(upbeat music) >> Hello, this is Dave Valente with theCUBE, and one of the most gratifying aspects of my role as a host of "theCUBE TV" is I get to cover a wide range of topics. And quite often, we're able to bring to our program a level of expertise that allows us to more deeply explore and unpack some of the topics that we cover throughout the year. And one of our favorite topics, of course, is data. Now, in 2021, after being in isolation for the better part of two years, a group of industry analysts met up at AWS re:Invent and started a collaboration to look at the trends in data and predict what some likely outcomes will be for the coming year. And it resulted in a very popular session that we had last year focused on the future of data management. And I'm very excited and pleased to tell you that the 2023 edition of that predictions episode is back, and with me are five outstanding market analyst, Sanjeev Mohan of SanjMo, Tony Baer of dbInsight, Carl Olofson from IDC, Dave Menninger from Ventana Research, and Doug Henschen, VP and Principal Analyst at Constellation Research. Now, what is it that we're calling you, guys? A data pack like the rat pack? No, no, no, no, that's not it. It's the data crowd, the data crowd, and the crowd includes some of the best minds in the data analyst community. They'll discuss how data management is evolving and what listeners should prepare for in 2023. Guys, welcome back. Great to see you. >> Good to be here. >> Thank you. >> Thanks, Dave. (Tony and Dave faintly speaks) >> All right, before we get into 2023 predictions, we thought it'd be good to do a look back at how we did in 2022 and give a transparent assessment of those predictions. So, let's get right into it. We're going to bring these up here, the predictions from 2022, they're color-coded red, yellow, and green to signify the degree of accuracy. And I'm pleased to report there's no red. Well, maybe some of you will want to debate that grading system. But as always, we want to be open, so you can decide for yourselves. So, we're going to ask each analyst to review their 2022 prediction and explain their rating and what evidence they have that led them to their conclusion. So, Sanjeev, please kick it off. Your prediction was data governance becomes key. I know that's going to knock you guys over, but elaborate, because you had more detail when you double click on that. >> Yeah, absolutely. Thank you so much, Dave, for having us on the show today. And we self-graded ourselves. I could have very easily made my prediction from last year green, but I mentioned why I left it as yellow. I totally fully believe that data governance was in a renaissance in 2022. And why do I say that? You have to look no further than AWS launching its own data catalog called DataZone. Before that, mid-year, we saw Unity Catalog from Databricks went GA. So, overall, I saw there was tremendous movement. When you see these big players launching a new data catalog, you know that they want to be in this space. And this space is highly critical to everything that I feel we will talk about in today's call. Also, if you look at established players, I spoke at Collibra's conference, data.world, work closely with Alation, Informatica, a bunch of other companies, they all added tremendous new capabilities. So, it did become key. The reason I left it as yellow is because I had made a prediction that Collibra would go IPO, and it did not. And I don't think anyone is going IPO right now. The market is really, really down, the funding in VC IPO market. But other than that, data governance had a banner year in 2022. >> Yeah. Well, thank you for that. And of course, you saw data clean rooms being announced at AWS re:Invent, so more evidence. And I like how the fact that you included in your predictions some things that were binary, so you dinged yourself there. So, good job. Okay, Tony Baer, you're up next. Data mesh hits reality check. As you see here, you've given yourself a bright green thumbs up. (Tony laughing) Okay. Let's hear why you feel that was the case. What do you mean by reality check? >> Okay. Thanks, Dave, for having us back again. This is something I just wrote and just tried to get away from, and this just a topic just won't go away. I did speak with a number of folks, early adopters and non-adopters during the year. And I did find that basically that it pretty much validated what I was expecting, which was that there was a lot more, this has now become a front burner issue. And if I had any doubt in my mind, the evidence I would point to is what was originally intended to be a throwaway post on LinkedIn, which I just quickly scribbled down the night before leaving for re:Invent. I was packing at the time, and for some reason, I was doing Google search on data mesh. And I happened to have tripped across this ridiculous article, I will not say where, because it doesn't deserve any publicity, about the eight (Dave laughing) best data mesh software companies of 2022. (Tony laughing) One of my predictions was that you'd see data mesh washing. And I just quickly just hopped on that maybe three sentences and wrote it at about a couple minutes saying this is hogwash, essentially. (laughs) And that just reun... And then, I left for re:Invent. And the next night, when I got into my Vegas hotel room, I clicked on my computer. I saw a 15,000 hits on that post, which was the most hits of any single post I put all year. And the