscaler CapEx, you know, call it what you want multi what multi-cloud should have been, the metacloud, the Uber cloud, whatever you like. But there are opportunities to play offense and that's clearly happening in the cloud ecosystem with the likes of Snowflake, Mongo, Hashi Corp. >>Hammer Spaces is a startup in this area. Aviatrix, CrowdStrike, Zeke Scaler, Okta, many, many more. And even the projects we see coming out of enterprise players like Dell, like with Project Alpine and what Pure Storage is doing along with a number of other of the backup vendors. So Q4 should be really interesting, but the real story is the investments that that companies are making now to leverage the cloud for digital transformations will be paying off down the road. This is not 1999. We had, you know, May might have had some good ideas and admittedly at a lot of bad ones too, but you didn't have the infrastructure to service customers at a low enough cost like you do today. The cloud is that infrastructure and so far it's been transformative, but it's likely the best is yet to come. Okay, let's call this a rap. >>Many thanks to Alex Morrison who does production and manages the podcast. Also Can Schiffman is our newest edition to the Boston Studio. Kristin Martin and Cheryl Knight helped get the word out on social media and in our newsletters. And Rob Ho is our editor in chief over@siliconangle.com, who does some wonderful editing for us. Thank you. Remember, all these episodes are available as podcasts. Wherever you listen, just search breaking analysis podcast. I publish each week on wiki bond.com at silicon angle.com. And you can email me at David dot valante@siliconangle.com or DM me at Dante or comment on my LinkedIn posts. And please do checkout etr.ai. They got the best survey data in the enterprise tech business. This is Dave Valante for the Cube Insights powered by etr. Thanks for watching and we'll see you next time on breaking analysis.
SUMMARY :
From the Cube Studios in Palo Alto in Boston, bringing you data driven insights from Have you ever been driving on the highway and traffic suddenly slows way down and then after In the survey, the table, you see that table insert there that Now, at the time we didn't update our forecast, it doesn't make sense for us And now that all the big three ha with all the big four with the exception of Alibaba have announced So we're using that guidance, you know, for our Q4 estimates. Whereas during the pandemic, many companies were, you know, they perhaps were not as focused So they just, you know, spend more dial it up. So the slowdown isn't due to the repatriation or And you can expect the cloud And one other point on this topic, you know, my business friend Matt Baker from Dell often says it's not a And I would totally agree it's not a dollar for dollar swap if you can continue to So what you see in the table insert is that all three have net scores But the churn of all three, even gcp, which we reported, you know, And the data set, that's the x axis net score on the, That's a point that we've made, you know, a number of times they're able to make it through the cloud, the viability of on-prem hi, you know, hybrid clouds like HPE GreenLake and Dell's So it, you know, it looks like for HPE it could be an outlier. off from, from the possibility that a new economic model emerges from the edge to And even the projects we see coming out of enterprise And you can email me at David dot valante@siliconangle.com or DM me at Dante
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Oracle Announces MySQL HeatWave on AWS
>>Oracle continues to enhance my sequel Heatwave at a very rapid pace. The company is now in its fourth major release since the original announcement in December 2020. 1 of the main criticisms of my sequel, Heatwave, is that it only runs on O. C I. Oracle Cloud Infrastructure and as a lock in to Oracle's Cloud. Oracle recently announced that heat wave is now going to be available in AWS Cloud and it announced its intent to bring my sequel Heatwave to Azure. So my secret heatwave on AWS is a significant TAM expansion move for Oracle because of the momentum AWS Cloud continues to show. And evidently the Heatwave Engineering team has taken the development effort from O. C I. And is bringing that to A W S with a number of enhancements that we're gonna dig into today is senior vice president. My sequel Heatwave at Oracle is back with me on a cube conversation to discuss the latest heatwave news, and we're eager to hear any benchmarks relative to a W S or any others. Nippon has been leading the Heatwave engineering team for over 10 years and there's over 100 and 85 patents and database technology. Welcome back to the show and good to see you. >>Thank you. Very happy to be back. >>Now for those who might not have kept up with the news, uh, to kick things off, give us an overview of my sequel, Heatwave and its evolution. So far, >>so my sequel, Heat Wave, is a fully managed my secret database service offering from Oracle. Traditionally, my secret has been designed and optimised for transaction processing. So customers of my sequel then they had to run analytics or when they had to run machine learning, they would extract the data out of my sequel into some other database for doing. Unlike processing or machine learning processing my sequel, Heat provides all these capabilities built in to a single database service, which is my sequel. He'd fake So customers of my sequel don't need to move the data out with the same database. They can run transaction processing and predicts mixed workloads, machine learning, all with a very, very good performance in very good price performance. Furthermore, one of the design points of heat wave is is a scale out architecture, so the system continues to scale and performed very well, even when customers have very large late assignments. >>So we've seen some interesting moves by Oracle lately. The collaboration with Azure we've we've covered that pretty extensively. What was the impetus here for bringing my sequel Heatwave onto the AWS cloud? What were the drivers that you considered? >>So one of the observations is that a very large percentage of users of my sequel Heatwave, our AWS users who are migrating of Aurora or so already we see that a good percentage of my secret history of customers are migrating from GWS. However, there are some AWS customers who are still not able to migrate the O. C. I to my secret heat wave. And the reason is because of, um, exorbitant cost, which was charges. So in order to migrate the workload from AWS to go see, I digress. Charges are very high fees which becomes prohibitive for the customer or the second example we have seen is that the latency of practising a database which is outside of AWS is very high. So there's a class of customers who would like to get the benefits of my secret heatwave but were unable to do so and with this support of my secret trip inside of AWS, these customers can now get all the grease of the benefits of my secret he trip without having to pay the high fees or without having to suffer with the poorly agency, which is because of the ws architecture. >>Okay, so you're basically meeting the customer's where they are. So was this a straightforward lifted shift from from Oracle Cloud Infrastructure to AWS? >>No, it is not because one of the design girls we have with my sequel, Heatwave is that we want to provide our customers with the best price performance regardless of the cloud. So when we decided to offer my sequel, he headed west. Um, we have optimised my sequel Heatwave on it as well. So one of the things to point out is that this is a service with the data plane control plane and the console are natively running on AWS. And the benefits of doing so is that now we can optimise my sequel Heatwave for the E. W s architecture. In addition to that, we have also announced a bunch of new capabilities as a part of the service which will also be available to the my secret history of customers and our CI, But we just announced them and we're offering them as a part of my secret history of offering on AWS. >>So I just want to make sure I understand that it's not like you just wrapped your stack in a container and stuck it into a W s to be hosted. You're saying you're actually taking advantage of the capabilities of the AWS cloud natively? And I think you've made some other enhancements as well that you're alluding to. Can you maybe, uh, elucidate on those? Sure. >>So for status, um, we have taken the mind sequel Heatwave code and we have optimised for the It was infrastructure with its computer network. And as a result, customers get very good performance and price performance. Uh, with my secret he trade in AWS. That's one performance. Second thing is, we have designed new interactive counsel for the service, which means that customers can now provision there instances with the council. But in addition, they can also manage their schemas. They can. Then court is directly from the council. Autopilot is integrated. The council we have introduced performance monitoring, so a lot of capabilities which we have introduced as a part of the new counsel. The third thing is that we have added a bunch of new security features, uh, expose some of the security features which were part of the My Secret Enterprise edition as a part of the service, which gives customers now a choice of using these features to build more secure applications. And finally, we have extended my secret autopilot for a number of old gpus cases. In the past, my secret autopilot had a lot of capabilities for Benedict, and now we have augmented my secret autopilot to offer capabilities for elderly people. Includes as well. >>But there was something in your press release called Auto thread. Pooling says it provides higher and sustained throughput. High concerns concerns concurrency by determining Apple number of transactions, which should be executed. Uh, what is that all about? The auto thread pool? It seems pretty interesting. How does it affect performance? Can you help us understand that? >>Yes, and this is one of the capabilities of alluding to which we have added in my secret autopilot for transaction processing. So here is the basic idea. If you have a system where there's a large number of old EP transactions coming into it at a high degrees of concurrency in many of the existing systems of my sequel based systems, it can lead to a state where there are few transactions executing, but a bunch of them can get blocked with or a pilot tried pulling. What we basically do is we do workload aware admission control and what this does is it figures out, what's the right scheduling or all of these algorithms, so that either the transactions are executing or as soon as something frees up, they can start executing, so there's no transaction which is blocked. The advantage to the customer of this capability is twofold. A get significantly better throughput compared to service like Aurora at high levels of concurrency. So at high concurrency, for instance, uh, my secret because of this capability Uh oh, thread pulling offers up to 10 times higher compared to Aurora, that's one first benefit better throughput. The second advantage is that the true part of the system never drops, even at high levels of concurrency, whereas in the case of Aurora, the trooper goes up, but then, at high concurrency is, let's say, starting, uh, level of 500 or something. It depends upon the underlying shit they're using the troopers just dropping where it's with my secret heatwave. The truth will never drops. Now, the ramification for the customer is that if the truth is not gonna drop, the user can start off with a small shape, get the performance and be a show that even the workload increases. They will never get a performance, which is worse than what they're getting with lower levels of concurrency. So this let's leads to customers provisioning a shape which is just right for them. And if they need, they can, uh, go with the largest shape. But they don't like, you know, over pay. So those are the two benefits. Better performance and sustain, uh, regardless of the level of concurrency. >>So how do we quantify that? I know you've got some benchmarks. How can you share comparisons with other cloud databases especially interested in in Amazon's own databases are obviously very popular, and and are you publishing those again and get hub, as you have done in the past? Take us through the benchmarks. >>Sure, So benchmarks are important because that gives customers a sense of what performance to expect and what price performance to expect. So we have run a number of benchmarks. And yes, all these benchmarks are available on guitar for customers to take a look at. So we have performance results on all the three castle workloads, ol DB Analytics and Machine Learning. So let's start with the Rdp for Rdp and primarily because of the auto thread pulling feature. We show that for the IPCC for attended dataset at high levels of concurrency, heatwave offers up to 10 times better throughput and this performance is sustained, whereas in the case of Aurora, the performance really drops. So that's the first thing that, uh, tend to alibi. Sorry, 10 gigabytes. B B C c. I can come and see the performance are the throughput is 10 times better than Aurora for analytics. We have done a comparison of my secret heatwave in AWS and compared with Red Ship Snowflake Googled inquiry, we find that the price performance of my secret heatwave compared to read ship is seven times better. So my sequel, Heat Wave in AWS, provides seven times better price performance than red ship. That's a very, uh, interesting results to us. Which means that customers of Red Shift are really going to take the service seriously because they're gonna get seven times better price performance. And this is all running in a W s so compared. >>Okay, carry on. >>And then I was gonna say, compared to like, Snowflake, uh, in AWS offers 10 times better price performance. And compared to Google, ubiquity offers 12 times better price performance. And this is based on a four terabyte p PCH workload. Results are available on guitar, and then the third category is machine learning and for machine learning, uh, for training, the performance of my secret heatwave is 25 times faster compared to that shit. So all the three workloads we have benchmark's results, and all of these scripts are available on YouTube. >>Okay, so you're comparing, uh, my sequel Heatwave on AWS to Red Shift and snowflake on AWS. And you're comparing my sequel Heatwave on a W s too big query. Obviously running on on Google. Um, you know, one of the things Oracle is done in the past when you get the price performance and I've always tried to call fouls you're, like, double your price for running the oracle database. Uh, not Heatwave, but Oracle Database on a W s. And then you'll show how it's it's so much cheaper on on Oracle will be like Okay, come on. But they're not doing that here. You're basically taking my sequel Heatwave on a W s. I presume you're using the same pricing for whatever you see to whatever else you're using. Storage, um, reserved instances. That's apples to apples on A W s. And you have to obviously do some kind of mapping for for Google, for big query. Can you just verify that for me, >>we are being more than fair on two dimensions. The first thing is, when I'm talking about the price performance for analytics, right for, uh, with my secret heat rape, the cost I'm talking about from my secret heat rape is the cost of running transaction processing, analytics and machine learning. So it's a fully loaded cost for the case of my secret heatwave. There has been I'm talking about red ship when I'm talking about Snowflake. I'm just talking about the cost of these databases for running, and it's only it's not, including the source database, which may be more or some other database, right? So that's the first aspect that far, uh, trip. It's the cost for running all three kinds of workloads, whereas for the competition, it's only for running analytics. The second thing is that for these are those services whether it's like shit or snowflakes, That's right. We're talking about one year, fully paid up front cost, right? So that's what most of the customers would pay for. Many of the customers would pay that they will sign a one year contract and pay all the costs ahead of time because they get a discount. So we're using that price and the case of Snowflake. The costs were using is their standard edition of price, not the Enterprise edition price. So yes, uh, more than in this competitive. >>Yeah, I think that's an important point. I saw an analysis by Marx Tamer on Wiki Bond, where he was doing the TCO comparisons. And I mean, if you have to use two separate databases in two separate licences and you have to do et yelling and all the labour associated with that, that that's that's a big deal and you're not even including that aspect in in your comparison. So that's pretty impressive. To what do you attribute that? You know, given that unlike, oh, ci within the AWS cloud, you don't have as much control over the underlying hardware. >>So look hard, but is one aspect. Okay, so there are three things which give us this advantage. The first thing is, uh, we have designed hateful foreign scale out architecture. So we came up with new algorithms we have come up with, like, uh, one of the design points for heat wave is a massively partitioned architecture, which leads to a very high degree of parallelism. So that's a lot of hype. Each were built, So that's the first part. The second thing is that although we don't have control over the hardware, but the second design point for heat wave is that it is optimised for commodity cloud and the commodity infrastructure so we can have another guys, what to say? The computer we get, how much network bandwidth do we get? How much of, like objects to a brand that we get in here? W s. And we have tuned heat for that. That's the second point And the third thing is my secret autopilot, which provides machine learning based automation. So what it does is that has the users workload is running. It learns from it, it improves, uh, various premieres in the system. So the system keeps getting better as you learn more and more questions. And this is the third thing, uh, as a result of which we get a significant edge over the competition. >>Interesting. I mean, look, any I SV can go on any cloud and take advantage of it. And that's, uh I love it. We live in a new world. How about machine learning workloads? What? What did you see there in terms of performance and benchmarks? >>Right. So machine learning. We offer three capabilities training, which is fully automated, running in France and explanations. So one of the things which many of our customers told us coming from the enterprise is that explanations are very important to them because, uh, customers want to know that. Why did the the system, uh, choose a certain prediction? So we offer explanations for all models which have been derailed by. That's the first thing. Now, one of the interesting things about training is that training is usually the most expensive phase of machine learning. So we have spent a lot of time improving the performance of training. So we have a bunch of techniques which we have developed inside of Oracle to improve the training process. For instance, we have, uh, metal and proxy models, which really give us an advantage. We use adaptive sampling. We have, uh, invented in techniques for paralysing the hyper parameter search. So as a result of a lot of this work, our training is about 25 times faster than that ship them health and all the data is, uh, inside the database. All this processing is being done inside the database, so it's much faster. It is inside the database. And I want to point out that there is no additional charge for the history of customers because we're using the same cluster. You're not working in your service. So all of these machine learning capabilities are being offered at no additional charge inside the database and as a performance, which is significantly faster than that, >>are you taking advantage of or is there any, uh, need not need, but any advantage that you can get if two by exploiting things like gravity. John, we've talked about that a little bit in the past. Or trainee. Um, you just mentioned training so custom silicon that AWS is doing, you're taking advantage of that. Do you need to? Can you give us some insight >>there? So there are two things, right? We're always evaluating What are the choices we have from hybrid perspective? Obviously, for us to leverage is right and like all the things you mention about like we have considered them. But there are two things to consider. One is he is a memory system. So he favours a big is the dominant cost. The processor is a person of the cost, but memory is the dominant cost. So what we have evaluated and found is that the current shape which we are using is going to provide our customers with the best price performance. That's the first thing. The second thing is that there are opportunities at times when we can use a specialised processor for vaccinating the world for a bit. But then it becomes a matter of the cost of the customer. Advantage of our current architecture is on the same hardware. Customers are getting very good performance. Very good, energetic performance in a very good machine learning performance. If you will go with the specialised processor, it may. Actually, it's a machine learning, but then it's an additional cost with the customers we need to pay. So we are very sensitive to the customer's request, which is usually to provide very good performance at a very low cost. And we feel is that the current design we have as providing customers very good performance and very good price performance. >>So part of that is architectural. The memory intensive nature of of heat wave. The other is A W s pricing. If AWS pricing were to flip, it might make more sense for you to take advantage of something like like cranium. Okay, great. Thank you. And welcome back to the benchmarks benchmarks. Sometimes they're artificial right there. A car can go from 0 to 60 in two seconds. But I might not be able to experience that level of performance. Do you? Do you have any real world numbers from customers that have used my sequel Heatwave on A W s. And how they look at performance? >>Yes, absolutely so the my Secret service on the AWS. This has been in Vera for, like, since November, right? So we have a lot of customers who have tried the service. And what actually we have found is that many of these customers, um, planning to migrate from Aurora to my secret heat rape. And what they find is that the performance difference is actually much more pronounced than what I was talking about. Because with Aurora, the performance is actually much poorer compared to uh, like what I've talked about. So in some of these cases, the customers found improvement from 60 times, 240 times, right? So he travels 100 for 240 times faster. It was much less expensive. And the third thing, which is you know, a noteworthy is that customers don't need to change their applications. So if you ask the top three reasons why customers are migrating, it's because of this. No change to the application much faster, and it is cheaper. So in some cases, like Johnny Bites, what they found is that the performance of their applications for the complex storeys was about 60 to 90 times faster. Then we had 60 technologies. What they found is that the performance of heat we have compared to Aurora was 100 and 39 times faster. So, yes, we do have many such examples from real workloads from customers who have tried it. And all across what we find is if it offers better performance, lower cost and a single database such that it is compatible with all existing by sequel based applications and workloads. >>Really impressive. The analysts I talked to, they're all gaga over heatwave, and I can see why. Okay, last question. Maybe maybe two and one. Uh, what's next? In terms of new capabilities that customers are going to be able to leverage and any other clouds that you're thinking about? We talked about that upfront, but >>so in terms of the capabilities you have seen, like they have been, you know, non stop attending to the feedback from the customers in reacting to it. And also, we have been in a wedding like organically. So that's something which is gonna continue. So, yes, you can fully expect that people not dressed and continue to in a way and with respect to the other clouds. Yes, we are planning to support my sequel. He tripped on a show, and this is something that will be announced in the near future. Great. >>All right, Thank you. Really appreciate the the overview. Congratulations on the work. Really exciting news that you're moving my sequel Heatwave into other clouds. It's something that we've been expecting for some time. So it's great to see you guys, uh, making that move, and as always, great to have you on the Cube. >>Thank you for the opportunity. >>All right. And thank you for watching this special cube conversation. I'm Dave Volonte, and we'll see you next time.
SUMMARY :
The company is now in its fourth major release since the original announcement in December 2020. Very happy to be back. Now for those who might not have kept up with the news, uh, to kick things off, give us an overview of my So customers of my sequel then they had to run analytics or when they had to run machine So we've seen some interesting moves by Oracle lately. So one of the observations is that a very large percentage So was this a straightforward lifted shift from No, it is not because one of the design girls we have with my sequel, So I just want to make sure I understand that it's not like you just wrapped your stack in So for status, um, we have taken the mind sequel Heatwave code and we have optimised Can you help us understand that? So this let's leads to customers provisioning a shape which is So how do we quantify that? So that's the first thing that, So all the three workloads we That's apples to apples on A W s. And you have to obviously do some kind of So that's the first aspect And I mean, if you have to use two So the system keeps getting better as you learn more and What did you see there in terms of performance and benchmarks? So we have a bunch of techniques which we have developed inside of Oracle to improve the training need not need, but any advantage that you can get if two by exploiting We're always evaluating What are the choices we have So part of that is architectural. And the third thing, which is you know, a noteworthy is that In terms of new capabilities that customers are going to be able so in terms of the capabilities you have seen, like they have been, you know, non stop attending So it's great to see you guys, And thank you for watching this special cube conversation.
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Breaking Analysis: H1 of ‘22 was ugly…H2 could be worse Here’s why we’re still optimistic
>> From theCUBE Studios in Palo Alto in Boston, bringing you data driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> After a two-year epic run in tech, 2022 has been an epically bad year. Through yesterday, The NASDAQ composite is down 30%. The S$P 500 is off 21%. And the Dow Jones Industrial average 16% down. And the poor holders at Bitcoin have had to endure a nearly 60% decline year to date. But judging by the attendance and enthusiasm, in major in-person tech events this spring. You'd never know that tech was in the tank. Moreover, walking around the streets of Las Vegas, where most tech conferences are held these days. One can't help but notice that the good folks of Main Street, don't seem the least bit concerned that the economy is headed for a recession. Hello, and welcome to this weeks Wiki Bond Cube Insights powered by ETR. In this Breaking Analysis we'll share our main takeaways from the first half of 2022. And talk about the outlook for tech going forward, and why despite some pretty concerning headwinds we remain sanguine about tech generally, but especially enterprise tech. Look, here's the bumper sticker on why many folks are really bearish at the moment. Of course, inflation is high, other than last year, the previous inflation high this century was in July of 2008, it was 5.6%. Inflation has proven to be very, very hard to tame. You got gas at $7 dollars a gallon. Energy prices they're not going to suddenly drop. Interest rates are climbing, which will eventually damage housing. Going to have that ripple effect, no doubt. We're seeing layoffs at companies like Tesla and the crypto names are also trimming staff. Workers, however are still in short supply. So wages are going up. Companies in retail are really struggling with the right inventory, and they can't even accurately guide on their earnings. We've seen a version of this movie before. Now, as it pertains to tech, Crawford Del Prete, who's the CEO of IDC explained this on theCUBE this very week. And I thought he did a really good job. He said the following, >> Matt, you have a great statistic that 80% of companies used COVID as their point to pivot into digital transformation. And to invest in a different way. And so what we saw now is that tech is now where I think companies need to focus. They need to invest in tech. They need to make people more productive with tech and it played out in the numbers. Now so this year what's fascinating is we're looking at two vastly different markets. We got gasoline at $7 a gallon. We've got that affecting food prices. Interesting fun fact recently it now costs over $1,000 to fill an 18 wheeler. All right, based on, I mean, this just kind of can't continue. So you think about it. >> Don't put the boat in the water. >> Yeah, yeah, yeah. Good luck if ya, yeah exactly. So a family has kind of this bag of money, and that bag of money goes up by maybe three, 4% every year, depending upon earnings. So that is sort of sloshing around. So if food and fuel and rent is taking up more, gadgets and consumer tech are not, you're going to use that iPhone a little longer. You're going to use that Android phone a little longer. You're going to use that TV a little longer. So consumer tech is getting crushed, really it's very, very, and you saw it immediately in ad spending. You've seen it in Meta, you've seen it in Facebook. Consumer tech is doing very, very, it is tough. Enterprise tech, we haven't been in the office for two and a half years. We haven't upgraded whether that be campus wifi, whether that be servers, whether that be commercial PCs as much as we would have. So enterprise tech, we're seeing double digit order rates. We're seeing strong, strong demand. We have combined that with a component shortage, and you're seeing some enterprise companies with a quarter of backlog, I mean that's really unheard of. >> And higher prices, which also profit. >> And therefore that drives up the prices. >> And this is a theme that we've heard this year at major tech events, they've really come roaring back. Last year, theCUBE had a huge presence at AWS Reinvent. The first Reinvent since 2019, it was really well attended. Now this was before the effects of the omicron variant, before they were really well understood. And in the first quarter of 2022, things were pretty quiet as far as tech events go But theCUBE'a been really busy this spring and early into the summer. We did 12 physical events as we're showing here in the slide. Coupa, did Women in Data Science at Stanford, Coupa Inspire was in Las Vegas. Now these are both smaller events, but they were well attended and beat expectations. San Francisco Summit, the AWS San Francisco Summit was a bit off, frankly 'cause of the COVID concerns. They were on the rise, then we hit Dell Tech World which was packed, it had probably around 7,000 attendees. Now Dockercon was virtual, but we decided to include it here because it was a huge global event with watch parties and many, many tens of thousands of people attending. Now the Red Hat Summit was really interesting. The choice that Red Hat made this year. It was purposefully scaled down and turned into a smaller VIP event in Boston at the Western, a couple thousand people only. It was very intimate with a much larger virtual presence. VeeamON was very well attended, not as large as previous VeeamON events, but again beat expectations. KubeCon and Cloud Native Con was really successful in Spain, Valencia, Spain. PagerDuty Summit was again a smaller intimate event in San Francisco. And then MongoDB World was at the new Javits Center and really well attended over the three day period. There were lots of developers there, lots of business people, lots of ecosystem partners. And then the Snowflake summit in Las Vegas, it was the most vibrant from the standpoint of the ecosystem with nearly 10,000 attendees. And I'll come back to that in a moment. Amazon re:Mars is the Amazon AI robotic event, it's smaller but very, very cool, a lot of innovation. And just last week we were at HPE Discover. They had around 8,000 people attending which was really good. Now I've been to over a dozen HPE or HPE Discover events, within Europe and the United States over the past decade. And this was by far the most vibrant, lot of action. HPE had a little spring in its step because the company's much more focused now but people was really well attended and people were excited to be there, not only to be back at physical events, but also to hear about some of the new innovations that are coming and HPE has a long way to go in terms of building out that ecosystem, but it's starting to form. So we saw that last week. So tech events are back, but they are smaller. And of course now a virtual overlay, they're hybrid. And just to give you some context, theCUBE did, as I said 12 physical events in the first half of 2022. Just to compare that in 2019, through June of that year we had done 35 physical events. Yeah, 35. And what's perhaps more interesting is we had our largest first half ever in our 12 year history because we're doing so much hybrid and virtual to compliment the physical. So that's the new format is CUBE plus digital or sometimes just digital but that's really what's happening in our business. So I think it's a reflection of what's happening in the broader tech community. So everyone's still trying to figure that out but it's clear that events are back and there's no replacing face to face. Or as I like to say, belly to belly, because deals are done at physical events. All these events we've been to, the sales people are so excited. They're saying we're closing business. Pipelines coming out of these events are much stronger, than they are out of the virtual events but the post virtual event continues to deliver that long tail effect. So that's not going to go away. The bottom line is hybrid is the new model. Okay let's look at some of the big themes that we've taken away from the first half of 2022. Now of course, this is all happening under the umbrella of digital transformation. I'm not going to talk about that too much, you've had plenty of DX Kool-Aid injected into your veins over the last 27 months. But one of the first observations I'll share is that the so-called big data ecosystem that was forming during the hoop and around, the hadoop infrastructure days and years. then remember it dispersed, right when the cloud came in and kind of you know, not wiped out but definitely dampened the hadoop enthusiasm for on-prem, the ecosystem dispersed, but now it's reforming. There are large pockets that are obviously seen in the various clouds. And we definitely see a ecosystem forming around MongoDB and the open source community gathering in the data bricks ecosystem. But the most notable momentum is within the Snowflake ecosystem. Snowflake is moving fast to win the day in the data ecosystem. They're providing a single platform that's bringing different data types together. Live data from systems of record, systems of engagement together with so-called systems of insight. These are converging and while others notably, Oracle are architecting for this new reality, Snowflake is leading with the ecosystem momentum and a new stack is emerging that comprises cloud infrastructure at the bottom layer. Data PaaS layer for app dev and is enabling an ecosystem of partners to build data products and data services that can be monetized. That's the key, that's the top of the stack. So let's dig into that further in a moment but you're seeing machine intelligence and data being driven into applications and the data and application stacks they're coming together to support the acceleration of physical into digital. It's happening right before our eyes in every industry. We're also seeing the evolution of cloud. It started with the SaaS-ification of the enterprise where organizations realized that they didn't have to run their own software on-prem and it made sense to move to SaaS for CRM or HR, certainly email and collaboration and certain parts of ERP and early IS was really about getting out of the data center infrastructure management business called that cloud 1.0, and then 2.0 was really about changing the operating model. And now we're seeing that operating model spill into on-prem workloads finally. We're talking about here about initiatives like HPE's Green Lake, which we heard a lot about last week at Discover and Dell's Apex, which we heard about in May, in Las Vegas. John Furrier had a really interesting observation that basically this is HPE's and Dell's version of outposts. And I found that interesting because outpost was kind of a wake up call in 2018 and a shot across the bow at the legacy enterprise infrastructure players. And they initially responded with these flexible financial schemes, but finally we're seeing real platforms emerge. Again, we saw this at Discover and at Dell Tech World, early implementations of the cloud operating model on-prem. I mean, honestly, you're seeing things like consoles and billing, similar to AWS circa 2014, but players like Dell and HPE they have a distinct advantage with respect to their customer bases, their service organizations, their very large portfolios, especially in the case of Dell and the fact that they have more mature stacks and knowhow to run mission critical enterprise applications on-prem. So John's comment was quite interesting that these firms are basically building their own version of outposts. Outposts obviously came into their wheelhouse and now they've finally responded. And this is setting up cloud 3.0 or Supercloud, as we like to call it, an abstraction layer, that sits above the clouds that serves as a unifying experience across a continuum of on-prem across clouds, whether it's AWS, Azure, or Google. And out to both the near and far edge, near edge being a Lowes or a Home Depot, but far edge could be space. And that edge again is fragmented. You've got the examples like the retail stores at the near edge. Outer space maybe is the far edge and IOT devices is perhaps the tiny edge. No one really knows how the tiny edge is going to play out but it's pretty clear that it's not going to comprise traditional X86 systems with a cool name tossed out to the edge. Rather, it's likely going to require a new low cost, low power, high performance architecture, most likely RM based that will enable things like realtime AI inferencing at that edge. Now we've talked about this a lot on Breaking Analysis, so I'm not going to double click on it. But suffice to say that it's very possible that new innovations are going to emerge from the tiny edge that could really disrupt the enterprise in terms of price performance. Okay, two other quick observations. One is that data protection is becoming a much closer cohort to the security stack where data immutability and air gaps and fast recovery are increasingly becoming a fundamental component of the security strategy to combat ransomware and recover from other potential hacks or disasters. And I got to say from our observation, Veeam is leading the pack here. It's now claiming the number one revenue spot in a statistical dead heat with the Dell's data protection business. That's according to Veeam, according to IDC. And so that space continues to be of interest. And finally, Broadcom's acquisition of Dell. It's going to have ripple effects throughout the enterprise technology business. And there of course, there are a lot of questions that remain, but the one other thing that John Furrier and I were discussing last night John looked at me and said, "Dave imagine if VMware runs better on Broadcom components and OEMs that use Broadcom run VMware better, maybe Broadcom doesn't even have to raise prices on on VMware licenses. Maybe they'll just raise prices on the OEMs and let them raise prices to the end customer." Interesting thought, I think because Broadcom is so P&L focused that it's probably not going to be the prevailing model but we'll see what happens to some of the strategic projects rather like Monterey and Capitola and Thunder. We've talked a lot about project Monterey, the others we'll see if they can make the cut. That's one of the big concerns because it's how OEMs like the ones that are building their versions of outposts are going to compete with the cloud vendors, namely AWS in the future. I want to come back to the comment on the data stack for a moment that we were talking about earlier, we talked about how the big data ecosystem that was once coalescing around hadoop dispersed. Well, the data value chain is reforming and we think it looks something like this picture, where cloud infrastructure lives at the bottom. We've said many times the cloud is expanding and evolving. And if companies like Dell and HPE can truly build a super cloud infrastructure experience then they will be in a position to capture more of the data value. If not, then it's going to go to the cloud players. And there's a live data layer that is increasingly being converged into platforms that not only simplify the movement in ELTing of data but also allow organizations to compress the time to value. Now there's a layer above that, we sometimes call it the super PaaS layer if you will, that must comprise open source tooling, partners are going to write applications and leverage platform APIs and build data products and services that can be monetized at the top of the stack. So when you observe the battle for the data future it's unlikely that any one company is going to be able to do this all on their own, which is why I often joke that the 2020s version of a sweaty Steve Bomber running around the stage, screaming, developers, developers developers, and getting the whole audience into it is now about ecosystem ecosystem ecosystem. Because when you need to fill gaps and accelerate features and provide optionality a list of capabilities on the left hand side of this chart, that's going to come from a variety of different companies and places, we're talking about catalogs and AI tools and data science capabilities, data quality, governance tools and it should be of no surprise to followers of Breaking Analysis that on the right hand side of this chart we're including the four principles of data mesh, which of course were popularized by Zhamak Dehghani. So decentralized data ownership, data as products, self-serve platform and automated or computational governance. Now whether this vision becomes a reality via a proprietary platform like Snowflake or somehow is replicated by an open source remains to be seen but history generally shows that a defacto standard for more complex problems like this is often going to emerge prior to an open source alternative. And that would be where I would place my bets. Although even that proprietary platform has to include open source optionality. But it's not a winner take all market. It's plenty of room for multiple players and ecosystem innovators, but winner will definitely take more in my opinion. Okay, let's close with some ETR data that looks at some of those major platform plays who talk a lot about digital transformation and world changing impactful missions. And they have the resources really to compete. This is an XY graphic. It's a view that we often show, it's got net score on the vertical access. That's a measure of spending momentum, and overlap or presence in the ETR survey. That red, that's the horizontal access. The red dotted line at 40% indicates that the platform is among the highest in terms of spending velocity. Which is why I always point out how impressive that makes AWS and Azure because not only are they large on the horizontal axis, the spending momentum on those two platforms rivals even that of Snowflake which continues to lead all on the vertical access. Now, while Google has momentum, given its goals and resources, it's well behind the two leaders. We've added Service Now and Salesforce, two platform names that have become the next great software companies. Joining likes of Oracle, which we show here and SAP not shown along with IBM, you can see them on this chart. We've also plotted MongoDB, which we think has real momentum as a company generally but also with Atlas, it's managed cloud database as a service specifically and Red Hat with trying to become the standard for app dev in Kubernetes environments, which is the hottest trend right now in application development and application modernization. Everybody's doing something with Kubernetes and of course, Red Hat with OpenShift wants to make that a better experience than do it yourself. The DYI brings a lot more complexity. And finally, we've got HPE and Dell both of which we've talked about pretty extensively here and VMware and Cisco. Now Cisco is executing on its portfolio strategy. It's got a lot of diverse components to its company. And it's coming at the cloud of course from a networking and security perspective. And that's their position of strength. And VMware is a staple of the enterprise. Yes, there's some uncertainty with regards to the Broadcom acquisition, but one thing is clear vSphere isn't going anywhere. It's entrenched and will continue to run lots of IT for years to come because it's the best platform on the planet. Now, of course, these are just some of the players in the mix. We expect that numerous non-traditional technology companies this is important to emerge as new cloud players. We've put a lot of emphasis on the data ecosystem because to us that's really going to be the main spring of digital, i.e., a digital company is a data company and that means an ecosystem of data partners that can advance outcomes like better healthcare, faster drug discovery, less fraud, cleaner energy, autonomous vehicles that are safer, smarter, more efficient grids and factories, better government and virtually endless litany of societal improvements that can be addressed. And these companies will be building innovations on top of cloud platforms creating their own super clouds, if you will. And they'll come from non-traditional places, industries, finance that take their data, their software, their tooling bring them to their customers and run them on various clouds. Okay, that's it for today. Thanks to Alex Myerson, who is on production and does the podcast for Breaking Analysis, Kristin Martin and Cheryl Knight, they help get the word out. And Rob Hoofe is our editor and chief over at Silicon Angle who helps edit our posts. Remember all these episodes are available as podcasts wherever you listen. All you got to do is search Breaking Analysis podcast. I publish each week on wikibon.com and siliconangle.com. You can email me directly at david.vellante@siliconangle.com or DM me at dvellante, or comment on my LinkedIn posts. And please do check out etr.ai for the best survey data in the enterprise tech business. This is Dave Vellante for theCUBE's Insights powered by ETR. Thanks for watching be well. And we'll see you next time on Breaking Analysis. (upbeat music)
SUMMARY :
This is Breaking Analysis that the good folks of Main Street, and it played out in the numbers. haven't been in the office And higher prices, And therefore that is that the so-called big data ecosystem
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Danny Allan, Veeam | VeeamON 2022
>>Hi, this is Dave Volonte. We're winding down Day two of the Cubes coverage of Vim on 2022. We're here at the area in Las Vegas. Myself and Dave Nicholson had been going for two days. Everybody's excited about the VM on party tonight. It's It's always epic, and, uh, it's a great show in terms of its energy. Danny Allen is here. He's cto of in his back. He gave the keynote this morning. I say, Danny, you know, you look pretty good up there with two hours of sleep. I >>had three. >>Look, don't look that good, but your energy was very high. And I got to tell you the story you told was amazing. It was one of the best keynotes I've ever seen. Even even the technology pieces were outstanding. But you weaving in that story was incredible. I'm hoping that people will go back and and watch it. We probably don't have time to go into it, but wow. Um, can you give us the the one minute version of that >>long story? >>Sure. Yeah. I read a book back in 2013 about a ship that sank off Portsmouth, Maine, and I >>thought, I'm gonna go find that >>ship. And so it's a long, >>complicated process. Five >>years in the making. But we used data, and the data that found the ship was actually from 15 years earlier. >>And in 20 >>18, we found the bow of the ship. We found the stern of the ship, but what we were really trying to answer was torpedoed. Or did the boilers explode? Because >>the navy said the boilers exploded >>and two survivors said, No, it was torpedoed or there was a German U boat there. >>And so >>our goal was fine. The ship find the boiler. >>So in 20 >>19, Sorry, Uh, it was 2018. We found the bow and the stern. And then in 2019, we found both boilers perfectly intact. And in fact, the rear end of that torpedo wasn't much left >>of it, of course, but >>data found that wreck. And so it, um, it exonerated essentially any implication that somebody screwed >>up in >>the boiler system and the survivors or the Children of the survivors obviously appreciated >>that. I'm sure. Yes, Several >>outcomes to it. So the >>chief engineer was one >>of the 13 survivors, >>and he lived with the weight of this for 75 years. 49 sailors dead because of myself. But I had the opportunity of meeting some of the Children of the victims and also attending ceremonies. The families of those victims received purple hearts because they were killed due to enemy action. And then you actually knew how to do this. I wasn't aware you had experience finding Rex. You've >>discovered several of >>them prior to this one. But >>the interesting connection >>the reason why this keynote was so powerful as we're a >>team, it's a data conference. >>You connected that to data because you you went out and bought a How do you say this? Magnanimous magnetometer. Magnetometer, Magnetometer. I don't know what that >>is. And a side >>scan Sonar, Right? I got that right. That was >>easy. But >>then you know what this stuff is. And then you >>built the model >>tensorflow. You took all the data and you found anomalies. And then you went right to that spot. Found the >>wreck with 12 >>£1000 of dynamite, >>which made your heart >>beat. But >>then you found >>the boilers. That's incredible. And >>but the point was, >>this is data >>uh, let's see, >>a lot of years after, >>right? >>Yeah. Two sets of data were used. One was the original set of side scan sonar >>data by the historian >>who discovered there was a U boat in the area that was 15 years old. >>And then we used, of >>course, the wind and weather and wave pattern data that was 75 years old to figure out where the boiler should be because they knew that the ship had continued to float for eight minutes. And so you had to go back and determine the models of where should the boilers >>be if it exploded and the boilers >>dropped out and it floated along >>for eight minutes and then sank? Where was >>that data? >>It was was a scanned was an electronic was a paper. How did you get that data? So the original side scan sonar data was just hard >>drive >>data by the historian. >>I wish I could say he used them to >>back it up. But I don't know that I can say that. But he still had >>the data. 15 years later, the >>weather and >>wind and wave data, That was all public information, and we actually used that extensively. We find other wrecks. A lot of wrecks off Boston Sunken World War Two. So we were We were used to that model of tracking what happened. Wow. So, yes, imagine if that data weren't available >>and it >>probably shouldn't have been right by all rights. So now fast forward to 2022. We've got Let's talk about just a cloud >>data. I think you said a >>couple of 100 >>petabytes in the >>cloud 2019. 500 in, Uh, >>no. Yeah. In >>20 2200 and 42. Petabytes in 20 2500 Petabytes last year. And we've already done the same as 2020. So >>240 petabytes >>in Q one. I expect >>this year to move an exhibit of >>data into the public cloud. >>Okay, so you got all that data. Who knows what's in there, right? And if it's not protected, who's going to know in 50 60 7100 years? Right. So that was your tie in? Yes. To the to the importance of data protection, which was just really, really well done. Congratulations. Honestly, one of the best keynotes I've ever seen keynotes often really boring, But you did a great job again on two hours. Sleep. So much to unpack here. The other thing that really is. I mean, we can talk about the demos. We can talk about the announcements. Um, so? Well, yeah, Let's see. Salesforce. Uh, data protection is now public. I almost spilled the beans yesterday in the cube. Caught myself the version 12. Obviously, you guys gave a great demo showing the island >>cloud with I think it >>was just four minutes. It was super fast. Recovery in four minutes of data loss was so glad you didn't say zero minutes because that would have been a live demos which, Okay, which I appreciate and also think is crazy. So some really cool demos, Um, and some really cool features. So I have so much impact, but the the insights that you can provide through them it's VM one, uh, was actually something that I hadn't heard you talk about extensively in the past. That maybe I just missed it. But I wonder if you could talk about that layer and why it's critical differentiator for Wien. It's >>the hidden gem >>within the Wien portfolio because it knows about absolutely >>everything. >>And what determines the actions >>that we take is the >>context in which >>data is surviving. So in the context of security, which we are showing, we look for CPU utilisation, memory utilisation, data change rate. If you encrypt all of the data in a file server, it's going to blow up overnight. And so we're leveraging heuristics in their reporting. But even more than that, one of the things in Wien one people don't realise we have this concept of the intelligent diagnostics. It's machine learning, which we drive on our end and we push out as packages intervene one. There's up to 200 signatures, but it helps our customers find issues before they become issues. Okay, so I want to get into because I often time times, don't geek out with you. And don't take advantage of your your technical knowledge. And you've you've triggered a couple of things, >>especially when the >>analysts call you said it again today that >>modern >>data protection has meaning to you. We talked a little bit about this yesterday, but back in >>the days of >>virtualisation, you shunned agents >>and took a different >>approach because you were going for what was then >>modern. Then you >>went to bare metal cloud hybrid >>cloud containers. Super Cloud. Using the analyst meeting. You didn't use the table. Come on, say Super Cloud and then we'll talk about the edge. So I would like to know specifically if we can go back to Virtualised >>because I didn't know >>this exactly how you guys >>defined modern >>back then >>and then. Let's take that to modern today. >>So what do you >>do back then? And then we'll get into cloud and sure, So if you go back to and being started, everyone who's using agents, you'd instal something in the operating system. It would take 10% 15% of your CPU because it was collecting all the data and sending it outside of the machine when we went through a virtual environment. If you put an agent inside that machine, what happens is you would have 100 operating systems all on the same >>server, consuming >>resources from that hyper visor. And so he said, there's a better way of capturing the data instead of capturing the data inside the operating system. And by the way, managing thousands of agents is no fun. So What we did is we captured a snapshot of the image at the hyper visor level. And then over time, we just leverage changed block >>tracking from the hyper >>visor to determine what >>had changed. And so that was modern. Because no more >>managing agents >>there was no impact >>on the operating system, >>and it was a far more >>efficient way to store >>data. You leverage CBT through the A P. Is that correct? Yeah. We used the VCR API >>for data protection. >>Okay, so I said this to Michael earlier. Fast forward to today. Your your your data protection competitors aren't as fat, dumb and happy as they used to be, so they can do things in containers, containers. And we talked about that. So now let's talk about Cloud. What's different about cloud data protection? What defines modern data protection? And where are the innovations that you're providing? >>Let me do one step in >>between those because one of the things that happened between hypervisors and Cloud was >>offline. The capture of the data >>to the storage system because >>even better than doing it >>at the hyper visor clusters >>do it on the storage >>array because that can capture the >>data instantly. Right? So as we go to the cloud, we want to do the same thing. Except we don't have access to either the hyper visor or the storage system. But what they do provide is an API. So we can use the API to capture all of the blocks, all of the data, all of the changes on that particular operating system. Now, here's where we've kind of gone full circle on a hyper >>visor. You can use the V >>sphere agent to reach into the operating system to do >>things like application consistency. What we've done modern data protection is create specific cloud agents that say Forget >>about the block changes. Make sure that I have application consistency inside that cloud operating >>system. Even though you don't have access to the hyper visor of the storage, >>you're still getting the >>operating system consistency >>while getting the really >>fast capture of data. So that gets into you talking on stage about how synapse don't equal data protection. I think you just explained it, but explain why, but let me highlight something that VM does that is important. We manage both snapshots and back up because if you can recover from your storage array >>snapshot. That is the best >>possible thing to recover from right, But we don't. So we manage both the snapshots and we converted >>into the VM portable >>data format. And here's where the super cloud comes into play because if I can convert it into the VM portable data format, I can move >>that OS >>anywhere. I can move it from >>physical to virtual to cloud >>to another cloud back to virtual. I can put it back on physical if I want to. It actually abstracts >>the cloud >>layer. There are things >>that we do when we go >>between clouds. Some use bio, >>some use, um, fee. >>But we have the data in backup format, not snapshot format. That's theirs. But we have been in backup format that we can move >>around and abstract >>workloads across. All of the infrastructure in your >>catalogue is control >>of that. Is that Is >>that right? That is about >>that 100%. And you know what's interesting about our catalogue? Dave. The catalogue is inside the backup, and so historically, one of the problems with backup is that you had a separate catalogue and if it ever got corrupted. All of your >>data is meaningless >>because the catalogue is inside >>the backup >>for that unique VM or that unique instance, you can move it anywhere and power it on. That's why people said were >>so reliable. As long >>as you have the backup file, you can delete our >>software. You can >>still get the data back, so I love this fast paced so that >>enables >>what I call Super Cloud we now call Super Cloud >>because now >>take that to the edge. >>If I want to go to the edge, I presume you can extend that. And I also presume the containers play a role there. Yes, so here's what's interesting about the edge to things on the edge. You don't want to have any state if you can help it, >>and so >>containers help with that. You can have stateless environment, some >>persistent data storage, >>but we not only >>provide the portability >>in operating systems. We also do this for containers, >>and that's >>true if you go to the cloud and you're using SE CKs >>with relational >>database service is already >>asked for the persistent data. >>Later, we can pick that up and move it to G K E or move it to open shift >>on premises. And >>so that's why I call this the super cloud. We have all of this data. Actually, I think you termed the term super thank you for I'm looking for confirmation from a technologist that it's technically feasible. It >>is technically feasible, >>and you can do it today and that's a I think it's a winning strategy. Personally, Will there be >>such a thing as edge Native? You know, there's cloud native. Will there be edge native new architectures, new ways of doing things, new workloads use cases? We talk about hardware, new hardware, architectures, arm based stuff that are going to change everything to edge Native Yes and no. There's going to be small tweaks that make it better for the edge. You're gonna see a lot of iron at the edge, obviously for power consumption purposes, and you're also going to see different constructs for networking. We're not going to use the traditional networking, probably a lot more software to find stuff. Same thing on the storage. They're going to try and >>minimise the persistent >>storage to the smallest footprint possible. But ultimately I think we're gonna see containers >>will lead >>the edge. We're seeing this now. We have a I probably can't name them, but we have a large retail organisation that is running containers in every single store with a small, persistent footprint of the point of sale and local data, but that what >>is running the actual >>system is containers, and it's completely ephemeral. So we were >>at Red Hat, I was saying >>earlier last week, and I'd say half 40 50% of the conversation was edge open shift, obviously >>playing a big role there. I >>know doing work with Rancher and Town Zoo. And so there's a lot of options there. >>But obviously, open shift has >>strong momentum in the >>marketplace. >>I've been dominating. You want to chime in? No, I'm just No, >>I yeah, I know. Sometimes >>I'll sit here like a sponge, which isn't my job absorbing stuff. I'm just fascinated by the whole concept of of a >>of a portable format for data that encapsulates virtual machines and or instances that can live in the containerised world. And once you once you create that common denominator, that's really that's >>That's the secret sauce >>for what you're talking about is a super club and what's been fascinating to watch because I've been paying attention since the beginning. You go from simply V. M. F s and here it is. And by the way, the pitch to E. M. C. About buying VM ware. It was all about reducing servers to files that can be stored on storage arrays. All of a sudden, the light bulbs went off. We can store those things, and it just began. It became it became a marriage afterwards. But to watch that progression that you guys have gone from from that fundamental to all of the other areas where now you've created this common denominator layer has has been amazing. So my question is, What's the singer? What doesn't work? Where the holes. You don't want to look at it from a from a glass half empty perspective. What's the next opportunity? We've talked about edge, but what are the things that you need to fill in to make this truly ubiquitous? Well, there's a lot of services out there that we're not protecting. To be fair, right, we do. Microsoft 3 65. We announced sales for us, but there's a dozen other paths services that >>people are moving data >>into. And until >>we had data protection >>for the assassin path services, you know >>you have to figure out how >>to protect them. Now here's the kicker about >>those services. >>Most of them have the >>ability to dump date >>out. The trick is, do they have the A >>P? I is needed to put data >>back into it right, >>which is which is a >>gap. As an industry, we need to address this. I actually think we need a common >>framework for >>how to manage the >>export of data, but also the import of data not at a at a system level, but at an atomic level of the elements within those applications. >>So there are gaps >>there at the industry, but we'll fill them >>if you look on the >>infrastructure side. We've done a lot with containers and kubernetes. I think there's a next wave around server list. There's still servers and these micro services, but we're making things smaller and smaller and smaller, and there's going to be an essential need to protect those services as well. So modern data protection is something that's going to we're gonna need modern data protection five years from now, the modern will just be different. Do you ever see the day, Danny, where governance becomes an >>adjacency opportunity for >>you guys? It's clearly an opportunity even now if you look, we spent a lot of time talking about security and what you find is when organisations go, for example, of ransomware insurance or for compliance, they need to be able to prove that they have certifications or they have security or they have governance. We just saw transatlantic privacy >>packed only >>to be able to prove what type of data they're collecting. Where are they storing it? Where are they allowed to recovered? And yes, those are very much adjacency is for our customers. They're trying to manage that data. >>So given that I mean, >>am I correct that architecturally you are, are you location agnostic? Right. We are a location agnostic, and you can actually tag data to allowable location. So the big trend that I think is happening is going to happen in in this >>this this decade. >>I think we're >>scratching the surface. Is this idea >>that, you know, leave data where it is, >>whether it's an S three >>bucket, it could be in an Oracle >>database. It could be in a snowflake database. It can be a data lake that's, you know, data, >>bricks or whatever, >>and it stays where >>it is. And it's just a note on the on the call of the data >>mesh. Not my term. Jim >>Octagon coined that term. The >>problem with that, and it puts data in the hands of closer to the domain experts. The problem with that >>scenario >>is you need self service infrastructure, which really doesn't exist today anyway. But it's coming, and the big problem is Federated >>computational >>governance. How do I automate that governance so that the people who should have access to that it can have access to that data? That, to me, seems to be an adjacency. It doesn't exist except in >>a proprietary >>platform. Today. There needs to be a horizontal >>layer >>that is more open than anybody >>can use. And I >>would think that's a perfect opportunity for you guys. Just strategically it is. There's no question, and I would argue, Dave, that it's actually >>valuable to take snapshots and to keep the data out at the edge wherever it happens to be collected. But then Federated centrally. It's why I get so excited by an exhibit of data this year going into the cloud, because then you're centralising the aggregation, and that's where you're really going to drive the insights. You're not gonna be writing tensorflow and machine learning and things on premises unless you have a lot of money and a lot of GPS and a lot of capacity. That's the type of thing that is actually better suited for the cloud. And, I would argue, better suited for not your organisation. You're gonna want to delegate that to a third party who has expertise in privacy, data analysis or security forensics or whatever it is that you're trying to do with the data. But you're gonna today when you think about AI. We talked about A. I haven't had a tonne of talk about AI some >>appropriate >>amount. Most of the >>AI today correct me if you think >>this is not true is modelling that's done in the cloud. It's dominant. >>Don't >>you think that's gonna flip when edge >>really starts to take >>off where it's it's more real time >>influencing >>at the edge in new use cases at the edge now how much of that data >>is going to be >>persisted is a >>point of discussion. But what >>are your thoughts on that? I completely agree. So my expectation of the way >>that this will work is that >>the true machine learning will happen in the centralised location, and what it will do is similar to someone will push out to the edge the signatures that drive the inferences. So my example of this is always the Tesla driving down the road. >>There's no way that that >>car should be figuring it sending up to the cloud. Is that a stop sign? Is it not? It can't. It has to be able to figure out what the stop sign is before it gets to it, so we'll do the influencing at the edge. But when it doesn't know what to do with the data, then it should send it to the court to determine, to learn about it and send signatures back out, not just to that edge location, but all the edge locations within the within the ecosystem. So I get what you're saying. They might >>send data back >>when there's an anomaly, >>or I always use the example of a deer running in front of the car. David Floyd gave me that one. That's when I want to. I do want to send the data back to the cloud because Tesla doesn't persist. A tonne of data, I presume, right, right less than 5% of it. You know, I want to. Usually I'm here to dive into the weeds. I want kind of uplevel this >>to sort of the >>larger picture. From an I T perspective. >>There's been a lot of consolidation going on if you divide the >>world into vendors >>and customers. On the customer side, there are only if there's a finite number of seats at the table for truly strategic partners. Those get gobbled up often by hyper >>scale cloud >>providers. The challenge there, and I'm part of a CEO accreditation programme. So this >>is aimed at my students who >>are CEOs and CIOs. The challenge is that a lot of CEOs and CIOs on the customer side don't exhaustively drag out of their vendor partners like a theme everything that Saveem >>can do for >>them. Maybe they're leveraging a point >>solution, >>but I guarantee you they don't all know that you've got cast in in the portfolio. Not every one of them does yet, let alone this idea of a super >>cloud and and and >>how much of a strategic role you can play. So I don't know if it's a blanket admonition to folks out there, but you have got to leverage the people who are building the solutions that are going to help you solve problems in the business. And I guess, as in the form of >>a question, >>uh, do you Do you see that as a challenge? Now those the limited number of seats at >>the Table for >>Strategic Partners >>Challenge and >>Opportunity. If you look at the types of partners that we've partnered with storage partners because they own the storage of the data, at the end of the day, we actually just manage it. We don't actually store it the cloud partners. So I see that as the opportunity and my belief is I thought that the storage doesn't matter, >>but I think the >>organisation that can centralise and manage that data is the one that can rule the world, and so >>clearly I'm a team. I think we can do amazing things, but we do have key >>strategic partners hp >>E Amazon. You heard >>them on stage yesterday. >>18 different >>integrations with AWS. So we have very strategic partners. Azure. I go out there all the time. >>So there >>you don't need to be >>in the room at the table because your partners are >>and they have a relationship with the customer as well. Fair enough. But the key to this it's not just technology. It is these relationships and what is possible between our organisations. So I'm sorry to be >>so dense on this, but when you talk about >>centralising that data you're talking about physically centralising it or can actually live across clouds, >>for instance. But you've got >>visibility and your catalogues >>have visibility on >>all that. Is that what you mean by centralised obliterated? We have understanding of all the places that lives, and we can do things with >>it. We can move it from one >>cloud to another. We can take, you know, everyone talks about data warehouses. >>They're actually pretty expensive. >>You got to take data and stream it into this thing, and there's a massive computing power. On the other hand, we're >>not like that. You've storage on there. We can ephemeral e. Spin up a database when you need it for five minutes and then destroy it. We can spin up an image when you need it and then destroy it. And so on your perspective of locations. So irrespective of >>location, it doesn't >>have to be in a central place, and that's been a challenge. You extract, >>transform and load, >>and moving the data to the central >>location has been a problem. We >>have awareness of >>all the data everywhere, >>and then we can make >>decisions as to what you >>do based >>on where it is and >>what it is. And that's a metadata >>innovation. I guess that >>comes back to the catalogue, >>right? Is that correct? >>You have data >>about the data that informs you as to where it is and how to get to it. And yes, so metadata within the data that allows you to recover it and then data across the federation of all that to determine where it is. And machine intelligence plays a role in all that, not yet not yet in that space. Now. I do think there's opportunity in the future to be able to distribute storage across many different locations and that's a whole conversation in itself. But but our machine learning is more just on helping our customers address the problems in their infrastructures rather than determining right now where that data should be. >>These guys they want me to break, But I'm >>refusing. So your >>Hadoop back >>in their rooms via, um that's >>well, >>that scale. A lot of customers. I talked to Renee Dupuis. Hey, we we got there >>was heavy lift. You >>know, we're looking at new >>ways. New >>approaches, uh, going. And of course, it's all in the cloud >>anyway. But what's >>that look like? That future look like we haven't reached bottle and X ray yet on our on our Hadoop clusters, and we do continuously examine >>them for anomalies that might happen. >>Not saying we won't run into a >>bottle like we always do at some >>point, But we haven't yet >>awesome. We've covered a lot of We've certainly covered extensively the research that you did on cyber >>security and ransomware. Um, you're kind of your vision for modern >>data protection. I think we hit on that pretty well casting, you know, we talked to Michael about that, and then, you know, the future product releases the Salesforce data protection. You guys, I think you're the first there. I think you were threatened at first from Microsoft. 3 65. No, there are other vendors in the in the salesforce space. But what I tell people we weren't the first to do data capture at the hyper >>visor level. There's two other >>vendors I won't tell you they were No one remembers them. Microsoft 3 65. We weren't the first one to for that, but we're now >>the largest. So >>there are other vendors in the salesforce space. But we're looking at We're going to be aggressive. Danielle, Thanks >>so much for coming to Cuba and letting us pick your brain like that Really great job today. And congratulations on >>being back >>in semi normal. Thank you for having me. I love being on all right. And thank you for watching. Keep it right there. More coverage. Day volonte for Dave >>Nicholson, By >>the way, check out silicon angle dot com for all the written coverage. All the news >>The cube dot >>net is where all these videos We'll we'll live. Check out wiki bond dot com I published every week. I think I'm gonna dig into the cybersecurity >>research that you guys did this week. If I can >>get a hands my hands on those charts which Dave Russell promised >>me, we'll be right back >>right after this short break. Mm.