responses were wildly pro and con. So, it pretty much validates my expectation in that data mesh really did hit a lot more scrutiny over this past year. >> Yeah, thank you for that. I remember that article. I remember rolling my eyes when I saw it, and then I recently, (Tony laughing) I talked to Walmart and they actually invoked Martin Fowler and they said that they're working through their data mesh. So, it takes a really lot of thought, and it really, as we've talked about, is really as much an organizational construct. You're not buying data mesh >> Bingo. >> to your point. Okay. Thank you, Tony. Carl Olofson, here we go. You've graded yourself a yellow in the prediction of graph databases. Take off. Please elaborate. >> Yeah, sure. So, I realized in looking at the prediction that it seemed to imply that graph databases could be a major factor in the data world in 2022, which obviously didn't become the case. It was an error on my part in that I should have said it in the right context. It's really a three to five-year time period that graph databases will really become significant, because they still need accepted methodologies that can be applied in a business context as well as proper tools in order for people to be able to use them seriously. But I stand by the idea that it is taking off, because for one thing, Neo4j, which is the leading independent graph database provider, had a very good year. And also, we're seeing interesting developments in terms of things like AWS with Neptune and with Oracle providing graph support in Oracle database this past year. Those things are, as I said, growing gradually. There are other companies like TigerGraph and so forth, that deserve watching as well. But as far as becoming mainstream, it's going to be a few years before we get all the elements together to make that happen. Like any new technology, you have to create an environment in which ordinary people without a whole ton of technical training can actually apply the technology to solve business problems. >> Yeah, thank you for that. These specialized databases, graph databases, time series databases, you see them embedded into mainstream data platforms, but there's a place for these specialized databases, I would suspect we're going to see new types of databases emerge with all this cloud sprawl that we have and maybe to the edge. >> Well, part of it is that it's not as specialized as you might think it. You can apply graphs to great many workloads and use cases. It's just that people have yet to fully explore and discover what those are. >> Yeah. >> And so, it's going to be a process. (laughs) >> All right, Dave Menninger, streaming data permeates the landscape. You gave yourself a yellow. Why? >> Well, I couldn't think of a appropriate combination of yellow and green. Maybe I should have used chartreuse, (Dave laughing) but I was probably a little hard on myself making it yellow. This is another type of specialized data processing like Carl was talking about graph databases is a stream processing, and nearly every data platform offers streaming capabilities now. Often, it's based on Kafka. If you look at Confluent, their revenues have grown at more than 50%, continue to grow at more than 50% a year. They're expected to do more than half a billion dollars in revenue this year. But the thing that hasn't happened yet, and to be honest, they didn't necessarily expect it to happen in one year, is that streaming hasn't become the default way in which we deal with data. It's still a sidecar to data at rest. And I do expect that we'll continue to see streaming become more and more mainstream. I do expect perhaps in the five-year timeframe that we will first deal with data as streaming and then at rest, but the worlds are starting to merge. And we even see some vendors bringing products to market, such as K2View, Hazelcast, and RisingWave Labs. So, in addition to all those core data platform vendors adding these capabilities, there are new vendors approaching this market as well. >> I like the tough grading system, and it's not trivial. And when you talk to practitioners doing this stuff, there's still some complications in the data pipeline. And so, but I think, you're right, it probably was a yellow plus. Doug Henschen, data lakehouses will emerge as dominant. When you talk to people about lakehouses, practitioners, they all use that term. They certainly use the term data lake, but now, they're using lakehouse more and more. What's your thoughts on here? Why the green? What's your evidence there? >> Well, I think, I was accurate. I spoke about it specifically as something that vendors would be pursuing. And we saw yet more lakehouse advocacy in 2022. Google introduced its BigLake service alongside BigQuery. Salesforce introduced Genie, which is really a lakehouse architecture. And it was a safe prediction to say vendors are going to be pursuing this in that AWS, Cloudera, Databricks, Microsoft, Oracle, SAP, Salesforce now, IBM, all advocate this idea of a single platform for all of your data. Now, the trend was also supported in 2023, in that we saw a big embrace of Apache Iceberg in 2022. That's a structured table format. It's used with these lakehouse platforms. It's open, so it ensures portability and it also ensures performance. And that's a structured table that helps with the warehouse side performance. But among those announcements, Snowflake, Google, Cloud Era, SAP, Salesforce, IBM, all embraced Iceberg. But keep in mind, again, I'm talking about this as something that vendors are pursuing as their approach. So, they're advocating end users. It's very cutting edge. I'd say the top, leading edge, 5% of of companies have really embraced the lakehouse. I think, we're now seeing the fast followers, the next 20 to 25% of firms embracing this idea and embracing a lakehouse architecture. I recall Christian Kleinerman at the big Snowflake event last summer, making the announcement about Iceberg, and he asked for a show of hands for any of you in the audience at the keynote, have you heard of Iceberg? And just a smattering of hands went up. So, the vendors are ahead of the curve. They're pushing this trend, and we're now seeing a little bit more mainstream uptake. >> Good. Doug, I was there. It was you, me, and I think, two other hands were up. That was just humorous. (Doug laughing) All right, well, so I liked the fact that we had some yellow and some green. When you think about these things, there's the prediction itself. Did it come true or not? There are the sub predictions that you guys make, and of course, the degree of difficulty. So, thank you for that open assessment. All right, let's get into the 2023 predictions. Let's bring up the predictions. Sanjeev, you're going first. You've got a prediction around unified metadata. What's the prediction, please? >> So, my prediction is that metadata space is currently a mess. It needs to get unified. There are too many use cases of metadata, which are being addressed by disparate systems. For example, data quality has become really big in the last couple of years, data observability, the whole catalog space is actually, people don't like to use the word data catalog anymore, because data catalog sounds like it's a catalog, a museum, if you may, of metadata that you go and admire. So, what I'm saying is that in 2023, we will see that metadata will become the driving force behind things like data ops, things like orchestration of tasks using metadata, not rules. Not saying that if this fails, then do this, if this succeeds, go do that. But it's like getting to the metadata level, and then making a decision as to what to orchestrate, what to automate, how to do data quality check, data observability. So, this space is starting to gel, and I see there'll be more maturation in the metadata space. Even security privacy, some of these topics, which are handled separately. And I'm just talking about data security and data privacy. I'm not talking about infrastructure security. These also need to merge into a unified metadata management piece with some knowledge graph, semantic layer on top, so you can do analytics on it. So, it's no longer something that sits on the side, it's limited in its scope. It is actually the very engine, the very glue that is going to connect data producers and consumers. >> Great. Thank you for that. Doug. Doug Henschen, any thoughts on what Sanjeev just said? Do you agree? Do you disagree? >> Well, I agree with many aspects of what he says. I think, there's a huge opportunity for consolidation and streamlining of these as aspects of governance. Last year, Sanjeev, you said something like, we'll see more people using catalogs than BI. And I have to disagree. I don't think this is a category that's headed for mainstream adoption. It's a behind the scenes activity for the wonky few, or better yet, companies want machine learning and automation to take care of these messy details. We've seen these waves of management technologies, some of the latest data observability, customer data platform, but they failed to sweep away all the earlier investments in data quality and master data management. So, yes, I hope the latest tech offers, glimmers that there's going to be a better, cleaner way of addressing these things. But to my mind, the business leaders, including the CIO, only want to spend as much time and effort and money and resources on these sorts of things to avoid getting breached, ending up in headlines, getting fired or going to jail. So, vendors bring on the ML and AI smarts and the automation of these sorts of activities. >> So, if I may say something, the reason why we have this dichotomy between data catalog and the BI vendors is because data catalogs are very soon, not going to be standalone products, in my opinion. They're going to get embedded. So, when you use a BI tool, you'll actually use the catalog to find out what is it that you want to do, whether you are looking for data or you're looking for an existing dashboard. So, the catalog becomes embedded into the BI tool. >> Hey, Dave Menninger, sometimes you have some data in your back pocket. Do you have any stats (chuckles) on this topic? >> No, I'm glad you asked, because I'm going to... Now, data catalogs are something that's interesting. Sanjeev made a statement that data catalogs are falling out of favor. I don't care what you call them. They're valuable to organizations. Our research shows that organizations that have adequate data catalog technologies are three times more likely to express satisfaction with their analytics for just the reasons that Sanjeev was talking about. You can find what you want, you know you're getting the right information, you know whether or not it's trusted. So, those are good things. So, we expect to see the capabilities, whether it's embedded or separate. We expect to see those capabilities continue to