SUMMARY :
He gave the keynote this morning. And I got to tell you the story you told off Portsmouth, Maine, and I And so it's a long, But we used data, and the data that found the ship was actually from 15 years earlier. We found the stern of the ship, but what we were really trying to answer was The ship find the boiler. We found the bow and the stern. data found that wreck. Yes, Several So the But I had the opportunity of meeting some of the Children of the victims and also attending ceremonies. them prior to this one. You connected that to data because you you went out and bought a How do you say this? I got that right. But And then you And then you went right to that spot. But the boilers. One was the original set of side scan sonar the boiler should be because they knew that the ship had continued to float for eight minutes. So the original side scan sonar data was just hard But I don't know that I can say that. the data. So we were We were used to that model of tracking So now fast forward to 2022. I think you said a cloud 2019. 500 in, And we've already done the same as 2020. I expect To the to the importance the insights that you can provide through them it's VM one, But even more than that, one of the things in Wien one people don't realise we have this concept of the intelligent diagnostics. data protection has meaning to you. Then you Using the analyst meeting. Let's take that to modern today. And then we'll get into cloud and sure, So if you go back to and being started, of capturing the data inside the operating system. And so that was modern. We used the VCR API Okay, so I said this to Michael earlier. The capture of the data all of the changes on that particular operating system. You can use the V cloud agents that say Forget about the block changes. Even though you don't have access to the hyper visor of the storage, So that gets into you talking on stage That is the best possible thing to recover from right, But we don't. And here's where the super cloud comes into play because if I can convert it into the VM I can move it from to another cloud back to virtual. There are things Some use bio, But we have been in backup format that we can move All of the infrastructure in your Is that Is and so historically, one of the problems with backup is that you had a separate catalogue and if it ever got corrupted. for that unique VM or that unique instance, you can move it anywhere and power so reliable. You can You don't want to have any state if you can help it, You can have stateless environment, some We also do this for containers, And Actually, I think you termed the and you can do it today and that's a I think it's a winning strategy. new hardware, architectures, arm based stuff that are going to change everything to edge Native Yes storage to the smallest footprint possible. of the point of sale and local data, but that what So we were I And so there's a lot of options there. You want to chime in? I yeah, I know. I'm just fascinated by the whole concept of of instances that can live in the containerised world. But to watch that progression that you guys have And until Now here's the kicker about The trick is, do they have the A I actually think we need a common but at an atomic level of the elements within those applications. So modern data protection is something that's going to we're gonna need modern we spent a lot of time talking about security and what you find is when organisations to be able to prove what type of data they're collecting. So the big trend that I think is happening is going to happen in scratching the surface. It can be a data lake that's, you know, data, And it's just a note on the on the call of the data Not my term. Octagon coined that term. The problem with that But it's coming, and the big problem is Federated How do I automate that governance so that the people who should have access to that it can There needs to be a horizontal And I would think that's a perfect opportunity for you guys. That's the type of thing that is actually better suited for the cloud. Most of the this is not true is modelling that's done in the cloud. But what So my expectation of the way the true machine learning will happen in the centralised location, and what it will do is similar to someone then it should send it to the court to determine, to learn about it and send signatures Usually I'm here to dive into the weeds. From an I T perspective. On the customer side, there are only if there's a finite number of seats at So this The challenge is that a lot of CEOs and CIOs on the customer side but I guarantee you they don't all know that you've got cast in in the portfolio. And I guess, as in the form of So I see that as the opportunity and my belief is I thought that the storage I think we can do amazing things, but we do have key You heard So we have very strategic partners. But the key to this it's not just technology. But you've got all the places that lives, and we can do things with We can take, you know, everyone talks about data warehouses. On the other hand, We can ephemeral e. Spin up a database when you need it for five minutes and then destroy have to be in a central place, and that's been a challenge. We And that's a metadata I guess that about the data that informs you as to where it is and how to get to it. So your I talked to Renee Dupuis. was heavy lift. And of course, it's all in the cloud But what's the research that you did on cyber Um, you're kind of your vision for modern I think we hit on that pretty well casting, you know, we talked to Michael about that, There's two other vendors I won't tell you they were No one remembers them. the largest. But we're looking at We're going to be aggressive. so much for coming to Cuba and letting us pick your brain like that Really great job today. And thank you for watching. the way, check out silicon angle dot com for all the written coverage. I think I'm gonna dig into the cybersecurity research that you guys did this week. right after this short break.
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Breaking Analysis: Cyber, Blockchain & NFTs Meet the Metaverse
>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is "Breaking Analysis" with Dave Vellante. >> When Facebook changed its name to Meta last fall, it catalyzed a chain reaction throughout the tech industry. Software firms, gaming companies, chip makers, device manufacturers, and others have joined in hype machine. Now, it's easy to dismiss the metaverse as futuristic hyperbole, but do we really believe that tapping on a smartphone, or staring at a screen, or two-dimensional Zoom meetings are the future of how we work, play, and communicate? As the internet itself proved to be larger than we ever imagined, it's very possible, and even quite likely that the combination of massive processing power, cheap storage, AI, blockchains, crypto, sensors, AR, VR, brain interfaces, and other emerging technologies will combine to create new and unimaginable consumer experiences, and massive wealth for creators of the metaverse. Hello, and welcome to this week's Wiki Bond Cube Insights, powered by ETR. In this "Breaking Analysis" we welcome in cyber expert, hacker gamer, NFT expert, and founder of ORE System, Nick Donarski. Nick, welcome, thanks so much for coming on theCUBE. >> Thank you, sir, glad to be here. >> Yeah, okay, so today we're going to traverse two parallel paths, one that took Nick from security expert and PenTester to NFTs, tokens, and the metaverse. And we'll simultaneously explore the complicated world of cybersecurity in the enterprise, and how the blockchain, crypto, and NFTs will provide key underpinnings for digital ownership in the metaverse. We're going to talk a little bit about blockchain, and crypto, and get things started there, and some of the realities and misconceptions, and how innovations in those worlds have led to the NFT craze. We'll look at what's really going on in NFTs and why they're important as both a technology and societal trend. Then, we're going to dig into the tech and try to explain why and how blockchain and NFTs are going to lay the foundation for the metaverse. And, finally, who's going to build the metaverse. And how long is it going to take? All right, Nick, let's start with you. Tell us a little bit about your background, your career. You started as a hacker at a really, really young age, and then got deep into cyber as a PenTester. You did some pretty crazy stuff. You have some great stories about sneaking into buildings. You weren't just doing it all remote. Tell us about yourself. >> Yeah, so I mean, really, I started a long time ago. My dad was really the foray into technology. I wrote my first program on an Apple IIe in BASIC in 1989. So, I like to say I was born on the internet, if you will. But, yeah, in high school at 16, I incorporated my first company, did just tech support for parents and teachers. And then in 2000 I transitioned really into security and focused there ever since. I joined Rapid7 and after they picked up Medis boy, I joined HP. I was one of their founding members of Shadowlabs and really have been part of the information security and the cyber community all throughout, whether it's training at various different conferences or talking. My biggest thing and my most awesome moments as various things of being broken into, is really when I get to actually work with somebody that's coming up in the industry and who's new and actually has that light bulb moment of really kind of understanding of technology, understanding an idea, or getting it when it comes to that kind of stuff. >> Yeah, and when you think about what's going on in crypto and NFTs and okay, now the metaverse it's you get to see some of the most innovative people. Now I want to first share a little bit of data on enterprise security and maybe Nick get you to comment. We've reported over the past several years on the complexity in the security business and the numerous vendor choices that SecOps Pros face. And this chart really tells that story in the cybersecurity space. It's an X,Y graph. We've shown it many times from the ETR surveys where the vertical axis, it's a measure of spending momentum called net score. And the horizontal axis is market share, which represents each company's presence in the data set, and a couple of points stand out. First, it's really crowded. In that red dotted line that you see there, that's 40%, above that line on the net score axis, marks highly elevated spending momentum. Now, let's just zoom in a bit and I've cut the data by those companies that have more than a hundred responses in the survey. And you can see here on this next chart, it's still very crowded, but a few call-outs are noteworthy. First companies like SentinelOne, Elastic, Tanium, Datadog, Netskope and Darktrace. They were all above that 40% line in the previous chart, but they've fallen off. They still have actually a decent presence in the survey over 60 responses, but under that hundred. And you can see Auth0 now Okta, big $7 billion acquisition. They got the highest net score CrowdStrike's up there, Okta classic they're kind of enterprise business, and Zscaler and others above that line. You see Palo Alto Networks and Microsoft very impressive because they're both big and they're above that elevated spending velocity. So Nick, kind of a long-winded intro, but it was a little bit off topic, but I wanted to start here because this is the life of a SecOps pro. They lack the talent in a capacity to keep bad guys fully at bay. And so they have to keep throwing tooling at the problem, which adds to the complexity and as a PenTester and hacker, this chaos and complexity means cash for the bad guys. Doesn't it? >> Absolutely. You know, the more systems that these organizations find to integrate into the systems, means that there's more components, more dollars and cents as far as the amount of time and the engineers that need to actually be responsible for these tools. There's a lot of reasons that, the more, I guess, hands in the cookie jar, if you will, when it comes to the security architecture, the more links that are, or avenues for attack built into the system. And really one of the biggest things that organizations face is being able to have engineers that are qualified and technical enough to be able to support that architecture as well, 'cause buying it from a vendor and deploying it, putting it onto a shelf is good, but if it's not tuned properly, or if it's not connected properly, that security tool can just hold up more avenues of attack for you. >> Right, okay, thank you. Now, let's get into the meat of the discussion for today and talk a little bit about blockchain and crypto for a bit. I saw sub stack post the other day, and it was ripping Matt Damon for pedaling crypto on TV ads and how crypto is just this big pyramid scheme. And it's all about allowing criminals to be anonymous and it's ransomware and drug trafficking. And yes, there are definitely scams and you got to be careful and lots of dangers out there, but these are common criticisms in the mainstream press, that overlooked the fact by the way that IPO's and specs are just as much of a pyramid scheme. Now, I'm not saying there shouldn't be more regulation, there should, but Bitcoin was born out of the 2008 financial crisis, cryptocurrency, and you think about, it's really the confluence of software engineering, cryptography and game theory. And there's some really powerful innovation being created by the blockchain community. Crypto and blockchain are really at the heart of a new decentralized platform being built out. And where today, you got a few, large internet companies. They control the protocols and the platform. Now the aspiration of people like yourself, is to create new value opportunities. And there are many more chances for the little guys and girls to get in on the ground floor and blockchain technology underpins all this. So Nick, what's your take, what are some of the biggest misconceptions around blockchain and crypto? And do you even pair those two in the same context? What are your thoughts? >> So, I mean, really, we like to separate ourselves and say that we are a blockchain company, as opposed to necessarily saying(indistinct) anything like that. We leverage those tools. We leverage cryptocurrencies, we leverage NFTs and those types of things within there, but blockchain is a technology, which is the underlying piece, is something that can be used and utilized in a very large number of different organizations out there. So, cryptocurrency and a lot of that negative context comes with a fear of something new, without having that regulation in place, without having the rules in place. And we were a big proponent of, we want the regulation, right? We want to do right. We want to do it by the rules. We want to do it under the context of, this is what should be done. And we also want to help write those rules as well, because a lot of the lawmakers, a lot of the lobbyists and things, they have a certain aspect or a certain goal of when they're trying to get these things. Our goal is simplicity. We want the ability for the normal average person to be able to interact with crypto, interact with NFTs, interact with the blockchain. And basically by saying, blockchain in quotes, it's very ambiguous 'cause there's many different things that blockchain can be, the easiest way, right? The easiest way to understand blockchain is simply a distributed database. That's really the core of what blockchain is. It's a record keeping mechanism that allows you to reference that. And the beauty of it, is that it's quote unquote immutable. You can't edit that data. So, especially when we're talking about blockchain, being underlying for technologies in the future, things like security, where you have logging, you have keeping, whether you're talking about sales, where you may have to have multiple different locations (indistinct) users from different locations around the globe. It creates a central repository that provides distribution and security in the way that you're ensuring your data, ensuring the validation of where that data exists when it was created. Those types of things that blockchain really is. If you go to the historical, right, the very early on Bitcoin absolutely was made to have a way of not having to deal with the fed. That was the core functionality of the initial crypto. And then you had a lot of the illicit trades, those black markets that jumped onto it because of what it could do. The maturity of the technology though, of where we are now versus say back in 97 is a much different world of blockchain, and there's a much different world of cryptocurrency. You still have to be careful because with any fed, you're still going to have that FUD that goes out there and sells that fear, uncertainty and doubt, which spurs a lot of those types of scams, and a lot of those things that target end users that we face as security professionals today. You still get mailers that go out, looking for people to give their social security number over during tax time. Snail mail is considered a very ancient technology, but it still works. You still get a portion of the population that falls for those tricks, fishing, whatever it might be. It's all about trying to make sure that you have fear about what is that change. And I think that as we move forward, and move into the future, the simpler and the more comfortable these types of technologies become, the easier it is to utilize and indoctrinate normal users, to be able to use these things. >> You know, I want to ask you about that, Nick, because you mentioned immutability, there's a lot of misconceptions about that. I had somebody tell me one time, "Blockchain's Bs," and they say, "Well, oh, hold on a second. They say, oh, they say it's a mutable, but you can hack Coinbase, whatever it is." So I guess a couple of things, one is that the killer app for blockchain became money. And so we learned a lot through that. And you had Bitcoin and it really wasn't programmable through its interface. And then Ethereum comes out. I know, you know a lot about Ether and you have solidity, which is a lot simpler, but it ain't JavaScript, which is ubiquitous. And so now you have a lot of potential for the initial ICO's and probably still the ones today, the white papers, a lot of security flaws in there. I'm sure you can talk to that, but maybe you can help square that circle about immutability and security. I've mentioned game theory before, it's harder to hack Bitcoin and the Bitcoin blockchain than it is to mine. So that's why people mine, but maybe you could add some context to that. >> Yeah, you know it goes to just about any technology out there. Now, when you're talking about blockchain specifically, the majority of the attacks happen with the applications and the smart contracts that are actually running on the blockchain, as opposed to necessarily the blockchain itself. And like you said, the impact for whether that's loss of revenue or loss of tokens or whatever it is, in most cases that results from something that was a phishing attack, you gave up your credentials, somebody said, paste your private key in here, and you win a cookie or whatever it might be, but those are still the fundamental pieces. When you're talking about various different networks out there, depending on the blockchain, depends on how much the overall security really is. The more distributed it is, and the more stable it is as the network goes, the better or the more stable any of the code is going to be. The underlying architecture of any system is the key to success when it comes to the overall security. So the blockchain itself is immutable, in the case that the owner are ones have to be trusted. If you look at distributed networks, something like Ethereum or Bitcoin, where you have those proof of work systems, that disperses that information at a much more remote location, So the more disperse that information is, the less likely it is to be able to be impacted by one small instance. If you look at like the DAO Hack, or if you look at a lot of the other vulnerabilities that exist on the blockchain, it's more about the code. And like you said, solidity being as new as it is, it's not JavaScript. The industry is very early and very infantile, as far as the developers that are skilled in doing this. And with that just comes the inexperience and the lack of information that you don't learn until JavaScript is 10 or 12 years old. >> And the last thing I'll say about this topic, and we'll move on to NFTs, but NFTs relate is that, again, I said earlier that the big internet giants have pretty much co-opted the platform. You know, if you wanted to invest in Linux in the early days, there was no way to do that. You maybe have to wait until red hat came up with its IPO and there's your pyramid scheme folks. But with crypto it, which is again, as Nick was explaining underpinning is the blockchain, you can actually participate in early projects. Now you got to be careful 'cause there are a lot of scams and many of them are going to blow out if not most of them, but there are some, gems out there, because as Nick was describing, you've got this decentralized platform that causes scaling issues or performance issues, and people are solving those problems, essentially building out a new internet. But I want to get into NFTs, because it's sort of the next big thing here before we get into the metaverse, what Nick, why should people pay attention to NFTs? Why do they matter? Are they really an important trend? And what are the societal and technological impacts that you see in this space? >> Yeah, I mean, NFTs are a very new technology and ultimately it's just another entry on the blockchain. It's just another piece of data in the database. But how it's leveraged in the grand scheme of how we, as users see it, it can be the classic idea of an NFT is just the art, or as good as the poster on your wall. But in the case of some of the new applications, is where are you actually get that utility function. Now, in the case of say video games, video games and gamers in general, already utilize digital items. They already utilize digital points. As in the case of like Call of Duty points, those are just different versions of digital currencies. You know, World of Warcraft Gold, I like to affectionately say, was the very first cryptocurrency. There was a Harvard course taught on the economy of WOW, there was a black market where you could trade your end game gold for Fiat currencies. And there's even places around the world that you can purchase real world items and stay at hotels for World of Warcraft Gold. So the adoption of blockchain just simply gives a more stable and a more diverse technology for those same types of systems. You're going to see that carry over into shipping and logistics, where you need to have data that is single repository for being able to have multiple locations, multiple shippers from multiple global efforts out there that need to have access to that data. But in the current context, it's either sitting on a shipping log, it's sitting on somebody's desk. All of those types of paper transactions can be leveraged as NFTs on the blockchain. It's just simply that representation. And once you break the idea of this is just a piece of art, or this is a cryptocurrency, you get into a world where you can apply that NFT technology to a lot more things than I think most people think of today. >> Yeah, and of course you mentioned art a couple of times when people sold as digital art for whatever, it was 60, 65 million, 69 million, that caught a lot of people's attention, but you're seeing, I mean, there's virtually infinite number of applications for this. One of the Washington wizards, tokenized portions of his contract, maybe he was creating a new bond, that's really interesting use cases and opportunities, and that kind of segues into the latest, hot topic, which is the metaverse. And you've said yourself that blockchain and NFTs are the foundation of the metaverse, they're foundational elements. So first, what is the metaverse to you and where do blockchain and NFTs, fit in? >> Sure, so, I mean, I affectionately refer to the metaverse just a VR and essentially, we've been playing virtual reality games and all the rest for a long time. And VR has really kind of been out there for a long time. So most people's interpretation or idea of what the metaverse is, is a virtual reality version of yourself and this right, that idea of once it becomes yourself, is where things like NFT items, where blockchain and digital currencies are going to come in, because if you have a manufacturer, so you take on an organization like Nike, and they want to put their shoes into the metaverse because we, as humans, want to individualize ourselves. We go out and we want to have that one of one shoe or that, t-shirt or whatever it is, we're going to want to represent that same type of individuality in our virtual self. So NFTs, crypto and all of those digital currencies, like I was saying that we've known as gamers are going to play that very similar role inside of the metaverse. >> Yeah. Okay. So basically you're going to take your physical world into the metaverse. You're going to be able to, as you just mentioned, acquire things- I loved your WOW example. And so let's stay on this for a bit, if we may, of course, Facebook spawned a lot of speculation and discussion about the concept of the metaverse and really, as you pointed out, it's not new. You talked about why second life, really started in 2003, and it's still around today. It's small, I read recently, it's creators coming back into the company and books were written in the early 90s that used the term metaverse. But Nick, talk about how you see this evolving, what role you hope to play with your company and your community in the future, and who builds the metaverse, when is it going to be here? >> Yeah, so, I mean, right now, and we actually just got back from CES last week. And the Metaverse is a very big buzzword. You're going to see a lot of integration of what people are calling, quote unquote, the metaverse. And there was organizations that were showing virtual office space, virtual malls, virtual concerts, and those types of experiences. And the one thing right now that I don't think that a lot of organizations have grasp is how to make one metaverse. There's no real player one, if you will always this yet, There's a lot of organizations that are creating their version of the metaverse, which then again, just like every other software and game vendor out there has their version of cryptocurrency and their version of NFTs. You're going to see it start to pop up, especially as Oculus is going to come down in price, especially as you get new technologies, like some of the VR glasses that look more augmented reality and look more like regular glasses that you're wearing, things like that, the easier that those technologies become as in adopting into our normal lifestyle, as far as like looks and feels, the faster that stuff's going to actually come out to the world. But when it comes to like, what we're doing is we believe that the metaverse should actually span multiple different blockchains, multiple different segments, if you will. So what ORE system is doing, is we're actually building the underlying architecture and technologies for developers to bring their metaverse too. You can leverage the ORE Systems NFTs, where we like to call our utility NFTs as an in-game item in one game, or you can take it over and it could be a t-shirt in another game. The ability for having that cross support within the ecosystem is what really no one has grasp on yet. Most of the organizations out there are using a very classic business model. Get the user in the game, make them spend their money in the game, make all their game stuff as only good in their game. And that's where the developer has you, they have you in their bubble. Our goal, and what we like to affectionately say is, we want to bring white collar tools and technology to blue collar folks, We want to make it simple. We want to make it off the shelf, and we want to make it a less cost prohibitive, faster, and cheaper to actually get out to all the users. We do it by supporting the technology. That's our angle. If you support the technology and you support the platform, you can build a community that will build all of the metaverse around them. >> Well, and so this is interesting because, if you think about some of the big names, we've Microsoft is talking about it, obviously we mentioned Facebook. They have essentially walled gardens. Now, yeah, okay, I could take Tik Tok and pump it into Instagram is fine, but they're really siloed off. And what you're saying is in the metaverse, you should be able to buy a pair of sneakers in one location and then bring it to another one. >> Absolutely, that's exactly it. >> And so my original kind of investment in attractiveness, if you will, to crypto, was that, the little guy can get an early, but I worry that some of these walled gardens, these big internet giants are going to try to co-op this. So I think what you're doing is right on, and I think it's aligned with the objectives of consumers and the users who don't want to be forced in to a pen. They want to be able to live freely. And that's really what you're trying to do. >> That's exactly it. You know, when you buy an item, say a Skin in Fortnite or Skin in Call of Duty, it's only good in that game. And not even in the franchise, it's only good in that version of the game. In the case of what we want to do is, you can not only have that carry over and your character. So say you buy a really cool shirt, and you've got that in your Call of Duty or in our case, we're really Osiris Protocol, which is our proof of concept video game to show that this all thing actually works, but you can actually go in and you can get a gun in Osiris Protocol. And if we release, Osiris Protocol two, you'll be able to take that to Osiris Protocol two. Now the benefit of that is, is you're going to be the only one in the next version with that item, if you haven't sold it or traded it or whatever else. So we don't lock you into a game. We don't lock you into a specific application. You own that, you can trade that freely with other users. You can sell that on the open market. We're embracing what used to be considered the black market. I don't understand why a lot of video games, we're always against the skins and mods and all the rest. For me as a gamer and coming up, through the many, many years of various different Call of Duties and everything in my time, I wish I could still have some this year. I still have a World of Warcraft account. I wasn't on, Vanilla, Burning Crusade was my foray, but I still have a character. If you look at it that way, if I had that wild character and that gear was NFTs, in theory, I could actually pass that onto my kid who could carry on that character. And it would actually increase in value because they're NFT back then. And then if needed, you could trade those on the open market and all the rest. It just makes gaming a much different thing. >> I love it. All right, Nick, hey, we're out of time, but I got to say, Nick Donarski, thanks so much for coming on the program today, sharing your insights and really good luck to you and building out your technology platform and your community. >> Thank you, sir, it's been an absolute pleasure. >> And thank you for watching. Remember, all these episodes are available as podcasts, just search "Breaking Analysis Podcast", and you'll find them. I publish pretty much every week on siliconangle.com and wikibond.com. And you can reach me @dvellante on Twitter or comment on my LinkedIn posts. You can always email me david.vellante@siliconangle.com. And don't forget, check out etr.plus for all the survey data. This is Dave Vellante for theCUBE Insights, powered by ETR, happy 2022 be well, and we'll see you next time. (upbeat music)
SUMMARY :
bringing you data-driven and even quite likely that the combination and how the blockchain, crypto, and NFTs and the cyber community all throughout, and the numerous vendor hands in the cookie jar, if you will, and the platform. and security in the way that and probably still the ones any of the code is going to be. and many of them are going to of data in the database. Yeah, and of course you and all the rest for a long time. and discussion about the believe that the metaverse is in the metaverse, and the users who don't want and mods and all the rest. really good luck to you Thank you, sir, it's all the survey data.
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Breaking Analysis: Cyber, Cloud, Hybrid Work & Data Drive 8% IT Spending Growth in 2021
>> From theCUBE studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE in ETR. This is Breaking Analysis with Dave Vellante. >> Every CEO is figuring out the right balance for new hybrid business models. Now, regardless of the chosen approach, which is going to vary, technology executives, they understand they have to accelerate their digital and build resilience as well as optionality into their platforms. Now, this is driving a dramatic shift in IT investments. And at the macro level, we expect total spending to increase at as much as 8% or even more in 2021, compared to last year's contraction. Investments in cybersecurity, cloud collaboration that are enabling hybrid work as well as data, including analytics, AI, and automation are at the top of the spending priorities for CXOs. Hello everyone. And welcome to this week's Wiki Bond Cube insights, powered by ETR. In this Breaking Analysis, we're pleased to welcome back Erik Bradley, who is the chief engagement strategist at our partner, ETR. Now in this segment, we're going to share some of the latest findings from ETR's surveys and provide our commentary on what it means for the markets, for sellers, and for buyers. Erik, great to see you, my friend. Welcome back to Breaking Analysis. >> Thank you for having me, always enjoy it. We've got some fresh data to talk about on this beautiful summer Friday, so I'm ready to go. >> All right. I'm excited too. Okay, last year we saw a contraction in IT spending by at least 5%. And now we're seeing a snapback to, as I said, at least 8% growth relative to last year. You got to go back to 2007 just before the financial crisis to see this type of top line growth. The shift to hybrid work, it's exposed us to new insidious security threats. And we're going to discuss that in a lot more detail. Cloud migration of course picked up dramatically last year, and based on the recent earnings results of the big cloud players, for now we got two quarters of data, that trend continues as organizations are accelerating their digital platform build-outs, and this is bringing a lot of complexity and a greater need for so-called observability solutions, which Erik is going to talk about extensively later on in this segment. Data, we think is entering a new era of de-centralization. We see organizations not only focused on analytics and insights, but actually creating data products. Leading technology organizations like JP Morgan, they're heavily leaning into this trend toward packaging and monetizing data products. And finally, as part of the digital transformation trend, we see no slow down in spending momentum for AI and automation, generally in RPA specifically. Erik, anything you want to add to that top level narrative? >> Yeah, there's a lot to take on the macro takeaways. The first thing I want to state is that that 8, 8.5% number that started off at just 3 to 4% beginning of the year. So as the year has continued, we are just seeing this trend in budgets continue to accelerate, and we don't have any reason to believe that's going to stop. So I think we're going to just keep moving on heading into 2021. And we're going to see a banner year of spend this year and probably next as well. >> All right, now we're going to bring up a chart that shows kind of that progression here of spending momentum. So Erik, I'm going to let you comment on this chart that tracks those projections over time. >> Erik: Yeah. Great. So thank you very much for pulling this up. As you can see in the beginning part of the year, when we asked people, "What do you plan to spend throughout 2021?" They were saying it would be about a 4% increase. Which we were happy with because as you said last year, it was all negative. That continues to accelerate and is only hyper accelerating now as we head into the back half of the year. In addition, after we do this data, I always host a panel of IT end users to kind of get their feedback on what we collected, to a man, every one of them expects continued increase throughout next year. There are some concerns and uncertainty about what we're seeing right now with COVID, but even with that, they're planning their budgets now for 2022 and they're planning for even further increases going forward. >> Dave: Great, thank you. So we circled that 8%. That's really kind of where we thought it was going to land. And so we're happy with that number, but let's take a look at where the action is by technology sector. This chart that we're showing you here, it tracks spending priorities back to last September. When I believe that was the point, Erik, that cyber became the top priority in the survey, ahead of cloud collaboration, analytics, and data, and the other sectors that you see there. Now, Erik, we should explain. These areas, they're the top seven, and they outrank all the other sectors. ETR tracks many, many other sectors, but please weigh in here and share your thoughts on this data. >> Erik: Yeah. Security, security, security. It hasn't changed. It had really hasn't. The hybrid work. The fact that you're behind the firewall one day and then you're outside working from home the next, switching in and out of networks. This is just a field day for bad actors. And we have no choice right now, but to continue to spend, because as you're going to talk about in a minute, hybrid's here to stay. So we have to figure out a way to secure behind the firewall on-prem. We also have to secure our employees and our assets that are not in the office. So it is a main priority. One of the things that point out on this chart, I had a couple of ITN users talk to me about customer experience and automation really need to move from the right part of that chart to the left. So they're seeing more in what you were talking about in RPA and automation, starting to creep up heading into next year. As cloud migration matures, as you know, cybersecurity spending has been ramping up. People are going to see a little bit more on the analytics and a little bit more on the automation side going forward. >> Dave: Great. Now, this next data view- well, first of all, one of the great things about the ETR dataset is that you can ask key questions and get a time series. And I will tell you again, I go back to last March, ETR hit it. They were the first on the work from home trend. And so if you were on that trend, you were able to anticipate it. And a lot of investors I think took advantage of that. Now, but we've shown this before, but there's new data points that we want to introduce. So the data tracks how CIOs and IT buyers have responded to the pandemic since last March. Still 70% of the organizations have employees working remotely, but 39% now have employees fully returning to the office and Erik, the rest of the metrics all point toward positives for IT spending, although accelerating IT deployments there at the right peaked last year, as people realized they had to invest in the future. Your thoughts? >> Erik: Yeah, this is the slide for optimism, without a doubt. Of the entire macro survey we did, this is the most optimistic slide. It's great for overall business. It's great for business travel. This is well beyond just IT. Hiring is up. I've had some people tell me that they possibly can't hire enough people right now. They had to furlough employees, they had to stop projects, and they want to re accelerate those now. But talent is very hard to find. Another point to you about your automation and RPA, another underlying trend for there. The one thing I did want to talk about here is the hybrid workplace, but I believe there's another slide on it. So just to recap on this extremely optimistic, we're seeing a lot of hiring. We're seeing increased spending, and I do believe that that's going to continue. >> Yeah I'm glad you brought that up because a session that you and I did a while ago, we pointed out, it was earlier this year, that the skill shortage is one potential risk to our positive scenario. We'll keep an eye on that, but so I want to show another set of data that we've showed previously, but ETR again, has added some new questions in here. So note here that 60% of employees still work remotely with 33% in a hybrid model currently, and the CIO's expect that to land on about 42% hybrid workforce with around 30% working remotely, which is around, it's been consistent by the way on your surveys, but that's about double the historic norm, Eric. >> Erik: Yeah, and even further to your point Dave, recently I did a panel asking people to give me some feedback on this. And three of those four experts basically said to me, if we had greed run this survey right now, that even more people would be saying remote. That they believe that that number, that's saying they're expecting that number of people to be back in office, is actually too optimistic. They're actually saying that maybe if we had- cause as a survey launched about six, seven weeks ago before this little blip on the radar, before the little COVID hiccup we're seeing now, and they're telling me that they believe if we reran this now that it would be even more remote work, even more hybrid and less returned to the office. So that's just an update I wanted to offer on this slide. >> Dave: Yeah. Thank you for that. I mean, we're still in this kind of day to day, week to week, month to month mode, but I want to do a little double click on this. We're not going to share this data, but there was so much ETR data. We got to be selective. But if you double click on the hybrid models, you'll see that 50% of organizations plan to have time roughly equally split between onsite and remote with again around 30 or 31% mostly remote, with onsite space available if they need it. And Erik, very few don't plan to have some type of hybrid model, at least. >> Yeah, I think it was less than 10% that said it was going to be exclusively onsite. And again, that was a more optimistic scenario six, seven weeks ago than we're seeing right now throughout the country. So I agree with you, hybrid is here to stay. There really is no doubt about it. from everyone I speak to when, you know, I basically make a living talking to IT end users. Hybrid is here to stay. They're planning for it. And that's really the drive behind the spending because you have to support both. You have to give people the option. You have to, from an IT perspective, you also have to support both, right? So if somebody is in office, I need the support staff to be in office. Plus I need them to be able to remote in and fix something from home. So they're spending on both fronts right now. >> Okay. Let's get into some of the vendor performance data. And I want to start with the cloud hyperscalers. It's something that we followed pretty closely. I got some Wiki bond data, that we just had earnings released. So here's data that shows the Q2 revenue shares on the left-hand side in the pie and the growth rates for the big four cloud players on the right hand side. It goes back to Q1 2019. Now the first thing I want to say is these players generated just under $39 billion in the quarter with AWS capturing 50% of that number. I said 39, it was 29 billion, sorry, with AWS capturing 50% of that in the quarter. As you're still tracking around a third in Alibaba and GCP in the, you know, eight or 9% range. But what's most interesting to me, Erik, is that AWS, which generated almost 15 billion in the quarter, was the only player to grow its revenue, both sequentially and year over year. And Erik, I think the street is missing the real story here on Amazon. Amazon announced earnings on Thursday night. The company had a 2% miss on the top line revenues and a meaningful 22% beat on earnings per share. So the retail side of the business missed its revenue targets, so that's why everybody's freaked out. But AWS, the cloud side, saw a 4% revenue beat. So the stock was off more than 70% after hours and into Friday. Now to me, a mix shift toward AWS, that's great news for investors. Now, tepid guidance is a negative, but the shift to a more profitable cloud business is a huge positive. >> Yeah, there's a lot that goes into stock price, right? I remember I was a director of research back in the day. One of my analysts said to me, "Am I crazy for putting a $1,000 target on Amazon?" And I laughed and I said, "No, you're crazy if you don't make it $2,000." (both chuckling) So, you know, at that time it was basically the mix shift towards AWS. You're a thousand percent right. I think the tough year over year comps had something to do with that reaction. That, you know, it's just getting really hard. What's that? The law of large numbers, right? It's really hard to grow at that percentage rate when you're getting this big. But from our data perspective, we're seeing no slowdown in AWS, in cloud, none whatsoever. The only slowdown we're seeing in cloud is GCP. But to, you know, to focus on AWS, extremely strong across the board and not only just in cloud, but in all their data products as well, data and analytics. >> Yeah and I think that the AWS, don't forget folks, that funds Amazon's TAM expansion into so many different places. Okay. As we said at the top, the world of digital and hybrid work, and multi-cloud, it's more complicated than it used to be. And that means if you need to resolve issues, which everybody does, like poor application performance, et cetera, what's happening at the user level, you have to have a better way to sort of see what's going on. And that's what the emergence of the observability space is all about. So Erik, let me set this up and you have a lot of comments here because you've recently had some, and you always have had a lot of round table discussions with CXOs on this topic. So this chart plots net score or spending momentum on the vertical axis, and market share or pervasiveness in the dataset on the horizontal axis. And we inserted a table that shows the data points in detail. Now that red dotted line is just sort of Dave Vellante's subjective mark in the sand for elevated spending levels. And there are three other points here. One is Splunk as well off is two-year peak, as highlighted in the red, but Signal FX, which Splunk acquired, has made a big move northward this last quarter. As has Datadog. So Erik, what can you share with us on this hot, but increasingly crowded space? >> Yeah. I could talk about the space for a long time. As you know, I've gotten some flack over the last year and a half about, you know, kind of pointing out this trend, this negative trend in Splunk. So I do want to be the first one to say that this data set is rebounding. Splunk has been horrific in our data for going back almost two years now, straight downward trend. This is the first time we're seeing any increase, any positivity there. So I do want to be fair and state that because I've been accused of being a little too negative on Splunk in the past. But I would basically say for observability right now, it's a rising tide lifts all boats, if I can use a New England phrase. The data across the board in analytics for these observability players is up, is accelerating. None more so than Datadog. And it's exactly your point, David. The complexity, the increased cloud migration is a perfect setup for Datadog, which is a cloud native. It focuses on microservices. It focuses on cloud observability. Old Splunk was just application monitoring. Don't get me wrong, they're changing, but they were on-prem application monitoring, first and foremost. Datadog came out as cloud native. They, you know, do microservices. This is just a perfect setup for them. And not only is Datadog leading the observability, it's leading the entire analytics sector, all of it. Not just the observability niche. So without a doubt, that is the strongest that we're seeing. It's leading Dynatrace new Relic. The only one that really isn't rebounding is Cisco App Dynamics. That's getting the dreaded legacy word really attached to it. But this space is really on fire, elastic as well, really doing well in this space. New Relic has shown a little bit of improvement as well. And what I heard when I asked my panelists about this, is that because of the maturity of cloud migration, that this observability has to grow. Spending on this has to happen. So they all say the chart looks right. And it's really just about the digital transformation maturity. So that's largely what they think is happening here. And they don't really see it getting, you know, changing anytime soon. >> Yeah, and I would add, and you see that it's getting crowded. You saw a service now acquired LightStep, and they want to get into the game. You mentioned, you know, last deck of the elk stack is, you know, the open source alternative, but then we see a company who's raised a fair amount of money, startup, chaos search, coming in, going after kind of the complexity of the elk stack. You've got honeycomb, which has got a really innovative approach, Jeremy Burton's company observes. So you have venture capital coming in. So we'll see if those guys could be disruptive enough or are they, you know, candidates to get acquired? We'll see how that all- you know that well. The M and A space. You think this space is ripe for M and A? >> I think it's ripe for consolidation, M and A. Something has to shake out. There's no doubt. I do believe that all of these can be standalone. So we shall see what's happened to, you mentioned the Splunk acquisition of Signal FX, just a house cleaning point. That was really nice acceleration by Signal FX, but it was only 20 citations. We'd looked into this a little bit deeper. Our data scientists did. It appears as if the majority of people are just signaling spunk and not FX separately. So moving forward for our data set, we're going to combine those two, so we don't have those anomalies going forward. But that type of acquisition does show what we should expect to see more of in this group going forward. >> Well that's I want to mention. That's one of the challenges that any data company has, and you guys do a great job of it. You're constantly having to reevaluate. There's so much M and A going on in the industry. You've got to pick the right spots in terms of when to consolidate. There's some big, you know, Dell and EMC, for example. You know, you've beautifully worked through that transition. You're seeing, you know, open shift and red hat with IBM. You just got to be flexible. And that's where it's valuable to be able to have a pipeline to guys like Erik, to sort of squint through that. So thank you for that clarification. >> Thank you too, because having a resource like you with industry knowledge really helps us navigate some of those as well for everyone out there. So that's a lot to do with you do Dave, >> Thank you. It's going to be interesting to watch Splunk. Doug Merritt's made some, you know, management changes, not the least of which is bringing in Teresa Carlson to run go to market. So if you know, I'd be interested if they are hitting, bouncing off the bottom and rising up again. They have a great customer base. Okay. Let's look at some of the same dimensions. Go ahead. You got a comment? >> A few of ETR's clients looked at our data and then put a billion dollar investment into it too. So obviously I agree. (Dave laughing) Splunk is looking like it's set for a rebound, and it's definitely something to watch, I agree. >> Not to rat hole in this, but I got to say. When I look back, cause theCUBE gives us kind of early visibility. So companies with momentum and you talk to the customers that all these shows that we go to. I will tell you that three companies stood out last decade. It was Splunk. It was Service Now and Tableau. And you could tell just from just discussions with their customers, the enthusiasm in that customer base. And so that's a real asset, and that helps them build them a moat. So we'll see. All right, let's take a look at the same dimensions now for cyber. This is cybersecurity net score in the vertical, and market share in the horizontal. And I filtered by in greater than a hundred shared in because just gets so crowded. Erik, the only things I would point out here is CrowdStrike and Zscaler continue to shine, CyberArk also showing momentum over that 40% line. Very impressively, Palo Alto networks, which has a big presence in the market. They've bounced back. We predicted that a while back. Your round table suggested people like working with Palo Alto. They're a gold standard. You know, we had reported earlier on that divergence with four to net in terms of valuation and some of the challenges they had in cloud, clearly, you know, back with the momentum. And of course, Microsoft in the upper, right. It's just, they're literally off the charts and obviously a major player here, but your thoughts on cyber? >> Erik: Yeah. Going back to the backdrop. Security, security, security. It has been the number one priority going back to last September. No one sees it changing. It has to happen. The threat vectors are actually expanding and we have no choice but to spend here. So it is not surprising to see. You did name our three favorite names. So as you know, we look at the dataset, we see which ones have the most positive inflections, and we put outlooks on those. And you did mention Zscaler, Okta and CrowdStrike, by far the three standouts that we're seeing. I just recently did a huge panel on Okta talking about their acquisition of Auth Zero. They're pushed into Sale Point space, trying to move just from single sign on and MFA to going to really privileged account management. There is some hurdles there. Really Okta's ability to do this on-prem is something that a little bit of the IT end users are concerned about. But what we're seeing right now, both Okta and Auth Zero are two of the main adopted names in security. They look incredibly well set up. Zscaler as well. With the ZTNA push more towards zero trust, Zscaler came out so hot in their IPO. And everyone was wondering if it was going to trail off just like Snowflake. It's not trailing off. This thing just keeps going up into the right, up into the right. The data supports a lot of tremendous growth for the three names that you just mentioned. >> Yeah. Yeah. I'm glad you brought up Auth Zero. We had reported on that earlier. I just feel like that was a great acquisition. You had Okta doing the belly to belly enterprise, you know, selling. And the one thing that they really lacked was that developer momentum. And that's what Auth Zero brings. Just a smart move by Todd McKinnon and company. And I mean, so this, you know, I want to, I want to pull up another chart show a quick snapshot of some of the players in the survey who show momentum and have you comment on this. We haven't mentioned Snowflake so far, but they remain again with like this gold standard of net score, they've consistently had those high marks with regard to spending velocity. But here's some other data. Erik, how should we interpret this? >> Erik: Yeah, just to harp on Snowflake for a second. Right, I mean the rich get richer. They came out- IPO was so hyped, so it was hard for us as a research company to say, "Oh, you know, well, you know, we agree." But we did. The data is incredible. You can't beat the management team. You can't beat what they're doing. They've got so much cash. I can't wait to see what they do with it. And meanwhile, you would expect something that debuted with that high of a net score, that high of spending velocity to trail off. It would be natural. It's not Dave, it's still accelerating. It's gone even higher. It's at all time highs. And we just don't see it stopping anytime soon. It's a really interesting space right now. Maybe another name to look at on here that I think is pretty interesting, kind of a play on return to business is Kupa. It's a great project expense management tool that got hit really hard. Listen, traveling stopped, business expense stopped, and I did a panel on it. And a lot of our guys basically said, "Yeah, it was the first thing I cut." But we're seeing a huge rebound in spending there in that space. So that's a name that I think might be worth being called out on a positive side. Negative, If you look down to the bottom right of that chart, unfortunately we're seeing some issues in RingCentral and Zoom. Anything that's sort of playing in this next, you know, video conferencing, IP telephony space, they seem to be having really decelerating spending. Also now with Zoom's acquisition of five nine. I'm not really sure how RingCentral's going to compete on that. But yeah, that's one where we debuted for the first time with a negative outlook on that name. And looking and asking to some of the people in our community, a lot of them say externally, you still need IP telepany, but internally you don't. Because the You Cast communication systems are getting so sophisticated, that if I have Teams, if I have Slack, I don't need phones anymore. (chuckling) That you and I can just do a Slack call. We can do a Teams call. And many of them are saying I'm truly ripping out my IP Telepany internally as soon as possible because we just don't need it. So this whole collaboration, productivity space is here to stay. And it's got wide ranging implications to some of these more legacy type of tools. >> You know, one of the other things I'd call out on this chart is Accenture. You and I had a session earlier this year, and we had predicted that that skill shortage was going to lead to an uptick in traditional services. We've certainly seen that. I mean, IBM beat its quarter on the strength of services largely. And seeing Accenture on that is I think confirmation. >> Yeah that was our New Year prediction show, right Dave? When we made top 10 predictions? >> That's right. That was part of our predictions show. Exactly, good memory. >> The data is really showing that continue. People want the projects, they need to do the projects, but hiring is very difficult. So obviously the number one beneficiary there are going to be the Accentures of the world. >> All right. So let's do a quick wrap. I'm going to make a few comments and then have you bring us home, Erik. So we laid out our scenario for the tech spending rebound. We definitely believe last year tracked downward, along with GDP contraction. It was interesting. Gardner doesn't believe, at least factions of Gardner don't believe there's a correlation between GDP and tech spending. But, you know, I personally think there generally is some kind of relatively proportional pattern there. And I think we saw contraction last year. People are concerned about inflation. Of course, that adds some uncertainty. And as well, as you mentioned around the Delta variant. But I feel as though that the boards of directors and CEOs, they've mandated that tech execs have to build out digital platforms for the future. They're data centric. They're highly automated, to your earlier points. They're intelligent with AI infused, and that's going to take investment. I feel like the tech community has said, "Look, we know what to do here. We're dealing with hybrid work. We can't just stop doing what we're doing. Let's move forward." You know, and as you say, we're flying again and so forth. You know, getting hybrid right is a major priority that directly impacts strategies. Technology strategies, particularly around security, cloud, the productivity of remote workers with collaboration. And as we've said many times, we are entering a new era of data that's going to focus on decentralized data, building data products, and Erik let's keep an eye on this observability space. Lot of interest there, and buyers have a number of choices. You know, do they go with a specialist, as we saw recently, we've seen in the past, or did they go with the generalist like Service Now with the acquisition of LightStep? You know, it's going to be interesting. A lot of people are going to get into this space, start bundling into larger platforms. And so as you said, there's probably not enough room for all the players. We're going to see some consolidation there. But anyway, let me give you the final word here. >> Yeah, no, I completely agree with all of it. And I think your earlier points are spot on, that analytics and automation are certainly going to be moving more and more to that left of that chart we had of priorities. I think as we continue that survey heading into 2022, we'll have some fresh data for you again in a few months, that's going to start looking at 2022 priorities and overall spend. And the one other area that I keep hearing about over and over and over again is customer experience. There's a transition from good old CRM to CXM. Right now, everything is digital. It is not going away. So you need an omni-channel support to not only track your customer experience, but improve it. Make sure there's a two way communication. And it's a really interesting space. Salesforce is going to migrate into it. We've got Qualtrics out there. You've got Medallia. You've got FreshWorks, you've got Sprinkler. You got some names out there. And everyone I keep talking to on the IT end user side keeps bringing up customer experience. So let's keep an eye on that as well. >> That's a great point. And again, it brings me back to Service Now. We wrote a piece last week that's sort of, Service Now and Salesforce are on a collision course. We've said that for many, many years. And you've got this platform of platforms. They're just kind of sucking in different functions saying, "Hey, we're friends with everybody." But as you know Erik, software companies, they want to own it all. (both chuckling) All right. Hey Erik, thank you so much. I want to thank you for coming back on. It's always a pleasure to have you on Breaking Analysis. Great to see you. >> Love the partnership. Love the collaboration. Let's go enjoy this summer Friday. >> All right. Let's do. Okay, remember everybody, these episodes, they're all available as podcasts, wherever you listen. All you got to do is search Breaking Analysis Podcast, click subscribe to the series. Check out ETR's website at etr.plus. They've just launched a new website. They've got a whole new pricing model. It's great to see that innovation going on. Now remember we also publish a full report every week on WikiBond.com and SiliconAngle.com. You can always email me, appreciate the back channel comments, the metadata insights. David.Vellante@SiliconAngle.com. DM me on Twitter @DVellante or comment on the LinkedIn posts. This is Dave Vellante for Erik Bradley and theCUBE insights powered by ETR. Have a great week, a good rest of summer, be well. And we'll see you next time. (inspiring music)
SUMMARY :
bringing you data-driven And at the macro level, We've got some fresh data to talk about and based on the recent earnings results So as the year has So Erik, I'm going to let back half of the year. and the other sectors that you see there. and a little bit more on the and Erik, the rest of the metrics Another point to you about and the CIO's expect that to land on returned to the office. on the hybrid models, I need the support staff to be in office. but the shift to a more One of my analysts said to me, And that means if you is that because of the last deck of the elk stack It appears as if the majority of people going on in the industry. So that's a lot to do with you do Dave, It's going to be something to watch, I agree. and some of the challenges that a little bit of the IT And I mean, so this, you know, I want to, Erik: Yeah, just to harp You know, one of the That was part of our predictions So obviously the number and that's going to take investment. And the one other area I want to thank you for coming back on. Love the partnership. It's great to see that
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Breaking Analysis: Mobile World Congress Highlights Telco Transformation
>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> Mobile World Congress is alive, theCUBE will be there and we'll certainly let you know if it's alive and well when we get on the ground. Now, as we approach a delayed mobile world congress, it's really appropriate to reflect in the state of the telecoms industry. Let's face it. Telcos have done of really good job of keeping us all connected during the pandemic, supporting work from home and that whole pivot, accommodating the rapid shift to landline traffic, securing the network and keeping it up and running but it doesn't change the underlying fundamental dilemma that Telco has faced. Telco is a slow growth, no growth industry, with revenue expectations in the low single digits. And at the same time network traffic continues to grow at 20% annually. And last year it grew at 40% to 50%. Despite these challenges, Telcos are still investing in the future. For example, the Telco industry collectively is selling out more than a trillion dollars in the first half of this decade on 5G and fiber infrastructure. And it's estimated that there are now more than 200 5G networks worldwide. But a lot of questions remain, not the least of which is, can and should Telcos go beyond connectivity and fiber. Can the Telcos actually monetize 5G or whatever's next beyond 5G? Or is that going to be left to the ecosystem? Now what about the ecosystem? How is that evolving? And very importantly, what role will the Cloud Hyperscalers play in Telco? Are they infrastructure on which the Telcos can build or are they going to suck the value out of the market as they have done in the enterprise? Hello everyone, and welcome to this week's Wiki Bond Cube Insights powered by ETR. In this breaking analysis, it's my pleasure to welcome a long time telecoms industry analyst and colleague, and the founding director of Lewis Insight, Mr. Chris Lewis. Chris, welcome to the program. Thanks for coming on >> Dave, it's a pleasure to be here. Thank you for having me. >> It is really our pleasure. So, we're going to cover a lot of ground today. And first thing, we're going to talk about Mobile World Congress. I've never been, you're an expert at that and what we can expect. And then we're going to review the current state of telecoms infrastructure, where it should go. We're going to dig into transformation. Is it a mandate? Is it aspirational? Can Telcos enter adjacent markets in ways they haven't been able to in the past? And then how about the ecosystem? We're going to talk about that, and then obviously we're going to talk about Cloud as I said, and we'll riff a little bit on the tech landscape. So Chris, let's get into it, Mobile World Congress, it's back on, what's Mobile World Congress typically like? What's your expectation this year for the vibe compared to previous events? >> Well Dave, the issue of Mobile World Congress is always that we go down there for a week into Barcelona. We stress ourselves building a matrix of meetings in 30 minutes slots and we return at the end of it trying to remember what we'd been told all the way through. The great thing is that with the last time we had a live, with around 110,000 people there, you could see anyone and everyone you needed to within the mobile, and increasingly the adjacent industry and ecosystem. So, he gave you that once a year, big download of everything new, obviously because it's the Mobile World Congress, a lot of it around devices, but increasingly over the last few years, we saw many, many stands with cars on them because the connected car became an issue, a lot more software oriented players there, but always the Telcos, always the people providing the network infrastructure. Increasingly in the last few years people provided the software and IT infrastructure, but all of these people contributing to what the network should be in the future, what needs to be connected. But of course the reach of the network has been growing. You mentioned during lockdown about connecting people in their homes, well, of course we've also been extending that connection to connect things whether it's in the home or the different devices, monitoring of doorbells and lights and all that sort of stuff. And in the industry environment, connecting all of the robots and sensors. So, actually the perimeter, the remit of the industry to connect has been expanding, and so is the sort of remit of Mobile World Congress. So, we set an awful lot of different suppliers coming in, trying to attach to this enormous market of roughly $1.5 trillion globally. >> Chris, what's the buzz in the industry in terms of who's going to show up. I know a lot of people have pulled out, I've got the Mobile World Congress app and I can see who's attending. And it looks like quite a few people are going to go but what's your expectation? >> Well, from an analyst point of view, obviously I'm mainly keeping up with my clients and trying to get new clients. I'm looking at it and going most of my clients are not attending in person. Now, of course, we need the DSMA, we need Mobile World Congress for future for the industry interaction. But of course, like many people having adopted and adapted to be online, then they're putting a lot of the keynotes online, a lot of the activities will be online. But of course many of the vendors have also produced their independent content and content to actually deliver to us as analysts. So, I'm not sure who will be there. I like you, but you'll be on the ground. You'll be able to report back and let us know exactly who turned up. But from my point of view, I've had so many pre-briefs already, the difference between this year and previous years, I used to get loads of pre-briefs and then have to go do the briefs as well. So this year I've got the pre-brief so I can sit back, put my feet up and wait for your report to come back as to what's happening on the ground. >> You got it. Okay, let's get into a little bit and talk about Telco infrastructure and the state, where it is today, where it's going, Chris, how would you describe the current state of Telco infrastructure? Where does it need to go? Like, what is the ideal future state look like for Telcos in your view? >> So there's always a bit of an identity crisis when it comes to Telco. I think going forward, the connectivity piece was seen as being table stakes, and then people thought where can we go beyond connectivity? And we'll come back to that later. But actually to the connectivity under the scenario I just described of people, buildings, things, and society, we've got to do a lot more work to make that connectivity extend, to be more reliable, to be more secure. So, the state of the network is that we have been building out infrastructure, which includes fiber to connect households and businesses. It includes that next move to cellular from 4G to 5G. It obviously includes Wi-Fi, wherever we've got that as well. And actually it's been a pretty good state, as you said in your opening comments they've done a pretty good job keeping us all connected during the pandemic, whether we're a fixed centric market like the UK with a lot of mobile on top and like the US, or in many markets in Africa and Asia, where we're very mobile centric. So, the fact is that every country market is different, so we should never make too many assumptions at a very top level, but building out that network, building out the services, focusing on that connectivity and making sure we get that cost of delivery right, because competition is pushing us towards having and not ever increasing prices, because we don't want to pay a lot extra every time. But the big issue for me is how do we bring together the IT and the network parts of this story to make sure that we build that efficiency in, and that brings in many questions that we going to touch upon now around Cloud and Hyperscalers around who plays in the ecosystem. >> Well, as you know, Telco is not my wheelhouse, but hanging around with you, I've learned, you've talked a lot about the infrastructure being fit for purpose. It's easy from an IT perspective. Oh yeah, it's fossilized, it's hardened, and it's not really flexible, but the flip side of that coin is as you're pointing out, it's super reliable. So, the big talk today is, "Okay, we're going to open up the network, open systems, and Open RAN, and open everything and microservices and containers. And so, the question is this, can you mimic that historical reliability in that open platform? >> Well, for me, this is the big trade-off and in my great Telco debate every year, I always try and put people against each other to try and to literally debate the future. And one of the things we looked at was is a more open network against this desire of the Telcos to actually have a smaller supplier roster. And of course, as a major corporation, these are on a national basis, very large companies, not large compared to the Hyperscalers for example, but they're large organizations, and they're trying to slim down their organization, slim down the supplier ecosystem. So actually in some ways, the more open it becomes, the more someone's got to manage and integrate all those pieces together. And that isn't something we want to do necessarily. So, I see a real tension there between giving more and more to the traditional suppliers. The Nokia's, Ericsson's, Huawei's, Amdocs and so on, the Ciscos. And then the people coming in breaking new ground like Mavenir and come in, and the sort of approach that Rakuten and Curve taken in bringing in more open and more malleable pieces of smaller software. So yeah, it's a real challenge. And I think as an industry which is notorious for being slow moving, actually we've begun to move relatively quickly, but not necessarily all the way through the organization. We've got plenty of stuff sitting on major or mainframes still in the back of the organization. But of course, as mobile has come in, we've started to deal much more closely, uninteractively in real time, God forbid, with the customers. So actually, at that front end, we've had to do things a lot more quickly. And that's where we're seeing the quickest adaptation to what you might see in your IT environment as being much more, continuous development, continuous improvement, and that sort of on demand delivery. >> Yeah, and we're going to get to that sort of in the Cloud space, but I want to now touch on Telco transformation which is sort of the main theme of this episode. And there's a lot of discussion on this topic, can Telcos move beyond connectivity and managing fiber? Is this a mandate? Is it a pipe dream that's just aspirational? Can they attack adjacencies to grow beyond the 1% a year? I mean, they haven't been successful historically. What are those adjacencies that might be, an opportunity and how will that ecosystem develop? >> Sure. >> So Chris, can and should Telcos try to move beyond core connectivity? Let's start there. >> I like what you did there by saying pipe dreams. Normally, pipe is a is a negative comment in the telecom world. But pipe dream gives it a real positive feel. So can they move beyond connectivity? Well, first of all, connectivity is growing in terms of the number of things being connected. So, in that sense, the market is growing. What we pay for that connectivity is not necessarily growing. So, therefore the mandate is absolutely to transform the inner workings and reduce the cost of delivery. So, that's the internal perspective. The external perspective is that we've tried in many Telcos around the world to break into those adjacent markets, being around media, being enterprise, being around IOT, and actually for the most part they've failed. And we've seen some very significant recent announcements from AT&T, Verizon, BT, beginning to move away from, owning content and not delivering content, but owning content. And the same as they've struggled often in the enterprise market to really get into that, because it's a well-established channel of delivery bringing all those ecosystem players in. So, actually rather than the old Telco view of we going to move into adjacent markets and control those markets, actually moving into them and enabling fellow ecosystem players to deliver the service is what I think we're beginning to see a lot more of now. And that's the big change, it's actually learning to play with the other people in the ecosystem. I always use a phrase that there's no room for egos in the ecosystem. And I think Telcos went in initially with an ego thinking we're really important, we are on connectivity. But actually now they're beginning to approach the ecosystem things saying, "How can we support partners? How can we support everyone in this ecosystem to deliver the services to consumers, businesses and whomever in this evolving ecosystem?" So, there are opportunities out there, plenty of them, but of course, like any opportunity, you've got to approach it in the right way. You've got to get the right investment in place. You've got to approach it with the right open API so everyone can integrate with your approach, and approach it, do I say with a little bit of humility to say, "Hey, we can bring this to the table, how do we work together? >> Well, it's an enormous market. I think you've shared with me, it's like 1.4 trillion. And I want to stay on these adjacencies for a minute, because one of the obvious things that Telcos will talk about is managed services. And I know we have to be careful of that term in an IT context, that it's different in a, you're talking about managing connectivity, but there's professional services. That's a logical sort of extension of their business and probably a safe adjacency, maybe not even adjacency, but they're not going to get into devices. I mean, they'll resell devices, but they're not going to be, I would presume not go back to trying to make devices, but there's certainly the edge and that's so, it'll define in opaque, but it's huge. If there's 5G, there's the IT component and that's probably a partnership opportunity. And as you pointed out, there's the ecosystem, but I wonder, how do you think about 5G as an adjacency or indoor opportunity? Is it a revenue opportunity for Telcos or is that just something that is really aspirational? >> Oh, absolutely it's a revenue opportunity, but I prefer to think of 5G as being a sort of a metaphor for the whole future of telecom. So, we usually talk, and MWC would normally talk about 5G just as a mobile solution. Of course, what you can get with, you can use this fixed wireless access approach, where the roots that sits in your house or your building. So, it's a potential replacement for some fixed lines. And of course, it's also, gives you the ability to build out, let's say in a manufacturing or a campus environment, a private 5G network. So, many of the early opportunities we're seeing with 5G are actually in that more private network environment addressing those very low latency, and high bandwidth requirements. So yeah, there are plenty of opportunities. Of course, the question here is, is connectivity enough, or especially with your comment around the edge, at the edge we need to manage connectivity, storage, compute, analytics, and of course the applications. So, that's a blend of players. It's not going to be in the hands of one player. So yes, plenty of opportunities but understanding what comes the other way from the customer base, where that's, you and I in our homes or outward as an about, or from a business point of view, an office or a campus environment, that's what should be driving, and not the technology itself. And I think this is the trap that the industry has fallen into many times, is we've got a great new wave of technology coming, how can we possibly deliver it to everybody rather than listening to what the customers really require and delivering it in a way consumable by all those different markets. >> Yeah now, of course all of these topics blend together. We try to keep them separately, but we're going to talk about Cloud, we're going to talk about competition, But one of the areas that we don't have a specific agenda item on is, is data and AI. And of course there's all this data flowing through the network, so presumably it's an opportunity for the Telcos. At the same time, they're not considered AI experts. They do when you talk about Edge, they would appear to have the latency advantage because of the last mile and their proximity, to various end points. But the Cloud is sort of building out as well. How do you think about data and AI as an opportunity for Telco? >> I think the whole data and AI piece for me sits on top of the cake or pie, whatever you want to call it. What we're doing with all this connectivity, what we're doing with all these moving parts and gathering information around it, and building automation into the delivery of the service, and using the analytics, whether you call it ML or AI, it doesn't really matter. But actually using that information to deliver a better service, a better outcome. Now, of course, Telcos have had much of this data for years and years, for decades, but they've never used it. So, I think what's happening is, the Cloud players are beginning to educate many of the Telcos around how valuable this stuff is. And that then brings in that question of how do we partner with people using open APIs to leverage that data. Now, do the Telcos keep hold of all that data? Do they let the Cloud players do all of it? No, it's going to be a combination depending on particular environments, and of course the people owning their devices also have a vested interest in this as well. So, you've always got to look at it end to end and where the data flows are, and where we can analyze it. But I agree that analysis on the device at the Edge, and perhaps less and less going back to the core, which is of course the original sort of mandate of the Cloud. >> Well, we certainly think that most of the Edge is going to be about AI inferencing, and then most of the data is going to stay at the edge. Some will come back for sure. And that is big opportunity for whether you're selling compute or conductivity, or maybe storage as well, but certainly insights at the Edge. >> Everything. >> Yeah. >> Everything, yeah. >> Let's get into the Cloud discussion and talk about the Hyperscalers, the big Hyperscaler elephant in the room. We're going to try to dig into what role the Cloud will play in the transformation of telecoms on Telecom TV at the great Telco debate. You likened the Hyperscalers, Chris, to Dementors from Harry Potter hovering over the industry. So, the question is, are the Cloud players going to suck the value out of the Telcos? Or are they more like Dobby the elf? They're powerful, there's sometimes friendly but they're unpredictable. >> Thank you for extending that analogy. Yes, it got a lot of reaction when I use that, but I think it indicates some of the direction of power shift where, we've got to remember here that Telcos are fundamentally national, and they're restricted by regulation, and the Cloud players are global, perhaps not as global as they'd like be, but some regional restrictions, but the global players, the Hyperscalers, they will use that power and they they will extend their reach, and they are extending their reach. If you think they now command some fantastic global networks, in some ways they've replaced some of the Telco international networks, all the submarine investments that tend to be done primarily for the Hyperscalers. So, they're building that out. So, as soon as you get onto their network, then you suddenly become part of that environment. And that is reducing some of the spend on the longer distances we might have got in the past approaches from the Telcos. Now, does that mean they're going to go all the way down and take over the Telcos? I don't believe so, because it's a fundamentally different business digging fiber in people's streets and delivering to the buildings, and putting antennas up. So, they will be a coexistence. And in fact, what we've already seen with Cloud and the Hyperscalers is that they're working much more close together than people might imagine. Now, you mentioned about data in the previous question, Google probably the best known of the of the AI and ML delivers from the Cloud side, working with many of the Telcos, even in some cases to actually have all the data outsourced into the Google Cloud for analytics purposes. They've got the power, the heavy lifting to do that. And so, we begin to see that, and obviously with shifting of workloads as appropriate within the Telco networking environment, we're seeing that with AWS, and of course with Azure as well. And Azure of course acquired a couple of companies in affirmed and Metro switch, which actually do some of the formal 5G core and the likes there within the connectivity environment. So, it's not clean cuts. And to go back to the analogy, those Dementors are swooping around and looking for opportunities, and we know that they will pick up opportunities, and they will extend their reach as far as they can down to that edge. But of course, the edge is where, as you rightly say, the Telcos have the control, they don't necessarily own the customer. I don't believe anyone owns the customer in this digital environment, because digital allows you to move your allegiance and your custom elsewhere anyway. So, but they do own that access piece, and that's what's important from a national point of view, from an economic point of view. And that's why we've seen some of the geopolitical activity banning Huawei from certain markets, encouraging more innovation through open ecosystem plays. And so, there is a tension there between the local Telco, the local market and the Hyperscaler market, but fundamentally they've got an absolute brilliant way of working together using the best of both worlds to deliver the services that we need as an economy. >> Well, and we've talked about this you and I in the past where the Telcos, portions of the Telco network could move into the Cloud. And there of course the Telcos all run the big data centers, and portions of that IT infrastructure could move into the Cloud. But it's very clear, they're not going to give up the entire family jewels to the Cloud players. Why would they? But there are portions of their IT that they could move into. Particularly, in the front end, they want to build like everybody. They want to build an abstraction layer. They're not going to move their core systems and their backend Oracle databases, they're going to put a brick wall around those, but they wanted abstraction layer, and they want to take advantage of microservices and use that data from those transaction systems. But the web front end stuff makes sense to put into Cloud. So, how do you think about that? >> I think you've hit the nail on the head. So you can't move those big backend systems straight away, gradually over time, you will, but you've got to go for those easy wins. And certainly in the research I've been doing with many of my clients, they're suggested that front end piece, making sure that you can onboard customers more easily, you can get the right mix of services. You can provide the omnichannel interaction from that customer experience that everybody talks about, for which the industry is not very well known at all by the way. So, any improvement on that is going to be good from an MPS point of view. So yeah, leveraging what we might, what we call BSS OSS in the telecom world, and actually putting that into the Cloud, leveraging both the Hyperscalers, but also by the way, many of the traditional players who people think haven't moved Cloud wards, but they are moving Cloud wards and they're embracing microservices and Cloud native. So, what you would have seen if we'd been in person down in Barcelona next week, would be a lot of the vendors who perhaps traditionally seems a bit slow moving, actually have done a lot of work to move their portfolio into the Cloud and into Cloud native environments. And yes, as you say, we can use that front end, we can use the API openness that's developed by people at the TM forum, to actually make sure we don't have to do the backend straight away, do it over time. Because of course the thing that we're not touching upon here, is the revenue stream is a consistent revenue stream. So, just because you don't need to change the backend to keep your revenue stream going, this is on a new, it keeps delivering every month, we keep paying our 50, 40, whatever bucks a month into the Telco pot. That's why it's such a big market, and people aren't going to stop doing that. So, I think the dynamics of the industry, we often spend a lot of time thinking about the inner workings of it and the potential of adjacent markets, whereas actually, we keep paying for this stuff, we keep pushing revenue into the pockets of all the Telcos. So, it's not a bad industry to be in, even if they were just pushed back to be in the access market, it's a great business. We need it more and more. The elasticity of demand is very inelastic, we need it. >> Yeah, it's the mother of old golden geese. We don't have a separate topic on security, and I want to touch on security here, is such an important topic. And it's top of mind obviously for everybody, Telcos, Hyperscalers, the Hyperscalers have this shared responsibility model, you know it well. A lot of times it's really confusing for customers. They don't realize it until there has been a problem. The Telcos are going to be very much tuned into this. How will all this openness, and we're going to talk about technology in a moment, but how will this transformation in your view, in the Cloud, with the shared responsibility model, how will that affect the whole security posture? >> Security is a great subject, and I do not specialize in it. I don't claim to be an expert by any stretch of the imagination, but I would say security for me is a bit like AI and analytics. It's everywhere. It's part of everything. And therefore you cannot think of it as a separate add on issue. So, every aspect, every element, every service you build into your micro services environment has to think about how do you secure that connection, that transaction, how do you secure the customer's data? Obviously, sovereignty plays a role in that as well in terms of where it sits, but at every level of every connection, every hop that we look through, every route to jump, we've got to see that security is built in. And in some ways, it's seen as being a separate part of the industry, but actually, as we collapse parts of the network down, we're talking about bringing optical and rooting together in many environments, security should be talked about in the same breath. So when I talked about Edge, when I talked about connectivity, storage, compute, analytics, I should've said security as well, because I absolutely believe that is fundamental to every chain in the link and let's face it, we've got a lot of links in the chain. >> Yeah, 100%. Okay, let's hit on technologies and competition, we kind of blend those together. What technology should we be paying attention to that are going to accelerate this transformation. We hear a lot about 5G, Open RAN. There's a lot of new tech coming in. What are you watching? Who are the players that we maybe should be paying attention to, some that you really like, that are well positioned? >> We've touched upon it in various of the questions that have proceeded this. So, the sort of Cloudification of the networking environment is obviously really important. The automation of the process we've got to move away from bureaucratic manual processes within these large organizations, because we've got to be more efficient, we've got to be more reliable. So, anything which is related to automation. And then the Open RAN question is really interesting. Once again, you raised this topic of when you go down an Open RAN routes or any open route, it ultimately requires more integration. You've got more moving parts from more suppliers. So, therefore there are potential security issues there, depending on how it's defined, but everybody is entering the Open RAN market. There are some names that you will see regularly next week, being pushed, I'm not going to push them anymore, because some of them just attract the oxygen of attention. But there are plenty out there. The good news is, the key vendors who come from the more traditional side are also absolutely embracing that and accept the openness. But I think the piece which probably excites me more, apart from the whole shift towards Cloud and microservices, is the coming together, the openness between the IT environment and the networking environment. And you see it, for example, in the Open RAN, this thing called the RIC, the RAN Interconnection Controller. We're actually, we're beginning to find people come from the IT side able to control elements within the wireless controller piece. Now that that starts to say to me, we're getting a real handle on it, anybody can manage it. So, more specialization is required, but understanding how the end to end flow works. What we will see of course is announcements about new devices, the big guys like Apple and Samsung do their own thing during the year, and don't interrupt their beat with it with MWC, but you'll see a lot of devices being pushed by many other providers, and you'll see many players trying to break into the different elements of the market. But I think mostly, you'll see the people approaching it from more and more Cloudified angle where things are much more leveraging, that Cloud capability and not relying on the sort of rigid and stodgy infrastructure that we've seen in the past >> Which is kind of interesting because Cloud, a lot of the Clouds are Walled Gardens, at the same time they host a lot of open technologies, and I think as these two worlds collide, IT and the Telco industry, it's going to be interesting to see how the Telco developer ecosystem evolves. And so, that's something that we definitely want to watch. You've got a comment there? >> Yeah, I think the Telco developer they've not traditionally been very big in that area at all, have they? They've had their traditional, if you go back to when you and I were kids, the plain old telephone service was a, they were a one trick pony, and they've moved onto that. In some ways, I'd like them to move on and to have the one trick of plain old broadband that we just get broadband delivered everywhere. So, there are some issues about delivering service to all parts of every country, and obviously the globe, whether we do that through satellite, we might see some interesting satellite stuff coming out during NWC. There's an awful lot of birds flying up there trying to deliver signal back to the ground. Traditionally, that's not been very well received, with the change in generation of satellite might help do that. But we've known traditionally that a lot of developer activity in there, what it does bring to the four though, Dave, is this issue of players like the Ciscos and Junipers, and all these guys of the world who bring a developer community to the table as well. This is where the ecosystem play comes in, because that's where you get the innovation in the application world, working with channels, working with individual applications. And so it's opening up, it's basically building a massive fabric that anybody can tap into, and that's what becomes so exciting. So, the barriers to entry come down, but I think it will see us settling down, a stabilization of relationship between the Telcos and the Hyperscalers, because they need each other as we talked about previously, then the major providers, the Ciscos, Nokias, Ericssons, Huawei's, the way they interact with the Telcos. And then allowing that level of innovation coming in from the smaller players, whether it's on a national or a global basis. So, it's actually a really exciting environment. >> So I want to continue that theme and just talk about Telco in the enterprise. And Chris, on this topic, I want to just touch on some things and bring in some survey data from ETR, Enterprise Technology Research, our partner. And of course the Telcos, they've got lots of data centers. And as we talked about, they're going to be moving certain portions into the Cloud, lots of the front end pieces in particular, but let's look at the momentum of some of the IT players within the ETR dataset, and look at how they compare to some of the Telcos that ETR captures specifically within the Telco industry. So, we filtered this data on the Telco industry. So, this is our X, Y graph that we show you oftentimes on the vertical axis, is net score which measures spending momentum, and in the horizontal axis is market share, which is a measure of pervasiveness in the dataset. Now, this data is for shared accounts just in the Telco sector. So we filtered on certain sectors, like within the technology sectors, Cloud, networking, and so it's narrow, it's a narrow slice of the 1500. It respondents, it represents about 133 shared accounts. And a couple of things to jump right out. Within the Telco industry, it's no surprise, but Azure and AWS have massive presence on the horizontal axis, but what's notable as they score very highly in the vertical axis, with elevated spending velocity on their platforms within Telco. Google Cloud doesn't have as much of a presence, but it's elevated as well. Chris was talking about their data posture before, Arista and Verizon, along with VMware are also elevated, as is Aruba, which is HPEs networking division, but they don't have the presence on the horizontal axis. And you got Red Hat OpenStack is actually quite prominent in Telco as we've reported in previous segments. Is no surprise You see Akamai there. Now remember, this survey is weighted toward enterprise IT, so you have to take that into consideration, but look at Cisco, very strong presence, nicely elevated as is Equinox, both higher than many of the others including Dell, but you could see Dell actually has pretty respectable spending in Telco. It's an area that they're starting to focus on more. And then you got that cluster below, your Juniper, AT&T, Oracle, the rest of HPE TELUM and Lumen which is formerly, century link via IBM. Now again, I'm going to caution you. This is an enterprise IT heavy survey, but the big takeaway is the Cloud players have a major presence inside of firms that say they're in the telecommunications industry. And certain IT players like Cisco, VMware and Red Hat appear to be well positioned inside these accounts. So Chris, I'm not sure if any of this commentary resonates with you, but it seems that the Telcos would love to partner up with traditional IT vendors and Cloud players, and maybe find ways to grow their respective businesses. >> I think some of the data points you brought out there are very important. So yes, we've seen a Microsoft Azure and AWS very strong working with Telcos. We've seen Google Cloud platform actually really aggressively pushed into the market certainly the last 12, 24 months. So yeah, they're well positioned, and they all come from a slightly different background. As I said, the Google with this, perhaps more data centric approach in its analytics, tools very useful, AWS with this outpost reaching out, connecting out, and as you'll, with its knowledge of the the Microsoft business market certainly pushing into private networks as well, by the way. So yeah, and Cisco, of course in there does have, and it's a mass scale division, a lot of activity there, some of the people collapsing, some of that rooting an obstacle together, their big push on Silicon. So, what you've got here is a sort of cross representation of many of the different sorts of suppliers who are active in this market. Now Telcos is a big spenders, the telecom market, as we said, a $1.4 trillion market, they spend a lot, they probably have to double bubble spend at the moment to get over the hump of 5G investment, to build out fiber where they need to build out. So, any anything that relates to that is of course a major spending opportunity, a major market opportunity for players. And we know when you need the infrastructure behind it, whether it's in data centers or in their own data centers or in the Cloud to deliver against it. So, what I do like about this as an analyst, a lot of people would focus on one particular piece of the market. So you specialize on handsets, people specialize on home markets and home gateways. So, I tend to sit back and try and look at the big picture, the whole picture. And I think we're beginning to see some very good momentum where people are, where companies are building upon, of course their core business within the telecom industry, extending it out. But the lines of demarcation are blurring between enterprise, Telco, and indeed moving down into small business. And you think about the SD-WAN Market, which came from nowhere to build a much more flexible solution for connecting people over the wide area network, which has been brilliant during the pandemic, because it's allowed us to extend that to home, but be of course, build a campus ready for the future as well. So there are plenty of opportunities out there. I think the big question in my mind is always about from going into the Telco, as I said, whether they wannna reduce the number of suppliers on the roster. So that puts a question mark against some of the open approaches, and then from the Telco to the end customer, because it goes to the Telcos, 30% of their revenue comes from the enterprise market, 60% from the consumer market. How do they leverage the channel? Which includes all the channels, we talked about security, all of the IT stuff that you've already touched upon and the Cloud. It's going to be a very interesting mix and balancing act between different channels to get the services that the customers want. And I think increasingly, customers are more aware of the opportunities open to them to reach back into this ecosystem and say, "Yeah, I want a piece of humans to Telco, but I want it to come to me through my local integrated channel, because I need a bit of their expertise on security." So, fascinating market, and I think not telecom's no longer considered in isolation, but very much as part of that broader digital ecosystem. >> Chris, it's very hard to compress an analysis of a $1.4 trillion business into 30 or 35 minutes, but you're just the guy to help me do it. So, I got to really thank you for participating today and bringing your knowledge. Awesome. >> Do you know, it's my pleasure. I love looking at this market. Obviously I love analogies like Harry Potter, which makes it bring things to life. But at the end of the day, we as people, we want to be connected, we as business, we want to be connected, in society we want to be connected. So, the fundamental of this industry are unbelievably strong. Let's hope that governments don't mess with it too much. And let's hope that we get the right technology comes through, and help support that world of connectivity going forward. >> All right, Chris, well, I'll be texting you from Mobile World Congress in Barcelona, and many thanks to my colleague, Chris Lewis, he brought some serious knowledge today and thank you. And remember, I publish each week on wikibond.com and siliconangle.com. And these episodes are all available as podcasts. You just got to search for Breaking Analysis podcasts. You can always connect with me on twitter @dvellante or email me at dave.vellante@siliconangle.com. And you can comment on my LinkedIn post, and don't forget to check out etr.plus for all the survey data. This is Dave Vellante, for theCUBE Insights powered by ETR. Be well, and we'll see you next time. (upbeat music)
SUMMARY :
bringing you data-driven and the founding director of Dave, it's a pleasure to be here. bit on the tech landscape. the remit of the industry to I've got the Mobile World Congress app a lot of the activities will be online. describe the current state and the network parts of this story And so, the question is this, And one of the things we looked at was sort of in the Cloud space, So Chris, can and should Telcos So, in that sense, the market is growing. because one of the and of course the applications. because of the last mile and of course the people but certainly insights at the Edge. and talk about the Hyperscalers, And that is reducing some of the spend in the past where the Telcos, and actually putting that into the Cloud, in the Cloud, with the about in the same breath. Who are the players that we maybe and not relying on the sort of rigid a lot of the Clouds are Walled Gardens, So, the barriers to entry come down, and in the horizontal or in the Cloud to deliver against it. So, I got to really thank So, the fundamental of this industry for all the survey data.