permeate the market. >> And a lot of those catalogs are driven now by machine learning and things. So, they're learning from those patterns of usage by people when people use the data. (airy laughs) >> All right. Okay. Thank you, guys. All right. Let's move on to the next one. Tony Bear, let's bring up the predictions. You got something in here about the modern data stack. We need to rethink it. Is the modern data stack getting long at the tooth? Is it not so modern anymore? >> I think, in a way, it's got almost too modern. It's gotten too, I don't know if it's being long in the tooth, but it is getting long. The modern data stack, it's traditionally been defined as basically you have the data platform, which would be the operational database and the data warehouse. And in between, you have all the tools that are necessary to essentially get that data from the operational realm or the streaming realm for that matter into basically the data warehouse, or as we might be seeing more and more, the data lakehouse. And I think, what's important here is that, or I think, we have seen a lot of progress, and this would be in the cloud, is with the SaaS services. And especially you see that in the modern data stack, which is like all these players, not just the MongoDBs or the Oracles or the Amazons have their database platforms. You see they have the Informatica's, and all the other players there in Fivetrans have their own SaaS services. And within those SaaS services, you get a certain degree of simplicity, which is it takes all the housekeeping off the shoulders of the customers. That's a good thing. The problem is that what we're getting to unfortunately is what I would call lots of islands of simplicity, which means that it leads it (Dave laughing) to the customer to have to integrate or put all that stuff together. It's a complex tool chain. And so, what we really need to think about here, we have too many pieces. And going back to the discussion of catalogs, it's like we have so many catalogs out there, which one do we use? 'Cause chances are of most organizations do not rely on a single catalog at this point. What I'm calling on all the data providers or all the SaaS service providers, is to literally get it together and essentially make this modern data stack less of a stack, make it more of a blending of an end-to-end solution. And that can come in a number of different ways. Part of it is that we're data platform providers have been adding services that are adjacent. And there's some very good examples of this. We've seen progress over the past year or so. For instance, MongoDB integrating search. It's a very common, I guess, sort of tool that basically, that the applications that are developed on MongoDB use, so MongoDB then built it into the database rather than requiring an extra elastic search or open search stack. Amazon just... AWS just did the zero-ETL, which is a first step towards simplifying the process from going from Aurora to Redshift. You've seen same thing with Google, BigQuery integrating basically streaming pipelines. And you're seeing also a lot of movement in database machine learning. So, there's some good moves in this direction. I expect to see more than this year. Part of it's from basically the SaaS platform is adding some functionality. But I also see more importantly, because you're never going to get... This is like asking your data team and your developers, herding cats to standardizing the same tool. In most organizations, that is not going to happen. So, take a look at the most popular combinations of tools and start to come up with some pre-built integrations and pre-built orchestrations, and offer some promotional pricing, maybe not quite two for, but in other words, get two products for the price of two services or for the price of one and a half. I see a lot of potential for this. And it's to me, if the class was to simplify things, this is the next logical step and I expect to see more of this here. >> Yeah, and you see in Oracle, MySQL heat wave, yet another example of eliminating that ETL. Carl Olofson, today, if you think about the data stack and the application stack, they're largely separate. Do you have any thoughts on how that's going to play out? Does that play into this prediction? What do you think? >> Well, I think, that the... I really like Tony's phrase, islands of simplification. It really says (Tony chuckles) what's going on here, which is that all these different vendors you ask about, about how these stacks work. All these different vendors have their own stack vision. And you can... One application group is going to use one, and another application group is going to use another. And some people will say, let's go to, like you go to a Informatica conference and they say, we should be the center of your universe, but you can't connect everything in your universe to Informatica, so you need to use other things. So, the challenge is how do we make those things work together? As Tony has said, and I totally agree, we're never going to get to the point where people standardize on one organizing system. So, the alternative is to have metadata that can be shared amongst those systems and protocols that allow those systems to coordinate their operations. This is standard stuff. It's not easy. But the motive for the vendors is that they can become more active critical players in the enterprise. And of course, the motive for the customer is that