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Day 1 Keynote Analysis | AWS re:Invent 2020
>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS and our community partners. >>Everyone welcome to the cubes Live coverage of AWS reinvent 2020 virtual were virtual this year We are the Cube Virtual I'm your host John for a joint day Volonte for keynote analysis Andy Jassy just delivered his live keynote. This is our live keynote analysis. Dave. Great to see you, Andy Jassy again. You know their eight year covering reinvent their ninth year. We're virtual. We're not in person. We're doing it. >>Great to see you, John. Even though we're 3000 miles apart, we both have the covert here. Do going Happy birthday, my friend. >>Thank you. Congratulations. Five years ago I was 50 and they had the cake on stage and on the floor. There's no floor, this year's virtual and I think one of the things that came out of Andy Jessie's keynote, obviously, you know, I met with him earlier. Telegraph some of these these moves was one thing that surprised me. He came right out of the gate. He acknowledged that social change, the cultural shift. Um, that was interesting but he went in and did his normal end to end. Slew of announcements, big themes around pivoting. And he brought kind of this business school kind of leadership vibe to the table early talking about what people are experiencing companies like ourselves and others around the change and cultural change around companies and leadership. It takes for the cloud. And this was a big theme of reinvent, literally like, Hey, don't hold on to the old And I kept thinking to myself, David, you and I both are Historians of the tech industry remind me of when I was young, breaking into the business, the mainframe guys and gals, they were hugging onto those mainframes as long as they could, and I looked at it like That's not gonna be around much longer. And they kept No, it's gonna be around. This is this is the state of the art, and then the extinction. Instantly this feels like cloud moment, where it's like it's the wake up call. Hey, everyone doing it the old way. You're done. This is it. But you know, this is a big theme. >>Yes. So, I mean, how do you curate 2.5 3 hours of Andy Jassy. So I tried to break it down at the three things in addition to what you just mentioned about him acknowledging the social unrest and and the inequalities, particularly with black people. Uh, but so I had market leadership. And there's some nuance there that if we have time, I'd love to talk about, uh, the feature innovation. I mean, that was the bulk of his presentation, and I was very pleased. I wrote a piece this weekend. As you know, talk about Cloud 2030 and my main focus was the last 10 years about I t transformation the next 10 years. They're gonna be about organizational and business and industry transformation. I saw a lot of that in jazz ces keynote. So you know, where do you wanna go? We've only got a few minutes here, John, >>but let's break. Let's break down the high level theme before we get into the announcement. The thematic part was, it's about reinventing 2020. The digital transformation is being forced upon us. Either you're in the cloud or you're not in the cloud. Either way, you got to get to the cloud for to survive in this post covert error. Um, you heard a lot about redefining compute new chips, custom chips. They announced the deal with Intel, but then he's like we're better and faster on our custom side. That was kind of a key thing, this high idea of computing, I think that comes into play with edge and hybrid. The other thing that was notable was Jessie's almost announcement of redefining hybrid. There's no product announcement, but he was essentially announcing. Hybrid is changed, and he was leaning forward with his definition of redefining what hybrid cloud is. And I think that to me was the biggest, um, signal. And then finally, what got my attention was the absolute overt call out of Microsoft and Oracle, and, you know, suddenly, behind the scenes on the database shift we've been saying for multiple times. Multiple databases in the cloud he laid that out, said there will be no one thing to rule anything. No databases. And he called out Microsoft would look at Microsoft. Some people like cloud wars. Bob Evans, our good friend, claims that Microsoft been number one in the cloud for like like year, and it's just not true right. That's just not number one. He used his revenue a za benchmark. And if you look at Microsoft's revenue, bulk of it is from propped up from Windows Server and Sequel Server. They have Get up in there that's new. And then a bunch of professional services and some eyes and passed. If you look at true cloud revenue, there's not much there, Dave. They're definitely not number one. I think Jassy kind of throws a dagger in there with saying, Hey, if you're paying for licenses mawr on Amazon versus Azure that's old school shenanigans or sales tactics. And he called that out. That, to me, was pretty aggressive. And then So I finally just cove in management stuff. Democratizing machine learning. >>Let me pick up on a couple things. There actually were a number of hybrid announcements. Um, E C s anywhere E k s anywhere. So kubernetes anywhere containers anywhere smaller outposts, new local zones, announced 12 new cities, including Boston, and then Jesse rattle them off and made a sort of a joke to himself that you made that I remembered all 12 because the guy uses no notes. He's just amazing. He's up there for three hours, no notes and then new wavelength zones for for the five g edge. So actually a lot of hybrid announcements, basically, to your point redefining hybrid. Basically, bringing the cloud to the edge of which he kind of redefined the data center is just sort of another edge location. >>Well, I mean, my point was Is that my point is that he Actually, Reid said it needs to be redefined. Any kind of paused there and then went into the announcements. And, you know, I think you know, it's funny how you called out Microsoft. I was just saying which I think was really pivotal. We're gonna dig into that Babel Babel Fish Open source thing, which could be complete competitive strategy, move against Microsoft. But in a way, Dave Jassy is pulling and Amazon's pulling the same move Microsoft did decades ago. Remember, embrace and extend right Bill Gates's philosophy. This is kind of what they're doing. They have embraced hybrid. They have embraced the data center. They're extending it out. You're seeing outpost, You see, five g, You're seeing these I o t edge points. They're putting Amazon everywhere. That was my take away. They call it Amazon anywhere. I think it's everywhere. They want cloud operations everywhere. That's the theme that I see kind of bubbling out there saying, Hey, we're just gonna keep keep doing this. >>Well, what I like about it is and I've said this for a long time now that the edge is gonna be one by developers. And so they essentially taking AWS and the data center is an AP, and they're bringing that data center is an A P I virtually everywhere. As you're saying, I wanna go back to something you said about leadership and Microsoft and the numbers because I've done a lot of homework on this Aziz, you know, And so Jassy made the point. He makes this point a lot that it's not about the the actual growth rate. Yeah, the other guys, they're growing faster. But there were growing from a much larger base and I want to share with you a nuance because he said he talked about how AWS grew incrementally 10 billion and only took him 12 months. I have quarterly forecast and I've published these on Wiki Bond, a silicon angle. And if you look at the quarterly numbers and now this is an estimate, John. But for Q four, I've got Amazon growing at 25%. That's a year on year as you're growing to 46% and Google growing at 50% 58%. So Google and and Azure much, much higher growth rates that than than Amazon. But what happens when you look at the absolute numbers? From Q three to Q four, Amazon goes from 11.6 billion to 12.4 billion. Microsoft actually stays flat at around 6.76 point eight billion. Google actually drops sequentially. Now I'm talking about sequentially, even though they have 58% growth. So the point of the Jazz is making is right on. He is the only company growing at half the growth rate year on year, but it's sequential. Revenues are the only of the Big Three that are growing, so that's the law of large numbers. You grow more slowly, but you throw off more revenue. Who would you rather be? >>I think I mean, it's clearly that Microsoft's not number one. Amazon's number one cloud certainly infrastructure as a service and pass major themes in the now so we won't go through. We're digging into the analyst Sessions would come at two o'clock in three o'clock later, but they're innovating on those two. They want they one that I would call this member. Jasio says, Oh, we're in the early innings Inning one is I as and pass. Amazon wins it all. They ran the table, No doubt. Now inning to in the game is global. I t. That was a really big part of the announcement. People might have missed that. If you if you're blown away by all the technical and complexity of GP three volumes for EBS and Aurora Surveillance V two or sage maker Feature store and Data Wrangler Elastic. All that all that complex stuff the one take away is they're going to continue to innovate. And I, as in past and the new mountain that they're gonna Klima's global I t spin. That's on premises. Cloud is eating the world and a W s is hungry for on premises and the edge. You're going to see massive surge for those territories. That's where the big spend is gonna be. And that's why you're seeing a big focus on containers and kubernetes and this kind of connective tissue between the data machine layer, modern app layer and full custom. I as on the on the bottom stack. So they're kind of just marching along to the cadence of, uh, Andy Jassy view here, Dave, that, you know, they're gonna listen to customers and keep sucking it in Obama's well and pushing it out to the edge. And and we've set it on the Cube many years. The data center is just a big edge. And that's what Jassy is basically saying here in the keynote. >>Well, and when when Andy Jassy gets pushed on Well, yes, you listen to customers. What about your partners? You know, he'll give examples of partners that are doing very well. And of course we have many. But as we've often said in the Cube, John, if you're a partner in the ecosystem, you gotta move fast. There were three interesting feature announcements that I thought were very closely related to other things that we've seen before. The high performance elastic block storage. I forget the exact name of it, but SAN in a cloud the first ever SAN in the cloud it reminds me of something that pure storage did last year and accelerate so very, very kind of similar. And then the aws glue elastic views. It was sort of like snowflake's data cloud. Now, of course, AWS has many, many more databases that they're connecting, You know, it, uh, stuff like as one. But the way AWS does it is they're copying and moving data and doing change data management. So what snowflake has is what I would consider a true global mesh. And then the third one was quicksight que That reminded me of what thought spots doing with search and analytics and AI. So again, if you're an ecosystem partner, you gotta move fast and you've got to keep innovating. Amazon's gonna do what it has to for customers. >>I think Amazon's gonna have their playbooks when it's all said and done, you know, Do they eat the competition up? I think what they do is they have to have the match on the Amazon side. They're gonna have ah, game and play and let the partners innovate. They clearly need that ecosystem message. That's a key thing. Um, love the message from them. I think it's a positive story, but as you know it's Amazons. This is their Kool Aid injection moment, David. Educational or a k A. Their view of the world. My question for you is what's your take on what wasn't said If you were, you know, as were in the virtual audience, what should have been talk about? What's the reality? What's different? What didn't they hit home? What could they have done? What, your critical analysis? >>Well, I mean, I'm not sure it should have been said, but certainly what wasn't said is the recognition that multi cloud is an opportunity. And I think Amazon's philosophy or belief at the current time is that people aren't spreading workloads, same workload across multiple clouds and splitting them up. What they're doing is they're hedging bets. Maybe they're going 70 30 90 10, 60 40. But so multi cloud, from Amazon standpoint is clearly not the opportunity that everybody who doesn't have a cloud or also Google, whose no distant third in cloud says is a huge opportunity. So it doesn't appear that it's there yet, so that was I wouldn't call it a miss, but it's something that, to me, was a take away that Amazon does not currently see that there's something that customers are clamoring for. >>There's so many threads in here Were unpacked mean Andy does leave a lot of, you know, signature stories that lines in there. Tons of storylines. You know, I thought one thing that that mass Amazon's gonna talk about this is not something that promotes product, but trend allies. I think one thing that I would have loved to Seymour conversation around is what I call the snowflake factor. It snowflake built their business on Amazon. I think you're gonna see a tsunami of kind of new cloud service providers. Come on the scene building on top of AWS in a major way of like, that kind of value means snowflake went public, uh, to the level of no one's ever seen ever in the history of N Y s e. They're on Amazon. So I call that the the next tier cloud scale value. That was one thing I'd like to see. I didn't hear much about the global i t number penetration love to hear more about that and the thing that I would like to have heard more. But Jassy kind of touched a little bit on it was that, he said at one point, and when he talked about the verticals that this horizontal disruption now you and I both know we've been seeing on the queue for years. It's horizontally scalable, vertically specialized with the data, and that's kind of what Amazon's been doing for the past couple of years. And it's on full display here, horizontal integration value with the data and then use machine learning with the modern applications, you get the best of both worlds. He actually called that out on this keynote. So to me, that is a message to all entrepreneurs, all innovators out there that if you wanna change the position in the industry of your company, do those things. There's an opportunity right now to integrate with the cloud to disrupt horizontally, but then on the vertical. So that will be very interesting to see how that plays out. >>And eventually you mentioned Snowflake and I was talking about multi cloud snowflake talks about multi cloud a lot, but I don't even think what they're doing is multi cloud. I think what they're doing is building a data cloud across clouds and their abstracting that infrastructure and so to me, That's not multi Cloud is in. Hey, I run on Google or I run on the AWS or I run on Azure ITT's. I'm abstracting that making that complexity disappeared, I'm creating an entirely new cloud at scale. Quite different. >>Okay, we gotta break it there. Come back into our program. It's our live portion of Cube Live and e. K s Everywhere day. That's multi cloud. If they won't say, that's what I'll say it for them, but the way we go, more live coverage from here at reinvent virtual. We are virtual Cuban John for Dave a lot. They'll be right back.
SUMMARY :
It's the Cube with digital coverage Great to see you, Andy Jassy again. Do going Happy birthday, my friend. He acknowledged that social change, the cultural shift. I mean, that was the bulk of his presentation, And I think that to me was the biggest, that you made that I remembered all 12 because the guy uses no notes. They have embraced the data center. I've done a lot of homework on this Aziz, you know, And so Jassy made the point. And I, as in past and the new mountain that they're And then the third one was quicksight que That reminded me of what I think Amazon's gonna have their playbooks when it's all said and done, you know, Do they eat the competition And I think Amazon's philosophy or belief at So I call that the the next Hey, I run on Google or I run on the AWS or I run on Azure ITT's. If they won't say, that's what I'll say it for them, but the way we go,
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Breaking Analysis: COVID-19 Takeaways & Sector Drilldowns Part II
>>from the Cube Studios in Palo Alto and Boston connecting with thought leaders all >>around the world. This is a cube conversation, Everyone. Welcome to this week's Cube insights, powered by ET are My name is Dave Volante, and we've been reporting every week really on the code. 19. Impact on Budgets Docker Korakia is back in with me soccer. It's great to see you really >>again for having >>your very welcome. Soccer is, of course, the director of research, that we are our data partner and man. I mean, you guys have just been digging into the data or a court reiterate We're down, you know, roughly around minus 5% for the year. The thing about what we're doing here and where they want to stress in the audience that that's going to change. The key point is we don't just do ah, placeholder and update you in December. Every time we get new information, we're going to convey it to you. So let's get right into it. What we want to do today is you kind of part two from the takeaways that we did last week. So let's start with the macro guys. If you bring up the first chart, take us through kind of the top three takeaways. And just to reiterate where we're at >>Yeah, no problem. And look, as you mentioned, uh, what we're doing right now is we're collecting the pulse of CIOs. And so things change on and we continue to expect them to change, you know, in the next few weeks, in the next few months, as things change with it. So just kind of give a recap of the survey and then kind of going through some of our top macro takeaways. So in March mid March, we launched our Technology Spending Intention Survey. We had 1250 CIOs approximately. Take that survey. They provided their updated 2020 verse 2019 spending intentions, right? So effectively, they first Davis, those 20 21st 19 spending intentions in January. And then they went ahead and up state of those based on what happened with move it and then in tandem with that, we did this kind of over 19 drill down survey where we asked CEOs to estimate the budget impact off overnight in versus what they originally forecast in the year. And so that leads us to our first take away here, where we essentially aggregated the data from all these CIOs in that Logan 19 drill down survey. And we saw a revision of 900 basis points so down to a decline of 5%. And so coming into the year, the consensus was about 4% growth. Ah, and now you can see we're down about 5% for the year. And again, that's subject to change. And we're going again re measure that a Z kind of get into June July and we have a couple of months under our belt with the folks at night. The second big take away here is, you know, the industries that are really indicating those declines and spend retail, consumer airlines, financials, telco I key services in consulting. Those are the verticals, as we mentioned last week, that we're really seeing some of the largest Pullbacks and spend from consumers and businesses. So it makes sense that they are revising their budgets downwards the most. And then finally, the last thing we captured that we spoke about last week as well as a few weeks before that, and I think that's really been playing out the last kind of week in 1/2 earnings is CIOs are continuing to press the pedal on digital transformation. Right? We saw that with Microsoft, with service now last night, right, those companies continued the post good numbers and you see good demand, what we're seeing and where those declines that we just mentioned earlier are coming from. It's it's the legacy that's the on premise that your place there's such a concentration of loss and deceleration within some of those companies. And we'll kind of get into that more a Z go through more slides. But that's really what kind of here, you know, that's really what we need to focus on is the declines are coming from very select vendors. >>Yeah, and of course you know where we were in earning season now, and we're paying close attention to that. A lot of people say I just ignore the earnings here, you know, you got the over 19 Mulligan, but But that's really not right. I mean, obviously you want to look at balance sheets, you want to look at cash flows, but also we're squinting through some of the data your point about I t services and insulting is interesting. I saw another research firm put out that you know, services and consulting was going to be OK. Our data does, you know, different. Uh, and we're watching. For instance, Jim Kavanaugh on IBM's earnings call was very specific about the metrics that they're watching. They're obviously very concerned about pricing and their ability. The book business. There we saw the cloud guys announced Google was up in the strong fifties. The estimate is DCP was even higher up in the 80% range. Azure, you know, we'll talk about this killing it. I mean, you guys have been all over of Microsoft and its presence, you know, high fifties aws solid at around 34% growth from a larger base. But as we've been reporting, you know, downturns. They've been they've been good to cloud. >>That's right. And I think, you know, based on the data that we've captured, um, you know, it's people are really pressing the pedal on cloud and SAS with this much remote work, you need to have you know, that structure in place to maintain productivity. >>Okay, let's bring up the next slide. Now. We've been reporting a lot on this sort of next generation work loads Bob one Dato all about storage and infrastructures of service. Compute. There's an obviously some database, but there's a new analytics workload emerging. Uh, and it's kind of replacing, or at least disinter mediating or disrupting the traditional e d ws. I've said for years. CDW is failed to live up to its expectations of 360 degree insights and real time data, and that's really what we're showing here is some of the traditional CDW guys are getting hit on Some of the emerging guys, um, are looking pretty good. So take us through what we're looking at here. Soccer. >>Yeah, no problem. So we're looking at the database data warehousing sector. What you're looking at here is replacement rates. Um And so, as example, if you see up in with roughly 20% replacement, what that means is one out of five people who took the survey for that particular sector for that vendor indicated that they were replacing, and so you can see here for their data. Cloudera, IBM, Oracle. They have very elevated and accelerating replacement rates. And so when we kind of think about this space. You can really see the bifurcation, right? Look how well positioned the Microsoft AWS is. Google Mongo, Snowflake, low replacements, right low, consistent replacements. And then, of course, on the left hand side of the screen, you're really seeing elevated, accelerating. And so this space is It kind of goes with that theme that we've been talking about that we covered last week by application, right when you think about the declines that you're seeing and spend again, it's very targeted for a lot of these kind of legacy legacy vendors. And we're again. We're seeing a lot of the next gen players that Microsoft AWS in your post very strong data. And so here, looking within database, it's very clear as to which vendors are well positioned for 2020 and which ones look like they're being ripped out and swapped out in the next few months. >>So this to me, is really interesting. So you know, you you've certainly reported on the impact that snowflake is having on Terra data. And in some of IBM's business, the old man, he's a business. You can see that here. You know, it's interesting. During the Hadoop days, Cloudera Horton works when they realize that it didn't really make money on Hadoop. They sort of getting the data management and data database and you're seeing that is under pressure. It's kind of interesting to me. Oracle, you know, is still not what we're seeing with terror data, right, Because they've got a stranglehold on the marketplace That's right, hanging in there. Right? But that snowflake would no replacements is very impressive. Mongo consistent performer. And in Google aws, Microsoft AWS supports with Red Shift. They did a one time license with Park Cell, which was an MPP database. They totally retooled a thing. And now they're sort of interestingly copycatting snowflake separating compute from storage and doing some other moves. And yet they're really strong partners. So interesting >>is going on and even, you know, red shift dynamodb all. They all look good. All these all these AWS products continue screen Very well. Ah, in the data warehousing space, So yeah, to your point, there's a clear divergence of which products CIOs want to use and which ones they no longer want in their stack. >>Yeah, the database market is very much now fragment that it used to be in an Oracle db two sequel server. As you mentioned, you got a lot of choices. The Amazon. I think I counted, you know, 10 data stores, maybe more. Dynamodb Aurora, Red shift on and on and on. So a really interesting space, a lot of activity in that new workload that I'm talking about taking, Ah, analytic databases, bringing data science, pooling into that space and really driving these real time insights that we've been reporting on. So that's that's quite an exciting space. Let's talk about this whole workflow. I t s m a service now. Just just announced, uh, we've been consistently crushing it. The Cube has been following them for many, many years, whether, you know, from the early days of Fred Luddy, Bruce Lukman, the short time John Donahoe. And now Bill McDermott is the CEO, but consistent performance since the AIPO. But what are we actually showing here? Saga? Yeah, You bring up that slot. Thank you. >>So our key take away on kind of the i t m m i t s m i t workflow spaces. Look, it's best in breed, which is service now, or some of the lower cost providers. Right There's really no room for middle of the pack, so >>this is an >>interesting charts. And so what you're looking at here, there's a few directives, so kind of walk you through it and then I'll walk through. The actual results is we're looking within service now accounts. And so we're seeing how these companies are doing within or among customers that are using service. Now, today, where you're looking at on the ex, access is essentially shared market share our shared customers, and then on the Y axis you're seeing essentially the spend velocity off those vendors within service. Now's outs, right? So if the vendor was doing well, you would see them moving up into the right, right? That means they're having more customer overlap with service now, and they're also accelerating Spend, but you can see if you will get zendesk. If you look at BMC, it's a managed right. You can see there either losing market share and spend within service now accounts or they're losing spend right and zendesk is another example Here, Um, and what's actually interesting is, and we've had a lot of anecdotal evidence from CIOs is that look they start with service. Now it's best in breed, but a few of them have said, Look, it's got expensive, Um, and so they would move over Rezendes. And then they would look at it versus a conference that last year, and we had a few CEO say, Look at last quarter of the price of zendesk. Andi moved away from Zendesk and subsequently well, with last year. And so it's just it's interesting that, you know, during these times where you know CIOs are reducing their budgets on that look, it's either best of breed or low cost. There's really no room in the middle, and so it's actually kind of interesting. In this space, it's It's an interesting dynamic and being usually it's best of breed or low cost. Rarely do you kind of see both win, and I think that's what kind of makes the space interesting. >>I've been following service now for a number of years. I just make a few comments there. First of all, you know, workday was the gold standard in enterprise software for the longest time and, you know, company and and and I I always considered service now to be kind of part of that you know Silicon Valley Mafia with Frank's Loop. But what's happened is, you know, Sluman did a masterful job of identifying the total available market and executing with demand, and now you know, his successors have picking it beyond there. You know, service now has a market cap that's not quite double, but I mean, I think workday last I checked was in the mid thirties. Service now is market valuation is up in the 60 billion range. I mean, they announced, um uh, just recently, very interestingly, they be expectations. They lowered their guidance relative to consensus guide, but I think the street hose, first of all, they beat their numbers and they've got that SAS model, that very predictable model. And I think people are saying, Look there, just leaving meat on the bone so they can continue to be because that's been their sort of m o these last several years. So you got to like their positioning and you get to talk to customers. They are pricey. You do hear complaints about that, and they've got a strong lock spec. But generally I got my experiences. If people can identify business value and clear productivity, they work through the lock in, you know, they'll just fight it out in the negotiations with procurement. >>That's right, and two things on that. So with service now and and even Salesforce, right, they are a platform like approach type of vendors right where you build on them. And that's what makes them such break companies, right? Even if they have, you know, little nicks and knacks here and there. When they report people see past that right, they understand their best of breed. You build your companies on the service now's and the sales forces of the world. And to the second point, you're exactly right. Businesses want to maintain consistent productivity on, and I think that, you know, is it kind of resonates with the theme, right, doubling down on Cloud and sas. Um, as as you have all this remote work, as you have kind of, you know, questionable are curating marquee a macro environment organizations want to make sure that their employees continue to execute that they're generating consistent productivity. And using these kind of best of breed tools is the way to go. >>It's interesting you mentioned, uh, salesforce and service now for years I've been saying they're on a collision course we haven't seen yet because they're both platforms. I still, uh I'm waiting for that to happen. Let's bring up the next card and let's get into networking way talk. Um Ah. Couple of weeks ago, about the whole shift from traditional Mpls moving to SD win. And this sort of really lays it out. Take us through the data here, please. >>Yeah, no problem. So we're just looking at a handful of vendors here. Really? We're looking at networking vendors that have the highest adoption rates within cloud accounts. And so what we did was we looked inside of aws azure GCC, right. We essentially isolated just those customers. And then we said which networking vendors are seeing the best spend data and the most adoptions within those cloud accounts. And so you get you can kind of see some, uh, some themes here, right? SD lan. Right. You can see Iraqi their VM. Where nsx. You see some next gen load balance saying are they're on the cdn side right then. And so you're seeing a theme here of more next gen players on You're not really seeing a lot of the mpls vendors here, right? They're the ones that have more flattening, decreasing and replacing data. And so the reason just kind of going on this slide is you know, when you kind of think about the networking space as a whole, this is where adoptions are going. This is this is where spends billing and expanded, arise it. And what we just talked about >>your networking such a fascinating space to me because you got you got the leader and Cisco That has helped 2/3 of the market for the longest time, despite competitors like Arista, Juniper and others trying to get in the Air Force and NSX. And the big Neisseria acquisition, you know, kind of potentially disrupted that. But you can see, you know, Cisco, they don't go down without a fight. And ah, there, let's take a look at the next card on Cdn. You know, this is interesting. Uh, you know, you think with all this activity around work from home and remote offices, there's a hot area, But what are we looking at here? >>Yeah, no problem. And that's right, right? You would think. And so we're looking at Cdn players here you would think with the uptake in traffic, you would see fantastic. That scores right for all the cdn vendor. So what you're looking at here and again there's a few lenses on here, so I kind of walk. You kind of walk the audience through here is first we isolated only those individuals that were accelerating their budgets due to work from home. Right. So we've had this conversation now for a few weeks where support employees working from home. You did see a decent number of organizations. I think it was 20 or 30% of organizations at the per server that indicated they're actually accelerate instead. So we're looking at those individuals. And then what we're doing is we're seeing how are how's Cloudflare and aka my performing within those accounts, right? And so we're looking at those specific customers and you could just see within Cloudflare and we practice and security and networking which by more the Cdn piece, How consistent elevated the date is right? This is spend in density, right? Not overall market share is obviously aka my you know, their brand father CD ends. They have the most market share and if you look at optimized to the right. Now you can see the spend velocity is not very good. It's actually negative across boats sector. So you know it's not. We're not saying that. Look, there's a changing of the guard that's occurring right now. We're still relatively small compared talk my But there's just such a start on trust here and again, it kind of goes to what we're talking about. Our macro themes, right? CIOs are continuing to invest in next gen Technologies, and better technologies on that is having an impact on some of these legacy. And, you know, grandfather providers. >>Well, I mean, I think as we enter this again, I've said a number of times. It's ironic overhead coming into a new decade. And you're seeing this throughout the I T. Stack, where you've got a lot of disruptors and you've got companies with large install bases, lot of on Prem or a lot of historical legacy. Yeah, and it's very hard for them to show growth. They often times squeeze R and D because they gotta serve Wall Street. And this is the kind of dilemma they're in, and the only good news with a comma here is there is less bad security go from negative 20% to a negative 8% net score. Um, but wow, what a what a contrast, but to your point, much, much smaller base, but still very relevant. We've seen this movie before. Let's let's wrap with another area that we've talked about. What is virtualization? Desktop virtualization? Beady eye again. A beneficiary of the work from home pivot. Um, And we're focused here, right on Fortune 500 net scores. But give us the low down on this start. >>Yeah, So this is something that look, I think it's it's pretty obvious to into the market you're seeing an uptake and spend across the board versus three months ago in a year ago and spending, etc. Among your desktop virtualization players, there's FBI, right? So that's gonna be your VPN right now. Obviously, they reported pretty good numbers there, so this is an obvious slide, but we wanted to kind of throw it in there. Just say, look, you know, these organizations are seeing nice upticks incent, you know, within the virtualization sectors, specifically within Fortune 500 again, that's kind of, you know, work from home spend that we're seeing here, >>right? So, I mean, this is really a 100% net score in the Fortune 500 for workspaces is pretty amazing. And I think the shared in on this that the end was actually quite large. It wasn't like single digits, Many dozens. I remember when Workspaces first came out, it maybe wasn't ready for prime time. But clearly there's momentum there, and we're seeing this across the board saga. Thanks so much for coming in this week. Really appreciate it. We're gonna be in touch with with you with the TR. We're gonna continue to report on this, but start Dr stay safe. And thanks again. >>Thanks again. Appreciate it. Looking for to do another one. >>All right. Thank you. Everybody for watching this Cube insights Powered by ET are this is Dave Volante for Dr Sadaaki. Remember, all these episodes are available as podcasts. I published weekly on wiki bond dot com Uh, and also on silicon angle dot com Don't forget tr dot Plus, Check out all the action there. Thanks for watching everybody. We'll see you next time. Yeah, yeah, yeah, yeah, yeah
SUMMARY :
It's great to see you really you know, roughly around minus 5% for the year. And so things change on and we continue to expect them to change, you know, A lot of people say I just ignore the earnings here, you know, you got the over 19 Mulligan, And I think, you know, based on the data that we've captured, um, So take us through what we're looking at here. and so you can see here for their data. So you know, you you've certainly reported on the impact that snowflake is is going on and even, you know, red shift dynamodb all. I think I counted, you know, 10 data stores, maybe more. So our key take away on kind of the i t m m i t s m i And so it's just it's interesting that, you know, you know, workday was the gold standard in enterprise software for the longest time and, you know, productivity on, and I think that, you know, is it kind of resonates with the theme, It's interesting you mentioned, uh, salesforce and service now for years I've been saying they're on a collision And so the reason just kind of going on this slide is you know, when you kind of think about the networking space as And the big Neisseria acquisition, you know, kind of potentially disrupted that. And so we're looking at Cdn players here you would think with the uptake in traffic, of the work from home pivot. specifically within Fortune 500 again, that's kind of, you know, work from home spend that we're seeing it. We're gonna be in touch with with you with the TR. Looking for to do another one. We'll see you next time.
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Breaking Analysis: CIOs Plan on 4% Budget Declines for 2020
from the cube studios in Palo Alto in Boston connecting with thought leaders all around the world this is a cube conversation [Music] hello everybody and welcome to this week wiki bond cube insights powered by ETR in this breaking analysis we want to update you on the latest spending data from EGR as you know we've been tracking this weekly saga kodachi is here he's the director of research at ET our saga thanks for coming on thanks for having me again Dave really appreciate it yes so so let me remind everybody so we entered the Year this year 2020 with a consensus IT spend for cast of plus 4% once coronavirus hit ET are launched its latest survey in March and we saw those numbers you'll come down last week we reported well the first report we made was it looked like it was flat last week we reported a slight negative and today we want to update you guys on those numbers so saga before we get into the data just give us the high level on where you guys are at in terms of your survey yeah no problem so currently we are forecasting a decline in global IT budgets about negative 4% I think what's happened you know over the last you know 10 or 15 days is you've just seen more and more information released that's given organizations more of an understanding of just how severe this you know epidemic is and so what we've been able to do on our end is kind of do an event study analysis or simulation analysis kind of what you're seeing here a really pinpoint the time period where organizations understood the severity of the epidemic and then really trying to measure the declines in IT budgets from there great so guys bring that slide back up I want to share with our audience what's happening here so what ETR has done is an event-based analysis and what you can see is where the survey launched on 3/11 you could see how sentiment has declined literally daily as the data rolled in then you see the US declared a national emergency you saw that the federal plan leaked for that you know penned pandemic protect projection and obviously New York became a hot spot and then you can see this the stimulus package in it and sagger it looks like there's a slight uptick here but generally speaking it's down now it could be worse but you guys were the first to report the offset from work it worked from home infrastructure we'll talk about that a little bit talk about this event analysis and what you're seeing here and how you compressed the analysis hosting these events no problem so let's start with a blue line here and just so the audience knows the x-axis is going to be date and the y-axis is going to be annual growth or decline in nit budgets what you're seeing here and if we start with the blue line is we started pulling on 3/11 and on that date we started to ask you know fortune 100 is fortune 500 how their budget was going to change based on the impacts of coded nineteen versus their original expectations coming into coming into the year and again consensus estimates coming to the year were positive four percent so if you track that line all the way through you get to a decline of about one percent now what's the issue of starting polling on 3/11 or using that blue line well one of the big issues is a few days later the US declared a national emergency so more information was released right I think organizations that took the survey in the first two days didn't have a complete picture as to what's going on and then effectively a week later you saw federal documents get leaked stating how bad this epidemic was right in terms of the last 18 18 plus months and so what we did was we did it effectively an event based analysis or defuse different simulation where if you take a look at the yellow and red lines to start what we're doing is we're effectively saying okay let's ignore everyone that took the survey prior to that let's take their budgets in terms of how they indicated change versus their original expectations for 2020 and then let's go ahead and map that and if you look at the yellow line as an example that goes to a decline of 2% and then once I think you know the next shoe dropped in terms of organizations understanding this is not going to be a few weeks or this is not the common cold or flu once organizations knew this was going to be an 18 plus epidemic you can see if we started pulling respondents from there how much more negative it gets and of course once NYC became the epicenter you saw a little another shoe drop so now those those scenarios or simulations are taking us between a decline of three and four percent and then of course if we look at that last purple line there when the stimulus got announced what we are seeing is it looks like it may have bottomed down we have to continue tracking it because you know again it's just a few days since the stimulus is was passed and so let's see if the data starts improve a little bit or at least stabilize but I think from the last three events in terms of the the federal plan being leaked NYC becoming the epicenter and the stimulus it looks like the market now is fully aware of what's going on and now we're kind of seeing some stabilization in the data in terms of the declines for 2020 so between the feds action and the the fiscal stimulus we've we've seen some optimism although people are really cautious of course remember folks this would be worse were it not for the shift in spend to work from home infrastructure not just collaboration and visualization tools but other infrastructure around that network bandwidth security desktop virtualization etc so guys if you bring up the next chart I want to set this up we've been reporting this framework for a while now what this shows is what the sentiment is in terms of the budget change and you can see the gray bar now is 35% it started at 40% so that's dropped so the percentage of CIO saying no change the green is held pretty steady at around 20 to 22% that's it's roughly in there and the red you know has been has been shifting and you can see most of the green ie spending more in 2020 is focused on that you know one to two ten percent but but Sagar bring us up to date now we're going to settle in it right now about three and a half to four percent on the negative side give us some color on this chart please yeah no problem so the best way to connect this chart with what we saw earlier is this is a snapshot so this is a single day so this is the data that is feeding the time series chart kind of help the audience understand what's going on so if we were to look at this exact chart Oh since March 11 you would see that midpoint Average effectively coming down every day and that's effectively what's making up that time series in terms of this chart you know Dave you kind of hit it right on the nail you're kind of seeing the positivity remain or be stable and again that's that work from home infrastructure as you as you mentioned right the collaboration pools no the virtualization support services networking bandwidth all that stuff right being more and more security but on the negative side I think what you're seeing is that again as organizations now understand the severity of the epidemic I think as we understand further and we've talked about this you know a few weeks ago that organizations were anticipating less demand they were anticipating an uptick in broken supply chains now you're starting to see some of that play out and as a result you're seeing organizations get more and more negative and that's why that midpoint average it keeps declining that's why those red bars keep going up is the the impacts in you know based on the data are are now starting to be to be seen and so you know let's see if the stimulus stabilizes this data and we'll continue tracking that you know over the next few weeks the next few months okay so basically we're coming in - three and a half to four percent that's where we are today we're not going to get detailed into some of the vendors today we talked a little bit about that last week and go back to last week's breaking analysis you can see some of that vendor commentary I want to talk about what happens next ETR now we'll go into a two-week quite self-imposed quiet period and really start crunching the data at the end of that quiet period they will release to their private clients the their latest thinking in a webcast after that time we at the cube are allowed to share public information and we're gonna drill down into some of the segments that our community is most interested in but-but-but etrs going quiet now so saga maybe you can explain that sequence and fill in any holes that I missed there yeah no problem the next two weeks so we've we've collected a tremendous amount of data you know we're over you know we're at a hundred fortune 100 organizations you know almost three four hundred global two thousand organizations and so we're at a point now where it's time to start aggregating the data start really analyzing it going through this Koga drill down that we conducted but also we conducted a tremendous study on technology spending intentions of crossing over 350 vendors dozens of Technology sectors and so now it's really a time to kind of drill in and you know what what we're looking for or even some of the biggest takeaways from from this Cove it you know drill down is you know if if you started polling before 3:23 chances are your forecast is gonna come in light and I think that's one of the things that we've learned as we're kind of going into this to hear it is we really want to measure the impact starting right around that 3:23 timeframe it looks right around then based on that time series chart that we showed earlier that's when the market fully understood the impact of this epidemic and so as we start over the next two weeks even though we started pulling a little bit early we really want to focus on that second set a second half of responses because that's probably gonna be more indicative of what's going on I think the second thing is gonna be look if condition of conditions continue to deteriorate things can get worse and so we may come out of the next two weeks with this data that we collected and again have to continue indicating that you know the environment has continued coming down and you know maybe we may have to make adjustments as we see fit so I think that's kind of you know this whole situation is so dynamic still and so we're gonna do our best in the next week and a half to kind of get this data to market to at least give everyone an idea here's how everything stands right now and so that people have a good benchmark and then move forward yeah so this is as close to real time really as you can get in some of this IT spending world saga mentioned some of the numbers and in the global 2000 fortune fortune 100 1000 this this end now just the reminder is up over 1200 I believe right Sahra the total and that you've collected this this month that's correct exactly every time we've been doing one of these it's been going up another a couple hundred respondents so yeah we're at a very comfortable level now our sample right now represents five hundred and fifty five billion dollars in annual IP spend you know and global IT spend every year is a little over you know three trillion so this is a significant significant portion of a global IT spend and we feel comfortable at this point kind of going into that quiet period as you mentioned and really start to dig through the results that you know now that we've kind of you know covered the the 10,000 foot or the macro layer so to speak in terms of where budgets are going now it's really time to start drilling down and do the sectors and vendors because this is this is not going to be a every vendors going down or whatever maybe there's so many different dynamics here some vendors are going to do very well because the work for MoMA infrastructure and I think some vendors are gonna do very poorly because one they're not only on the legacy side but they're not really aligned from this whole work from home infrastructure movement so you're gonna see a lot of bifurcation you know as we get into 53 that's right and we're gonna dig into all those segments we're gonna look at the work from home we're gonna look at the traditional stuff we're gonna look at cloud we're gonna drill into specific segments that are that are of interest to our community it's a pleasure to really have you on here Sagar thank you for for sharing giving us access to this data and and stay safe and we will be watching go to ETR dot plus and you know check out what's happening there Silicon Engel Tom will obviously cover this and I published weekly on wiki bond comm again that saga thanks so much for coming on the cube yeah no problem thank you so much and looking forward to catching up in a few weeks all right then thank you for watching everybody this is Dave a latte for the cube or wiki bounce cube insights powered by ETR we'll see you next time [Music]
**Summary and Sentiment Analysis are not been shown because of improper transcript**
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COVID-19: IT Spending Impact March 26, 2020
>> From theCUBE studios in Palo Alto in Boston, connecting with our leaders all around the world, this is theCUBE Conversation. >> Hello everyone, and welcome to this week's Wiki Bond CUBE Insights powered by ETR. In this breaking analysis, we're changing the format a little bit, we're going right to the new data from ETR. You might recall that last week, ETR received survey results from over 1000 CIOs and IT practitioners. And they made a call at that time, which said that actually surprisingly, a large number of respondents about 40% said they didn't expect a change in their 2020 IT spending. At the same time about 20% of the survey said they're going to spend more largely related to Work From Home infrastructure. ETR was really the first to report on this. And it wasn't just collaboration tool like zoom and video conferencing. It was infrastructure around that security, network bandwidth and other types of infrastructure to support Work From Home like desktop virtualization. ETR made the call at that time, that it looked like budgets, were going to be flat for 2020. Now, you also might recall consensus estimates for 2020 came into the year at about 4%, slightly ahead of GDP. Obviously, that's all is changed. Last week, ETR took the forecast down, and we're going to update you today. We're now gone slightly negative. And with me to talk about that again, is Sagar Kadakia, who's the Director of Research at ETR. Sagar, great to see you again, thank you for coming on. >> Thanks for having me again David, really appreciate it. >> Let's get right into it. I mean, if you look at the time series chart that we showed last week, you can see how sentiment changed over time. That blue line was basically people who responded to the survey starting at 3/11. Now you've updated that, that forecast, really tracking after the COVID-19 really kicked in. Can you explain what we're seeing here in this chart? >> Yeah, no problem. The last time we spoke, we were around an N or sample size of about 1000. And we were right around that zero percent growth rate. One of the unique things that we've done is we've left this survey open. And so what that allows us to do is really track the impact on annual IP growth, essentially daily. And so as things have progressed, as you look at that blue line, you can really see the growth rate has continued to trend downwards. And as of just a day or two ago, we're now below zero. And so I think because of what's occurring right now, the overall current climate continues to slightly deteriorate. You're seeing that in a lot of the CIOs responses. >> If you bring that slide back up Andrew, I want to just sort of stay on this for a second. What I really like about what you guys are doing is you're essentially bringing event analysis in this. So if you see that blue line, you see on 3/13, a national emergency was declared and that's really when the blue line started to decline. What ETR has done is kind of reset that, reset the data since 3/13. Because it's now a more accurate reflection of what's actually happening happening in the market. Notice in the upper right, it says the US approved... The Senate last night approved a stimulus package. Actually, they're calling it an Aid Package. It's really not a stimulus package. It's an aid package that they're injecting to help. A number of our workers actually sounds like existing workers and small businesses and even large businesses like Boeing. Boeing was up significantly yesterday powering the Dow and potentially airlines. As you can see ETR is going to continue to monitor the impact, and roll this out. Really ETR is the only company that I know of anyway, that can track this stuff on a daily basis. So Sagar, that event analysis is really key, and you're going to be watching the impact of this stimulus slash aid packet. >> Yeah, so here's what we're doing on that chart. If you look at that yellow line again, effectively what you're seeing is, if we remove the first I think six or seven 100 respondents that took the survey and start tracking how budgets are changing as a 3/13, that's when the US declared a national emergency. We can recalculate the growth rate. And we can see it's around... It's almost negative one and a half. And so the beauty of doing this, really polling daily, is it allows us to be just as dynamic, as a lot of these organizations are. I think one of the things we talked about the last time was some of these budget changes are going to be temporary. And organizations are figuring out what they're doing day by day. And a lot of that is dictated based on government actions. And so uniquely here, what we're able to do is kind of give people a range and also say, "based on these events, "this is how things are changing."" And so I think we think the first biggest event was on 3/13, where the US effectively declared a national emergency over COVID-19. And now what we're going to start tracking between today and over the weekend, and Monday is: Are people getting more positive? Is there no change? Or is there further deterioration because of this aid package that got passed this morning? >> Now I want to share with our audience. I've been down to ETR's headquarters in New York, it's staffed with a number of data scientists and statistical experts. The ends here are well over 1000. I think we're over 1100 now, is that correct? What is the end that we're at today? >> That's right. Yeah, we're we're pushing right over 1200. And we're going to expect a few more hundred respondents. The good thing is it's balanced, which is important. All these events that are occurring, we want to make sure that we have at least a few hundred more CIOs and IT executives answering. And so every week as we kind of continue to do some of these breaking analysis, there are going to be a few more hundred CIOs. And we'll really be able to zero in or hone in on what they're saying. The growth rate on the IT side, it's going to continue to fluctuate. It's going to continue to be dynamic over the next few weeks, but right now versus (murmurs). We are in negative territory now. >> I want to also explain I mean, the end is important. But in and of itself, it's not the be all end all, what's important about the end, the larger it is, the more cuts you can make. And I want to share... You guys have been doing this for the better part of a decade. And so you have firm level data. And you've got indicators and markers that you've tracked over the years. For example, one of the things that ETR tracks is Giant Public and Private GDP we call it. And that's for example, I'm not saying that, that Mars is one of the companies but Mars is a huge private company, UPS before they went public, huge private company. ETR tracks firm level data, they of course anonymize that, but they can see markers and trackers and trends, and probably have, I don't know dozens of those types of segments. So the bigger the end is, the more... The higher the end within those buckets, and the better the confidence interval. And you guys are experts at really digging into that in trying to understand and read the tea leaves. >> That's right. The key to this survey is, it's not anonymous, we know who is taking the survey. Now to your point, we do anonymize and aggregate it when we display those results. But one of the unique capabilities is we're able to see all of these trend lines. The entire drill down survey that we did on COVID-19 through the lenses of different verticals so we can take a look at industrials materials manufacturing, healthcare, pharma, airlines, delivery services, health, and all these other verticals and get a feel for which ones are deteriorating the most, which ones look stable. And, we talked about last week and it continues to remain true this week. And again, the ends have gone up on all these verticals on the supply chain side. Industrials, materials manufacturing, healthcare, pharma, they continue and they also anticipate to see these things in the next few months, broken supply chains and on the demand side, it's really retail consumer airlines delivery services. That's coming down quite substantial. And I think, based on what United and some of these other airlines have done these last few days in terms of cutting capacity, that's just a reflection of what we're seeing. >> Let's dig into the data a little bit more and bring up the next chart. Last week, we're about 40% actually, exactly 40% where that gray line that said: CIOs and IT practitioners said, "no change." They're like the budget of the green. The green was actually at about 20 21%. So it's slightly up now at 22%. And you can see, most of the the green is in that one to 10% range. And you can see in the left hand side, it's obviously changing. Now we're at 37% in the gray line, slightly up in the green, and a little bit more down and in the red. So take us through what's changed Sagar. >> Yeah, to reiterate what we were talking about last week, and then I'll kind of talk about some of the change is, I think the market and a lot of our clients, they were expecting the growth rate to be more negative. Last week when we talked about zero percent. The reason that, it wasn't more negative is because we saw all these organizations accelerating spend because they had to keep employees productive. They don't want to catastrophe in productivity. And so you saw this acceleration, as you mentioned earlier in the interview around Work From Home tools, like collaboration tools, increasing bandwidth on the VPN networking side, laptops, MDM, so forth and so on. That continues to hold true today. Again, if we use the same example that we talked about last week, (mumbles) organizations, they have 40 50 60,000 employees or more working from home. You have to be able to support these individuals and that's why we're actually seeing some organizations accelerate spend and the majority organizations even though they are declining spend, some of that is still being offset by having to spend more on what we're calling kind of this Work From Home infrastructure. But I will say this: you are seeing more organizations versus last week, which is why the growth rate has come down, moving more and more towards the negative buckets. Again, there is some offset there. But the offset we talked about last week, Work From Home infrastructure is not a one-for-one when it comes to taking down your IT budget, and that continues to hold true. >> Let's talk a little bit about some of the industries retail, airlines, industrials, pharma, healthcare, what are you seeing in terms of the industry impact, particularly when it relates to supply chains, but other industry data that went through? >> I think the biggest takeaway is that healthcare pharma, industry materials, manufacturing organizations, they've indicated the highest levels of broken supply chains today. And they think in three months from now, it's actually going to get worse. And so we spoke about this last time, I don't think this is going to be a V shaped recovery from the standpoint of things are going to get better in the next few weeks or the next month or two. CIOs are indicating that they expect conditions to worsen over the next three months on the supply chain side and even demand the ones that are getting hit the hardest on the retail consumer side airlines, delivery services, they are again indicating that they anticipate demand to be worse three months from now. The goal is to continue serving and pulling these individuals over the next few weeks and months and to see if we can get a better timeline as we get into two edge but for the next few months, conditions look like they're going to get worse. >> I want to highlight some of the industries and let's make some comments here. Retail... You guys called out retail airlines, delivery services, industrials, materials, manufacturing, pharma and healthcare, there's some of the highest impact. I'll just make a few comments here. I think retail really, this accelerates the whole digital transformation. We already saw this starting, I think you'll see further consolidation and some permanence in the way in which companies are pivoting to digital. Obviously, the big guys like Walmart and the like are competing very effectively with Amazon. But, there's going to be some more consolidation there. I would say potentially the same thing in airlines that really are closely watching what the government is going to do. But, do we need this this many airlines? Do we need all this capacity? Maybe yes, maybe no. So watching that. And of course, healthcare right now, as I said last week in the braking analysis, they're just too distracted right now to buy anything. And they're overwhelmed. Now, of course, pharma, they're manufacturing, so they've got disruptions in supply chain and obviously the business. But there could be an upside down the road as COVID-19 vaccines come to the market. >> On the upside, I think you kind of hit it, right on the nail. When you get these type of events that occur. Sometimes it speeds up digital transformation. one of the things that the team and I have been talking about internally is: this is not your father's Keep The Lights On strategy so to speak. Organizations are very focused on maintaining productivity versus significantly cutting costs. What does that mean? Maybe three to five years ago, if this had occurred, you would have seen a lot of infrastructure as a service platform, as a service... A lot of these cloud providers, you'd have seen those projects decline as organization spent more on on plan. And we're not seeing that. We're seeing continued elevated budgets on the Cloud side and Micron just reported this morning and again, cited strong demand on the Cloud and data center side. That just goes to show that organizations are trying to maintain productivity. They want to continue these IT roadmaps and they're going to cut budgets where they can, but it's not going to be on the Cloud side. >> You know what, that's a really important point. This is not post Y2K, not 2008, 2007, 2008, 2009 because we've, pretended but a 10 year bull market, companies are doing pretty well, balance sheets are generally strong. They somewhat in whether, it was used to stronger companies, whether they're so they're not focused right now anyway, on cut cut cut as it was in the last few downturns. Let's go into some of the vendor data and some of the sector data, Andrew if you'd bring up the next chart. What we're showing here is really comparing the the blue is the January survey to the current survey in the yellow, and you're seeing some of the sectors that are up taking. You've identified mobile device management, big data and Cloud, some of the productivity, you mentioned DocuSign, Adobe zoom, Citrix, even VMware with the desktop virtualization. We've talked about security, you've got marketing and LinkedIn, my LinkedIn inbound is going through the roof as people are probably signing up for a LinkedIn premium. Let's talk about this a little bit. What you're seeing... Help us interpret this data. >> Yeah, sure. One of the things that everybody wants to know is, okay, so Work From Home infrastructures getting more spend for the vendors that are benefiting the most. One of the unique things that we can do is because we're kind of collecting all the DNA, from a tech stack aside from these organizations, we can overlap, how they're spending on these vendors. And also with the data that they provide in terms of whether they are increasing or decelerating their IT budgets because of COVID-19. What you're looking at here, is we isolated to all of those organizations and customers that indicated that they're increasing their budgets because of COVID-19. Because of the Work From Home infrastructure. And what we're doing is we're then isolating to vendors that are getting the most upticks in spend. This actually really nicely aligns with a lot of the themes that we were talking about collaboration tools. You see that VMware, they're all right on the virtualization side, MDM with Microsoft. And you're seeing a lot of other vendors with Citrix and Zoom and Adobe. These are the ones that we think are going to benefit from this kind of Work From home infrastructure movement. And again, it's all very... It's not just the qualitative and the commentary. This is all analytics, we really went in and analyzed every single one of these organizations that were increasing their budgets and tried to pinpoint using different data analysis techniques, and to see which vendors were really getting the majority or the largest, pie of that span. >> We had Sanjay Poonen, who's the CEO of VMware on yesterday and he was very sensitive but not trying to hear as your ambulance chasing because obviously they do desktop virtualization and VDI big workload. At the same time. I think he was also being cautious because there's probably portions of their business that are going to get hit, Michael Dell similarly, I think he was quoted in CRN as saying, "hey, are we seeing momentum in our laptop "business in our mobile business?" But as you guys pointed out, the flip side of that is their on prem business is probably going to suffer somewhat. It's a kind of like the Work From Home is a partial offset, but it's not a total offset. You're seeing that with a lot of these companies. Obviously, Microsoft, AWS, a lot of the cloud companies are very well positioned, how about some of the guys that are going to get impacted? Obviously, as I said that the on-prem folks, you guys talked about earlier it's not your father's Keep Your Lights On strategy. Okay but this... You asked the question, is this a reprieve for the legacy guys? Not quite, was your conclusion. What did you mean by that? >> I think a lot of times when you have these sub-events, the clients a lot of the market think okay, "some of the legacy vendors are going to do well "because, we're in malicious times, "and we don't want to keep on this kind "of next generation strategy." We're not seeing that and to the point that you highlighted earlier. There are... Even though these companies like Dell, like Cisco, where they're seeing some products accelerate, there are products to your point that are not doing as well The desktops, right? As an example for Dell or the storage. On the negative side or the legacy side where we're just not seeing any traction, the IBM's the Oracle on-prem, Symantec, which got acquired by Broadcom, checkpoint MicroStrategy. And there's another half dozen other vendors that we're seeing where they are not capitalizing. There is no reprieve for these legacy names. And we don't anticipate them getting additional spend, because of this Work From Home infrastructure kind of movement. >> Let's unpack that a little bit. It's interesting Symantec and checkpoint in security, security you think would get an uplift there, but what you're seeing here is... Let me just tell the audience who you called out. Symantec Teradata MicroStrategy, NET app Checkpoint Oracle and IBM, and I know there are others. But I would say this: These are companies that are getting impacted in a big way by the Cloud. Particularly like Symantec and checkpoint. That's a Cloud security companies are actually probably still doing pretty well. You take Teradata, their data is getting impact by the Cloud from folks like Snowflake and Redshift, MicroStrategy a lot of modern BI coming out. NetApp here's a company that's embraced the Cloud, but the vast majority of the business changess to be on-prem. I think IBM and Oracle are interesting. They're somewhat different. Actually a lot different IBM has services exposure, and you guys call that out, particularly around outsourcing. At the same time, it's going to be interesting to see IBM is going to get a lot of resources. Going to be interesting to see if they start coming out with corona virus related services. So watching for that, and then Oracle, their whole story is, "okay, we got Gen 2 Cloud and Mission Critical in the Cloud, but they're on-prem businesses, I think clearly going to be affected here is kind of what you guys pointed out, and I would agree with your thoughts. >> I think what we're seeing is organizations they had a Cloud roadmap, and that roadmap is continuing. The one thing that is changing in some of that roadmap is we need to be able to support employees as they work from home as we achieve this roadmap. And so that's why we're not seeing a reprieve on the legacy side. But we are seeing upticks and spin where we just wouldn't anticipate them right on maybe on Citrix, on Dell laptops, Adobe and a few other areas. Now, in terms of security side, some of the next gen security vendors like CrowdStrike APi, which is an MFA, those vendors are doing well. It makes sense, where you have more people working from home, you have more devices that are connecting to data applications. Just a component itself. And so you would expect spend to continue going up as you need more authentication, more Endpoint Protection. Cisco Meraki they do Cloud Networking. That piece is looking very good, even though Hardware networking is not looking very good at all. The Cloud Networking is looking good, which again makes sense, as you're increasing bandwidth on that side. >> Definitely stories of two sides of that coin. >> That's right >> I want to... Andrew, if you want to... If you wouldn't mind bringing up the next job, we're going to go back to the first one that we showed you with the time series. This is a very important point. Again, we can't stress it enough. We want to understand the impact of the stimulus or aid package. And ETR is going to continue to track that. What can we expect from you guys over the next week or so? >> The goal is to determine whether or not the stimulus is having an impact on how people are responding to our survey as a relates to how they're changing their budgets. The next four or five days, if we start seeing an uptick in this yellow and blue lines here, I think that's a positive. I think that shows that people are kind of wrapping their heads around, great government is taking action here. There is a roadmap in place to help us get out of this. But if the line continues coming down, it just may be that the last few weeks or the last month or so, there was just so much damage. There's not really... There's no coming back from this at least in the near term. So we are kind of watching out for that. >> Well, the Fed is definitely active. >> They're doing right what they can, they're pushing liquidity into the marketplace. People think out of bullets. I don't agree with the Fed. Fed has a quite a bit of of headroom and some dry powder, (murmurs) which is awesome. But the Fed itself, can't do it. You needed to have this fiscal stimulus. So we're excited to see that come to market. I think what I would say to our audiences, my concern is uncertainty. The markets don't like uncertainty and right now there's a lot of uncertainty. If you saw the piece on medium of The Hammer And The Dance it lays out some scenarios about what could happen to the healthcare system. You see people who say, "hey, we should shut down for 10 weeks." The president saying, "hey, we want "to get back to work by by April." The big concern that I have is: okay, maybe we can stamp it out in the near term and get back to work by late April, early May. But then what happens? Are people going to start traveling again? Are people going to start holding events again? And I think there's going to be some real question marks around that. That uncertainty I think, is something that we obviously have to watch. I think there is light at the end of the tunnel, when you look at China and some of the other things that are happening around the world, but we still don't know how long that tunnel is. I'll give you final thoughts before we wrap. >> I think and that's the biggest thing here is the uncertainty, which is why we're doing a lot of this event analysis. We're trying to figure out: after each one of these big events, is there more certainty in people's responses? And just we were talking about, sectors and verticals and vendors that are not doing well. Because the uncertainty we're seeing a lot of down ticks and spend amongst outsource IT and IT consulting vendors. And as long as the uncertainty continues, you're going to see more and more IT projects frozen, less and less spend on those outsource IT and IT consulting vendors and others. And until there's something really in place here where people feel comfortable, you're going to probably see budgets remain where they are, which right now they're negative. >> Folks as we said last week, Sagar and I, ETR is committed, theCUBE is committed to keep you updated on a regular basis. Right now on a weekly cadence. As we have new information, we will bring it to you. Sagar, thanks so much for coming on and supporting us. >> You're welcome and thanks for having me again. >> You're welcome. Thank you for watching this CUBE Insights powered by ETR. And remember all these breaking analysis available on podcast, go to etr.plus that's where all the action is in terms of the survey work. siliconangle.comm covers these breaking analysis and I published weekly on wikibond.com. Thanks for watching everybody. Stay safe. And we'll see you next time.
SUMMARY :
this is theCUBE Conversation. Sagar, great to see you again, thank you for coming on. that we showed last week, You're seeing that in a lot of the CIOs responses. Really ETR is the only company that I know of anyway, And so the beauty of doing this, What is the end that we're at today? The growth rate on the IT side, the larger it is, the more cuts you can make. And again, the ends have gone up and a little bit more down and in the red. But the offset we talked about last week, from the standpoint of things are going to get better and some permanence in the way in which companies On the upside, I think you kind of hit it, is the January survey to the current survey in the yellow, One of the unique things that we can do Obviously, as I said that the on-prem folks, "some of the legacy vendors are going to do well At the same time, it's going to be interesting to see IBM some of the next gen security vendors like CrowdStrike APi, sides of that coin. And ETR is going to continue to track that. it just may be that the last few weeks And I think there's going to be some And as long as the uncertainty continues, theCUBE is committed to keep you updated on a regular basis. And we'll see you next time.
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Breaking Analysis: VMware Announces vSphere 7
>>from the Silicon Angle Media office in Boston, Massachusetts. It's the Cube now here's your host, Dave Vellante. >>Hello, everyone. And welcome to this breaking analysis. We're here to assess the VM Ware v Sphere seven announcement, which is the general availability of so called Project Pacific. VM Ware has called this the biggest change to V sphere in the last 10 years. Now Project Specific Pacific supports kubernetes and natively in VM Ware environments. Why is this important? This is critical for multi and hybrid cloud because Kubernetes and its surrounding orchestration enable application portability and management. Yeah, as we've been reporting, VM Ware is one of the big players eyeing multi cloud, along with a crowded field of aspirants that include IBM with Red hat, Microsoft, Cisco, Google and a host of specialists in the ecosystem. Like how she and rancher as well play. Some players have focused in their respective stack swim lanes like security and data protection, storage, networking, etcetera. And with me to dig into this announcement is stew. Minutemen's Do is a senior analyst at Wiki Bond and co host of The Cube is too good to see you and let's get into it great to talk about this state. Okay, so the Sphere seven, what is being announced? And why is it relevant? >>Yes. So, David, as you said in the open, this is the general availability of what they talked about at VM World 2019 as Project Pacific. So it really is integrating kubernetes into V sphere. The VM ware, of course, will position this is that they're now enabling, you know, the 90% of the data centers around the world that have VM ware. Hey, your kubernetes enabled. Congratulations. You're cloud native. Everything like that. Only being a little facetious here. But this is very important. How do we get from where we were to live in this more cloud? Native environments. So containers in general and kubernetes specifically are being a first class citizen. There's a lot of work, Dave, and my understanding this has been going on for a number of years. You know, it's not like they just started working at this six months ago. A overhaul to how this works. Because it's not just we're going to stick a couple of containers on top of, you know, the guest operating system in the virtual machine. But there is a supervisor cluster for kubernetes at the hyper visor level. And there's a lot of, you know, in the weeds things that we're all trying to understand and figure out because you've got you know, we've got a hyper visor and you've got VM. And now you've got the containers and kubernetes on. Some of them are living in my data center. Some VM ware, of course, lives on multiple clouds like the VM ware on AWS. Solutions of this will go there on and, you know, how do I manage that? How does this impact my operations? You know, how did this change my application portfolio? Because, you know, the early value proposition for VM Ware always was. Hey, you're gonna put VM ware on there. You don't need to touch your applications. Everything runs like it did before you were running windows APS on a physical server. You move into virtual. It's all great. There's a lot of nuance and complexity. So when VM Ware says this is the biggest change in a decade probably is, I think back to you know, I remember when the fx 2.0, rolled out in V motion really changed the landscape. That was big V balls. Move to really ah storage. To really understand that architecture and really fix storage was was a huge undertaking that took many years. This this definitely stacks up with some of those previous changes to really change the way that we think about VM Ware. I think the advertising you have even seen from being where some places is don't think of them as VM ware their cloud where our container ware with like because vm zehr still there. But VM Ware is much more than VMS today, >>so this feels like it's bm were trying to maintain its relevance in a cloud native world and really solidify its because, let's face it, VM Ware is a platform that Pat Gelsinger's has ride. The Waves tried many times in many angles to try to ride the cloud wave, and it's finally settled on the partnerships with AWS specifically. But others on DSO really Is this their attempt to become cloud native, not get left behind and be cloud naive? His many say >>Yeah, great question, David. Absolutely. There's the question as to you know what's happening with my applications, you know lots of customers. They say, Well, I'm just going to satisfy the environments. Watched the huge growth of companies like service now workday. Those applications, well, customers don't even know what they live on. Do they live on virtualization? Environment is a containers I don't need to worry about because SAS takes care of that. If I'm building modern applications, well, I'm probably not starting with VMS. Containers are the way that most people are doing that. Or they might even be going serverless now if we take these environments. So how does VM ware make sure that they have the broadest application support? Kubernetes really won the container orchestration wars on. And this is a way that VM ware now can enable customers to move down that path to modernize their environments on. And what they wanna have is really some consistency between what's happening in the cloud and happening in the environments that they control >>themselves. Vm ware saying that containers in our first class citizen within v sphere what does that mean? Why is that important? First of all, are they really And what does that mean? And why is that important? >>Yes. So, Dave, my understanding is, you know, absolutely. It's their, You know, the nuances that you will put there is. You know, we're not just running bare metal servers with Lennox and running containers on top of it. It is. You're still sitting on top of the hyper visors. One of the things I'm trying to understand when you dig down is you know what? The device driver level VM ware always looked a little bit like Linux. But the people that use it and operate it, they're not letting people Dave, these, you know, the OS. The number one os that always ran on VM ware was Windows and the traditional applications that ran there. So when we talk about containers and we're enabling that in a kubernetes environment, there are some questions about how do we make sure that my applications get certified? Dave, you got a lot of history knowing things like s ap and Oracle. I need to make sure that we've tested everything in this works. This is not what we were running traditionally in VM ware and VM ware. Just thanks. Hey, v Sphere seven, turn the crank. Everything certified Well, I would tell customers make sure you understand that your application has been tested, that your Eyes V has certified this environment because this is definitely, as VM Ware says, a huge architectural change. So therefore, there's some ripple effects to make sure that what I'm doing in this environment stays fully supported. Of course, I'm sure VM Ware is working with their huge ecosystem to make sure that all the pieces or environment you mentioned things like data protection. We absolutely know that VM Ware is making sure the day one the data protection plugs in and supported in these environments when you're using the kind of kubernetes persona or containers solutions in V sphere. >>Well, this brings me to my next question. I mean, we were talking to Bernard Golden the other day and he was saying, You know, Kubernetes is necessary for multi cloud, but it's insufficient. And so this seems to me to be a first step and, as I say, VM ware maintaining and growing its relevance. But there's gonna be a roadmap here that goes beyond just containers and portability. There's other management factors you mentioned security of enabling the ecosystem to plug in. So maybe talk about that a little bit in terms of what's necessary to really build this out over the next >>decade. And actually, it's a great point. So, first of all, you know, V. Sphere, of course, is the core of VM Ware's business. But there's only a piece of the overall portfolio said this lives in. I believe they would consider this part of what they call their Tansu family. Tando is their cloud native overarching piece of it, and one of the updates is their product hands admission control. Which of the existing product really came out of the Hep D Oh acquisition is how we can really manage any kubernetes anywhere, and this is pure software. Dave. I'm sure you saw the most recent earnings announcement from VM Ware, and you know what's going sass. What's going subscription? VM Ware is trying to build out some of their software portfolio that that isn't kind of the more traditional shrink wrap software, so Tan Xue can manage any kubernetes environment. So, of course, day one Hey, obviously or seven, it's a kubernetes distribution. Absolutely. It's going to manage this environment and but also if I've got Cooper days from azure kubernetes from Amazon communities from other environment. Tanja can manage across all of those environments. So when when you're what VM Ware has always done. If you think back in the early days of virtualization, I had a lot of different servers. How do I manage across those environments? Well, VM ware was a layer that lived across them. VM Ware is trying to do the same thing in the cloud. Talk about multi cloud. And how do I manage that? How do we get value across them? Well, there's certain pieces that you know VM Ware is looking to enable with their management software to go across them. But there are a lot of other companies, you know, Amazon Google actually not Amazon yet for multi cloud. But Microsoft and Google absolutely spent a lot of time talking about that in the last year. A swell as you mentioned. Companies like Rancher and Hashi Corp absolutely play across What Lots of these multi cloud. Well, >>let's talk about the competition. Who do you see is the number one competitors >>Well, so the number one competitor absolutely has to be red hat, Dave. So you know, when I've been in the kubernetes ecosystem for a number of years for many years. When I talk to practitioners, the number one, you know what kubernetes you're using? Well, the answer for many years was, Well, I'm grabbing it, you know, the open source and I'm building my own stack. And the reason customers did that was because there wasn't necessarily maturity, and this was kind of leading edge, bleeding edge customers in this space. The number two besides build my own was Red Hat was because I'm a red hat customer, a lot of Lennox tooling the way of building things the way my application developers do. Things fit in that environment. And therefore, that's why Red Hat has over 2000 open shift customers leading distribution for Kubernetes. And you know, this seems purely directly targeted at that market. That red hat did you know it was a big reason why IBM spent $34 billion on the Red Hat acquisition is to go after this multi cloud opportunity. So you know, absolutely this shot across the bow because Red Hat is a partner of VM Ware's, but absolutely is also a competitive >>Well, Maritz told me years ago that's true. We're with everybody and you could see that playing out. What if you look at what VM Ware could do and some of their options if they gave it away, that would really be a shot across the bow at open shift, wouldn't it? >>Yeah, absolutely, Dave, because kubernetes is not free if you're enabling kubernetes on my Google environment, I, you know, just within the last week's awesome things that were like, Okay, wait. If you're testing an environment, yes, it is free. But, you know, started talking about the hourly charges for the management layer of kubernetes. So you know kubernetes again. A color friend, Cory Quinn. Communities absolutely is not free, and he will give you an earful and his thoughts on it s o in Amazon or Google. And absolutely, Dave, it's an important revenue stream for red hat. So if I'm vm ware and you know, maybe for some period of time, you make it a line item, it's part of my l. A. You know, a good thing for customers to look out for is when you're renegotiating your l a toe, understand? If you're going to use this, what is the impact? Because absolutely, you know, from a financial standpoint, you know, Pat Gelsinger on the VM Ware team has been doing a lot of acquisitions. Many of those Dave have been targeted at this space. You know, not to step Geo, but a bit NAMI. And even the pivotal acquisition all fit in this environment. So they've spent billions of dollars. It shouldn't be a net zero revenue to the top line of what VM Ware is doing in the space. >>So that would be an issue from Wall Street's perspective. But at the same time, it's again, they're playing the long game here. Do we have any pricing data at this point? >>So I still have not gotten clear data as to how they're doing pricing now. >>Okay, Um, and others that are in there and in the mix. We talked about Red Hat. Certainly Microsoft is in there with Arc. I've mentioned many times Cisco coming at this from a networking perspective. But who else do you see and then Antos with Google? >>Yeah. And you know, Dave, all the companies we're talking about here, you know, Pat Gelsinger has had to leverage his intel experience to how to balance that line between a partner with everybody but slowly competing against everybody. So, you know, we've spent many hours talking about the VM Ware Amazon relationship. Amazon does not admit the multi cloud a solution yet and does not have a management tool for supporting all of the kubernetes environment. But absolutely Microsoft and Google do. Cisco has strong partnerships with all the cloud environment and is doing that hybrid solution and Dave Justice nothingto expand on a little bit there. If you talk about V sphere, you say, Okay, Visa or seven trolling out Well, how long will it take most of the customer base to roll to this environment? There will be some that absolutely want to take advantage of kubernetes and will go there. But we know that is typically a multi year process to get most of the install base over onto this. And if you extend that out to where VM Ware is putting their solution into cloud environments, there's that tension between, you know, Is there a match actually, between what I have in my data center and what is in the managed environment managed by VM Ware and Amazon, or manage for to support some of the other cloud environment. So the positioning always is that you're going to do VM Ware everywhere, and therefore it's going to be consistent everywhere. Well, the devil's in the details because I have control on what's in my data center, and I might have a little bit less control to some of those managed services that I'm consuming. So absolutely something to keep a close eye on. And not just for VM, where everybody is having these concerns. Even if you talk about the native kubernetes distributions, most of the kubernetes services from the cloud providers are not, you know, immediately on the latest revision of kubernetes, >>right, So Okay, well, let's let's talk about that. Remember when open Stack first came out? It was a Hail Mary against Amazon. Yeah, well, the new Hail Mary and looks like it has more teeth is kubernetes right, because it allows portability and and and of course, you know Amazon doesn't publicly say this, but it's not. That's not good for Amazon. If you're reporting things, applications, moving things around, moving them out of the Amazon cloud, and that makes it easier. Of course, Amazon does support kubernetes right, But you've got >>alternatives. So, David, it's fascinating. So I've talked to many practitioners that have deployed kubernetes and one of the top reasons that they say that why they're using Kubernetes is so they have options with the cloud. When you also ask them what cloud they're running, they're running Amazon. Did they have planned to move off of it? Well, probably not. I had a great customer that I didn't interview with that one of the Cube con shows, and they actually started out with Azure just because it was a little further head with kubernetes and then for the services they wanted. They ended up moving to AWS and Dave. It's not a click a button and you move from one kubernetes to another. You need toe match up and say, Okay, here's the five or six services I'm using. What are the equivalent? What changes do I need to make? Multi cloud is not simple. Today, I mentioned Hashi Corp is one of those companies that help people across these environments. If you have haji solution and you're managing across multiple clouds, you look in the code and you understand that there's a lot of difference between those different clouds, and they simplify that. But don't eliminate it. Just it is not. There is not a way today. This is not a utility when you talk about the public cloud. So you know Kubernetes absolutely is existentially a little bit of a threat to Amazon but Amazon still going strong in that space. And you know that the majority of customers that have deployed kubernetes in the public cloud are doing it on Amazon just because of their position in the marketplace and what they're. >>So let's double click on that. So Jassy, an exclusive interview with John Furrier before last year's re invent, said, Look, we understand there's a lot of reasons why people might choose multiple clouds, you know, go through them in a developer preference. And I think I think, you know, people want o optionality and reduce lock in potentially. But I've always said, by the way, just as an aside, that that the risk of lock in it is far down on the list relative to business value, people will choose business value over over, you know, no lock in every time. About 15% of the customers you might not agree. Nonetheless, Jassy claimed that typically when you get into a multiple cloud environment, he didn't use the term multi cloud that it's it's not a 50 50. It's a premier primary cloud supplier. So might be 70 30 or 80 20 or even 90 10. But it's really that kind of, you know, imbalance. First of all, do you see that? And then what does that mean for how they approach of this space? Multi cloud and in particular. >>So I'm sorry. You're asking how Amazon should approach the space. And you've said that I don't think they'll >>eventually enter this market place. >>Yeah, you know, absolutely, Dave. You know, first of all, in general, yes, I do agree. It is not. There are certain financial companies that, you know, have always chosen two of everything. Because for regulation and you know certain we need to protect ourselves. We're gonna have to suppliers. We're going to keep them as even as possible. But that is a corner case. Most customers I have a primary cloud. That's what I'm doing. That what I t tries to get everybody on and you need to have Is there a reason why you want to use a secondary or tertiary cloud because there's a service that they need. Of course, Google. You often run it. It's like, Oh, well, there's certain data services that they're doing well And, of course, the business productivity solutions that Microsoft's doing where the relationship with Oracle that are driving people towards Microsoft. But just as we saw Amazon soften on their hybrid solutions, we spent a lot of time at re invent talking about all the various hybrid solutions. Um, since their customers are going to have multiple clouds on and even you take most of their customers that have M and a involved you buy another company, they might be using another cloud. As Microsoft's position in the marketplace has grown, you would expect that Amazon would have not just migration services but management services to match what customers need, especially in this kubernetes environment, seems that it seems a natural fit for them. It's possible they might just leverage, you know, partnerships with red hat VM ware, you know, in some of the other players for the time being. But if the market gets big enough and customers are asking for it, that's usually when Amazon response >>So let's let's wrap with what this means to the customer. And I've said that last decade really multi cloud was a symptom of multi vendor and not so much of the strategy that's changing. You know, clearly, jokes CIOs are being called in to clean up the crime scene on do you know, put in edicts corporate edicts around security and governance and compliance and so forth. So it started to become a complicated situation for a lot of companies. We've said that multi cloud is gonna it's gonna be they're going. People are going to put the right war load and the right cloud, etcetera, and this advantages to certain clouds. But what should customers be thinking specifically as it relates to v. Sphere seven? >>Yes. So, Dave, the biggest thing I would say that people need to look at it is that understanding in your organization that that boundary and line between infrastructure and application people have often looked at you looked at the ascendancy of VM Ware, Andi V. M's and then what's happening with cloud and containers. And we think of it from an infrastructure standpoint that I'm just changing the underlying pieces. This is where it lives and where I put things. But the really important thing is it's about my data and my applications, Dave. So if I'm moving an application to a new environment, how do I take advantage of it? You know, we don't just move it to a new environment and run it the same way we were doing it. I need to take advantage of those new environments. Kubernetes is involved in infrastructure, but the real piece is how I have my application, my developers, my app. Dev's working on this environment and therefore it might be that if VM Ware's the right environment, I'm doing a lot of it that the development team says, Hey, I need you to give me a pool and provisioned this for me and I can have my sandbox where I can move really fast. But VM Ware helped initially customers when they went from physical to virtual, move faster. From an infrastructure standpoint, what it needs to do to really enable this environment is help me move faster on the application side. And that's a big gap from VM. Ware's history is where the pivotal people and hefty O people and bit NAMI and all the new people are helping along to help that whole cloud native team. But that is a big shift from customers. So for this to be successful, it's not just, oh, the virtualization admin. He upgraded to the new thing. He made some changes and said, Okay, hey, I can give you a kubernetes cluster when you need it. It's really understanding what's going to happen on the application side in a lot of that is going to be very similar to what you're doing in cloud environments. And I think this is Dave often where your customers, they say, Oh, well, I did that cloud and it was too expensive and it was too hard, and I repatriated. Everything else is, well, you probably didn't plan properly and you didn't understand what you're getting yourself into. And you jumped into the deep end of the pool and oh, wait, I forgot how to learn how to swim. So you know, that is where we are. You know, Dave, you know the technology parts. Always the easiest piece. It's getting all of the organizational and political things sorted out. And you know the developer we know how important that is, we're seeing. It's great to see VM Ware pushing faster in this environment. Kudos to them for how fast they moved. Project Pacific to G. A. That is really impressive to see and can't wait to hear the customers roll out because if this is successful, we should be hearing great transformation stories from customers as to how this is enabling their business, enabling them to move faster on. You know, that has been what, one of the favorite stories that I've been telling with customers on the Cube last couple of years. >>The vast majority of VM Ware's business, of course, is on print, and essentially they're doing here is enabling developers in their customer base and the half a 1,000,000 customers to really develop in a cloud native manner. The question is, you know, from a ah, from a cultural standpoint, is that actually gonna happen? Or the developers gonna reject the organ and say, No, I want to develop in AWS or Microsoft in the cloud. I think VM Ware would say, We're trying to embrace no matter where they want to develop, but they're still going to be. That's interesting organizational tension or developer attention in terms of what their primary choices is. They're not. >>Yeah, Dave, Absolutely. We've been saying for years. That cloud is not a location. It is an operating model. So this is helping to enable that operating model more in the data center. There's still questions and concerns, of course around, you know, consumption on demand versus you know, whether whether you've bought the entire thing as more and more services become available in the public cloud, are those actually enabled to be able to be used, you know, in my data center hosted environment. So you know, this story is not completed, but we're definitely ready. I believe we're saying it's the multi clouds Chapter three of what? We've been watching >>you and you're seeing a major tam expansion yet again from VM Ware that started with the NSX. And then, of course, went in tow networking and storage. And now they've got a cloud security division. We're talking about the the cloud native capabilities here and and on and on, it goes to thanks for helping us break this VC seven announcement down and good job fixed. All right. And thank you for watching everybody. This is Dave Volante for stew Minimum. We'll see you next time on the Cube. >>Yeah,
SUMMARY :
It's the Cube now VM Ware has called this the biggest change to V sphere in the I think back to you know, I remember when the fx 2.0, rolled out in V motion many times in many angles to try to ride the cloud wave, and it's finally settled on the partnerships There's the question as to First of all, are they really And what does that mean? One of the things I'm trying to understand when you dig And so this seems to me to be a So, first of all, you know, V. Sphere, of course, is the core of Who do you see is the number one competitors When I talk to practitioners, the number one, you know what kubernetes you're using? and you could see that playing out. you know, started talking about the hourly charges for the management layer of kubernetes. But at the same time, But who else do you see and are not, you know, immediately on the latest revision of kubernetes, because it allows portability and and and of course, you know Amazon doesn't publicly This is not a utility when you talk about the public cloud. But it's really that kind of, you know, You're asking how Amazon should approach the space. you know, partnerships with red hat VM ware, you know, on do you know, put in edicts corporate edicts around security and governance and compliance and And you know the developer we know how important that is, The question is, you know, So this is helping to enable that operating model more in the data center. And thank you for watching everybody.
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Cisco Live Enterprise Tech Analysis | Cisco Live EU Barcelona 2020
>>live from Barcelona, Spain. It's the Cube covering Cisco Live 2020 right to you by Cisco and its ecosystem partners. >>Live on Welcome to the Cube. 2020 is the first Cube segment and session for 2020 next 10 years. This is the 10th year the Cube has been in operation. We're here in Barcelona for Cisco Live, but we're going to spend the next few minutes talking about the Enterprise Tech trends for 2020 and beyond. Really looking back at the past 10 years and then forward 10 years, I'm John Furrier, host of The Cube with Dave Vellante, Stew Minimum and The Cube team. The analysts want to analyze Enterprise tech. You know we love to do that day, but I think more notable is this is our first interview in 2020 for the year. We're kicking off our 10th year as we close down the Cube for 10 year anniversary in May. Quite an evolution. A lot of things we got right with Wiki bond research and the Cuban sites. Ah, lot of things we saw early, and that's the benefit of the Cube. And now, more than ever, it's more complex. It's a lot of noise. A lot of people talking about value propositions here. They're a lot of cloud. I think the reality is set in Cloud is here. It's not a question of why and when it's now. And the impact is just hitting mainstream Tech and Enterprises now leading the category in investments, venture capital, private equity M and A over consumer companies seeing much more focused emphasis on what's going on in the enterprise, which is business. Incredible opportunity ahead. 2020. What's in store? >>Well, you know, the last decade we obviously saw the consumer ization of i t. There was all that social media hype, and I think you're right, John. The enterprises now where the action is. But the last 10 years have been all about Cloud. What got us here to 2020 is not what's going to power through the next 10 years. I think it's not only Cloud, it's cloud plus data, which we definitely bet on it, right. But now the injection of machine intelligence on that data, which, of course, is running in the cloud for scale. So the real big question now is what's gonna happen in the cloud guys Amazon and Azure and clearly have momentum. Google actually beginning to pick it up a little bit, but particularly the case of Amazon who dominated the last decade. Yeah, it's gonna be not as easy for them going forward, You know, everybody now realizes. Wow, they got it right. You said many times they were misunderstood. Well, I think now people are beginning to realize how powerful they are. And the enterprise players have really begun to respond. And they don't like to give up their position to be really interesting to see how that goes. And, of course, you know we're going to talk more about Cisco, but still what? Your thoughts? >>Yeah. So, John, I think some of the things that we looked at as bleeding edge over the last 10 years are becoming a bit more mainstream. The role of the developer. We know the developers, the new king maker. You look where we are in the DEV Net zone. Definite zone. A couple years ago was small and there was people were kind of exciting everything. You look at it today, it looks much more like the regular show. It has really become mainstream. Dave said Cloud Cloud is mainstream developers mainstream that connection between the business enterprise, tech talk about and these other pieces really coming together. That's where the data really is the next fly wheel for what's happening and obviously machine learning the application developer. And still, it's about moving faster that companies are looking to do, and that is what all of the last 10 years has been building for. And now it's the new normal >>great, and I want to get into some of the ways I think when you look at this, because we can always rattle into any kind of technology. But you know, one things that we love to do is look at the ways what waves are going to come where you get your thoughts on that. But I think just let's reflect on what's going on around us right now. The Cube is the 10th year finishing up its 10th year. We're in the media business had a comment from someone here, a distinguished engineer at Cisco said. I can't believe you guys are a technology company. I had tweeted out yesterday on Barcelona about our Cube alumni list. It's turning into an expert network If you look at what's going on with Facebook and with Trump and the impeachment, you're seeing a changing of the guard in the media business. So we as media with Cube, it's looking angle has become interesting, and I think I bring this up because that's kind of out our new model that we've been doing for 10 years. But if you look at how people share information, misinformation, quality information, you're starting to see a paradigm where you don't know what the trust vendor A says they could do this vendor b so they could do that. Amazon says. This Azure says that. So I think the practitioners and consumers of I t in Enterprise Tech, the buyer's Where's the truth day? I mean, the models are completely changing. I've heard comments in the analyst firms are struggling to get modern press outlets are being dwindled down to a handful in the enterprise that new networks are being formed. The expert APS are out there. So this is a tell sign, Yeah, that the world more complex and different than ever before. >>The authentic community doesn't lie right, And your peers at the other day when you have private conversations. That's where the truth comes out. To the extent that you can like to bring that to the Cuban sessions like this, that's really where you say, extract the signal from the noise. We try to do that. We try to do it for 10 years, and I think that's part of the reason why we've been so successful. But at the same time, Look way no were funded by sponsors, which is great. We really appreciate their support, but at the end of the day, we've always gotta put forth what we think is actually happening out there. >>Let's get into some of the ways because it sets the context. So as you have these networks forming, you have cloud technology. You know, Os, I model looks, but I look back at the nineties, and I think this is a proposed to the Cisco show at that time. Dave, During the mini computer wave that set the stage for what became the PC revolution and then ultimately inter networking category, you had proprietary network operating systems, IBM s and a digital equipment corporation deck net, etcetera, etcetera and incomes. The open systems interconnect seven layer stack that changed the industry. In today's world, we have open source, but people are chirping about open core. There seems to be a trend towards proprietary now. Amazon is the big proprietary cloud. >>I don't >>mean proprietary in the sense of you can work with it, but scale is the new proprietary. So you almost have this revert back to old tactics of differentiation, and I think that's not good for customers. I think you look at the customer situation, it creates more complexity. And so I think that's why we're seeing multi Cloud really be a trend, because whoever can connect all the clouds and do that seamlessly is going to win big. And I think that's a TCP I peed like Dynamic >>John. It's a really interesting point because open source in general is more important than ever before. Enterprise companies are contributing. The big vendor community is spending more time on open source than they are on standards anymore. Over. If you look at the big projects out there limits kubernetes like more than half of the contributors have full time jobs. They work for big companies, but as you said, how am I consuming that get hub is a company at the core of open source. But get the platform itself is a proprietary, that open core model that you talked about. And of course, Microsoft built them for a big number. And some people have a little bit concerned >>when might get Lab is there >>and get lab right. Of course, similar they deliver their application itself. Is that open core model so open source is there. Open core is the model that they're doing. Absolutely. It is interesting because, as you said, open source is more pervasive than ever. But I'm consuming it more as >>a service >>from Amazon or from these >>providers face to the bitching and moaning that's going on the open source because there is kind of a lot of chirping going on around. Well, you know, if I build this in the open, is it truly open being co opted by? So the big clouds and you got Microsoft Microsoft Open Office 3 65 That's not gonna go away for the next 10 years. They've SAS ified, their core offering almost like a lock in. I mean, so so it seems to be just >>it smells >>like that old nasty >>habit. Everything we're entering this decade with four trillion years of Amazon hit Trillionaire Club in 2018. Drop town lost Akamas, Russ Hanneman would say, But but Apple, Google, Microsoft and an Amazon they looking vulnerable, don't in the trillions club. But I mean, I would point out, You're saying John, there will be a backlash. Open source Open, open distributed computing tier networks. I don't think I mean history would suggest that these big whales, they're not invulnerable. They can be taken down and open. Source is is one way out? >>Well, it's interesting. One of the things you look at one of the big threat for Cisco for a long time was like, Oh, STN is going to take over what Cisco's doing Well, Cisco still doing just fine with software defined networking and what that having the open compute model for networking is also a threat. If I look at Microsoft, Azure is leveraging their model that the big hyper scaler aren't necessarily coming to Cisco for gear. They're shifting as to where Cisco will be involved. When we talk about cloud models, they're spending much more time up the stack. John in the layer four through seven, they are down in their traditional Vera to three. >>The pressure on these monopolies, historically to continue to perform as public companies, has been enormous, and they get more proprietary to your point, John. And eventually the open markets has hold on. You know that opens up new opportunities. It takes a while, but it's always happened. >>I don't think I think your point about the big incumbent. Players are not going to yield to just being rolled over by the incumbent growing cloud companies. But you cannot deny the fact that, say, Amazon. Dave, I want to get your thoughts on this because what Amazon did to compute change the game in my mind, they completely changed the capabilities. The consumption models, the cost structures. All the economics were changed with compute looking outpost wavelengths. When things are getting in, they have their own networking. So the question is, if you have the cloud ification of the Holy Trinity of infrastructure, which is storage, compute networking. Okay, you can see almost the cloud guys almost changing radically. All three of them computes Already done. Stories is already done. Networking is left, so you have networking battleground because you got to move the packets around. You don't need Mpls route routes because you just go through the cloud. How things are stored data, backup recovery. The list goes on and on. Ultimately, that's the infrastructure as code ethos that's going to change the application environment. So it will. Amazon will Google Will azure commoditized or change networking? >>Yeah. I mean, John, we already see that happening when we came two years ago. One of the challenges for most network engineers is what I need to manage. A large part of it I can't actually touch. I have to rely on third party. It's outside. I don't control it. But if something goes wrong, I'm on the hook for it. And if you go look forward a little bit, you know, if I'm deploying serverless architectures, is their networking involved? Yes. So I know what it is. I know my platform underneath it is going to take care of it, you know, sitting here talking about that transformation of the workforce, Dave, you wrote about it in your piece. That future of work is if you're you know, really, you know, putting together, You know, I'm a CCP my job is being a Cisco certified engineer, and my role will be racking, stacking, configuring and changing and managing those boxes today, it's well, I better get involved in the security side or the application side, because that's where I'm actually connected to the business and the data of things. Because if I'm just concerned about the moving packets around, yeah, there's gonna be either automation or clarification or combination of those things. They take that away from a >>couple thoughts on this. John, you were the very first to report trillion dollar opportunity for Andy Jassy and Amazon, and there was a 35 billion, so they have a long way to go. So I think a big theme for Amazon is gonna be tam. Expansion in one of those areas is, of course, networking, and you've seen the cloud slowly eat away reported this in my Wiki Bond post from the data because slowly eating away over the last 10 years. It's the networking share, and one practitioner said, as we put our data into the cloud, we're going to spend less on traditional networking, so it's clearly a threat. So Cisco, obviously diversifying its portfolio, we're gonna talk about that this week. But but more focused, as we've said do under the leadership of Chuck Robbins than it was. >>Well, Dave, here's a question for you because if you look at enterprise spend, they're increasing their spend on public cloud. But their data center stuff. It has stayed relatively solid. We haven't yet seen the erosion there. So are you saying networking is going to road before the rest of it? Because you know the story of data gravity? What? >>I think you're seeing the networking road not necessarily in terms of shrinking Cisco, although there guiding to a flat to down quarter. But you've certainly seen their growth slowdown, and especially in their core networking space. I mean, they've tried to double down on their switching and routing, and they just made new announcements in that space that John, you know well, but unquestionably the cloud is that it had an impact on Cisco's business. >>Well, 20 point, let's look ahead to the next 10 years. We've got a lot going on, so I think wait and see the big wave. So, to me, the big wave will start David on the ways I think the big wave is value proposition. Is the business model evolution? I think that's going to be a way that will constantly be the North Star or transformation. If whatever people are buying or operating, whether it's their infrastructure or their operating model, it has to have direct contribution to the business model, the company. So I think that's 12 I think AI and data will continue to power a lot of the value. And I think networking is going to be cloud ified. And the impact of that is going to be that as cloud and hybrid computing becomes a technical solution that achieves cheese, the operation model of companies you're going to start to see Multi Cloud emerged as a solution of that meaning Multi cloud isn't a technology. It's an outcome of hybrid combination of cloud. And that's going to change how packets are routed, how packets are networked. I think data ai and a complete transformation of the of the engine of business is gonna happen the next 10 years more than we've ever seen before. And I call this Dev Ops 234 point. Oh, do this. Is it a complete new engine of innovation. Technically, with storage, compute networking, where the application focus is going to be business driven, almost dynamic, almost real time. I think that will be a 10 year horizon. I wrote a Twitter post on this just a few minutes ago, and the lead architect for Azure tweeted back and said late, See, Layton sees never changes >>John. The innovation cocktail, as you said, is, What's the driver going forward, Right? >>Yes, exactly The speed of light. You can't solve that problem without putting points of presence all over, but >>the network architecture is what defines. It's, too, and I've been talking about network automation. We talked about Dev ops. But if you think of hybrid as a technical solution, how you work with public and private premises, Edge is just now a new network configuration that is going to be a very instrumental engineering task, which will actually impact how the software engineers, >>to your point, the latency that's physics and that's the plumbing and the plumbing is going to be there. But I do feel like we're exiting the cloud era into a new era of this innovation cocktail that you talk about the sandwich, which is cloud data plus AI plus digital services. And that's really what we're gonna be talking about 8 to 10 years from now is how organizations are applying those digital services and which companies, whether they're cloud native companies or guys like Cisco and IBM, HP Deli, EMC, how they're leveraging those waves and applying them >>to their business. And I'd be curious. See how the standards evolve around, whether it's de facto standards around interoperability around data, >>and you could look at what's >>happening with data privacy. You start to see the tell signs that data is going to be starting managed, just like packets are managed. It's like a whole interesting dynamic. >>But really what? This is the payoff for what company has been working on to be able to move faster. It was before was okay, used to take 18 months, and now I could do it a few months. But now I can react to that business between the automation, the machine learning, you know, putting together cloud, and you're gonna be able to refocus your workforce to be able to respond to the business and drive new value. >>All right, guys, we got to wrap up guest coming up. Appreciate the commentary. I'll just say that Dave Tesla. You mentioned one of your bringing analysis what Tesla did to the automobile company. I think there's going to be someone in the enterprise that comes out of the woodwork that changes the game on everybody. I think opportunity for that kind of new entrant >>in the same way Amazon. >>Did you think? >>I think Amazon is now an incumbent. I mean, look at the size and scale of it is always an opportunity for that bowl start up company. So it takes a kind of new dynamic electricity with cars, so we'll see. Okay, that's a wrap up. This is a cube conversation here in Barcelona for Cisco Live. I'm John. First Minutemen. Dave Vellante breaking down the Enterprise for the next 10 >>years. Yeah, yeah, yeah, yeah
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Cisco Live 2020 right to you by Cisco and its ecosystem And the impact is just hitting mainstream Tech and Enterprises now leading the category And the enterprise players have really begun to respond. And now it's the new normal I've heard comments in the analyst firms are struggling to get modern press outlets To the extent that you can like to bring that to the Cuban sessions like this, and I think this is a proposed to the Cisco show at that time. I think you look at the customer situation, it creates more complexity. get hub is a company at the core of open source. Open core is the model that they're doing. So the big clouds and you got Microsoft Microsoft Open Office 3 65 That's don't in the trillions club. One of the things you look at one of the big threat for Cisco for a long time was like, And eventually the So the question is, if you have the cloud ification I better get involved in the security side or the application side, because that's where I'm actually connected to the Bond post from the data because slowly eating away over the last 10 years. the rest of it? the cloud is that it had an impact on Cisco's business. And the impact of that is going to be that as cloud You can't solve that problem without putting points Edge is just now a new network configuration that is going to be a very instrumental engineering the cloud era into a new era of this innovation cocktail that you talk about the sandwich, See how the standards evolve around, whether it's de facto standards around You start to see the tell signs that data is going to be starting managed, This is the payoff for what company has been working on I think there's going to be someone in the enterprise that comes out of the woodwork that changes the game on everybody. I mean, look at the size and scale of it is always an opportunity for that years.
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Todd Osborne, New Relic & Josh Hofmann, AWS | AWS re:Invent 2019
>>LA from Las Vegas. It's the cube covering AWS reinvent 2019 brought to you by Amazon web services and along with its ecosystem partners. >>Hey, welcome back everyone. Live cube covers here at reinvent 2019 in Las Vegas. I'm John, your host extracting the signal from the noise with Stu Miniman analysts at Silicon angle, the cube and Wiki bond. We've got two great guests talking about the ecosystem and the future of software and how customers are consuming it in the cloud. Todd Osborne G VP of alliances and channels at new Relic and Josh Hoffman, GM and global lead of ISB partner ecosystem of AWS. Guys, welcome to the cube. Thanks so much for having us. So guys, we're the top story to me at this show. So far as I'll see infrastructure at scale. The software development life cycle is continuing to evolve. We are more automation, more as Andy says, heavy lifting's being done, which means that application developers are going to get more and more goodness. Dev ops created infrastructure as code check. Now we've got data, tons of data everywhere. So we're, we're seeing an ISB Renaissance more software. You guys are out there writing software. So what you guys take so far of the impact of the ISV here, Josh, to talk about that because this is a big story, does >>massive, I mean if you walk around the floor, you'll see folks that are automating new ways of doing dev ops. You're looking at new ways of securing serverless functions. Um, you're looking at new types of storage. So you could go across every category of technology in this room and you will see an incredible amount of batim innovation. Our partners are really driving that. >>Talk about the relationship with AWS, new Relic, longstanding partnership. Where is it now? Where's it going? It's, I mean, it's off the charts. So even just the last year, the amount of momentum we've built together as has been fantastic. So we participated in a whole bunch of different programs. We've got dozens, hundreds of joint customers that were doing things together. I mean, just look at this event. It's just a, it's just astonishing. We operate in a lot of different partner models, um, from, from reselling, uh, with, with various partners to building technology programs to participating, uh, with Josh and team and our friends. Uh, our friend Dave McCann and team on a eight of us marketplace. Just a whole host of different things that just continue to, to, uh, expand the partnership at scale. And the consumer is ation of the software, the procurement process she's had Teresa crossing off from public sector, whether you're in the public sector or commercial procurement still stuck in 1995 it feels like, right? >>I mean, like, are they modernizing? They've got a lot more ways to get software with the marketplace. What are you guys seeing with customers? Is it really that bad? Am I over over it? It's not that bad, but you know what I'm saying? I mean, so from my perspective, one of the cool we're seeing is, um, AWS in the cloud. Providers are driving a consolidation of budget of modern stuff, of cloud, of, of all the new things that companies want to do. That's all getting consolidated either in a new groups or new budget cycles and AWS is making it really easy to participate in those. So through programs like the marketplace, through various other other initiatives that we're doing, we can combine what we want to achieve with, with what the customer wants to achieve, which is speed to market with, which is with what AWS wants to achieve, which is faster adoption of all the different services and bringing the right ecosystem along with it. >>So the modernization of the procurement cycles along with the monetization of the technology is really cool to watch. Well, I wanted to ask that before. I want to get to the question that I'm that interested Andy Jassy his point on this keynote, Hey, this is the first time I heard him talk like this. We see two types of developers and two types of customers. People want the low level building blocks, the builders and then a new set of customers who want solutions. Yup. This is, this is your wheelhouse. This is where the solution network kind of ecosystem is evolving very quickly. Can you guys share your observations on what that, what he means by that and what does it mean for customers? >>I'll share it in the context of what we're doing with new Relic. Um, when you think of the concept of a solution, a lot of our customers, hundreds of our enterprise customers are going through our migration programs. They need help making sure that what they're doing on prem is translating to what's happening in the cloud, what the applications are doing on prem, and how they're performing in the cloud. So we've collaborated with NewRelic over the last year and a half on a number of new, not just migration programs, but windows or views into how the applications are performing. And we've designed those specifically for customers who are going through those migrations. So you just take that one little category. Um, and it's an area where we're collaborating together to bring something that is a full solution to the customer for those who are going through that migration journey. >>Your take on the whole solution thing. Yeah. So we, uh, last year at reinvent, we announced really the first solution that new Relic had ever launched trying to meet that market need and we, we announced the cloud adoption solution. So everybody knows we've got this great platform with all these cool features. We had never really gone to market and said, not only do we just address application monitoring or infrastructure mining, we actually address the business outcome of migrating to the cloud and all the benefits of doing that. So we announced that as a methodology last year. We added to that over this, this past year because we've enhanced our platform to, uh, have this new capability that we call programmability, which is the ability to write applications on top of the new Relic platform. So we've built, and we launched today a cloud adoption solution application. Kind of a mouthful. >>But what it is, is it is, it's the ability to use our technology and our platform to very easily drop that into a customer and help them very quickly get time to value of delivering on a solution and ultimately achieving the business outcome they're looking for. Yeah, I taught actually. So as you know, I was at your conference earlier this year in New York city where you really defined what a platform should be. And just like Amazon, what you want is you want builders and you want them putting solutions on Dabo. It gives a little bit of the momentum of what you've seen since new Relic one, and then the rollouts. So I don't know the formal count, but I know we're way past the dozen applications that we launched since then. Uh, we also added several different features including logging and some other technologies. We've closed a bunch of different deals with these new technologies since then. >>Um, and then a couple of the cool things from the partner ecosystem that we've done is with the platform capabilities we have, uh, firstly we're now, uh, getting ready to embark on building our first technology partner program. So we were talking to dozens of different partners in this room about how they can build with us on new Relic to make the platform even stickier, uh, for our customers that can now integrate NewRelic with various other technologies. And then the second, uh, thing we were proud to announce today is we've, we've actually just signed a three new managed service providers. So kind of another partner motion that we're driving in this ecosystem. And the new, all the new features of the neurotic platform helped enable us, uh, to do some really cool things with the platform and also evolving business model, uh, to close. Uh, so we were excited to to close three, top 80 best partners, which is best been global, uh, uh, blaze clan and out of California mission cloud as three new partners that we, uh, just, uh, signed agreements with. >>So we're happy to do that. Yeah. When we talk about the transformation, you know, one of the biggest challenges for customers is their application portfolio. I noticed new Relic has two boosts here. There's one specifically just focused on serverless, which I think is awesome. It's got some cool things. They're very focused on that developer app dev deployment there. Um, but you know, your customers, they've got a broad spectrum of applications and that journey to transformation in a modern nation is going to take time. How do you deal with the spectrum of what they're dealing with? But Todd, maybe start with you and then Josh would love your viewpoints too. I mean the spectrum. Massive. So our biggest challenge is keeping up with everything and continuing to innovate with all the things that are happening. But again, the benefits of the platform that we have enables us to do that in the enhancements. >>We wait and we made this year, this year. Um, now that our platform is, is more open, we can connect data, collect data from multiple entities, not just the new Relic, uh, agents that we've, that we were built on. So, uh, the concept of observability and being able to observe the entire application environment, um, is built on the fact that data's gotta come from all these different places. Then we need to turn that around and curate it, uh, into the right experience and the right use case that the customer's looking for. So, uh, all I can say is that, uh, our, our company is built on innovation. We try and stay on the cutting edge of all that. Try and stay current with that and meet the customer's needs as, as everyone here is innovating like S easy at scale. Todd, talk about what's going on in New York. >>What's the coolest thing going out with new Relic right now? Cause Lou always comes on the Q lose to CEO and he's cool. We love him, but he's always got his hands in something. Yes, he got the observability down. Cloud operations becoming standard. That's a tailwind for you guys as a company. But what cool things are you guys working on right now? Um, I certainly can't do Lou any justice. So the customer stories and things and he comes up with are amazing, but you know, from an industry's perspective, like gaming is hot. Um, and it's just like media and entertainment is hot. So we're just doing some really cool things with some really cool customers. Um, maybe not as cool as Lou would be, but you know, customers like, uh, are really adopting our migration story and we're really driving some significant business together. So customers like world fuel services and fleet complete, uh, we've recently come out and announced the stories of how we're helping these companies migrate. >>And frankly that's what's, that's what's cool about it is like everyone wants to get on the cloud faster, do more faster, and we're, we're enabling that, uh, in some really cool customers. So I'll to get your both reactions just to memes that we're developing on the cube this week. One is called, one is cloud native. If you take the T out, it's cloud naive. Okay. So, and the other one is something that I use on my post when my Andy story I did was you got born in the cloud, which is clear benefits. There's no, there's no discussion there. Check winning builder, but reborn in the cloud as companies are becoming reborn, this isn't the Mike, not just migration. There's a fundamental mind shift shift. Yeah. This is a reborn enterprise. And if you're not be born in the cloud and you're probably not going to be around longer, that seems to be the message. What's your reaction to cloud native without the T and reborn in the cloud? >>Well, I think it's, I think it's an accurate statement. It's funny. It's the first I've heard it. I may steal it. If I can use it, please pass it on. I will. Um, I would say that from an APM perspective, many of our partners are in different phases of their journey. Um, and so everything that we do is around three anchor points, which is helping those companies build great software if they haven't already, or if they're making that transition. Once they've made that transition, how do we help them market the software? And then the third piece is really how do we help them sell it? So in the case of new Relic, um, we've got a number of folks around the world that are helping with that co-sale process based on the solutions that we've jointly defined. Um, and then we also help build out the channel because as AWS, we've got tens of thousands of consulting partners. So the idea when you talk about that journey of becoming cloud native is how do you help a partner through that? You've got to hit on all three of those pillars to do it right. The leadership's got to be there for the top. Totally. You've got to have board alignment. You've got to have executive sponsorship, you've got to have technical buying, all of it. >>You guys have a very savvy customer base, Bray cloud native observability. What is the naivety uh, um, issue? What are people mostly naive about? Cause if you don't do it right with instrumentation observability if you're naive about that, you're going to get bitten in the, you know what? Well being, being naive there is not having your observability platform in place. So, but, but you really can't anymore. The old world of if you had a monolithic application running on servers monitoring, sometimes it was optional or a nice to have something today. You couldn't, you could only afford on your most mission critical applications as soon as you flipped a dev ops, a bunch of cloud native technologies, um, modern applications, but on the most modern frameworks with entities that are, that have all these dependencies to make sure that application works. Monitoring is a must, must have an observability is a must have. >>So that's now even in day one, out of the box, out of the one and two, the in to the reborn comment. As soon as you cross that path, you report, you rebirth yourself every day. Like it's constant. You're releasing code daily or multiple times a day, and so there's no like reborn statement anymore. It's a completely agile process. System changeover. This is not just saying it. You got to really believe what you're doing. You have to measure improvement, which is what new Relic is great at because if you take what's happening now on premise and you go to that transformation, you've got to show that you've actually achieved not just savings, but you're helping developers be more efficient and so you, you can't prove that story without the before and after. Yeah, yeah. Love talking to the cloud native gurus that you guys are, congratulations on your marketplace and ISV success. It's only getting the beginning of that run. It's kicking butt. Congratulations. Hundreds of thousands of customers are buying and hundreds of thousands more talk congratulates a new rule. Always great to have you guys on X. Great, impressive company, great results. Always great team, great product cloud, native ashore. Props to that. Thanks for coming on. Appreciate shit. Thanks so much. I'm John here in the cube, extracting the signal in the noise day. Two of three days of wall-to-wall coverage. Two sets here on the ground. Thanks for watching. We'll be right back.