things will run better and more completely. So, I've been looking at this in terms of two kinds of metadata. One is the meaning metadata, which says what data can be put together. The other is the operational metadata, which says basically where did it come from? Who created it? What's its current state? What's the security level? Et cetera, et cetera, et cetera. The good news is the operational stuff can actually be done automatically, whereas the meaning stuff requires some human intervention. And as we've already heard from, was it Doug, I think, people are disinclined to put a lot of definition into meaning metadata. So, that may be the harder one, but coordination is key. This problem has been with us forever, but with the addition of new data sources, with streaming data with data in different formats, the whole thing has, it's been like what a customer of mine used to say, "I understand your product can make my system run faster, but right now I just feel I'm putting my problems on roller skates. (chuckles) I don't need that to accelerate what's already not working." >> Excellent. Okay, Carl, let's stay with you. I remember in the early days of the big data movement, Hadoop movement, NoSQL was the big thing. And I remember Amr Awadallah said to us in theCUBE that SQL is the killer app for big data. So, your prediction here, if we bring that up is SQL is back. Please elaborate. >> Yeah. So, of course, some people would say, well, it never left. Actually, that's probably closer to true, but in the perception of the marketplace, there's been all this noise about alternative ways of storing, retrieving data, whether it's in key value stores or document databases and so forth. We're getting a lot of messaging that for a while had persuaded people that, oh, we're not going to do analytics in SQL anymore. We're going to use Spark for everything, except that only a handful of people know how to use Spark. Oh, well, that's a problem. Well, how about, and for ordinary conventional business analytics, Spark is like an over-engineered solution to the problem. SQL works just great. What's happened in the past couple years, and what's going to continue to happen is that SQL is insinuating itself into everything we're seeing. We're seeing all the major data lake providers offering SQL support, whether it's Databricks or... And of course, Snowflake is loving this, because that is what they do, and their success is certainly points to the success of SQL, even MongoDB. And we were all, I think, at the MongoDB conference where on one day, we hear SQL is dead. They're not teaching SQL in schools anymore, and this kind of thing. And then, a couple days later at the same conference, they announced we're adding a new analytic capability-based on SQL. But didn't you just say SQL is dead? So, the reality is that SQL is better understood than most other methods of certainly of retrieving and finding data in a data collection, no matter whether it happens to be relational or non-relational. And even in systems that are very non-relational, such as graph and document databases, their query languages are being built or extended to resemble SQL, because SQL is something people understand. >> Now, you remember when we were in high school and you had had to take the... Your debating in the class and you were forced to take one side and defend it. So, I was was at a Vertica conference one time up on stage with Curt Monash, and I had to take the NoSQL, the world is changing paradigm shift. And so just to be controversial, I said to him, Curt Monash, I said, who really needs acid compliance anyway? Tony Baer. And so, (chuckles) of course, his head exploded, but what are your thoughts (guests laughing) on all this? >> Well, my first thought is congratulations, Dave, for surviving being up on stage with Curt Monash. >> Amen. (group laughing) >> I definitely would concur with Carl. We actually are definitely seeing a SQL renaissance and if there's any proof of the pudding here, I see lakehouse is being icing on the cake. As Doug had predicted last year, now, (clears throat) for the record, I think, Doug was about a year ahead of time in his predictions that this year is really the year that I see (clears throat) the lakehouse ecosystems really firming up. You saw the first shots last year. But anyway, on this, data lakes will not go away. I've actually, I'm on the home stretch of doing a market, a landscape on the lakehouse. And lakehouse will not replace data lakes in terms of that. There is the need for those, data scientists who do know Python, who knows Spark, to go in there and basically do their thing without all the restrictions or the constraints of a pre-built, pre-designed table structure. I get that. Same thing for developing models. But on the other hand, there is huge need. Basically, (clears throat) maybe MongoDB was saying that we're not teaching SQL anymore. Well, maybe we have an oversupply of SQL developers. Well, I'm being facetious there, but there is a huge skills based in SQL. Analytics have been built on SQL. They came with lakehouse and why this really helps to fuel a SQL revival is that the core need in the data lake, what brought on the lakehouse was not so much SQL, it was a need for acid. And what was the best way to do it? It was through a relational table structure. So, the whole idea of acid in the lakehouse was not to turn it into a transaction database, but to make the data trusted, secure, and