SUMMARY :
AWS reinvent 2019 brought to you by Amazon web services the impact of the ISV here, Josh, to talk about that because this is a big story, So you could go across every category of technology So even just the last year, I mean, so from my perspective, one of the cool we're seeing is, So the modernization of the procurement cycles along with the monetization of the technology is really cool to I'll share it in the context of what we're doing with new Relic. So everybody knows we've got this great platform with all these cool features. So as you know, I was at your conference earlier this year Um, and then a couple of the cool things from the partner ecosystem that we've done is with the platform But again, the benefits of the platform that we have enables us to do that in the enhancements. into the right experience and the right use case that the customer's looking for. So the customer stories and things and he comes up with are amazing, So, and the other one is something that I use on my post when my Andy story I did was you got born in the cloud, So the idea when you talk about that journey of becoming cloud native is how do you help a What is the naivety uh, You have to measure improvement, which is what new Relic is great at because if you take what's happening now on premise
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Secure SaaS Backup for AWS
our studios in the heart of Silicon Valley Palo Alto California this is a cute conversation welcome to another wiki bond digital community event this one's sponsored by Columbia I'm your host Peter Burris any business that aspires to be a digital business needs to think about its data differently it needs to think about how data can be applied to customer experience value propositions operations that improve profitability and strategic options for the business as it moves forward but that means openly either we're thinking about how we embed data more deeply into our operations that means we must also think about how we're going to protect that data so the business does not suffer because someone got a hold of our data or corrupted our data or that a system just failed and we needed to restore that data very quickly now what we want to be able to do is we want to do that in a way that's natural and looks a lot like a cloud because we want that cloud experience in our data protection as well so that's we're going to talk about with clue Meo today a lot of folks think in terms of moving all the data into the cloud we think increasingly we have to recognize a cloud is not a strategy for centralizing data but rather distributing data and being able to protect that data where it is utilizing a simple common cloud like experience it's becoming an increasingly central competitive need for a lot of digital enterprises the first conversation we had was with a puja and Kumar who John is a CEO and co-founder of comeö let's hear a puja I had to say about data value data services and clue me oh who john welcome to the show Thank You Bertram nice to be here so give us the update in Colombia so Tomio is a two year old company right we just recently launched out of stealth so so far you know we we came out with the innovative offering which is a SAS solution to go and protect on premises you know VMware and BMC environments that's what we launched out of style two months ago we our best of show when we came out of stealth in in VMware 2019 well ultimately we started with a vision about you know protecting data irrespective of where it resides so it was all about you know you know on-premises on cloud and other SAS services so one single service that protects data irrespective of where it resides so far we executed on on-premises VMware and VM see today what we are announcing for the first time is our protection to go and protect applications natively built on AWS so these are applications that an aptitude natively built on AWS that clue me or as a service will protect irrespective of you know them running you know in one region or cross region cross accounts and a single service that will allow our customers to protect native AWS applications the other big announcement we are making is a new round of financing and that is testament to the interest in the space and the innovative nature of the platform that we have built so when we came out of stealth we announced we had raised two rounds of financing 51 million dollars in series a and Series B rounds of financing today what we are announcing is a Series C round of financing of 135 million dollars the largest I would say Series C financing for a SAS enterprise company especially a company that's a little over two years old Oh congratulations that's gonna buy a lot of new technology and a lot of customer engagement but what customers as I said up from where customers are really looking for is they're looking for tooling and methods and capabilities that allow them to treat their data differently talk a little bit about the central importance of data and how it's driving decisions of Cluny oh yes so fundamentally you know when we built out the the data platform it was about going after the data protection as the first use case in the platform longer term the journey really is to go from a data protection company to a data management company and this is possible for the first time because you have the public cloud on your side if you truly built a platform for the cloud on the public cloud you have this distinct advantage of now taking the data that you're protecting and really leveraging it for others that you can enable the enterprise for and this is exactly what enterprises are asking for especially as they you know you know make a transition from on-premises to the public cloud where they are powering on more and more applications in the public cloud and they really you know sometimes have no idea in terms of where the data is sitting and how they can take advantage of all these data sources that ultimately Klum is protecting well no idea where the data is sitting take advantage of these data sources presumably facilitate new classes of integration because that's how you generate value out of data that suggests that we're not just looking at protection as crucially important as it is we're looking at new classes of services they're going to make it possible to alter the way you think about data management if I got that right and what are those new services yes it's it's a journey as I said right so starting with you know again data protection it's also about doing data protection across multiple clouds right so ultimately we are a platform even though we are announcing you know AWS you know application support today we've already done VMware and VM C as we go along you'll see us kind of doing this across multiple clouds so an application that's built on the cloud running across multiple clouds AWS asher and GC p or whatever it might be you see as kind of doing data protection across in applications in multiple clouds and then it's about going and saying you know can we take advantage of the data that we are protecting and really power on adjacent use cases you know they could be security use cases because we know exactly what's changing when it's changing there could be infrastructure analytics use cases because people are running tens of thousands of instances and containers and n VMs in the public cloud and if a problem happens nobody really knows what caused it and we have all the data and we can kind of you know index it in the backend analyze in the backend without the customer needing to lift a finger and really show them what happened in their environment that they didn't know about right so there's a lot of interesting use cases that get powered on because you have the ability to index all the data here you have the ability to essentially look at all the changes that are happening and really give that visibility to the end customer and all of this one-click and automating it without the customer needing to do much I will tell you this that we've talked to a number of customers of Cuneo and the fundamental choice the clue mio choice was simplicity how are you going to sustain that even as you add these new classes of services yes that is the key right and that is about the foundation we have built at the end of the day right so if you look at all of our customers that have you know on-boarded today it's really the experience where in less than you know 15 minutes they can essentially start enjoying the power of the platform and the backend that we have built and the focus on design that we have is ultimately why we are able to do this with simplicity so so when we when we think about you know all the things we do in the backend there's obviously a lot of complexity in the backend because it is a complex platform but every time we ask ourselves the question that okay from a customer perspective how do we make sure that it is one click and easy for them so that focus and that attention to detail that we have behind the scenes to make sure that the customer ultimately should just consume the service and should not need to do anything more than what they absolutely need to do so that they can essentially focus on what adds value to their business takes a lot of Technology a lot of dedication to make complex things really simple absolutely whoo John Kumar CEO and co-founder of Clue leo thanks very much for being on the cube Thank You bigger great conversation with poo John data value leading to data services now let's think a little bit more about how enterprises ultimately need to start thinking about how to manifest that in a cloud rich world Chad Kenny is the vice president and chief technologist at Kumi oh and Chad and I had an opportunity to sit down and talk about some of the interesting approaches that are possible because of cloud and very importantly to talk about a new announcement that clew mios making as they expand their support of different cloud types let's see what Chad had to say the notion of data services has been around for a long time but it's being upended recast reformed as a consequence of what cloud can do but that also means that cloud is creating new ways of thinking about data services new opportunities to entry and drive this powerful approach of thinking about digital businesses centralized assets and to have that conversation about what that means we've got Chad Kenny who's a VP and chief technologist of comeö with us today Chad welcome to the cube thanks so much for having me okay so let's start with that notion of data services and the role the clouds gonna play loomio has looked at this problem with this challenge from the ground up what does that mean so if you look at the the cloud as a whole customers have gone through a significant journey we've seen you know that the first shadow IT kind of play out where people decided to go to the cloud IT was too slow it moved into kind of a cloud first movement where people realize the power of cloud services that then got them to understand a little bit of interesting things that played out one moving applications as they exist were not very efficient and so they needed to react exort anapa second SAS was a core way of getting to the cloud in a very simplistic fashion without having to do much of whatsoever and so for applications that were not core competencies they realized they should go SAS and for anything that was a core competency they needed to really reaaargh attack to be able to take advantage of those you know very powerful cloud services and so when you look at it if people were to develop applications today cloud is the default that you'd go towards and so for us we had the luxury of building from the cloud up on these very powerful cloud services to enable a much more simple model for our customers to consume but even more so to be able to actually leverage the agility and elasticity of the cloud think about this for a quick second we can take facilities break them up expand them across many different computer resources within the cloud versus having to take kind of what you did on Prem in a single server or multitudes of servers and try to plant that in the cloud from a customer's experience perspective it's vastly different you get a world where you don't think about how you manage the infrastructure how you manage the service you just consume it and the value that customers get out of that is not only getting their data there which is the on-ramp around our data protection mechanisms but also being able to leverage cloud native services on top of that data in the longer term as we have this one common global index and path and what we're super excited today to announce is that we're adding in AWS native capabilities to be able to date and protect that data in the public cloud and this is kind of the default place where most people go to from a cloud perspective to really get their applications up and running and take advantage of a lot of those cloud native services well if you're gonna be cloud native and promised to customers as you can support their workloads you got to be obviously on AWS so congratulations on that but let's go back to this notion of user word powerful mm-hmm 80 of us is a mature platform GCPs coming along very rapidly asher is you know also very very good and there are others as well but sometimes enterprises discover that they have to make some trade-offs to get the simplicity they have to get less function to get the reliability they have to get rid of simplicity how does ku mio think through those trade-offs to deliver that simple that powerful that reliable platform for something as important as data protection and data services in general so we wanted to create an experience that was single click discover everything and be able to help people consume that service quickly and if you look at the problem that people are dealing with a customer's talked to us about this all the time is the power of the cloud resulted in hundreds if not thousands of accounts within AWS and now you get into a world where you're having to try to figure out how do I manage all of these for one discover all of it and consistently make sure that my data which as you've mentioned is incredibly important to businesses today as protect it and so having that one common view is incredibly important to start with and the simplicity of that is immensely powerful when you look at what we do as a business to make sure that that continues to occur is first we leverage cloud native services on the back which are complex and and and you know getting those things to run and orchestrate are things that we build on the back end on the front end we take the customer's view and looking at what is the most simple way of getting this experience to occur for both discovery as well as you know backup for recovery and even being able to search in a global fashion and so really taking their seats to figure out what would be the easiest way to both consume the service and then also be able to get value from it by running that service AWS has been around well AWS in many respects founded the cloud industry it's it's you know certainly Salesforce and the south side but AWS is the first company to make the promise that it was going to provide this very flexible very powerful very agile infrastructure as a service and they've done an absolutely marvelous job about it and they've also advanced the state of the art of the technology dramatically and in many respects are in the driver's seat what trade offs what limits does your new platform face as it goes to AWS or is it the same coolio experience adding now all of the capabilities of AWS it's a great question because I think a lot of solutions out there today are different parts and pieces kind of klom together well we built is a platform that these new services just get instantly added next time you log into that service you'll see that that available to you and you can just go ahead and log in to your accounts and be able to discover directly and I think that the Vout the power of SAS is really that not only have we made it immensely secure which is something that people think about quite a bit with having you know not only data in flight but data at rest encryption and and leveraging really the cloud capabilities of security but we've made it incredibly simple for them to be able to consume that easily literally not lift a finger to get anything done it's available for you when you log into that system and so having more and more data sources in one single pane of glass and being able to see all the accounts especially in AWS where you have quite a few of those accounts and to be able to apply policies in a consistent fashion to ensure that you're you know compliant within the environment for whatever business requirements that you have around data protection is immensely powerful to our customers Chad Kenney chief technologist plumie Oh thanks very much for being on the tube thank you great conversation Chad especially interested in hearing about how klum EO is being extended to include AWS services within its overall data protection approach and obviously into Data Services but let's take a little bit more into that Columbia was actually generated and prepared a short video that we could take a look at that goes a little bit more deeply into how this is all going to work [Music] enterprises are moving rapidly to the cloud embracing sass for simplified delivery of key services in this cloud centric world IT teams can focus on more strategic work accelerating digital transformation initiatives when it comes to backup IT is stuck designing patching and capacity planning for on-premise systems snapshots alone for data protection in the public cloud is risky and there are hundreds of unprotected SAS applications in the typical enterprise the move to cloud should make backup simpler but it can quickly become exponentially worse it's time to rethink the backup experience what if there were no hardware software or virtual appliances to size configure manage or even buy it all and by adding Enterprise backup public cloud workloads are no longer exposed to accidental data deletion and ransomware at Clube o we deliver secure data backup and recovery without any of that complexity or risk we provide all of the critical functions of enterprise backup d dupe and scheduling user and key management and cataloging because we're built in the public cloud we can rapidly deliver new innovations and take advantage of inherent data security controls our mission is to protect your data wherever it's stored the clew mio authentic SAS backup experienced scales on-demand to manage and protect your data more easily and efficiently and without things like cloud bills or egress charges pluto gives you predictable costs monitoring global backup compliance is far simpler and the built-in always-on security of Clue mio means that your data is safe take advantage of the cloud for backup with no constraints clew mio authentic SAS for the enterprise great video as we think about moving forward in the future and what customers are trying to do we have to think more in terms of the native services that cloud can provide and how to fully exploit them to increase the aggregate flexible both within our enterprises but also based on what our supplies have to offer we had a great conversation with wounds Young who is the CTO and co-founder of Clue mio about just that let's hear it wound had to say everybody's talking about the cloud and what the cloud might be able to do for their business the challenge is there are a limited number of people in the world who really understands what it means to build for the cloud utilizing the cloud it's a lot of approximations out there but not a lot of folks are deeply involved in actually doing it right we've got one here with us today woo Jung is the CTO and co-founder of Cluny o moon welcome to the cube how they tittie here so let's start with this issue of what it means to build for the cloud now loomio has made the decision to have everything fit into that as a service model what is that practically mean so from the engineering point of view building our SAS application is fundamentally different so the way that I'll go and say is that at Combe you know we actually don't build software and ship software what we actually do it will service and service is what we actually ship to our customers let me give you an example in the case of chromium they say backups fail like software sometimes fails and we get that failures too the difference in between criminal and traditional solutions is that if something were to fail we are the one detecting that failure before our customers - not only that when something fails we actually know exactly why you fail therefore we can actually troubleshoot it and we can actually fix it and upgrade the service without the customer intervention so it's not about the bugs also or about the troubleshooting aspect but it's also about new features if you were to introduce our new features we can actually do this without having customers upgraded code we will actually do it ourselves so essentially it frees the customers from actually doing all these actions because we will do them on behalf of them at scale and I think that's the second thing I want to talk about quickly is that the ability to use the cloud to do many of the things that you're talking about at scale creates incredible ranges of options that customers have at their disposal so for example AWS customers have historically used things like snapshots to provide a modicum of data protection to their AWS workloads but there are other new options that could be applied if the system's are built to supply them give us a sense of how kkumeul is looking at this question of you know snapshots versus something else yeah so basically traditionally even on the on print side of the things you have something called a snapshot and you had your backups right and they're they're fundamentally different but if you actually shift your gears and you look at what they WS offers today they actually offers the ability for you to take snapshots but actually that's not a backup right and they're fundamentally different so let's talk about it a little bit more what it means to be snapshots and a backup right so let's say there's a bad actor and your account gets compromised like your AWS account gets compromised so then the bad actor has access not only to the EBS volumes but also to the EBS snapshots what that means is that that person can actually go ahead and delete the EBS volume as well as the EBS snapshots now if you had a backup let's say you actually take a backup of that EBS volume to Kumu that bad actor will have access to the EBS volumes however you won't be able to delete the backup that we actually have in Kumu so in the whole thing the idea of Kumi on is that you should be able to protect all of your assets that being either an on-prem or an AWS by setting up a single policies and these are true backups and not just snapshots and that leads to the last question I have which is ultimately the ability to introduce these capabilities at scale creates a lot of new opportunities that customers can utilize to do a better job of building applications but also I presume managing how they use AWS because snapshots and other types of service can expand dramatically which can increase your cost how is doing it better with things like native backup services improve a customer's ability to administer their AWS spend and accounts great question so essentially if you look at the enterprise's today obviously they have multiple you know on-premise data centers and also a different cloud providers that the you like AWS and Azure and also a few SAS applications right so then the idea is for kkumeul is to create this single platform where all of these things can actually be backed up in a uniform way where you can actually manage all of them and then the other thing is all doing it in the cloud so if you think about it if you don't solve the poem fundamentally in the cloud there's things that you end up paying later on so let's take an example right moving bytes moving bytes in between one server to the other traditionally basically moving bytes from one rack to the other it was always free you never had to pay anything for that certainly in the data center alright but if you actually go to the public cloud you cannot say the same thing right basically moving by it across aw s recent regions is not free anymore moving data from AWS to the on premises that's not free either so these are all the things that any you know car provider service provider like ours has to consider and actually solve so that the customers can only back it up into Kumu but then they actually can leverage different cloud providers you know in a seamless way without having to worry all of this costs associated with it so kkumeul we should be able to back it up but we should be able to also offer mobility in between either AWS backup VMware or VNC so if I can kind of summarize what you just said that you want to be able to provide to an account to an enterprise the ability to not have to worry about the backend infrastructure from a technical and process standpoint but not also have to worry so much about the backend infrastructure from a cost and financial standpoint that by providing a service and then administering how that service is optimally handled the customer doesn't have to think about some of those financial considerations of moving data around in the same way that they used to oh I got that right I absolutely yes basically multiple accounts multiple regions multiple providers it is extremely hard to manage what Cuneo does it will actually provide you a single pane of glass where you can actually manage them all but then if you actually think about just and manageability this actually you can actually do that by just building a management layer on top of it but more importantly you and we need to have a single data you know repository for you for us to be able to provide a true mobility in between them one is about managing but the other thing is about if you're done if you're done it the real the right way it provides you the ability to move them and it leverages the cloud power so that you don't have to worry about the cloud expenses but kkumeul internally is the one are actually optimizing all of this try our customers wound jeong CTO and co-founder of Kaleo thanks very much for being on the queue thank you thanks very much moon I want to thank chromeo for providing this important content about the increasingly important evolution of data protection and cloud now here's your opportunity to weigh in on this crucially important arena what do you think about this evolving relationship how do you foresee it operating in your enterprise what comments do you have what questions do you have of the thought leaders from Cluny oh and elsewhere that's what we're gonna do now we're gonna go into the crowd chat and we're gonna hear from each other about this really important topic and what you foresee in your enterprise as your digital business transforms let's crouch at
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Keynote Analysis | AnsibleFest 2019
live from Atlanta Georgia it's the tube covering ansible fest 2019 brought to you by Red Hat hello everyone welcome to the queue we are broadcasting live here in Atlanta Georgia I'm John force too many men my co-host the cubes coverage of Red Hat ansible Fest this is probably one of the hottest topic areas that we've been seeing in Enterprise tech emerging along with observability automation and observability is the key topics here automation is the theme stew ansible just finished their keynote keynote analysis general availability of their new platform the ansible automation platform is the big news this is a big I mean it seems nuanced for the general tech practitioner out there what's ansible doing why we here we saw the rise of network management turned into observability as the hottest category in the cloud cloud 2.0 companies going public a lot of M&A activity and observability is data-driven automations this other category that is just exploding and growth and change huge impact to all industries and it's coming from the infrastructure scale side where the blocking and tackling of DevOps has been this is the focus of ansible and their show automation for all your analysis of the keynote what's the most important thing going on here yes so John as you said automation is a super hot topic you know I was just at the New Relic show talking about observability last week we've got the Pedro Duty show also going on this week the the automation is so critical we know that IT can't keep up with things if they can't automate it and it's not just replacing some scripting I loved in the keynote they talked about strategically thinking about automation we've been watching the RP a companies talking about automation so there's lots of different automation there's the right way to do it and another thing angle John that we love covering is you know what's going on with open source you were just at the open core summit in San Francisco the Red Hat team very clear open source is not their business model it is they use open source and everything that Red Hat does is a hundred percent open source and that was core and key to what ansible was and how its created this isn't a product pitch here it's a community you know it's John this is the six most active you know repository in github so out of over a hundred million repositories out there the six most active so that tells you that this is being used by the community it's not a couple of companies using this but it's a broad ecosystem we hear Microsoft and Cisco f5 lots of companies that are contributing as well as just all of the end users we of JPMorgan in the keynote this morning so a lot of participation there but you know it is building out that suite with the platform that you talked about and we're gonna spend a lot of time in the next few days understanding this maturation and growth yeah the automation platform that they announced that's the big news the general availability of their automation platform and stew the word they're using here is scale okay and this is something that you brought up to open core summit which I attended last week was the inaugural conference a lot of controversy and this is a generational shift we are seeing in the midst of our own eyes right in front of us on the ground floor of a shift in open source community how the platform of open source is evolving what Amazon now azure and Google and the others are doing is they're showing that scale has changed the game in how open-source is going to not only grow and evolve but shape application developers and the reason why ansible is so important right now in this conference is that we all know that when you stand up stuff infrastructure you've got to configure the hell out of it DevOps has always been infrastructure is code and as more stuff gets scaled up as more stuff gets provision as more stuff gets built and created the management and the controlling of the configurations this has been a real hot spot this has been an opportunity and a problem so you know everyone who's here they're they're active because you know what this is a major pain point this is a problem area that's an opportunity to take what is a blocking and tackling operational role configurating standing up infrastructure enabling applications and making it a competitive advantage this is why the game is changing starting to see platforms not tools your analysis are they positioned was this keynote successful John and I really liked rut Robin Bergeron came out and talked about the key principles of what antal is done its simplicity its modularity and it's learning from open source this project was only started in 2012 so one of the things I always look at is in the old days you wanted you know to have that experience there's no compression algorithm for experience today if I could start from day one today and build with the latest tools you know heavily using DevOps understanding all of the experience that's happened in open source we can move forward so from 2012 to 2015 Red Hat you know acquired ansible to today in 2019 they're making huge growth and helping companies really leverage and mature their IT processes and move towards you know true business innovation with leveraging automation dude this is not and again this is not for the faint of heart either again these are Rockstar DevOps infrastructure folks who are evolving in taking either network and or infrastructure development to enable and software abstraction layer for applications and this not it's not a joke either I mean got some big names up on stage of just one tweet I want to call out and get your reaction to JP Morgan on his presentation the exact there he was tweet came out from Christopher Festa 500 developers are working to automate business processes leading to among other benefits ninety-eight percent improvement in recovery times what used to take six to eight hours to recover now takes two to five minutes Christopher Festa student so John that's what we want is how can we take these things that took you know hours and I had to go through this ticketing process and make that change what I loved of what Chris from JP Morgan said is he brought us inside he said look to make this change it took us a year of sorting through the security the cyber the the control processes we understand there's not just you know oh hey let's sprinkle a little DevOps on everything and it's wonderful we need to get you know buy-in from the team it you know and it can spread between groups and you know change that culture it's something that you know we've tracked in Red Hat for years and all of these environments this something that does require commitment because it's not just John taking oh I scripted something and and and that's good we need to be able to really look at these changes because automation if we just automate a bad process that's not gonna help our business we really need to make sure we understand what we're automating the business value and and what is going are going to be the ramification to what we're doing well one of the things I want to share with folks watching is some research that we did at Silk'n angle the cube and wiki bond it's part of our cube insights do I know you were part of this we talked to a bunch of practitioners and customers and dozens of our of our community members and we found that observability we've just pointed out has been you know explosive category that automation has been identified and we're putting a stake in the ground right here in the cube as one of the next big sectors that will rise up as a small little white space will become a massive market automation you watch that cloud 2.0 sector called automation why the reasoning was this and here's the results of our of our survey automation is quickly becoming a critical foundational element of the network as enterprises focus on multi cloud network being infrastructure servers and storage a multi cloud rapid application development and deployment software-defined everything's happening pretty much we've been covering that on the cube and most enterprises are just crap lling with this concept and see opportunities the benefits that people see in automation as we've discovered still in the following one focused on focused efforts for better results efficiency security is a top driver on all these things because you got to have security built into the software and then automation is creating job satisfaction for these guys I mean they've been doing this is mundane tasks being automated way so people are happier so job satisfaction and finally this is an opportunity to rescale do these are the key bullet points that we found in talking to our serve our community your reaction to those those results yeah John I love that we know ultimately when we want to be able to provide not only better value to my ultimate end user but I need to look internal as you said John you know how can i you know retool some of my sales force and get them engaged and if you want to hire the Millennials they want a bit just and not be doing the drudgery they want to do something where they feel that they are making a difference and you know you laid out a lot of good reasons why it would help and why people would want to get involved John you know the government I've talked to a number of government agencies when they talk about you know we changed that 40-year old process and now we're doing things faster and better and that means I can really hire that next generation of workforce because otherwise I wouldn't be able to hire them to just do things the old way this is about cloud 2 point and this is about modernization and you mention open source open core summit that I think is a tell sign that open source is changing the communities are changing this is gonna be a massive wave again we've been chronicling this cloud 2 point of the week we coined that term we're trying to identify those key points obviously observability automation but look at the end of the day you got to have a focused effort to make the job go better you heard JP Morgan pointing out minutes versus hours this is the benefits of infrastructure as code in the end of the day employee satisfaction the people that you want to hire to re-skill that can be redeployed into new roles analytics math quantitative analysis versus the mundane tasks automation is going to impact all aspects of the stack so final questions do what are you expecting for the next two days we're gonna be here for two days what do you expect to hear from our guests yeah so John one of the things I'm going to really look at is as you mentioned infrastructure is that where this all started so you know how do I easy to play a VM you know ansible is there you know VMware I've already talked to a number of people in the virtualization community they love and embrace ansible we saw Microsoft up on stage loving embrace it as we move towards micro service architectures containerization and all of these cloud native deployments you know how is ansible in this community doing where the stumbling blocks to be honest from what I hear John coming into this anta Buhl's been doing well Red Hat has helped them grow even more and the expectation is that IBM will help proliferate this in even further the traditional competitors to ansible you think about the chef's in puppet to the world have been struggling with that cloud native world John I know I see ansible when I go to the cloud shows and I hear customers talking about it so ansible seems to be making that transition towards cloud native well but other threats in the cloud native world you know if I've said you know that when I when I go to the server lists you know conference I I don't I have not yet heard you know where this fits into the environment so we always know that that next generation and technology you know how will you know this automation move forward as Red Hat starts to get much more proliferating into major enterprises with IBM which will take their extend their lead even further in the enterprise it's an opportunity for ansible and the community angle is interesting I saw our tweets don't get your community your angle real quick on this I saw a tweet from NetApp their tagline at their booth is simplify automate and orchestrate sounds like they're leading into the kubernetes world containers you got to start thinking about software abstractions and this is the st. the you know provisioning hardware anymore whole new ballgame your assessment of an Sable's community presence mentioned I was a tweet from Red Hat I mean NetApp what's your take on the community angle here John it's all about community we the github stats speak for themselves this is very much a community invent you know kudos to the team here a lot on the diversity inclusion effort so really pushing those things forward John something we always notice at the tech shows the ratio of you know gender is way to more diverse at an event like this we know we see it in the developer communities that there was more diversity in there so by the way when they took over this hotel all of the bathrooms are I believe it's you know it's gender-neutral so you can use whatever bathroom yeah you know you you want there let's make sure I'm using the right pronoun when I'm going saying a lot of people Stu thanks for commentary keynote analysis I'm John first dude minimun breaking down why we are here why ansible why is automation important we believe automation will be a killer category we want to see a lot of growth here and again the impact is with machine learning and AI this is where it all starts automating the data the technology and the configuration is going to empower the next generation modern enterprise more live coverage from ansible fests after this short break
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Jim HPE DCE 3 Segment
thanks Peter I'm here with James kabila Sawicki bonds lead analyst for data science Jim been hearing a lot about data science and how machine learning is coming into this environment give it give us a little bit of a guidance as to how that this this whole space fits into data science you know how does that that infrastructure fit in with data science today yeah well stew data science is a set of practices for building and training statistical models often known as machine learning models to be deployed into applications to do things like predictive analysis automating next best offers and marketing and so forth so what machine learning is all about is the statistical model and those are built by a category of professionals known as data scientists but data scientists operated in teams there are data engineers who manage your data lake there are data modelers who build the models themselves there are there are professionals who specialize in training the models and deploying them trainings like Quality Assurance so what it's all about is really these part these functions are increasingly being combined into workflows they have to conform with DevOps practices because this is an important set of application development capabilities that are absolutely essential to deploy machine learning into AI in AI is really the secret sauce of so many apps nowadays all right Jim is we've looked at data center Ops walk us through the tech the process and the people okay data center else really is data science ops or often well wiki bomb we've referred to as DevOps for data science and really what we start with the the start with the people I've already been to sketch those up so in terms of the people the professionals involved in building and training and deploying and evaluating and iterating machine learning models there are the data scientists who are this justjust iskele modelers you might call them the algorithm jockeys though that may be regarded as a pejorative but nonetheless these are the high-powered professionals who who build who know which algorithm is correct for what the challenge they build the models on there are the data engineers who not only manage your data lakes the data lakes is where the training data is maintained the data for building the model and for training the models are maintained in data lakes the data engineers manage that they also manage data preparation data transformation data cleansing to get the data clean and correct so that it can be used to build high quality models there are other functions that are absolutely essential there are as what some call ml architour machine learning architects I like to think of them as subject-matter experts who work with the data scientist to build what are called the feature sets the predictors that need to be built into machine learning models for those models to do therefore perform their function correctly whether it be a prediction or like face recognition or natural language processing for your ear your chat BOTS and so forth you need the subject matter experts with you to provide guidance to the data scientists as to what variables to build into these models there was also coders there's a lot of coding that's done in data science and ml ops that's done in Python and Java and Scala and a variety of other languages and there's other functions as well but these are the core functions that need to be performed in a team environment really in a workflow and that is where the process comes in the workflow for data science in teams is DevOps it's really the continuous integration of different data sets as well as different models as well as different features into the building and training of AI so these need to be pretty nice functions need to be performed in a workflow that's highly structured where there's checkpoints and there's governance and there's a transparency and auditability so it really all this needs to be performed in a DevOps environment where you have the data lake which is the source of the the data of course we also have a source repository for managing the current and past versions of the models themselves where you also do governance on the code builds that are with each of the models that are deployed into your application environment so that's the process site at all and then the platform our tech side is really revolves around with some colleague data science workbench or a data science platform there's a variety of terms for it but essentially it is a development environment that enables a high degree of automation and all across all these functions because automation is absolutely essential for speed and consistency in terms of how models are built and entrained there's also a need for our collaboration capability strong ones within these platforms so these different human roles can work together in a cohesive fashion and really like a well-oiled machine screaming there's a need for repositories - like I said managed in govern the current versions of all the artifacts be they data be they models be they code bills and so forth that are essential so all of these people processes and Texas and there is building high-quality AI yeah so Jim I noticed you call it DevOps for data science so yes there's a real emphasis there on how we get all of these new things aligned with the process for DevOps and maybe help us put a point on you know why that's so important well because DevOps is how applications are built and deployed now everywhere which is essentially it so it's a workflow it's a standard workflow that involves a scaleable organization where you have code that is built and managed and governed according to a standard workflow standard repositories with checkpoints and transparency as a way of consensual e ensuring that high quality code is deployed into working applications according to essentially a factory-style automation or an industrialized workflow so data science is a development discipline data science needs to as a as a workflow needs to conform with the established DevOps practices that your application developers your coders have already established in fact most AI applications most machine learning applications involve code involved machine learning models but also involve containers and kubernetes and increasingly serverless interfaces and so forth so data science is not separated from the other aspects of the DevOps workflow itting and christie is a unified and integrated piece of your operations and they needs to be managed as such all right well Jim appreciate you going through the evolution on that I know you've written quite a bit about this topic on the wiki bond website and Peter will send it back to you
**Summary and Sentiment Analysis are not been shown because of improper transcript**
#HybridStorage
from our studios in the heart of Silicon Valley Palo Alto California this is a cute conversation hi I'm Peter Burris analyst at wiki bond welcome to another wiki bond the cube digital community event this one sponsored by HP and focusing on hybrid storage like all of our digital community events this one will feature about 25 minutes of video followed by a crowd chat which will be your opportunity to ask your questions share your experiences and push forward the community's thinking on the important issues facing business today so what are we talking about today again hybrid storage let's get going so what is hybrid storage in a lot of shops most people have associated the cloud with public cloud but as we gain experience with the challenges associated with transforming to digital business in which we use data as a singular value producing asset increasingly IT professionals are starting to realize this important relationship between data storage and cloud services and in many respects that's really what we're trying to master today is a better understanding of how the business is going to use data to affect significant changes in how it behaves in the marketplace and it's that question of behavior that question of action that question of location that is pushing business to think differently about how its cloud architectures are going to work we're going to keep data proximate to where it's created to where it's going to be used to where it's going to be able to generate value which demands that we have storage resources in place close to that data proximate to that activity near that value producing activity and that the cloud services will have to follow in many respects that's what we're talking about when we talk about hybrid cloud today we're talking about the increasing recognition that we're going to move cloud services to the data default and not move the data into the cloud public cloud specifically so it's this ongoing understanding as we gain experience with this powerful set of technologies that data architecture is going to be increasingly distributed that storage therefore will be increasingly distributed and that cloud services will flow to where the data is required utilizing storage technologies that can best serve that set of workload so it's a more complex world that demands new levels of simplicity ease of use and optimization so that's where we're going to start our conversation so these crucial questions of how data storage and cloud are going to come together to create hybrid architectures was the basis for a great cubed conversation between silicon angle wiki bonds david Volante and HPE sun dip aurora let's hear what they had to say talk about let's talk about the break down those three things cost efficiency ease of use and resource optimization let's start with cost efficiency so obviously there's TCO there's also the way in which I consume the people I presume are looking for a different pricing model is that are you hearing that yeah absolutely so as part of the cost of of running their business and being able to operate like a cloud everybody is looking at a variety of different procurement and utilization models one of the ways HPE provides utilization model that can map to their cloud journey a public cloud journey is through Greenlake the ability to use and consume data on-demand consume compute on demand across the entire portfolio of products HPE has essentially is what a Greenlake journey looks like and let's go into ease-of-use so what do you mean by that I mean people look they think cloud they think swipe the credit card and start you know deploying machines what do you mean by easy for us ease of use translates back to how do you map to a simpler operating and support model for us the support model is the is the key for customers to be able to to realize the benefits of going to that cloud to get to a simpler support model we use AI ops and for us a offs means using a product called info site info site is a product that is uses deep learning and machine learning algorithms to look at a wide net of call home data from physical resources out there and then be able to take that data and make it actionable and the action behind that is predictiveness the prescriptive nosov creating automated support tickets enclosing automated support tickets without anybody ever having to pick up a phone and call IT support that info site model now is being expanded across the board to all HP products it started with nimble now info site is available on three part it's available on synergy and a recent announcement said it's also available on pro alliance and we expect that info set becomes the glue the automation a I do that goes across the entire portfolio of HP products so this is a great example of applying AI to data so it's like call home taking to a whole new level isn't it yeah it absolutely is and in fact what it does is it uses the call home data that we've had for a long time with products like 3par which essentially was amazing data but not being auctioned on in an automated fashion it takes that data and creates an automation tasks around it and many times that automation task leads to much simpler support experience all right third item you mentioned was resource optimization let's let's drill down into that I infer from that there's there are performance implications is maybe governance compliance you know physical placement can you elaborate that's in color yes I think it's all of the above that he just talked about it's definitely about applying the right performance level to the right set of applications we call this application of air storage the ability to be able to understand which application is creating the data allows us to understand how that data needs to be accessed which in turn means we know where it needs to reside one of the things that HP is doing in the storage domain is creating a common storage fabric with the cloud we call that the fabric for the cloud the idea there is that we have a single layer between the on-premises and off premises resources that allows us to move data as needed depending on the application needs and depending on the user needs so this crucial new factors that have to be incorporated through everyone's thinking of cost efficiency ease of use and resource optimization it's going to place new types of stress on the storage hierarchy it's gonna require new technologies to better support digital transformation David Flor an analyst here in wiki bon has been a leading thinker of the relationship between the storage hierarchy and workloads and digital thinking for quite some time I had a great conversation with David not too long ago let's hear what he had to say about this new storage hierarchy and the new technologies they're gonna make possible these changes have you've been looking at this notion of modern storage architectures for 10 years now and you've been relatively prescient in understanding what's going to happen you were one of the first guys to predict well in advance of everybody else that the crossover between flash and HDD was gonna happen sooner rather than later so I'm not gonna spend a lot of time quizzing you what do you see as a modern storage architecture let's just let it rip ok well let's start with one simple observation the days of stand-alone systems for data have gone we're in a software-defined world and you want to be able to run those data architectures anywhere where you the data is and that means in your data center where you've is created or in the cloud or in a public cloud or at the edge you want to be able to be flexible enough to be able to do all of the data services where the best place is and that means everything has to be software German Software Defined is the first proposition of a modern day in a storage so so the second thing is that there are different types of technology you have the very fastest storage which is in the in in the DRAM itself you have env dim which is the next one down from that expensive but a lot cheaper than the dim and then you have different sorts of flash you have the high-performance flash and you have the 3d flash you know as many layers as you can which is much cheaper flash and then at the bottom you have HD DS and an even tape as storage devices so how the key question is how do you manage that sort of environment well let me start because it still sounds like we still have a storage hierarchy absolutely and it still sounds like that hierarchy is defined largely in terms of access speeds yep and price point size points yes those are the two mason and and bandwidth and latency as well with it which are tied into the richer tied into those yes so what you if you're gonna have this everywhere and you need services everywhere what you have to have is an architecture which takes away all of that complexity so that you all you see from an application point of view is data and how it gets there and how it's put away and how it's stored and how it's protected that's under the covers so the first thing is you need a virtualization of that data layer the physical layer the virtualization of that physical yes and secondly you need that physical layer to extend to all the places that may be using this data you you don't want to be constrained to this data set lives here you want to be able to say ok I want to move this piece of programming to the data as quickly as I can that's much much faster than moving the data to the to the processing so I want to be able to know where all the data is for this particular dataset or file or whatever it is where they all are how they connect together what the latency is between everything I want to understand that architecture and I want a virtualized view of that across that whole the nodes that make up my hybrid cloud so let me be clear here so so we are going to use a software-defined infrastructure that allows us to place the physical devices that have the right cost performance characteristics where they need to be based on the physical realities of latency of you know power availability hardening etc on the network and the network but we want to mask that complexity from the application the application developer an application administrator yes and Software Defined helps do that but doesn't completely do it No well you you want services which say exactly so their service is on top of all that apps that are that are recognizable by the developer by the you know the business person by the administrator as they think about how they use data towards those outcomes not use a storage or use a device but use the data to reach application outcomes that's absolutely right then that's what I call the data plane which is a series of services which enable that to happen and and driven by the application required so we've looked at this and some of the services include you know and and compression deduplication the backup restore security data protection so that's kind of that's kind of the services that now the enterprise by or needs to think about so that those services can be applied with you know by policy yes wherever they're required based on the utilization of the data correct where it's kind of where the event takes place and then you still have at the bottom of that you have the different types of devices you still have you still want of hamsters Mickey you still want hard disk they're not disappearing but if you're gonna use hard disks then you want to use it in the right way if you're using a hard disk you know you want to give it large box you to have it going sequentially in and out all the time so the storage administration and the day the physical schema and everything else is still important in all this but it's less important less the centerpiece of the buying decision correct increasingly it's how well does this stuff prove support the services that the business is using to achieve their outcomes and you want to use course the lowest cost that you can and there will be many different options over more more options open but but the automation of that is absolutely key and that automation from a vendor point of view one of the key things they have to do is to be able to learn from the usage by their customers across as broad a number of customers as they can learn what works what doesn't work learn so that they can put automation into their own software their own software services well sounds like we're talking four things we got we got software-defined still have a storage hierarchy defined by cost and performance but with mainly semiconductor stuff we've got great data services that are relevant to the business and automation that masks the complexity from the artificial AI there is also also made many things fantastic so David's thinking on the new storage hierarchy and how it's going to relate to new classes of workload is a baseline for a lot of the changes happening in the industry today but we still have to turn technology into services that deliver higher levels of value once again let's go back to Dave volantes conversation with Sun dip Arora and here what Sun dip has to say about some of the new digital services some of the new data services they're gonna be essential to supporting these new hybrid storage capabilities we have and what it does it it gives us the opportunity now not just you look at column data from storage but then also look at call home data from the compute side and then what we can do is correlate the data coming back to have better predictability and outcomes on your data center operations as opposed to doing it at the layer of infrastructure you also set out a vision of this this orchestration yeah lair can you talk more about that are we talking about across all clouds whether it's on pram or at the edge or in the public cloud yeah we are we're talking about making it as simple as possible where the customers are not necessarily picking and choosing it allows them to have a strategy that allows them to go across the data center whether it's a public cloud building their own private infrastructure or running on a traditional on-premises sand structure so this vision for us cloud fabric vision for us allows for customers to do that and what about software-defined storage yeah where does that fit into this whole equation yeah I'm glad you mentioned that because that was a third tenant of what HP truly brings to our customers software-defined is is something that allows us to maximize the utilization of the existing resources that our customers have so what we've done is we've partnered with a great deal of really strong software-defined vendors such as comm world cohesive accumulo de terre I know we work very closely with the likes of veeam Zotoh and and the goal there is to do to provide our customers with a whole range of options to drive building a software-defined infrastructure build off the Apollo series of products Apollo servers or storage products for us are extremely dense storage products that allow for both cost and resource optimization so Sunday I made some fantastic points about how new storage technologies are going to be turned into usable services that digital businesses will require as they conceived of their overall hybrid storage approach here's an opportunity hear a little bit more about what HPE thinks about some of these crucial areas let's hear what they have to say in this Chuck talk short take I'm gonna introduce you to HPE primary storage if you want the agility of the public cloud but need the resiliency and speed of high-end storage for mission-critical applications this force is a trade-off of agility for resiliency high-end storage is fast and reliable but falls short on agility and simplicity what if you could have it all what if you could have both agility and resiliency for your mission-critical apps introducing the world's most intelligent storage for mission-critical apps HP primary it delivers an on-demand experience so storage is instantly available Apple wear resiliency backed with a hundred percent availability guarantee predictive acceleration so apps aren't fast some of the time but fast all the time with embedded AI let me tell you more about HPE primarily was engineered to drive unique value in high-end storage there are four areas we focus on global intelligence powered with the most advanced AI for infrastructure info site an all active architecture with multiple nodes for higher resiliency and limitless parallelization a service centric OS that eliminates the risk and simplifies management and timeless storage with a new ownership experience that keeps getting better to learn more go to hp.com slash storage slash prime era so that's been a great series of conversations about hybrid storage and I want to thank Sun dip Arora of HPE David floor of wiki bonds to look at angle jim kanby lists of wiki bonds to look and angle and my colleague David Volante for helping out on the interview side I'm Peter Burris and this has been another wiki bond the cube digital community event sponsored by HPE now stay tuned for our Crouch at which will be your opportunity to ask your questions share your experiences and push for the community's thinking on hybrid storage once again thank you very much for watching let's crouch at
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Randy Arseneau & Steve Kenniston, IBM | CUBEConversation, August 2019
from the silicon angle media office in Boston Massachusetts it's the queue now here's your host David on tape all right buddy welcome to this cute conversation my name is Dave Ville on time or the co-host of the cube and we're gonna have a conversation to really try to explore does infrastructure matter you hear a lot today I've ever since I've been in this business I've heard Oh infrastructure is dead hardware is dead but we're gonna explore that premise and with me is Randy Arsenault and Steve Kenaston they're both global market development execs at IBM guys thanks for coming in and let's riff thanks for having us Dave so here's one do I want to start with the data we were just recently at the MIT chief data officer event 10 years ago that role didn't even exist now data is everything so I want to start off with you here this bro my data is the new oil and we've said you know what data actually is more valuable than oil oil I can put in my car I can put in my house but I can't put it in both data is it doesn't follow the laws of scarcity I can use the same data multiple times and I can copy it and I can find new value I can cut cost I can raise revenue so data in some respects is more valuable what do you think right yeah I would agree and I think it's also to your point kind of a renewable resource right so so data has the ability to be reused regularly to be repurposed so I would take it even further we've been talking a lot lately about this whole concept that data is really evolving into its own tier so if you think about a traditional infrastructure model where you've got sort of compute and network and applications and workloads and on the edge you've got various consumers and producers of that data the data itself has those pieces have evolved the data has been evolving as well it's becoming more complicated it's becoming certainly larger and more voluminous it's better instrumented it carries much more metadata it's typically more proximal with code and compute so the data itself is evolving into its own tier in a sense so we we believe that we want to treat data as a tier we want to manage it to wrap the services around it that enable it to reach its maximum potential in a sense so guys let's we want to make this interactive in a way and I'd love to give you my opinions as well as links are okay with that but but so I want to make an observation Steve if you take a look at the top five companies in terms of market cap in the US of Apple Google Facebook Amazon and of course Microsoft which is now over a trillion dollars they're all data companies they've surpassed the bank's the insurance companies the the Exxon Mobil's of the world as the most valuable companies in the world what are your thoughts on that why is that I think it's interesting but I think it goes back to your original statement about data being the new oil the and unlike oil Ray's said you can you can put it in house what you can't put it in your car you also when it's burnt it's gone right but with data you you have it around you generate more of it you keep using it and the more you use it and the more value you get out of it the more value the company gets out of it and so as those the reason why they continue to grow in value is because they continue to collect data they continue to leverage that data for intelligent purposes to make user experiences better their business better to be able to go faster to be able to new new things faster it's all part of part of this growth so data is one of the superpowers the other superpower of course is machine intelligence or what everybody talks about as AI you know it used to be that processing power doubling every 18 months was what drove innovation in the industry today it's a combination of data which we have a lot of it's AI and cloud for scaling we're going to talk about cloud but I want to spend a minute talking about AI when I first came into this business AI was all the rage but we didn't have the amount of data that we had today we don't we didn't have the processing power it was too expensive to store all this data that's all changed so now we have this emerging machine intelligence layer being used for a lot of different inks but it's sort of sitting on top of all these workloads that's being injected into databases and applications it's being used to detect fraud to sell us more stuff you know in real time to save lives and I'm going to talk about that but it's one of these superpowers that really needs new hardware architectures so I want to explore machine intelligence a little bit it really is a game changers it really is and and and tying back to the first point about sort of the the evolution of data and the importance of data things like machine learning and adaptive infrastructure and cognitive infrastructure have driven to your point are a hard requirement to adapt and improve the infrastructure upon which that lives and runs and operates and moves and breathes so we always had Hardware evolution or development or improvements and networks and the basic you know components of the infrastructure being driven again by advances in material science and silicon etc well now what's happening is the growth and importance and and Dynamis city of data is far outpacing the ability of the physical sciences to keep pace right that's a reality that we live in so therefore things like you know cognitive computing machine learning AI are kind of bridging the gap almost between the limitations we're bumping up against in physical infrastructure and the immense unlocked potential of data so that intermediary is really where this phenomenon of AI and machine learning and deep learning is happening and you're also correct in pointing out that it's it's everywhere I mean it's imbuing every single workload it's transforming every industry and a fairly blistering pace IBM's been front and center around artificial intelligence in cognitive computing since the beginning we have a really interesting perspective on it and I think we bring that to a lot of the solutions that we offer as well Ginni Rometty a couple years ago actually use the term incumbent disruptors and when I think of that I think about artificial intelligence and I think about companies like the ones I mentioned before that are very valuable they have data at their core most incumbents don't they have data all over the place you know they might have a bottling plant at the core of the manufacturing plant or some human process at the core so to close that gap artificial intelligence from the incumbents the appointees they're gonna buy that from companies like IBM they're gonna you know procure Watson or other AI tools and you know or maybe you know use open-source AI tools but they're gonna then figure out how to apply those to their business to do whatever fraud detection or recommendation engines or maybe even improve security and we're going to talk about this in detail but Steve this there's got to be new infrastructure behind that we can't run these new workloads on infrastructure that was designed 30 40 years ago exactly I mean I think I am truly fascinated by with this growth of data it's now getting more exponential and why we think about why is it getting more exponential it's getting more exponential because the ease at which you can actually now take advantage of that data it's going beyond the big financial services companies the big healthcare companies right we're moving further and further and further towards the edge where people like you and I and Randi and I have talked about the maker economy right I want to be able to go in and build something on my own and then deliver it to either as a service as a person a new application or as a service to my infrastructure team to go then turn it on and make something out of that that infrastructure it's got to come down in cost but all the things that you said before performance reliability speed to get there intelligence about data movement how do we get smarter about those things all of the underlying ways we used to think about how we managed protect secure that it all has evolved and it's continuing to evolve everybody talks about the journey the journey to cloud why does that matter it's not just the cloud it's also the the componentry underneath and it's gonna go much broader much bigger much faster well and I would just add just amplify what Steve said about this whole maker movement one of the other pressures that that's putting on corporate IT is it's driving essentially driving product development and innovation out to the end to the very edge to the end user level so you have all these very smart people who are developing these amazing new services and applications and workloads when it gets to the point where they believe it can add value to the business they then hand it off to IT who is tasked with figuring out how to implement it scale it protect it secured debt cetera that's really where I believe I um plays a key role or where we can play a key role add a lot of values we understand that process of taking that from inception to scale and implementation in a secure enterprise way and I want to come back to that so we talked about data as one of the superpowers an AI and the third one is cloud so again it used to be processor speed now it's data plus AI and cloud why is cloud important because cloud enables scale there's so much innovation going on in cloud but I want to talk about you know cloud one dot o versus cloud two dot o IBM talks about you know the new era of cloud so what was cloud one dot o it was largely lift and shift it was taking a lot of crap locations and putting him in the public cloud it was a lot of tests in dev a lot of startups who said hey I don't need to you know have IT I guess like the cube we have no ID so it's great for small companies a great way to experiment and fail fast and pay for you know buy the drink that was one dot o cloud to dot all to datos is emerging is different it's hybrid it's multi cloud it's massively distributed systems distributed data on Prem in many many clouds and it's a whole new way of looking at infrastructure and systems design so as Steve as you and I have talked about it's programmable so it's the API economy very low latency we're gonna talk more about what that means but that concept of shipping code to data wherever it lives and making that cloud experience across the entire infrastructure no matter whether it's on Prem or in cloud a B or C it's a complicated problem it really is and when you think about the fact that you know the big the big challenge we started to run into when we were talking about cloud one always shadow IT right so folks really wanted to be able to move faster and they were taking data and they were actually copying it to these different locations to be able to use it for them simply and easily well once you broke that mold you started getting away from the security and the corporate furnance that was required to make sure that the business was safe right it but it but it but following the rules slowed business down so this is why they continued to do it in cloud 2.0 I like the way you position this right is the fact that I no longer want to move data around moving data it within the infrastructure is the most expensive thing to do in the data center so if I can move code to where I need to be able to work on it to get my answers to do my AI to do my intelligent learning that all of a sudden brings a lot more value and a lot more speed and speed as time as money rate if I can get it done faster I get more valuable and then just you know people often talk about moving data but you're right on you the last thing you want to do is move data in just think about how long it takes to back up the first time you ever backed up your iPhone how long it took well and that's relatively small compared to all the data in a data center there's another subtext here from a standpoint of cloud 2.0 and it involves the edge the edge is a new thing and we have a belief inside of wiki bond and the cube that we talk about all the time that a lot of the inference is going to be done at the edge what does that mean it means you're going to have factory devices autonomous vehicles a medical device equipment that's going to have intelligence in there with new types of processors and we'll talk about that but a lot of the the inference is that conclusions were made real-time and and by the way these machines will be able to talk to each other so you'll have a machine to machine communication no humans need to be involved to actually make a decision as to where should I turn or you know what should be the next move on the factory floor so again a lot of the data is gonna stay in place now what does that mean for IBM you still have an opportunity to have data hubs that collect that data analyze it maybe push it up to the cloud develop models iterate and push it back down but the edge is a fundamentally new type of approach that we've really not seen before and it brings in a whole ton of new data yeah that's a great point and it's a market phenomenon that has moved and is very rapidly moving from smartphones to the enterprise right so right so your point is well-taken if you look in the fact is we talked earlier that compute is now proximal to the data as opposed to the other way around and the emergence of things like mesh networking and you know high bandwidth local communications peer-to-peer communications it's it's not only changing the physical infrastructure model and the and the best practices around how to implement that infrastructure it's also fundamentally changing the way you buy them the way you consume them the way you charge for them so it's it's that shift is changing and having a ripple effect across our industry in every sense whether it's from the financial perspective the operational perspective the time to market perspective it's also and we talked a lot about industry transformation and disruptors that show up you know in an industry who work being the most obvious example and just got an industry from the from the bare metal and recreate it they are able to do that because they've mastered this new environment where the data is king how you exploit that data cost-effectively repeatably efficiently is what differentiates you from the pack and allows you to create a brand new business model that that didn't exist prior so that's really where every other industry is going you talking about those those those big five companies in North America that are that are the top top companies now because of data I often think about rewind you know 25 years do you think Amazon when they built Amazon really thought they were going to be in the food service business that the video surveillance business the drone business all these other book business right maybe the book business right but but their architecture had to scale and change and evolve with where that's going all around the data because then they can use these data components and all these other places to get smarter bigger and grow faster and that's that's why they're one of the top five this is a really important point especially for the young people in the audience so it used to be that if you were in an industry if you were in health care or you were in financial services or you were in manufacturing you were in that business for life every industry had its own stack the sales the marketing the R&D everything was wired to that industry and that industry domain expertise was really not portable across businesses because of data and because of digital transformations companies like Amazon can get into content they can get into music they can get it to financial services they can get into healthcare they can get into grocery it's all about that data model being portable across those industries it's a very powerful concept that you and I mean IBM owns the weather company right so I mean there's a million examples of traditional businesses that have developed ways to either enter new markets or expand their footprint in existing markets by leveraging new sources of data so you think about a retailer or a wholesale distributor they have to very accurately or as accurately as possible forecast demand for goods and make sure logistically the goods are in the right place at the right time well there are million factors that go into that there's whether there's population density there's local cultural phenomena there's all sorts of things that have to be taken into consideration previously that would be near impossible to do now you can sit down again as an individual maker I can sit down at my desk and I can craft a model that consumes data from five readily available public api's or data sets to enhance my forecast and I can then create that model execute it and give it to two of my IT guy to go scale-out okay so I want to start getting into the infrastructure conversation again remember the premise of this conversation it doesn't read for structure matter we want to we want to explore that oh I start at the high level with with with cloud multi-cloud specifically we said cloud 2.0 is about hybrid multi cloud I'm gonna make a statements of you guys chime in my my assertion is that multi cloud has largely been a symptom of multi-vendor shadow IT different developers different workloads different lines of business saying hey we want to we want to do stuff in the cloud this happened so many times in the IT business all and then I was gonna govern it how is this gonna be secure who's got access control on and on and on what about compliance what about security then they throw it over to IT and they say hey help us fix this and so itea said look we need a strategy around multi cloud it's horses for courses maybe we go for cloud a for our collaboration software cloud B for the cognitive stuff cloud C for the you know cheap and deep storage different workloads for different clouds but there's got to be a strategy around that so I think that's kind of point number one and I T is being asked to kind of clean up this stuff but the future today the clouds are loosely coupled there may be a network that connects them but there's there's not a really good way to take data or rather to take code ship it to data wherever it lives and have it be a consistent well you were talking about an enterprise data plane that's emerging and that's kind of really where the opportunity is and then you maybe move into the control plane and the management piece of it and then bring in the edge but envision this mesh of clouds if you will whether it's on pram or in the public cloud or some kind of hybrid where you can take metadata and code ship it to wherever the data is leave it there much smaller you know ship five megabytes of code to a petabyte of data as opposed to waiting three months to try to ship you know petabytes to over the network it's not going to work so that's kind of the the spectrum of multi cloud loosely coupled today going to this you know tightly coupled mesh your guys thoughts on that yeah that's that's a great point and and I would add to it or expand that even further to say that it's also driving behavioral fundamental behavioral and organizational challenges within a lot of organizations and large enterprises cloud and this multi cloud proliferation that you spoke about one of the other things that's done that we talked about but probably not enough is it's almost created this inversion situation where in the past you'd have the business saying to IT I need this I need this supply chain application I need this vendor relationship database I need this order processing system now with the emergence of this cloud and and how easy it is to consume and how cost-effective it is now you've got the IT guys and the engineers and the designers and the architects and the data scientists pushing ideas to the business hey we can expand our footprint and our reach dramatically if we do this so you've get this much more bi-directional conversation happening now which frankly a lot of traditional companies are still working their way through which is why you don't see you know 100% cloud adoption but it drives those very productive full-duplex conversations at a level that we've never seen before I mean we encounter clients every day who are having these discussions are sitting down across the table and IT is not just doesn't just have a seat at the table they are often driving the go-to-market strategy so that's a really interesting transformation that we see as well in addition to the technology so there are some amazing things happening Steve underneath the covers and the plumbing and infrastructure and look at we think infrastructure matters that's kind of why we're here we're infrastructure guys but I want to make a point so for decades this industry is marked to the cadence of Moore's law the idea that you can double processing speeds every 18 months disk drive processors disk drives you know they followed that curve you could plot it out the last ten years that started to attenuate so what happened is chip companies would start putting more cores on to the real estate well they're running out of real estate now so now what's happening is we've seen this emergence of alternative processors largely came from mobile now you have arm doing a lot of offload processing a lot of the storage processing that's getting offloaded those are ARM processors in video with GPUs powering a lot of a lot of a is yours even seeing FPGAs they're simple they're easy them to spin up Asics you know making a big comeback so you've seen these alternative processes processors powering things underneath where the x86 is and and of course they're still running applications on x86 so that's one sort of big thing big change in infrastructure to support this distributed systems the other is flash we saw flash basically take out spinning disk for all high-speed applications we're seeing the elimination of scuzzy which is a protocol that sits in between the the the disk you know and the rest of the network that's that's going away you're hearing things like nvme and rocky and PCIe basically allowing stores to directly talk to the so now a vision envision this multi-cloud system where you want to ship metadata and code anywhere these high speed capabilities interconnects low latency protocols are what sets that up so there's technology underneath this and obviously IBM is you know an inventor of a lot of this stuff that is really gonna power this next generation of workloads your comments yeah I think I think all that 100% true and I think the one component that we're fading a little bit about it even in the infrastructure is the infrastructure software right there's hardware we talked a lot talked about a lot of hardware component that are definitely evolving to get us better stronger faster more secure more reliable and that sort of thing and then there's also infrastructure software so not just the application databases or that sort of thing but but software to manage all this and I think in a hybrid multi cloud world you know you've got these multiple clauses for all practical purposes there's no way around it right marketing gets more value out of the Google analytic tools and Google's cloud and developers get more value out of using the tools in AWS they're gonna continue to use that at the end of the day I as a business though need to be able to extract the value from all of those things in order to make different business decisions to be able to move faster and surface my clients better there's hardware that's gonna help me accomplish that and then there are software things about managing that whole consetta component tree so that I can maximize the value across that entire stack and that stack is multiple clouds plus the internal clouds external clouds everything yeah so it's great point and you're seeing clear examples of companies investing in custom hardware you see you know Google has its own ship Amazon its own ship IBM's got you know power 9 on and on but none of this stuff works if you can't manage it so we talked before about programmable infrastructure we talked about the data plane and the control plane that software that's going to allow us to actually manage these multiple clouds as at least a quasi single entity you know something like a logical entity certainly within workload classes and in Nirvana across the entire you know network well and and the principal or the principle drivers of that evolution of course is containerization right so the containerization phenomenon and and you know obviously with our acquisition of red hat we're now very keenly aware and acutely plugged into the whole containerization phenomenon which is great we're you're seeing that becoming almost the I can't think of us a good metaphor but you're seeing containerization become the vernacular that's being spoken in multiple different types of reference architectures and use case environments that are vastly different in their characteristics whether they're high throughput low latency whether they're large volume whether they're edge specific whether they're more you know consolidated or hub-and-spoke models containerization is becoming the standard by which those architectures are being developed and with which they're being deployed so we think we're very well-positioned working with that emerging trend and that rapidly developing trend to instrument it in a way that makes it easier to deploy easier to instrument easier to develop so that's key and I want to sort of focus now on the relevance of IBM one side one thing that we understand because that that whole container is Asian think back to your original point Dave about moving data being very expensive and the fact that the fact that you want to move code out to the data now with containers microservices all of that stuff gets a lot easier development becomes a lot faster and you're actually pushing the speed of business faster well and the other key point is we talked about moving code you know to the data as you move the code to the data and run applications anywhere wherever the data is using containers the kubernetes etc you don't have to test it it's gonna run you know assuming you have the standard infrastructure in place to do that and the software to manage it that's huge because that means business agility it means better quality and speed alright let's talk about IBM the world is complex this stuff is not trivial the the more clouds we have the more edge we have the more data we have the more complex against IBM happens to be very good at complex three components of the innovation cocktail data AI and cloud IBM your customers have a lot of data you guys are good with data it's very strong analytics business artificial intelligence machine intelligence you've invested a lot in Watson that's a key component business and cloud you have a cloud it's not designed to compete not knock heads and the race to zero with with the cheap and deep you know storage clouds it's designed to really run workloads and applications but you've got all three ingredients as well you're going hard after the multi cloud world for you guys you've got infrastructure underneath you got hardware and software to manage that infrastructure all the modern stuff that we've talked about that's what's going to power the customers digital transformations and we'll talk about that in a moment but maybe you could expand on that in terms of IBM's relevance sure so so again using the kind of maker the maker economy metaphor bridging from that you know individual level of innovation and creativity and development to a broadly distributed you know globally available work loader or information source of some kind the process of that bridge is about scale and reach how do you scale it so that it runs effectively optimally is easily managed Hall looks and feels the same falls under the common umbrella of services and then how do you get it to as many endpoints as possible whether it's individuals or entities or agencies or whatever scale and reach iBM is all about scale and reach I mean that's kind of our stock and trade we we are able to take solutions from small kind of departmental level or kind of skunkworks level and make them large secure repeatable easily managed services and and make them as turnkey as possible our services organizations been doing it for decades exceptionally well our product portfolio supports that you talk about Watson and kind of the cognitive computing story we've been a thought leader in this space for decades I mean we didn't just arrive on the scene two years ago when machine learning and deep learning and IO ste started to become prominent and say this sounds interesting we're gonna plant our flag here we've been there we've been there for a long time so you know I kind of from an infrastructure perspective I kind of like to use the analogy that you know we are technology ethos is built on AI it's built on cognitive computing and and sort of adaptive computing every one of our portfolio products is imbued with that same capability so we use it internally we're kind of built from AI for AI so maybe that's the answer to this question of it so what do you say that somebody says well you know I want to buy you know my flash storage from pure AI one of my bi database from Oracle I want to buy my you know Intel servers from Dell you know whatever I want to I want to I want control and and and I gotta go build it myself why should I work with IBM do you do you get that a lot and how do you respond to that Steve I think I think this whole new data economy has opened up a lot of places for data to be stored anywhere I think at the end of the day it really comes down to management and one of the things that I was thinking about as you guys were we're conversing is the enterprise class or Enterprise need for things like security and protection that sort of thing that rounds out the software stack in our portfolio one of the things we can bring to the table is sure you can go by piece parts and component reform from different people that you want right and in that whole notion around fail-fast sure you can get some new things that might be a little bit faster that might be might be here first but one of the things that IBM takes a lot of pride was a lot of qual a lot of pride into is is the quality of their their delivery of both hardware and software right so so to me even though the infrastructure does matter quite a bit the question is is is how much into what degree so when you look at our core clients the global 2,000 right they want to fail fast they want to fail fast securely they want to fail fast and make sure they're protected they want to fail fast and make sure they're not accidentally giving away the keys to the kingdom at the end of the day a lot of the large vendor a lot of the large clients that we have need to be able to protect their are their IP their brain trust there but also need the flexibility to be creative and create new applications that gain new customer bases so the way I the way I look at it and when I talk to clients and when I talk to folks is is we want to give you them that while also making sure they're they're protected you know that said I would just add that that and 100% accurate depiction the data economy is really changing the way not only infrastructure is deployed and designed but the way it can be I mean it's opening up possibilities that didn't exist and there's new ones cropping up every day to your point if you want to go kind of best to breed or you want to have a solution that includes multi vendor solutions that's okay I mean the whole idea of using again for instance containerization thinking about kubernetes and docker for instance as a as a protocol standard or a platform standard across heterogeneous hardware that's fine like like we will still support that environment we believe there are significant additive advantages to to looking at IBM as a full solution or a full stack solution provider and our largest you know most mission critical application clients are doing that so we think we can tell a pretty compelling story and I would just finally add that we also often see situations where in the journey from the kind of maker to the largely deployed enterprise class workload there's a lot of pitfalls along the way and there's companies that will occasionally you know bump into one of them and come back six months later and say ok we encountered some scalability issues some security issues let's talk about how we can develop a new architecture that solves those problems without sacrificing any of our advanced capabilities all right let's talk about what this means for customers so everybody talks about digital transformation and digital business so what's the difference in a business in the digital business it's how they use data in order to leverage data to become one of those incumbent disruptors using Ginny's term you've got to have a modern infrastructure if you want to build this multi cloud you know connection point enterprise data pipeline to use your term Randy you've got to have modern infrastructure to do that that's low latency that allows me to ship data to code that allows me to run applet anywhere leave the data in place including the edge and really close that gap between those top five data you know value companies and yourselves now the other piece of that is you don't want to waste a lot of time and money managing infrastructure you've got to have intelligence infrastructure you've got to use modern infrastructure and you've got to redeploy those labor assets toward a higher value more productive for the company activities so we all know IT labor is a chop point and we spend more on IT labor managing Leung's provisioning servers tuning databases all that stuff that's gotta change in order for you to fund digital transformations so that to me is the big takeaway as to what it means for customer and we talked about that sorry what we talked about that all the time and specifically in the context of the enterprise data pipeline and within that pipeline kind of the newer generation machine learning deep learning cognitive workload phases the data scientists who are involved at various stages along the process are obviously kind of scarce resources they're very expensive so you can't afford for them to be burning cycles and managing environments you know spinning up VMs and moving data around and creating working sets and enriching metadata that they that's not the best use of their time so we've developed a portfolio of solutions specifically designed to optimize them as a resource as a very valuable resource so I would vehemently agree with your premise we talked about the rise of the infrastructure developer right so at the end of the day I'm glad you brought this topic up because it's not just customers it's personas Pete IBM talks to different personas within our client base or our prospect base about why is this infrastructure important to to them and one of the core components is skill if you have when we talk about this rise of the infrastructure developer what we mean is I need to be able to build composable intelligent programmatic infrastructure that I as IT can set up not have to worry about a lot of risk about it break have to do in a lot of troubleshooting but turn the keys over to the users now let them use the infrastructure in such a way that helps them get their job done better faster stronger but still keeps the business protected so don't make copies into production and screw stuff up there but if I want to make a copy of the data feel free go ahead and put it in a place that's safe and secure and it won't it won't get stolen and it also won't bring down the enterprise's is trying to do its business very key key components - we talked about I infused data protection and I infused storage at the end of the day it's what is an AI infused data center right it needs to be an intelligent data center and I don't have to spend a lot of time doing it the new IT person doesn't want to be troubleshooting all day long they want to be in looking at things like arm and vme what's that going to do for my business to make me more competitive that's where IT wants to be focused yeah and it's also we just to kind of again build on this this whole idea we haven't talked a lot about it but there's obviously a cost element to all this right I mean you know the enterprise's are still very cost-conscious and they're still trying to manage budgets and and they don't have an unlimited amount of capital resources so things like the ability to do fractional consumption so by you know pay paper drink right buy small bits of infrastructure and deploy them as you need and also to Steve's point and this is really Steve's kind of area of expertise and where he's a leader is kind of data efficiency you you also can't afford to have copy sprawl excessive data movement poor production schemes slow recovery times and recall times you've got a as especially as data volumes are ramping you know geometrically the efficiency piece and the cost piece is absolutely relevant and that's another one of the things that often gets lost in translation between kind of the maker level and the deployment level so I wanted to do a little thought exercise for those of you think that this is all you know bromide and des cloud 2.0 is also about we're moving from a world of cloud services to one where you have this mesh which is ubiquitous of of digital services you talked about intelligence Steve you know the intelligent data center so all these all these digital services what am I talking about AI blockchain 3d printing autonomous vehicles edge computing quantum RPA and all the other things on the Gartner hype cycle you'll be able to procure these as services they're part of this mesh so here's the thought exercise when do you think that owning and driving your own vehicle is no longer gonna be the norm right interesting thesis question like why do you ask the question well because these are some of the disruptions so the questions are designed to get you thinking about the potential disruptions you know is it possible that our children's children aren't gonna be driving their own car it's because it's a it's a cultural change when I was 16 year olds like I couldn't wait but you started to see a shifted quasi autonomous vehicles it's all sort of the rage personally I don't think they're quite ready yet but it's on the horizon okay I'll give you another one when will machines be able to make better diagnosis than doctors actually both of those are so so let's let's hit on autonomous and self-driving vehicles first I agree they're not there yet I will say that we have a pretty thriving business practice and competency around working with a das providers and and there's an interesting perception that a das autonomous driving projects are like there's okay there's ten of them around the world right maybe there's ten metal level hey das projects around the world what people often don't see is there is a gigantic ecosystem building around a das all the data sourcing all the telemetry all the hardware all the network support all the services I mean building around this is phenomenal it's growing at a had a ridiculous rate so we're very hooked into that we see tremendous growth opportunities there if I had to guess I would say within 10 to 12 years there will be functionally capable viable autonomous vehicles not everywhere but they will be you will be able as a consumer to purchase one yeah that's good okay and so that's good I agree that's a the time line is not you know within the next three to five years all right how about retail stores will well retail stores largely disappeared we're we're rainy I was just someplace the other day and I said there used to be a brick-and-mortar there and we were walking through the Cambridge Tseng Galleria and now the third floor there's no more stores right there's gonna be all offices they've shrunken down to just two floors of stores and I highly believe that it's because you know the brick you know the the retailers online are doing so well I mean think about it used to be tricky and how do you get in and and and I need the Walmart minute I go cuz I go get with Amazon and that became very difficult look at places like bombas or Casper or all the luggage plate all this little individual boutique selling online selling quickly never having to have to open up a store speed of deployment speed of product I mean it's it's it's phenomenal yeah and and frankly if if Amazon could and and they're investing billions of dollars and they're trying to solve the last mile problem if Amazon could figure out a way to deliver ninety five percent of their product catalog Prime within four to six hours brick-and-mortar stores would literally disappear within a month and I think that's a factual statement okay give me another one will banks lose control traditional banks lose control of the payment systems you can Moselle you see that banks are smart they're buying up you know fin tech companies but right these are entrenched yeah that's another one that's another one with an interesting philosophical element to it because people and some of its generational right like our parents generation would be horrified by the thought of taking a picture of a check or using blockchain or some kind of a FinTech coin or any kind of yeah exactly so Bitcoin might I do my dad ask you're not according I do I don't bit going to so we're gonna we're waiting it out though it's fine by the way I just wanted to mention that we don't hang out in the mall that's actually right across from our office I want to just add that to the previous comment so there is a philosophical piece of it they're like our generation we're fairly comfortable now because we've grown up in a sense with these technologies being adopted our children the concept of going to a bank for them will be foreign I mean it will make it all have no context for the content for the the the process of going to speak face to face to another human it just say it won't exist well will will automation whether its robotic process automation and other automation 3d printing will that begin to swing the pendulum back to onshore manufacturing maybe tariffs will help to but again the idea that machine intelligence increasingly will disrupt businesses there's no industry that's safe from disruption because of the data context that we talked about before Randy and I put together a you know IBM loves to use were big words of transformation agile and as a sales rep you're in the field and you're trying to think about okay what does that mean what does that mean for me to explain to my customer so he put together this whole thing about what his transformation mean to one of them was the taxi service right in the another one was retail so and not almost was fencers I mean you're hitting on on all the core things right but this transformation I mean it goes so deep and so wide when you think about exactly what Randy said before about uber just transforming just the taxi business retailers and taxis now and hotel chains and that's where the thing that know your customer they're getting all of that from data data that I'm putting it not that they're doing work to extract out of me that I'm putting in so that autonomous vehicle comes to pick up Steve Kenaston it knows that Steve likes iced coffee on his way to work gives me a coupon on a screen I hit the button it automatically stops at Starbucks for me and it pre-ordered it for me you're talking about that whole ecosystem wrapped around just autonomous vehicles and data now it's it's unbeliev we're not far off from the Minority Report era of like Anthem fuck advertising targeted at an individual in real time I mean that's gonna happen it's almost there now I mean you just use point you will get if I walk into Starbucks my phone says hey why don't you use some points while you're here Randy you know so so that's happening at facial recognition I mean that's all it's all coming together so and again underneath all this is infrastructure so infrastructure clearly matters if you don't have the infrastructure to power these new workloads you're drugged yeah and I would just add and I think we're all in agreement on that and and from from my perspective from an IBM perspective through my eyes I would say we're increasingly being viewed as kind of an arms dealer and that's a probably a horrible analogy but we're being used we're being viewed as a supplier to the providers of those services right so we provide the raw materials and the machinery and the tooling that enables those innovators to create those new services and do it quickly securely reliably repeatably at a at a reasonable cost right so it's it's a step back from direct engagement with consumer with with customers and clients and and architects but that's where our whole industry is going right we are increasingly more abstracted from the end consumer we're dealing with the sort of assembly we're dealing with the assemblers you know they take the pieces and assemble them and deliver the services so we're not as often doing the assembly as we are providing the raw materials guys great conversation I think we set a record tends to be like that so thank you very much for no problem yeah this is great thank you so much for watching everybody we'll see you next time you're watching the cube
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HPE Data Platform
from our studios in the heart of Silicon Valley Palo Alto California this is a cute conversation hi I'm Peter Burris analyst wiki Bond welcome to another wiki Bond the cube digital community event this one's sponsored by HPE like all of our digital community events this one will feature about 25 minutes of video followed by a crowd chat which will be your opportunity to ask your questions share your experiences and push forward the community's thinking on important issues facing business today so what are we talking about today over the course of the last say six months or so we've had a lot of conversations with our customers about the core issues that multi-cloud is going to engender with in business one of them clearly is how do we bring greater intelligence to how we move manage and administer data within the enterprise some of the more interesting conversations we've had turns out to have been with HPE and that's what we're going to talk about today we're going to be spending a few minutes with a number of HPE professionals as well as wiki bond professionals and thought leaders talking about the challenges that enterprises face as a consider intelligent data platforms so let's get started the first conversation that we're going to talk about is with Sandeep Singh who is the vice president at HPE Sandeep let's have that conversation about the challenges facing business today as it pertains to data so Sandeep I started off by making the observation that we've got this mountain of data coming in a lot of enterprises at the same time there seems to be a the the notion of how data is going to create new classes of business value seems to be pretty deeply ingrained and acculturated to a lot of decision-makers so they want more value out of their data but they're increasingly concerned about the volume of data that's going to hit them how in your conversations with customers are you hearing them talk about this fundamental challenge so that that's a great question you know across the board data is at the heart of applications pretty much everything that organizations do and when they look at it in conversations with customers it really boils down to a couple of areas one is how is my data just effortlessly available all the time it's always fast because fundamentally that's driving the speed of my business and that's incredibly important and how can my various audiences including developers just consume it like the public cloud in a self-service fashion and then the second part of that conversation is really about this massive data storm or mountain of data that's coming and it's gonna be available how do how do I Drive a competitive advantage how do i unlock these hidden insights in that data to uncover new revenue streams new customer experiences those are the areas that we hear about and fundamentally underlying it the challenge for customers is boy I have a lot of complexity and how do I ensure that I have the necessary insights in a the infrastructure management so I am not beholden am or my IT staff isn't beholden to fighting the IT fires that can cause disruptions and delays to projects so fundamentally we want to be able to push time and attention in the infrastructure in the administration of those devices that handle the data and move that time and attention up into how we deliver the data services and ideally up into the applications that are going to actually generate a new class of work within a digital business so I got that right absolutely it's about infrastructure that just runs seamlessly it's always on it's always fast people don't have to worry about what is it gonna go down is my data available or is it gonna slow down people don't want sometimes faster one always fast right I and that's governing the application performance that ultimately I can deliver and you talked about while geez if it if the data infrastructure just work seamlessly then can I eventually get to the applications and building the right pipelines ultimately for mining that data drive doing the AI and the machine learning analytics driven insides from there great discussion about the importance of data in the enterprise and how it's changing the way we think about business we're going to come back to Sandeep shortly but first let's spend some time talking with David floor who's the wiki bond analyst about the new mindset that is required to take advantage of some of these technologies and solve some of these problems specifically we need to think increasingly about data services let's hear what David has to say explain what that new mindset is yes I completely agree that that new mindset is required and it starts with you want to be able to deal with data wherever it's gonna be you in we are in a hybrid world hybrid cloud world your own clouds other public clouds partner clouds all of these need to be integrated and data is at the core of it so that the requirement then is to have rather than think about each individual piece is to think about services which are going to be applied to that data and can be applied not only to the data in one place but across all of that data and there isn't such a thing is just one set of services there going to be multiple sets of these services available but hope we will see some degree of conversion so they'll be the same lexicon and conceptual etcetera there'll be the same levels of things that are needed within each of these architectures but there'll be different emphasis on different areas we need to look at the way we administer data as a set of services that create outcomes for the business and as opposed to that are then translated into individual devices let me so let's jump into this notion of of what those services look like it seems as though we can list off a couple of them sure yeah so we must have of data reduction techniques so you must have deduplication compression type of techniques and you want to apply that our crosses bigger an amount of data as you can the more data you apply those the higher the levels of compression and deduplication you can get so that's clearly you've got those sort of sets of services across there you must backup and restore data in another place and be able to restore it quickly and easily there's that again is a service how quickly how integrated that recovery again that's going to be a variable that's a differentiation in the service exactly you're going to need data data protection in general end to end protection of once or another for example you need end-to-end encryption across there it's no longer good enough to say this bits been encrypted and then this bits the encrypted has got to be an end-to-end from one location to another location seamlessly provided that sort of thing well let me let me let me press on it cuz I think it's a really important point and and and it's you know the notion that the weakest link determines the strength of the chain right the what you just described says if you have encryption here and you don't have encryption there but because of the nature of digital you can start you start bringing that data together guess what the weakest link determines the protection of the overall data absolutely yes and then you need services like snapshots like like other services which provide much better usage of that data one of the great things about flash and that's brought about this about is that you can take a copy of that in real time and use that first totally different purpose and have that being changed in a different way so there are some really significantly great improvements you can have with services like snapshots and then you need some other services which are becoming even more important in my opinion the advent of [Music] bad actors in the in the world has really bought about the requirement for things like air gaps to have your data with the metadata all in one place and completely separated from everything else there are such things as called logical air gaps I think they as long as they're real in the real sense that the two paths can't interfere with each other those are going to be services which become very very important that's generally as an example of a general class of security data services they require so ultimately what we're describing is we're describing a new mindset that says that a storage administrator has to think about the services that the applications in the business requires and then seek out technologies that can provide those services at the price point with the degree of power consumption in the space or the environmental or with the type of maintenance and services related support that required based on the physical location the degree to which is under their control etc so that kind of what how we're thinking about this I think absolutely and the again if there's going to be multiple of these around in the marketplace one size is not going to fit all yeah you if you're wanting super fast response time at an edge and and if you don't get that response in time it's going to be no use whatsoever you're going to take you're going to have a different architecture a different way of doing it then if you need to be a hundred percent certain that every bit is captured and you know in a financial sort of environment but from a service standpoint you want to be able to look at that specific solution in a common way current policies current bilities correct great observations by David Flor it's very clear that for enterprises to get more control over their data their data assets and how they create value out of data they have to take a services mentality but the challenge that we all face is just taking a service mentality is not going to be enough we have to think about how we're going to organize those services into a platform that is pertinent and relevant to how business operates in a digital sense so let's go back to Sandeep saying and talk to him a little bit about this HPE notion of the intelligent data platform you've been one of the leaders in the complex systems arena for a long time and that includes storage where are you guys taking some of these technologies yeah so our strategy is to deliver an intelligent data platform and that intelligent data platform begins with workload optimized composable systems that can span the mission critical workloads general purpose secondary Big Data ai workloads we also deliver cloud data services that enable you to embrace hybrid cloud all of these systems including all the way to cloud data services are plumbed with data mobility and so for example use cases of even modernizing protection and going all the way to protecting cost effectively in the public cloud are enabled but really all of these systems then are imbued with a level of intelligence with a global intelligence engine that begins with predicting and proactively resolving issues before they occur but it goes way beyond that in delivering these prescriptive insights that are built on top of global learning across hundreds of thousands of systems with over a billion data points coming in on a daily basis to be able to deliver at the information at the fingertips of even the virtual machine admins to say this virtual machine is sapping the performance of this node and if you were to move it to this other node the performance or the SLA for all of the virtual machine farm will be even better we build on top of that to deliver pre-built automation so that it's hooked in with a REST API for strategy so that developers can consume it in a containerized application that's orchestrated with kubernetes or they can leverage it as an infrastructure as code whether it's with ansible puppet or chef we accelerate all of the application workloads and bring up where data protection and so it's available for the traditional business applications whether they're built on sa P or Oracle or sequel or the virtual machine farms or the new stack containerized applications and then customers can build their AI and big data pipelines on top of the infrastructure with a plethora of tools whether they're using basically Kafka lastic map our h2o that complete flexibility exists and within HPE were then able to turn around and deliver all of this with an as a service experience with HPE Greenlake to customers so that's where I want to take you next so how invasive is this going to be to a large shop well it is completely seamless in that way so with Greenlake we're able to deliver a fully managed service experience where the a cloud like page you go consumption model and combining it with HPE financial services we're also able to transform their organization in terms of this journey and make it a fully self-funding journey as well so today the typical administrator the typical shop has got a bunch of administrators that are administrating devices that's starting to change they've introduced automation that typically is associated with those devices but if we think three to five years out folks going to be thinking more in terms of data services and how those services get consumed and that's going to be what the storage part of I t's going to be thinking about they can almost become day to administrators if I got that right yes intelligence is fundamentally changing everything not only on the consumer side but on the business side of it a lot of what we've been talking about is intelligence is the game changer we actually see the dawn of the intelligence era and through this AI driven experience what it means for customers as a it enables a support experience that they just absolutely love secondly it means that the infrastructure is always on it's always fast it's always optimized in that sense and thirdly in terms of making these data services that are available and data insights that are being unlocked it's all about how can you enable your innovators and the data scientists and the data analysts to shrink that time to deriving insights from months literally down to minutes today there's this chasm that exists where there's a great concept of how can i leverage the AI technology and between that concept to making it real to thinking about a where can I actually fit and then how do i implement an end-to-end solution and a technology stack so then I just have a pipeline that's available to me that chasm literally is a matter of months and what we're able to deliver for example with HPE blue data is literally a catalog self-service experience where you can select and seamlessly build a pipeline literally in a matter of minutes and it's just all completely hosted seamlessly so making AI and machine learning essentially available for the mainstream through so the ontology data platform makes it possible to see these new classes of applications become routine without forcing the underlying storage administrators themselves to become data scientists absolutely all right the intelligent data platform is a very great concept but it's got to be made real and it's being made real today by HP Calvin Zito's a thought leader at HPE and he's done a series of chalk talks as it pertains to improving storage improving data management one of the more interesting ones was specifically on the intelligent data platform let's watch Calvin Zito's chalk talk hey guys I love it's time for another around the storage black chalk talk in this chalk top we're gonna look at the intelligent Data Platform let me set up the discussion at HP we see the dawn of the intelligence error the flatshare brought a speed with flash flash is now table stakes the cloud era brought new levels of agility and everyone expects as a service experience going forward the intelligence era with an AI driven experience for infrastructure operations in AI enabled unlocking of insights is poised to catapult businesses forward so the intelligent era will see the rise of the intelligent enterprise the enterprise will be always on always fast always agile to respond to different challenges but most of all the intelligent enterprise will be built for innovation innovation that can ilish new services revenue streams and business models every enterprise will need to have an intelligent data strategy where your data is always on and always fast automated an on-demand hybrid by design and applies global intelligence for visibility and lifecycle management our strategy is to deliver an intelligent data platform that turns your data challenges into business opportunities it begins with workload optimized composable systems for multiple workloads and we deliver cloud services for a hybrid cloud environment so that you can seamlessly move data throughout its lifecycle I'll have more on this in a moment the global intelligence engine infuses the entire infrastructure with intelligence it starts with predicting and proactively resolving issues before they occur it creates a unique workload fingerprint and these workload fingerprints combined with global learning enable us to drive recommendations to keep your app workloads and supporting infrastructure always optimized and delivering predictable speed we have a REST API first strategy and offer pre build automation connectors we bring Apple wear protection for both traditional and modern new stack application workloads and you can use the intelligent data platform to build and deliver flexible big data and AI pipelines for driving real-time analytics let's take a quick look at the portfolio of workload optimized composable systems these are systems across mission-critical general-purpose workloads as well secondary data and solutions for the emerging big data and AI applications because our portfolio is built for the cloud we offer comprehensive cloud data services for both production workloads and backup and archive in the cloud HPE info site provides the global intelligence across the portfolio and we give you flexibility of consuming these solutions as a service with HPE Greenlake I want to close with one more thing the HPE intelligent data platform has three main attributes first it's AI driven it removes the burden of managing infrastructure so that IT can focus on innovating and not administrating second it's built for cloud and it enables easy data and workload mobility across hybrid cloud environments finally the intelligent data platform delivers and as a service experience so you can be your own cloud provider to learn more go to hp.com intelligent data always love to hear from you on Twitter where you can find me as calvin zito you can find my blog at hp.com slash blog until next time thanks for joining me on this around the storage black chalk talk I think Calvin makes a compelling case that the opportunity to use these technologies is available today not something that we're just going to wait for in the future and that's good because one of the most important things that business has to think about is how are they going to utilize some of these new AI and related technologies to alter the way that they engage their customers run their businesses and handle their operations and ultimately improve their overall efficiency and effectiveness in the marketplaces it's very clear that this intelligent data platform is required to do many of the advanced AI things that business wants to do but it also requires AI in the platform itself so let's go back to Sandeep Singh and talk to Sandeep about how HPE foresees AI being embedded in them into the intelligent data platform so it can make possible greater utilization of AI and the rest of the application portfolio so we've got the significant problem we now have to figure out how to architect because we want predictability and certainty and and cost clarity and to how we're going to do this part of the challenge or part of the pushers new use cases for AI so we're trying to push data up so that we can build these new use cases but it seems that we have to also have to take some of those very same technologies and drive them down into the infrastructure so we get greater intelligence greater self meter and greater self management self administration within the infrastructure itself I got that right yes absolutely what becomes important for customers is when you think about data and ultimately storage that underlies the data is you can build and deploy fast and reliable storage but that's only solving half the problem greater than 50% of the issues actually end up arising from the higher layers for example you could change the firmware on the host bus adapter inside a server that can trickle down and cause a data unavailability or a performance slowdown issue you need to be able to predict that all the way at that higher level and then prevent that from occurring or your virtual machines might be in a state of over memory commitment at the server level or you CPU over commitment how do you discover those issues and prevent them from happening the other area that's becoming important is when we talk about this whole notion of cloud and hybrid cloud right that complexity tends to multiply exponentially so when the smarts you guys are going after building that hybrid cloud infrastructure fundamental challenges even as I've got a new workload and I want to place that you even on premises because you've had lots of silos how do you even figure out where should I place a workload a and how it'll react with workloads B and C on a given system and now you multiply that across hundreds of systems multiple clouds and the challenge you can see that it's multiplying exponentially oh yeah well I would say that having you know where do I put workload a the right answer today maybe here but the right answer tomorrow maybe some where else and you want to make sure that the service is right required to perform workload a our resident and available without a lot of administrative work necessary to ensure that there's commonality that's kind of what we mean by this hybrid multi cloud world isn't it absolutely and you when you start to think about it basically you end up in requiring and fundamentally needing the data mobility aspect of it because without the data you can't really move your workloads and you need consistency of data services so that your app if it's architected for reliability and a set of data services those just go along with the application and then you need building on top of that the portability for your actual application workload consistently managed with a hybrid management interface there so we want to use an intelligent data platform that's capable of assuring performance assuring availability and assuring security and going beyond that to then deliver a simplified automated experience right so that everything is just available through a self-service interface and then it brings along a level of intelligence that's just built into it globally so that in instead of trying to manually predict and landing in a world of reactive after IT fires have occurred is that there are sea of sensors and it's automatic the infrastructures automatically for predicting and preventing issues before they ever occur and then going beyond that how can you actually fingerprint the individual application workloads to then deliver prescriptive insights right to keep the infrastructure always optimized in that sense so discerning the patterns of data utilization so that the administrative costs of making sure the data is available where it needs to be number one number two assuring that data as assets is made available to developers as they create new applications new new things that create new work but also working very closely with the administrators so that they are not bound [Music] as you know an explosion in the number of tasks adapt to perform to keep this all working across the board yes I want to thank Sandeep Singh and calvin zito both of HPE as well as wiki bonds David Floyd for sharing their ideas on this crucially important topic of how we're going to take more of a platform approach to do a better job of managing crucial data assets in today's and tomorrow's digital businesses I'm Peter Burris and this has been another wiki bomb the cube digital community event sponsored by HPE now stay tuned for our crowd chat which will be your opportunity to ask your questions share your experiences and push for the community's thinking on important issues facing business today thank you very much for watching and now let's crouch [Music]
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Rich Colbert, Dell EMC | CUBEConversation, July 2019