more granularly governed, where you could govern down to column and row level, which you really could not do in a data lake or a file system. So, while lakehouse can be queried in a manner, you can go in there with Python or whatever, it's built on a relational table structure. And so, for that end, for those types of data lakes, it becomes the end state. You cannot bypass that table structure as I learned the hard way during my research. So, the bottom line I'd say here is that lakehouse is proof that we're starting to see the revenge of the SQL nerds. (Dave chuckles) >> Excellent. Okay, let's bring up back up the predictions. Dave Menninger, this one's really thought-provoking and interesting. We're hearing things like data as code, new data applications, machines actually generating plans with no human involvement. And your prediction is the definition of data is expanding. What do you mean by that? >> So, I think, for too long, we've thought about data as the, I would say facts that we collect the readings off of devices and things like that, but data on its own is really insufficient. Organizations need to manipulate that data and examine derivatives of the data to really understand what's happening in their organization, why has it happened, and to project what might happen in the future. And my comment is that these data derivatives need to be supported and managed just like the data needs to be managed. We can't treat this as entirely separate. Think about all the governance discussions we've had. Think about the metadata discussions we've had. If you separate these things, now you've got more moving parts. We're talking about simplicity and simplifying the stack. So, if these things are treated separately, it creates much more complexity. I also think it creates a little bit of a myopic view on the part of the IT organizations that are acquiring these technologies. They need to think more broadly. So, for instance, metrics. Metric stores are becoming much more common part of the tooling that's part of a data platform. Similarly, feature stores are gaining traction. So, those are designed to promote the reuse and consistency across the AI and ML initiatives. The elements that are used in developing an AI or ML model. And let me go back to metrics and just clarify what I mean by that. So, any type of formula involving the data points. I'm distinguishing metrics from features that are used in AI and ML models. And the data platforms themselves are increasingly managing the models as an element of data. So, just like figuring out how to calculate a metric. Well, if you're going to have the features associated with an AI and ML model, you probably need to be managing the model that's associated with those features. The other element where I see expansion is around external data. Organizations for decades have been focused on the data that they generate within their own organization. We see more and more of these platforms acquiring and publishing data to external third-party sources, whether they're within some sort of a partner ecosystem or whether it's a commercial distribution of that information. And our research shows that when organizations use external data, they derive even more benefits from the various analyses that they're conducting. And the last great frontier in my opinion on this expanding world of data is the world of driver-based planning. Very few of the major data platform providers provide these capabilities today. These are the types of things you would do in a spreadsheet. And we all know the issues associated with spreadsheets. They're hard to govern, they're error-prone. And so, if we can take that type of analysis, collecting the occupancy of a rental property, the projected rise in rental rates, the fluctuations perhaps in occupancy, the interest rates associated with financing that property, we can project forward. And that's a very common thing to do. What the income might look like from that property income, the expenses, we can plan and purchase things appropriately. So, I think, we need this broader purview and I'm beginning to see some of those things happen. And the evidence today I would say, is more focused around the metric stores and the feature stores starting to see vendors offer those capabilities. And we're starting to see the ML ops elements of managing the AI and ML models find their way closer to the data platforms as well. >> Very interesting. When I hear metrics, I think of KPIs, I think of data apps, orchestrate people and places and things to optimize around a set of KPIs. It sounds like a metadata challenge more... Somebody once predicted they'll have more metadata than data. Carl, what are your thoughts on this prediction? >> Yeah, I think that what Dave is describing as data derivatives is in a way, another word for what I was calling operational metadata, which not about the data itself, but how it's used, where it came from, what the rules are governing it, and that kind of thing. If you have a rich enough set of those things, then not only can you do a model of how well your vacation property rental may do in terms of income, but also how well your application that's measuring that is doing for you. In other words, how many times have I used it, how much data have I used and what is the relationship between the data that I've used and the benefits that I've derived from using it? Well, we don't have ways of doing that. What's interesting to me is that folks in the content world are way ahead of us here, because they have always tracked their content using these kinds of attributes. Where did it come from? When was it created, when was it modified? Who modified it? And so on and so forth. We need to do more of that with the structure data that we have, so that we can track what it's used. And also, it tells us how well we're doing with it. Is it really benefiting us? Are we being efficient? Are there improvements in processes that we need to consider? Because maybe data gets created and then it isn't used or it gets used, but it gets altered in some way that actually misleads people. (laughs) So, we need the mechanisms to be able to do that. So, I would say that that's... And I'd say that it's true that we need that stuff. I think, that starting to expand is probably the right way to put it. It's going to be expanding for some time. I think, we're still a distance from having all that stuff really working together. >> Maybe we should say it's gestating. (Dave and Carl laughing) >> Sorry, if I may- >> Sanjeev, yeah, I was going to say this... Sanjeev, please comment. This sounds to me like it supports Zhamak Dehghani's principles, but please. >> Absolutely. So, whether we call it data mesh or not, I'm not getting into that conversation, (Dave chuckles) but data (audio breaking) (Tony laughing) everything that I'm hearing what Dave is saying, Carl, this is the year when data products will start to take off. I'm not saying they'll become mainstream. They may take a couple of years to become so, but this is data products, all this thing about vacation rentals and how is it doing, that data is coming from different sources. I'm packaging it into our data product. And to Carl's point, there's a whole operational metadata associated with it. The idea is for organizations to see things like developer productivity, how many releases am I doing of this? What data products are most popular? I'm actually in right now in the process of formulating this concept that just like we had data catalogs, we are very soon going to be requiring data products catalog. So, I can discover these data products. I'm not just creating data products left, right, and center. I need to know, do they already exist? What is the usage? If no one is using a data product, maybe I want to retire and save cost. But this is a data product. Now, there's a associated thing that is also getting debated quite a bit called data contracts. And a data contract to me is literally just formalization of all these aspects of a product. How do you use it? What is the SLA on it, what is the quality that I am prescribing? So, data product, in my opinion, shifts the conversation to the consumers or to the business people. Up to this point when, Dave, you're talking about data and all of data discovery curation is a very data producer-centric. So, I think, we'll see a shift more into the consumer space. >> Yeah. Dave, can I just jump in there just very quickly there, which is that what Sanjeev has been saying there, this is really central to what Zhamak has been talking about. It's basically about making, one, data products are about the lifecycle management of data. Metadata is just elemental to that. And essentially, one of the things that she calls for is making data products discoverable. That's exactly what Sanjeev was talking about. >> By the way, did everyone just no notice how Sanjeev just snuck in another prediction there? So, we've got- >> Yeah. (group laughing) >> But you- >> Can we also say that he snuck in, I think, the term that we'll remember today, which is metadata museums. >> Yeah, but- >> Yeah. >> And also comment to, Tony, to your last year's prediction, you're really talking about it's not something that you're going to buy from a vendor. >> No. >> It's very specific >> Mm-hmm. >> to an organization, their own data product. So, touche on that one. Okay, last prediction. Let's bring them up. Doug Henschen, BI analytics is headed to embedding. What does that mean? >> Well, we all know that conventional BI dashboarding reporting is really commoditized from a vendor perspective. It never enjoyed truly mainstream adoption. Always that 25% of employees are really using these things. I'm seeing rising interest in embedding concise analytics at the point of decision or better still, using analytics as triggers for automation and workflows, and not even necessitating human interaction with visualizations, for example, if we have confidence in the analytics. So, leading companies are pushing for next generation applications, part of this low-code, no-code movement we've seen. And they want to build that decision support right into the app. So, the analytic is right there. Leading enterprise apps vendors, Salesforce, SAP, Microsoft, Oracle, they're all building smart apps with the analytics predictions, even recommendations built into these applications. And I think, the progressive BI analytics vendors are supporting this idea of driving insight to action, not necessarily necessitating humans interacting with it if there's confidence. So, we want prediction, we want embedding, we want automation. This low-code, no-code development movement is very important to bringing the analytics to where people are doing their work. We got to move beyond the, what I call swivel chair integration, between where people do their work and going off to separate