from our studios in the heart of Silicon Valley Palo Alto California this is a cute conversation hey welcome back everybody Jeffrey here with the cube we're in our Palo Alto Studios here today for a cute conversation it's a little bit of a dog days of summer conference seasons a little bit slow so we're excited we can kind of take a step back and we're gonna look back actually in time we're excited to have a very special guest rich Kolbert he is the field CTO at Dell EMC but really what we're talking about today is this data domain is 10-year anniversary of the date domain acquisition so rich first off welcome to the to the cube thanks Jeff excited to be here thanks for the invitation appreciate it I can't believe we're talking before we turned the cameras on that you join in 2006 and yet it's been 10 years I'm like wait 2006 was more than 10 can that be we're just getting old I don't know things are changing too fast no it's like a trip down memory lane and it just seems so long ago and yes in a way it also seems like yesterday I think things have gone so quickly so we're also joined in this segment by our top data analyst also the founder of wiki bond and co-ceo of Silicon angle media and founder of that as well so Dave Villante is joining us all the way from Boston Dave good to see ya hey Jeff hi rich to talk to you guys hey Dave so let's take a quick trip back 10 years ago actually maybe 11 years ago things were starting to heat up there was a lot of different vendors out there a lot of different players and things started to consolidate so I wonder if you can give us a little bit of your perspective what what's going on rich and then we'll get Dave's perspective yeah it was an interesting time right before the data domain acquisition we actually went through some economic times in 2008 and the markets are changing and and and some companies are becoming more successful some companies were struggling through that time customers were also looking for ways to to you know save money and do some interesting things there so it was a mixed feeling set of you know through that times data domain had IPO in 2007 and we were kind of going through this this explosive period of growth but you know across the board we just saw so many things change all at once and we really were surprised I think when initially was NetApp that an that they had intentions to bias and I think that was due to some of the economic factors of play and then of course EMC stepped in and and started a bidding contest with NetApp for for the company right so I Dave wonder if you could share your perspective you're sitting as an analyst you got Jo TG The Godfather of storage back in Boston what were you seeing in terms of the kind of the market dynamics and was it a surprise wouldn't that app decided to make a move well if you know first first of all I had left the storage industry for quite some time and when I started wiki bond we looked at storage and nothing had changed except one thing which was David deduplication that was new until a new tape was finally I always hated the tape the tape was finally being attacked so it was it was amazing time and EMC at the time we had some obviously great management yet Frank Sluman running data domain yo Joe Tucci who always balanced out acquisitions with organic you know in how to R&D and when Tom Georgians and NetApp said they were gonna go by David domain emt's walk right in and said no way so it was somewhat of a defensive move but at the same time when you talk to the M&A guys they said no no it's not just defense we can actually make this a growth play and that's exactly what happened Dayna domain I think at the time rich was probably a couple of hundred million dollar company and then they they popped that at the EMC and scaled that to you know well over a billion dollars and it'll maintain the the franchise and then grew it quite dramatically beyond where all the expectations were for the market the market team at the time was probably around a billion and I think ID seen rich as a over three billion today yeah one of the things that's so don't quote me on all the numbers because I'm not like you know watching the market caps and stocks but I think we'd gotten up to about a 500 million dollar run rate in terms of sales and prior to the crash I think our market cap was actually significantly higher so so our price came down you know which is one of the things I think that attracted NetApp to the game so the interesting dynamic inside the company was that the NetApp offer was was kind of the first one so they were working with the data domain leadership and they were speaking with us EMC was more of a kind of unsolicited offer so there was less communication and I remember there was a morning I was at San Francisco Airport going out to meet a customer and Joe to Chi put out a full-page ad in a local newspaper and we were reading that and that was his way of communicating to the to the people a data domain saying he wants to welcome us into the family it was quite a moment well it sure was and of course you guys were fierce competitors data domain was fierce competitors with with EMC you know fighting for for the install base and then all of a sudden you know the cultures it's somehow work EMC was was very good at acquisitions and he made it work and they not active it was an outside observer but you were there you know Frank Sluman came in did it's kind of running the the data protection organization but a lot has changed since then hasn't it I mean back then you stored you know a little bit of data I think accounting of terabytes today we live in a petabyte scale world I could talk about what's changed well you know the scales and performance certainly has changed I think the data domain platform today is about a thousand times larger than it was when it first came to market and in fact when we were being bid on by NetApp and EMC we had a flagship product is the DD 690 you know behind the scenes we had a system that was coming out that was double that size and EMC nor Netta knew about that so once the deal closed they got to find out that our size had just doubled in our performance and doubled at the same time but you're right you kind of talked about the dynamics inside of EMC EMC had a very large data protection you know division they had avemar networker santaros v TLS they also had an OEM arrangement for a competing product with the data domain platform so it was really like you know I compared to going to Hogwarts right where you have all of these different houses and we came in with with data domain and and I think the thing that really the glue that really helped it come to get was Joe Tucci you know tapping Frank's Luqman on the shoulder as the leader to bring this together and taking what was the borough division and and reforming it as the BRS division and I think we came together very quickly as a team even though people came from all of these different backgrounds you know standing for these different products rich let me follow up on that because there's a lot of M&A activity going on right now and and not very many big M&A deals are ultimately successful it turns out so what you said a little bit about you know Joe and Frank you know coming together but what are some of the other attributes that you would say that made it work it actually did what everybody hopes on an acquisition which is take great technology put it into a big sales machine and watch it grow and grow I think part of it you know quite frankly just comes down to the product and being differentiated because there are a lot of products out there and and if you take a step back they have good things that they're doing but it's very hard to find a product that says hey you're doing something that even if you put the blueprints out there it's very hard for other people to follow in those footsteps and create a similar value proposition and I think I think in this case it was a differentiated product and it had a lot of energy of its own and and I think from an EMC perspective they just stood back and said let's take this momentum and and play it out and see how how far it can take itself unfortunately I think a lot of times they don't do that right a lot of times acquiring companies don't just take this great thing and kind of get out of the way and add the juice where they can but you try to to try to change it so that's a really nice statement on Joe to G and what he was able to accomplish yeah no he was fantastic for us and and his support was tremendous but also his you know delegation and and kind of seeing how this but you know kind of having a vision of how this business unit should be formed right I think what was was very prison and then now you're part of Dell so obviously Michael Dell big personality as well the Dell technology stories he's doing a great job of pulling all these pieces together and you know kind of reinvigorating the brand coming back out of the little little side bar you know make it private for a while and come back so I wonder if you can talk about that integration how's that going as you've gone now a couple of times well I think it's been very exciting for us because the one piece that EMC had always been lacking had been the the compute part of the picture and now we have really the ability to go in and talk about the entire stack with our customers and that's that's a lot more powerful than saying here is an element of it and then if you want to go and add compute to that perhaps you know put in your virtual or physical servers then you're gonna we're going to need to partner with somebody and you know it's it's just a much cleaner story from end to end right right so the big big change obviously that wasn't around ten years ago that is around today is public cloud right huge impact not only directly in in taking workloads to the public cloud but also I think much more importantly changing the way people think about provisioning thinking about the way people think about elastic capacity so as as the market has evolved the rise of AWS and any other public clouds how has that changed what you guys are doing how are you reacting to that house at a new opportunity you know to kind of grow the maturity of the core product yeah well the thing is we have taken a lot of approach you know that's been learning and evolving as well right so so you know developers and applications really figured out AWS and the public cloud early I think data protection has has followed along with a couple years of lag in terms of doing that so you know our perspective is we learned as well right so so 2015 2016 I think there was some resistance and I think ultimately when we started to follow those workloads into the cloud there was a little bit of a lift and shift what we've learned is that the architecture really matters when you get to the cloud so the efficient use of resources the ability to do things in a cloud like way to use for example object storage instead of block storage when when the case presents itself so we took our products and virtualize them and followed them into the cloud but we realized that just taking the on-premise version of the product and putting it in the cloud itself isn't enough right because at the end of the day the customer is paying for all the underlying resources and so if your architecture is an efficient from a cost perspective as well as a performance perspective it's not going to be a viable solution and so 2017-2018 we've really seen a big acceleration in our adoption in the cloud because we have adapted our architecture to be more cloud friendly and more cost-effective for our customers to deploy but it was a learning experience for sure you know and and I think we're continuing to learn and continue to develop in that space and there's a lot of opportunity ahead of us the other big change I think that's come that we see over and over and over is really data as an asset only as an asset but as a huge valuable asset that drives your business drives real lytx but then becomes actually something that drives your company value and I think we see that and the Facebook's of the world and the googles of the world of why they have these crazy high valuations relative to here to their revenue and their profits because they're getting value for the data alright great news for you right it used to be a sample the day of the day was a pain it was expensive to store I didn't want to keep it all now everyone wants all the data they want to analyze it in real time and they want to put it in a place where they can actually put multiple applications across that same data set to do all kinds of new analytics so again super opportunity for you guys people aren't storing any less data no absolutely yeah no the data amount being stored is definitely growing one of the things that we're seeing that that's this kind of pervasive is this idea of of really using the right data the right place the right time so accessibility to whether it is a data Lake or it is your protection copies or you know an instant access of your protection copies there's a lot of different thing customers are doing with data but it's no longer a one-size-fits-all proposition like it was back in the tape automation days where I'm just throwing all of this stuff into a box and and never accessing it again right so the dynamics are changing and continue to evolve I expect that if we have this conversation two or three years down the road we're going to see some amazing things happen in the next couple of years that and some of it we were not predicting now we're gonna find out as customer demand and as innovation guides us along right because then the other big piece is the media right we've talked about tapes and the original data domain was was in response to some issues with tape and we get spinning rust as everybody likes to call it and now of course flash so yeah again see change in terms of capability the cost is coming down it's no longer the super high-end thing just for super high value applications so very transfer transformative opportunity on the on the media side as well on the flashlight as well you hit on a couple of really key things data domain was very successful because it became viable and practical to displace tape automation and nobody was a fan of their tape automation environments and now I think we're gonna see that's that same shift you know spinning disk is right now being relegated to archival and backup purposes but we're gonna hit an inflection point very soon I think we're where every instance of spinning disk probably can be questioned and so we are actually doing the you know kind of getting ahead of that curve and coming out with all flash products as a choice for a customer so we'll still have spinning disk for some backup use cases but we'll also have you know be able to offer customers a choice of the data domain technology on an all flash set of platforms and that will give customers a chance to get out of the yeah that spinning disk business as well right good I wonder if I get what if I get chime in here I you guys were talking about the the technologies and the cloud and the architecture it's interesting it David the main really started out don't hate me for saying this but as a feature product and the key feature was data deduplication data domain had the best you had a lot of guys doing post process you had you know some guys trying to do server-side avemar itself for example but they domain really killed it with regard to data David II do and if this feature product became a platform and had an architecture people became as you know unicorn times 2 plus plus and so I wanted to ask you rich about that architecture and aware it can go you're talking about different media now beyond spinning disk you know it used to be just a kind of a dumb target you've now got integrated appliances you've got software that's integrated there so it's you know you talked about the scale and the capacity where do you see this architecture going I wonder if you could comment on yeah well I think a lot of that belongs in in the realm of the data management software that speaks to it and and by having a distributed ecosystem and having things like you know distributed segment processing so we can take data domains technology and extend it out into those data management activities because a lot of the what's happening in the market is as new workloads are coming into the market they're having their own methods and native tools built-in for data protection and to be able to leverage those and have a highly consolidated affect on the backend is still extremely valuable to our customers and you're right it was a differentiated product from a deduplication standpoint but really the feature was that I can keep my 30 60 or 90 days worth of copies that are separate from my primary copies so I putting them somewhere safe I can even put them under different governance from my primary storage or my primary application owners right and it's practical and feasible and and prior to that the only real way to do that was with tape automation deduplication has become more of a broader word itself and it goes beyond what data domain does so there's deduplication and primary storage but if you look at primary storage deduplication it's good but it's designed to help you reduce the use of primary storage by 2 or 3 times it doesn't touch on the 30 60 90 days of retention that data domain does so there the similar technologies and a common use of the word but but they're two different use cases that the the remains separate I think yeah and you know as a former practitioner the other you are I think a former customer the genius part of the genius of data domain was its ability to just plug in to existing processes yes you didn't have to change things up and so it was an easy in but but it's impressive that you've been able to keep that that architecture going I wanted to ask you about market share you aided them in has always had a sixty plus percent market share I think it's at sixty now but it's it's like the Cisco of purpose-built backhaul appliances you're able to sort of dominate that little segment of the market which keeps getting bigger what but now you've got a lot of new entrants you know on VC money pouring in a lot of noise in the marketplace I feel like you guys maybe a couple years ago took your eye off the wall and now you've got this renewed sense of a vigor you know maybe it was parked partly the acquisition but you know we've talked to Beth Phelan about this a number of times you've really refreshed the portfolio so so wonder if you can talk about that and my question is what gives you confidence that you can continue to maintain your dominance yeah that's a great question and things have really changed I think starting around 2014 we were having some internal conversations about things like simplification the consumerization of IT and and all of those those dollars that you're talking about are really being poured into companies that are trying to take a different approach they're going into the white space that we had kind of left open which was simplicity right if you if you look back 10 or 15 years and you look at the the data management and enterprise backup software space enterprise backup software has been complicated and as you add more use cases it has become even more complicated and the customer base is no longer tolerant of that that's something that that maybe 10 or 15 years ago that was kind of a badge of honor to be working with complex and people just don't have the time for that there's a lot of IT generalists and folks that are out there that don't want to go to training class you know you know five days or ten days out of the year to learn how to use a product so that was a really good thing that we're seeing in the marketplace in terms of making products simpler easier to use and more approachable with things like discoverable functionality we certainly have the you know put a lot of effort into going in that direction because we think that's the right direction but what gives me confidence is the underlying storage value proposition about efficiency and performance and scale is something that we've still think that we have a strong upper hand on and when it comes down to that you know we take cloud as an example our data reduction in the cloud we think allows a much lower cost to serve and you know the customer is going to pay for that cloud storage or that cloud compute regardless of which vendor they're trusting in terms of their their solutions so simple only goes so far we think we can get there with simple but we don't necessarily see our competition having the efficiencies scalability and and so forth that we've already had so that that's good that gives me a lot of confidence so when you talk to customers what's the big problem the big hairy problem that they're trying to solve in your space and how are you guys helping so I one of the two big problems I see is is really a lot of IT teams are confronted with they've got a digital transformation going on they've got a cloud strategy going on an IT isn't necessarily being invited to the table early enough or often enough to go ahead and help with that process so what you have is you a cloud team building applications bringing things online and then the data protection the backups the snapshots whatever they're doing to make sure that that data is safe is is a bit of an afterthought and it you know I think of DevOps and I think about the ops part and I've never really come across an application team that wanted to own the business responsibility for the risk of you know backups recovery replication and all of that and I think IT has a lot of established practices that would be good to inform how those things should be built so the number one thing that I'm talking to with my customers when we're talking about this whole you know tectonic shift and in the way things are being done is that IT and the digital transformation or the cloud team do need to speak early and often and proactively about how they approach data protection because they continue to need to have a strategy that evolves and make sure they keep themselves protected as they start moving these critical workloads into the cloud it's an age-old problem with backup and data protection people think of it as a back as a bolt-on is an afterthought and your point is right on it's got to be a fundamental part of any transformation it's just like security you can't bolt it on earth just doesn't scale yeah and it's very much like you know back in the day when open systems was just coming of age there was a lot of operational discipline that the mainframe teams had and the mid-range teams had but the open systems was the Wild West and eventually open systems learned and and and a lot of that you know was knowledge sharing about best practices and you know Mis became IT now IT is becoming you know DevOps and digital transformation we're seeing a lot of that same dynamic happening again and and you know my main point is just you know start those conversations and if you're on the IT side start those conversations proactively you might not be getting invited to the digital transformation party invite yourself rich has been quite a 10 years and and as I was just watching an Andy Jazzy interview if you think the last 10 years have been crazy you ain't seen nothing yet so you guys are in a great position to stay agile and I'm gonna steal your line that it's no longer an honor to work on complicated systems that's great yeah it's been great being here thanks for having me and looking forward to maybe coming back in ten years and seeing what changed so hopefully we won't wait 10 years so rich thanks for stopping by Dave thanks for checking in from Boston and it's great to see you as well thanks you guys thanks Dave thanks Jeff [Music]
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Deploying AI in the Enterprise
(orchestral music) >> Hi, I'm Peter Burris and welcome to another digital community event. As we do with all digital community events, we're gonna start off by having a series of conversations with real thought leaders about a topic that's pressing to today's enterprises as they try to achieve new classes of business outcomes with technology. At the end of that series of conversations, we're gonna go into a crowd chat and give you an opportunity to voice your opinions and ask your questions. So stay with us throughout. So, what are we going to be talking about today? We're going to be talking about the challenge that businesses face as they try to apply AI, ML, and new classes of analytics to their very challenging, very difficult, but nonetheless very value-producing outcomes associated with data. The challenge that all these businesses have is that often, you spend too much time in the infrastructure and not enough time solving the problem. And so what's required is new classes of technology and new classes of partnerships and business arrangements that allow for us to mask the underlying infrastructure complexity from data science practitioners, so that they can focus more time and attention on building out the outcomes that the business wants and a sustained business capability so that we can continue to do so. Once again, at the end of this series of conversations, stay with us, so that we can have that crowd chat and you can, again, ask your questions, provide your insights, and participate with the community to help all of us move faster in this crucial direction for better AI, better ML and better analytics. So, the first conversation we're going to have is with Anant Chintamaneni. Anant's the Vice President of Products at BlueData. Anant, welcome to theCUBE. >> Hi Peter, it's great to be here. I think the topic that you just outlined is a very fascinating and interesting one. Over the last 10 years, data and analytics have been used to create transformative experiences and drive a lot of business growth. You look at companies like Uber, AirBnB, and you know, Spotify, practically, every industry's being disrupted. And the reason why they're able to do this is because data is in their DNA; it's their key asset and they've leveraged it in every aspect of their product development to deliver amazing experiences and drive business growth. And the reason why they're able to do this is they've been able to leverage open-source technologies, data science techniques, and big data, fast data, all types of data to extract that business value and inject analytics into every part of their business process. Enterprises of all sizes want to take advantage of that same assets that the new digital companies are taking and drive digital transformation and innovation, in their organizations. But there's a number of challenges. First and foremost, if you look at the enterprises where data was not necessarily in their DNA and to inject that into their DNA, it is a big challenge. The executives, the executive branch, definitely wants to understand where they want to apply AI, how to kind of identify which huge cases to go after. There is some recognition coming in. They want faster time-to-value and they're willing to invest in that. >> And they want to focus more on the actual outcomes they seek as opposed to the technology selection that's required to achieve those outcomes. >> Absolutely. I think it's, you know, a boardroom mandate for them to drive new business outcomes, new business models, but I think there is still some level of misalignment between the executive branch and the data worker community which they're trying to upgrade with the new-age data scientists, the AI developer and then you have IT in the middle who has to basically bridge the gap and enable the digital transformation journey and provide the infrastructure, provide the capabilities. >> So we've got a situation where people readily acknowledge the potential of some of these new AI, ML, big data related technologies, but we've got a mismatch between the executives that are trying to do evidence-based management, drive new models, the IT organization who's struggling to deal with data-first technologies, and data scientists who are few and far between, and leave quickly if they don't get the tooling that they need. So, what's the way forward, that's the problem. How do we move forward? >> Yeah, so I think, you know, I think we have to double-click into some of the problems. So the data scientists, they want to build a tool chain that leverages the best in-class, open source technologies to solve the problem at hand and they don't want, they want to be able to compile these tool chains, they want to be able to apply and create new algorithms and operationalize and do it in a very iterative cycle. It's a continuous development, continuous improvement process which is at odds with what IT can deliver, which is they have to deliver data that is dispersed all over the place to these data scientists. They need to be able to provide infrastructure, which today, they're not, there's an impotence mismatch. It takes them months, if not years, to be able to make those available, make that infrastructure available. And last but not the least, security and control. It's just fundamentally not the way they've worked where they can make data and new tool chains available very quickly to the data scientists. And the executives, it's all about faster time-to-value so there's a little bit of an expectation mismatch as well there and so those are some of the fundamental problems. There's also reproducibility, like, once you've created an analytics model, to be able to reproduce that at scale, to be then able to govern that and make sure that it's producing the right results is fundamentally a challenge. >> Audibility of that process. >> Absolutely, audibility. And, in general, being able to apply this sort of model for many different business problems so you can drive outcomes in different parts of your business. So there's a huge number of problems here. And so what I believe, and what we've seen with some of these larger companies, the new digital companies that are driving business valley ways, they have invested in a unified platform where they've made the infrastructure invisible by leveraging cloud technologies or containers and essentially, made it such that the data scientists don't have to worry about the infrastructure, they can be a lot more agile, they can quickly create the tool chains that work for the specific business problem at hand, scale it up and down as needed, be able to access data where it lies, whether it's on-prem, whether it's in the cloud or whether it's a hybrid model. And so that's something that's required from a unified platform where you can do your rapid prototyping, you can do your development and ultimately, the business outcome and the value comes when you operationalize it and inject it into your business processes. So, I think fundamentally, this start, this kind of a unified platform, is critical. Which, I think, a lot of the new age companies have, but is missing with a lot of the enterprises. >> So, a big challenge for the enterprise over the next few years is to bring these three groups together; the business, data science world and infrastructure world or others to help with those problems and apply it successfully to some of the new business challenges that we have. >> Yeah, and I would add one last point is that we are on this continuous journey, as I mentioned, this is a world of open source technologies that are coming out from a lot of the large organizations out there. Whether it's your Googles and your Facebooks. And so there is an evolution in these technologies much like we've evolved from big data and data management to capture the data. The next sort of phase is around data exploitation with artificial intelligence and machine learning type techniques. And so, it's extremely important that this platform enables these organizations to future proof themselves. So as new technologies come in, they can leverage them >> Great point. >> for delivering exponential business value. >> Deliver value now, but show a path to delivery value in the future as all of these technologies and practices evolve. >> Absolutely. >> Excellent, all right, Anant Chintamaneni, thanks very much for giving us some insight into the nature of the problems that enterprises face and some of the way forward. We're gonna be right back, and we're gonna talk about how to actually do this in a second. (light techno music) >> Introducing, BlueData EPIC. The leading container-based software platform for distributed AI, machine learning, deep learning and analytics environments. Whether on-prem, in the cloud or in a hybrid model. Data scientists need to build models utilizing various stacks of AI, ML and DL applications and libraries. However, installing and validating these environments is time consuming and prone to errors. BlueData provides the ability to spin up these environments on demand. The BlueData EPIC app store includes, best of breed, ready to run docker based application images. Like TensorFlow and H2O driverless AI. Teams can also add their own images, to provide the latest tools that data scientists prefer. And ensure compliance with enterprise standards. They can use the quick launch button. which provides pre configured templates with the appropriate application image and resources. For example, they can instantly launch a new Sandbox environment using the template for TensorFlow with a Jupyter Notebook. Within just a few minutes, it'll be automatically configured with GPUs and easy access to their data. Users can launch experiments and make GPUs automatically available for analysis. In this case, the H2O environment was set up with one GPU. With BlueData EPIC, users can also deploy end points with the appropriate run time. And the inference run times can use CPUs or GPUs. With a container based BlueData Platform, you can deploy fully configured distributed environments within a matter of minutes. Whether on-prem, in the public cloud, or in a hybrid a architecture. BlueData was recently acquired by Hewlett Packward Enterprise. And now, HPE and BlueData are joining forces to help you on your AI journey. (light techno music) To learn more, visit www.BlueData.com >> And we're back. I'm Peter Burris and we're continuing to have this conversation about how businesses are turning experience with the problems of advance analytics and the solutions that they seek into actual systems that deliver continuous on going value and achieve the business capabilities required to make possible these advanced outcomes associated with analytics, AI and ML. And to do that, we've got two great guests with us. We've got Kumar Sreekanti, who is the co-founder and CEO of BlueData. Kumar, welcome back to theCUBE. >> Thank you, it is nice to be here, back again. >> And Kumar, you're being joined by a customer. Ramesh Thyagarajan, is the executive director of the Advisory Board Company which is part of Optum now. Ramesh, welcome to theCUBE. >> Great to be here. >> Alright, so Kumar let's start with you. I mentioned up front, this notion of turning technology and understanding into actual business capabilities to deliver outcomes. What has been BlueData's journey along, to make that happen? >> Yeah, it all started six years ago, Peter. It was a bold vision and a big idea and no pun intended on big data which was an emerging market then. And as everybody knows, the data was enormous and there was a lot of innovation around the periphery. but nobody was paying attention to how to make the big data consumable in enterprise. And I saw an enormous opportunity to make this data more consumable in the enterprise and to give a cloud-like experience with the agility and elasticity. So, our vision was to build a software infrastructure platform like VMware, specially focused on data intensity distributed applications and this platform will allow enterprises to build cloud like experiences both on enterprise as well as on hybrid clouds. So that it pays the journey for their cloud experience. So I was very fortunate to put together a team and I found good partners like Intel. So that actually is the genesis for the BlueData. So, if you look back into the last six years, big data itself has went through a lot of evolution and so the marketplace and the enterprises have gone from offline analytics to AI, ML based work loads that are actually giving them predictive and descriptive analytics. What BlueData has done is by making the infrastructure invisible, by making the tool set completely available as the tool set itself is evolving and in the process, we actually created so many game changing software technologies. For example, we are the first end-to-end content-arised enterprise solution that gives you distributed applications. And we built a technology called DataTap, that provides computed data operation so that you don't have to actually copy the data, which is a boom for enterprises. We also actually built multitenancy so those enterprises can run multiple work loads on the same data and Ramesh will tell you in a second here, in the healthcare enterprise, the multitenancy is such a very important element. And finally, we also actually contributed to many open source technologies including, we have a project called KubeDirector which is actually is our own Kubernetes and how to run stateful workloads on Kubernetes. which we have actually very happy to see that people like, customers like Ramesh are using the BlueData. >> Sounds like quite a journey and obviously you've intercepted companies like the advisory board company. So Ramesh, a lot of enterprises have mastered or you know, gotten, understood how to create data lakes with a dupe but then found that they still weren't able to connect to some of the outcomes that they saw. Is that the experience that you had. >> Right, to be precise, that is one of the kind of problems we have. It's not just the data lake that we need to be able to do the workflows or other things, but we also, being a traditional company, being in the business for a long time, we have a lot of data assets that are not part of this data lake. We're finding it hard to, how do we get the data, getting them and putting them in a data lake is a duplication of work. We were looking for some kind of solutions that will help us to gather the benefits of leaving the data alone but still be able to get into it. >> This is where (mumbles). >> This is where we were looking for things and then I was lucky and fortunate to run into Kumar and his crew in one of the Hadoop conferences and then they demonstrated the way it can be done so immediately hit upon, it's a big hit with us and then we went back and then did a POC, very quickly adapt to the technology and that is also one of the benefits of corrupting this technology is the level of contrary memorization they are doing, it is helping me to address many needs. My data analyst, the data engineers and the data scientists so I'm able to serve all of them which otherwise wouldn't be possible for me with just this plain very (mumbles). >> So it sounds as though the partnership with BlueData has allowed you to focus on activities and problems and challenges above the technology so that you can actually start bringing data science, business objectives and infrastructure people together. Have I got that right? >> Absolutely. So BlueData is helping me to tie them all together and provide an excess value to my business. We being in the healthcare, the importance is we need to be able to look at the large data sets for a period of time in order to figure out how a patient's health journey is happening. That is very important so that we can figure out the ways and means in which we can lower the cost of health care and also provide insights to the physician, they can help get people better at health. >> So we're getting great outcomes today especially around, as you said that patient journey where all the constituents can get access to those insights without necessarily having to learn a whole bunch of new infrastructure stuff but presumably you need more. We're talking about a new world that you mentioned before upfront, talking about a new world, AI, ML, a lot of changes. A lot of our enterprise customers are telling us it's especially important that they find companies that not only deliver something today but demonstrate a commitment to sustain that value delivery process especially as the whole analytics world evolves. Are you experiencing that as well? >> Yes, we are experiencing and one of the great advantage of the platform, BlueData platform that gave me this ability to, I had the new functionality, be it the TensorFlow, be it the H2O, be it the heart studio, anything that I needed, I call them, they give me the images that are plug-and-play, just put them and all the prompting is practically transparent to nobody need to know how it is achieved. Now, in order to get to the next level of the predictive and prescriptive analytics, it is not just you having the data, you need to be able to have your curated data asset set process on top of a platform that will help you to get the data scientists to make you. One of the biggest challenges that are scientist is not able to get their hands on data. BlueData platform gives me the ability to do it and ensure all the security meets and all the compliances with the various other regulated compliances we need to make. >> Kamar, congratulations. >> Thank you. >> Sounds like you have a happy customer. >> Thank you. >> One of the challenges that every entrepreneur faces is how did you scale the business. So talk to us about where you are in the decisions that you made recently to achieve that. >> As an entrepreneur, when you start a company, odds are against you, right? You're always worried about it, right. You make so many sacrifices, yourself and your team and all that but the the customer is the king. The most important thing for us to find satisfied customers like Rameshan so we were very happy and BlueData was very successful in finding that customer because i think as you pointed out, as Ramesh pointed out, we provide that clean solution for the customer but as you go through this journey as a co-founder and CEO, you always worry about how do you scale to the next level. So we had partnerships with many companies including HPE and we found when this opportunity came in front of me with myself and my board, we saw this opportunity of combining the forces of BlueData satisfied customers and innovative technology and the team with the HPs brand name, their world-class service, their investment in R&D and they have a very long, large list of enterprise customers. We think putting these two things together provides that next journey in the BlueData's innovation and BlueData's customers. >> Excellent, so once again Kumar Sreekanti, co-founder and CEO of BlueData and Ramesh Thyagarajan who is the executive director of the advisory board company and part of Optum, I want to thank both of you for being on theCUBE. >> Thank you >> Thank you, great to be here. >> Now let's hear a little bit more about how this notion of bringing BlueData and HPE together is generating new classes of value that are making things happen today but are also gonna make things happen for customers in the future and to do that we've got Dave Velante who's with Silicon Angle Wiki Bond joined by Patrick Osbourne who's with HPE in our Marlborough studio so Dave over to you. >> Thanks Peter. We're here with Patrick Osbourne, the vice president and general manager of big data and analytics at Hewlett Packard Enterprise. Patrick, thanks for coming on. >> Thanks for having us. >> So we heard from Kumar, let's hear from you. Why did HPE purchase, acquire BlueData? >> So if you think about it from three angles. Platform, people and customers, right. Great platform, built for scale addressing a number of these new workloads and big data analytics and certainly AI, the people that they have are amazing, right, great engineering team, awesome customer success team, team of data scientists, right. So you know, all the folks that have some really, really great knowledge in this space so they're gonna be a great addition to HPE and also on the customer side, great logos, major fortune five customers in the financial services vertical, healthcare, pharma, manufacturing so a huge opportunity for us to scale that within HP context. >> Okay, so talk about how it fits into your strategy, specifically what are you gonna do with it? What are the priorities, can you share some roadmap? >> Yeah, so you take a look at HPE strategy. We talk about hybrid cloud and specifically edge to core to cloud and the common theme that runs through that is data, data-driven enterprises. So for us we see BlueData, Epic platform as a way to you know, help our customers quickly deploy these new mode to applications that are fueling their digital transformation. So we have some great plans. We're gonna certainly invest in all the functions, right. So we're gonna do a force multiplier on not only on product engineering and product delivery but also go to market and customer success. We're gonna come out in our business day one with some really good reference architectures, with some of our partners like Cloud Era, H2O, we've got some very scalable building block architectures to marry up the BlueData platform with our Apollo systems for those of you have seen that in the market, we've got our Elastic platform for analytics for customers who run these workloads, now you'd be able to virtualize those in containers and we'll have you know, we're gonna be building out a big services practice in this area. So a lot of customers often talk to us about, we don't have the people to do this, right. So we're gonna bring those people to you as HPE through Point Next, advisory services, implementation, ongoing help with customers. So it's going to be a really fantastic start. >> Apollo, as you mentioned Apollo. I think of Apollo sometimes as HPC high performance computing and we've had a lot of discussion about how that's sort of seeping in to mainstream, is that what you're seeing? >> Yeah absolutely, I mean we know that a lot of our customers have traditional workloads, you know, they're on the path to almost completely virtualizing those, right, but where a lot of the innovation is going on right now is in this mode two world, right. So your big data and analytics pipeline is getting longer, you're introducing new experiences on top of your product and that's fueling you know, essentially commercial HPC and now that folks are using techniques like AI and modeling inference to make those services more scalable, more automated, we're starting to bringing these more of these platforms, these scalable architectures like Apollo. >> So it sounds like your roadmap has a lot of integration plans across the HPE portfolio. We certainly saw that with Nimble, but BlueData was working with a lot of different companies, its software, is the plan to remain open or is this an HPE thing? >> Yeah, we absolutely want to be open. So we know that we have lots of customers that choose, so the HP is all about hybrid cloud, right and that has a couple different implications. We want to talk about your choice of on-prem versus off-prem so BlueData has a great capability to run some of these workloads. It essentially allows you to do separation of compute and storage, right in the world of AI and analytics we can run it off-prem as well in the public cloud but then we also have choice for customers, you know, any customer's private cloud. So that means they want to run on other infrastructure besides HPE, we're gonna support that, we have existing customers that do that. We're also gonna provide infrastructure that marries the software and the hardware together with frameworks like Info Site that we feel will be a you know, much better experience for the customers but we'll absolutely be open and absolutely have choice. >> All right, what about the business impact to take the customer perspective, what can they expect? >> So I think from a customer perspective, we're really just looking to accelerate deployment of AI in the enterprise, right and that has a lot of implications for us. We're gonna have very scalable infrastructure for them, we're gonna be really focused on this very dynamic AI and ML application ecosystems through partnerships and support within the BlueData platform. We want to provide a SAS experience, right. So whether that's GPUs or accelerators as a service, analytics as a service, we really want to fuel innovation as a service. We want to empower those data scientists there, those are they're really hard to find you know, they're really hard to retain within your organization so we want to unlock all that capability and really just we want to focus on innovation of the customers. >> Yeah, and they spend a lot of time wrangling data so you're really going to simplify that with the cloud (mumbles). Patrick thank you, I appreciate it. >> Thank you very much. >> Alright Peter, back to you in Palo Alto. >> And welcome back, I'm Peter Burris and we've been talking a lot in the industry about how new tooling, new processes can achieve new classes of analytics, AI and ML outcomes within a business but if you don't get the people side of that right, you're not going to achieve the full range of benefits that you might get out of your investments. Now to talk a little bit about how important the data science practitioner is in this equation, we've got two great guests with us. Nanda Vijaydev is the chief data scientists of BlueData. Welcome to theCUBE. >> Thank you Peter, happy to be here. >> Ingrid Burton is the CMO and business leader at H2O.AI, Ingrid, welcome to the CUBE. >> Thank you so much for having us. >> So Nanda Vijaydev, let's start with you. Again, having a nice platform, very, very important but how does that turn into making the data science practitioner's life easier so they can deliver more business value. >> Yeah thank you, it's a great question. I think end of the day for a data scientist, what's most important is, did you understand the question that somebody asked you and what is expected of you when you deliver something and then you go about finding, what do I need for them, I need data, I need systems and you know, I need to work with people, the experts in the process to make sure that the hypothesis I'm doing is structured in a nice way where it is testable, it's modular and I have you know, a way for them to go back to show my results and keep doing this in an iterative manner. That's the biggest thing because the satisfaction for a data scientist is when you actually take this and make use of it, put it in production, right. To make this whole thing easier, we definitely need some way of bringing it all together. That's really where, especially compared to the traditional data science where everything was monolithic, it was one system, there was a very set way of doing things but now it is not so you know, with the growing types of data, with the growing types of computation algorithms that's available, there's a lot of opportunity and at the same time there is a lot of uncertainty. So it's really about putting that structure and it's really making sure you get the best of everything and still deliver the results, that is the focus that all data scientists strive for. >> And especially you wanted, the data scientists wants to operate in the world of uncertainty related to the business question and reducing uncertainty and not deal with the underlying some uncertainty associated with the infrastructure. >> Absolutely, absolutely you know, as a data scientist a lot of time used to spend in the past about where is the data, then the question was, what data do you want and give it to you because the data always came in a nice structured, row-column format, it had already lost a lot of context of what we had to look for. So it is really not about you know, getting the you know, it's really not about going back to systems that are pre-built or pre-processed, it's getting access to that real, raw data. It's getting access to the information as it came so you can actually make the best judgment of how to go forward with it. >> So you describe the world with business, technology and data science practitioners are working together but let's face it, there's an enormous amount of change in the industry and quite frankly, a deficit of expertise and I think that requires new types of partnerships, new types of collaboration, a real (mumbles) approach and Ingrid, I want to talk about what H2O.AI is doing as a partner of BlueData, HPE to ensure that you're complementing these skills in pursuit or in service to the customer's objectives. >> Absolutely, thank you for that. So as Nanda described, you know, data scientists want to get to answers and what we do at H2O.AI is we provide the algorithms, the platforms for data scientist to be successful. So when they want to try and solve a problem, they need to work with their business leaders, they need to work with IT and they actually don't want to do all the heavy lifting, they want to solve that problem. So what we do is we do automatic machine learning platforms, we do that with optimizing algorithms and doing all the kind of, a lot of the heavy lifting that novice data scientists need and help expert data scientists as well. I talk about it as algorithms to answers and actually solving business problems with predictions and that's what machine learning is really all about but really what we're seeing in the industry right now and BlueData is a great example of kind of taking away some of the hard stuff away from a data scientist and making them successful. So working with BlueData and HPE, making us together really solve the problems that businesses are looking for, it's really transformative and we've been through like the digital transformation journey, all of us have been through that. We are now what I would term an AI transformation of sorts and businesses are going to the next step. They had their data, they got their data, infrastructure is kind of seamlessly working together, the clusters and containerization that's very important. Now what we're trying to do is get to the answers and using automatic machine learning platforms is probably the best way forward. >> That's still hard stuff but we're trying to get rid of data science practitioners, focusing on hard stuff that doesn't directly deliver value. >> It doesn't deliver anything for them, right. They shouldn't have to worry about the infrastructure, they should worry about getting the answers to the business problems they've been asked to solve. >> So let's talk a little bit about some of the new business problems that are going to be able to be solved by these kinds of partnerships between BlueData and H2O.AI. Start, Nanda, what do you, what gets you excited when we think about the new types of business problems that customers are gonna be able to solve. >> Yeah, I think it is really you know, the question that comes to you is not filtered through someone else's lens, right. Someone is trying an optimization problem, someone is trying to do a new product discovery so all this is based on a combination of both data-driven and evidence-based, right. For us as a data scientist, what excites me is that I have the flexibility now that I can choose the best of the breed technologies. I should not be restricted to what is given to me by an IT organization or something like that but at the same time, in an organization, for things to work, there has to be some level of control. So it is really having this type of environments or having some platforms where some, there is a team that can work on the control aspect but as a data scientist, I don't have to worry about it. I have my flexibility of tools of choice that I can use. At the same time, when you talk about data, security is a big deal in companies and a lot of times data scientists don't get access to data because of the layers and layers of security that they have to go through, right. So the excitement of the opportunity for me is if someone else takes care of the problem you know, just tell me where is the source of data that I can go to, don't filter the data for me you know, don't already structure the data for me but just tell me it's an approved source, right then it gives me more flexibility to actually go and take that information and build. So the having those controls taken care of well before I get into the picture as a data scientist, it makes it extremely easy for us to focus on you know, to her point, focus on the problem, right, focus on accessing the best of the breed technology and you know, give back and have that interaction with the business users on an ongoing basis. >> So especially focus on, so speed to value so that you're not messing around with a bunch of underlying infrastructure, governance remaining in place so that you know what are the appropriate limits of using the data with security that is embedded within that entire model without removing fidelity out of the quality of data. >> Absolutely. >> Would you agree with those? >> I totally agree with all the points that she brought up and we have joint customers in the market today, they're solving very complex problems. We have customers in financial services, joint customers there. We have customers in healthcare that are really trying to solve today's business problems and these are everything from, how do I give new credit to somebody? How do I know what next product to give them? How do I know what customer recommendations can I make next? Why did that customer churn? How do I reach new people? How do I do drug discovery? How do I give a patient a better prescription? How do I pinpoint disease than when I couldn't have seen it before? Now we have all that data that's available and it's very rich and data is a team sport. It takes data scientists, it takes business leaders and it takes IT to make it all work together and together the two companies are really working to solve problems that our customers are facing, working with our customers because they have the intellectual knowledge of what their problems are. We are providing the tools to help them solve those problems. >> Fantastic conversation about what is necessary to ensure that the data science practitioner remains at the center and is the ultimate test of whether or not these systems and these capabilities are working for business. Nanda Vijaydev, chief data scientist of BlueData, Ingrid Burton CMO and business leader, H2O.AI, thank you very much for being on theCUBE. >> Thank you. >> Thank you so much. >> So let's now spend some time talking about how ultimately, all of this comes together and what you're going to do as you participate in the crowd chat. To do that let me throw it back to Dave Velante in our Marlborough studios. >> We're back with Patrick Osbourne, alright Patrick, let's wrap up here and summarize. We heard how you're gonna help data science teams, right. >> Yup, speed, agility, time to value. >> Alright and I know a bunch of folks at BlueData, the engineering team is very, very strong so you picked up a good asset there. >> Yeah, it means amazing technology, the founders have a long lineage of software development and adoption in the market so we're just gonna, we're gonna invested them and let them loose. >> And then we heard they're sort of better together story from you, you got a roadmap, you're making some investments here, as I heard. >> Yeah, I mean so if we're really focused on hybrid cloud and we want to have all these as a services experience, whether it's through Green Lake or providing innovation, AI, GPUs as a service is something that we're gonna be you know, continuing to provide our customers as we move along. >> Okay and then we heard the data science angle and the data science community and the partner angle, that's exciting. >> Yeah, I mean, I think it's two approaches as well too. We have data scientists, right. So we're gonna bring that capability to bear whether it's through the product experience or through a professional services organization and then number two, you know, this is a very dynamic ecosystem from an application standpoint. There's commercial applications, there's certainly open source and we're gonna bring a fully vetted, full stack experience for our customers that they can feel confident in this you know, it's a very dynamic space. >> Excellent, well thank you very much. >> Thank you. Alright, now it's your turn. Go into the crowd chat and start talking. Ask questions, we're gonna have polls, we've got experts in there so let's crouch chat.
SUMMARY :
and give you an opportunity to voice your opinions and to inject that into their DNA, it is a big challenge. on the actual outcomes they seek and provide the infrastructure, provide the capabilities. and leave quickly if they don't get the tooling So the data scientists, they want to build a tool chain that the data scientists don't have to worry and apply it successfully to some and data management to capture the data. but show a path to delivery value in the future that enterprises face and some of the way forward. to help you on your AI journey. and the solutions that they seek into actual systems of the Advisory Board Company which is part of Optum now. What has been BlueData's journey along, to make that happen? and in the process, we actually created Is that the experience that you had. of leaving the data alone but still be able to get into it. and that is also one of the benefits and challenges above the technology and also provide insights to the physician, that you mentioned before upfront, and one of the great advantage of the platform, So talk to us about where you are in the decisions and all that but the the customer is the king. and part of Optum, I want to thank both of you in the future and to do that we've got Dave Velante and general manager of big data and analytics So we heard from Kumar, let's hear from you. and certainly AI, the people that they have are amazing, So a lot of customers often talk to us about, about how that's sort of seeping in to mainstream, and modeling inference to make those services more scalable, its software, is the plan to remain open and storage, right in the world of AI and analytics those are they're really hard to find you know, Yeah, and they spend a lot of time wrangling data of benefits that you might get out of your investments. Ingrid Burton is the CMO and business leader at H2O into making the data science practitioner's life easier and at the same time there is a lot of uncertainty. the data scientists wants to operate in the world of how to go forward with it. and Ingrid, I want to talk about what H2O and businesses are going to the next step. that doesn't directly deliver value. to the business problems they've been asked to solve. of the new business problems that are going to be able and a lot of times data scientists don't get access to data So especially focus on, so speed to value and it takes IT to make it all work together to ensure that the data science practitioner remains To do that let me throw it back to Dave Velante We're back with Patrick Osbourne, Alright and I know a bunch of folks at BlueData, and adoption in the market so we're just gonna, And then we heard they're sort of better together story that we're gonna be you know, continuing and the data science community and then number two, you know, Go into the crowd chat and start talking.
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11 25 19 HPE Launch Floyer 4 (Do not make public)
from our studios in the heart of Silicon Valley Palo Alto California this is a cute conversation welcome to the cube studios for the cube conversation where we go in-depth with thought leaders driving business outcomes with technology I'm your host Peter Burris digital business and the need to drive the value of data within organizations is creating an explosion of technology in multiple domains systems networking and storage we've seen advances in flash we've seen advances in HD DS we've seen advances and all kinds of different elements but it's essential that users and enterprises still think in terms not just of these individual technologies piecemeal but as solutions that are applied to use cases now you always have to be aware of what are the underlying technology components but it's still important to think about how systems integration is going to bring them together and apply them to serve business outcomes now to have that conversation we've got David Fleur who's the CTO and co-founder of wiki bond and my colleague David welcome to the cube thank you very much Peter all right so I've just laid out this proposition that systems integration as a discipline is not gonna go away when we think about how to build these capabilities that businesses need in digital business so let's talk about that what are some of the key features of systems integration especially in the storage world that will continue to be a helps differentiate between winners and losers absolutely so you you need to be able to use software to be able to combine all these different layers and it has to be an architect software solution that will work wherever you've got equipment and where have you got data so it needs to work in the cloud it needs to work in a private cloud it needs to work at the edge all of these needs to be architected in a way which is available to the users to put where the data is going to be created as opposed to bring it all in in one super large collection of data and so we've got different types of technology at the very fastest we've got DRAM we've got we've got non-volatile DRAM which is coming very fast indeed we've got flash and there are many different sorts of flash there's obtained from Intel that may be trying to get in between there as well and then there are different HD DS as well so we got a long hierarchy the important thing is that we protect the application and the operations from all of that complexity by having an overall hierarchy and utilizing software from an integration standpoint but it suggests that when an enterprise thinks about a solution for how they store their data they need to think in terms of as you said first off physically where is it going to be secondly what kinds of services at the software level am I going to utilize to ensure that I can have a common administrative experience and the differentiated usage experience based on the physical characteristics of where it's being used and then obviously and very importantly from an administration standpoint I need to ensure that I'm not having to learn new and unique administration practices everywhere because I would just blow everything up absolutely but there is a real there's going to be in my opinion a large number of these solutions out there I mean one data architecture is not going to be sufficient for all applications they're gonna have many different architectures out there I think it's probably useful just to start with one as an example in this area just let's take one as an example and then we can see what the major characteristics of you are so let's take something that would fit in most places a mid-range type solution let's take nimble nimble storage which has a very specific architecture so it was started off by being a virtualization of all those different layers so the application sees that everything is in flash and in cash or whatever it is but where it is is totally different it can be anywhere within that hierarchy so the application sees effectively a pool of resources that it can call yes all it sees and and it doesn't know and nobody and it doesn't need to know that it's on disk or a hard disk or in in memory in in in a cache inside the controller or wherever it is so it starts with using nimble as an example nimble is successfully masking the complexities and specificities of that storage heart and from the application right so so and and that's an advantage because it's simpler but it's also needs to cover more things you need to be able to do everything within that virtualized environment so you need for example to be able to take snapshots and you the snapshots need all the metadata about the snapshots needs to be put in a separate place so one of the things you find that comes from this sort of architecture is that the metadata is separated out completely different from the actual data itself but still proximate to the data because data locality still matters absolutely has to be there but it's in a different part of a hierarchy it's much further up the hierarchy all the metadata so what we've got the metadata we've got the flash high speed we've got the the fastest which is the DRAM itself that when for writes is has a protection mechanism for that that part of the DRAM specialized hardware in that area so that allows you to do writes very very quickly indeed and then you come down to the next layer which is flash and indeed within the in the in taking the nimble example you have two sorts of flash you can have the high-speed flash at the top and if you want to you can have lower performance flash you know using the 3d quad flash or whatever it is you can have lower performance flash if that's what you need and then going lower down then you have HD DS and the architecture combines the benefits of flash with the character and the characteristics of flash with the benefits of HD d which is much lower cost but the characteristics of HD d which are slower but very suited to writing out large volumes or reading in large volumes so that's read out to the disk but where where it's all held is held in the metadata so it's really looking at the workloads that are going to be they're gonna hit the data and then with out of making the application aware of it utilizing the underlying storage hierarchy to so best support those workloads again with a virtualized interface that keeps it really simple from an administration development and runtime perspective actually all right David foyer thanks very much for being on the cube and talking about some of these new solution-oriented requirements for thinking about storage over the next few years once again I'm Peter Burris see you next time you [Music]
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