reports and dashboards, and having to interpret and analyze before you can go back and do take action. >> And Dave Menninger, today, if you want, analytics or you want to absorb what's happening in the business, you typically got to go ask an expert, and then wait. So, what are your thoughts on Doug's prediction? >> I'm in total agreement with Doug. I'm going to say that collectively... So, how did we get here? I'm going to say collectively as an industry, we made a mistake. We made BI and analytics separate from the operational systems. Now, okay, it wasn't really a mistake. We were limited by the technology available at the time. Decades ago, we had to separate these two systems, so that the analytics didn't impact the operations. You don't want the operations preventing you from being able to do a transaction. But we've gone beyond that now. We can bring these two systems and worlds together and organizations recognize that need to change. As Doug said, the majority of the workforce and the majority of organizations doesn't have access to analytics. That's wrong. (chuckles) We've got to change that. And one of the ways that's going to change is with embedded analytics. 2/3 of organizations recognize that embedded analytics are important and it even ranks higher in importance than AI and ML in those organizations. So, it's interesting. This is a really important topic to the organizations that are consuming these technologies. The good news is it works. Organizations that have embraced embedded analytics are more comfortable with self-service than those that have not, as opposed to turning somebody loose, in the wild with the data. They're given a guided path to the data. And the research shows that 65% of organizations that have adopted embedded analytics are comfortable with self-service compared with just 40% of organizations that are turning people loose in an ad hoc way with the data. So, totally behind Doug's predictions. >> Can I just break in with something here, a comment on what Dave said about what Doug said, which (laughs) is that I totally agree with what you said about embedded analytics. And at IDC, we made a prediction in our future intelligence, future of intelligence service three years ago that this was going to happen. And the thing that we're waiting for is for developers to build... You have to write the applications to work that way. It just doesn't happen automagically. Developers have to write applications that reference analytic data and apply it while they're running. And that could involve simple things like complex queries against the live data, which is through something that I've been calling analytic transaction processing. Or it could be through something more sophisticated that involves AI operations as Doug has been suggesting, where the result is enacted pretty much automatically unless the scores are too low and you need to have a human being look at it. So, I think that that is definitely something we've been watching for. I'm not sure how soon it will come, because it seems to take a long time for people to change their thinking. But I think, as Dave was saying, once they do and they apply these principles in their application development, the rewards are great. >> Yeah, this is very much, I would say, very consistent with what we were talking about, I was talking about before, about basically rethinking the modern data stack and going into more of an end-to-end solution solution. I think, that what we're talking about clearly here is operational analytics. There'll still be a need for your data scientists to go offline just in their data lakes to do all that very exploratory and that deep modeling. But clearly, it just makes sense to bring operational analytics into where people work into their workspace and further flatten that modern data stack. >> But with all this metadata and all this intelligence, we're talking about injecting AI into applications, it does seem like we're entering a new era of not only data, but new era of apps. Today, most applications are about filling forms out or codifying processes and require a human input. And it seems like there's enough data now and enough intelligence in the system that the system can actually pull data from, whether it's the transaction system, e-commerce, the supply chain, ERP, and actually do something with that data without human involvement, present it to humans. Do you guys see this as a new frontier? >> I think, that's certainly- >> Very much so, but it's going to take a while, as Carl said. You have to design it, you have to get the prediction into the system, you have to get the analytics at the point of decision has to be relevant to that decision point. >> And I also recall basically a lot of the ERP vendors back like 10 years ago, we're promising that. And the fact that we're still looking at the promises shows just how difficult, how much of a challenge it is to get to what Doug's saying. >> One element that could be applied in this case is (indistinct) architecture. If applications are developed that are event-driven rather than following the script or sequence that some programmer or designer had preconceived, then you'll have much more flexible applications. You can inject decisions at various points using this technology much more easily. It's a completely different way of writing applications. And it actually involves a lot more data, which is why we should all like it. (laughs) But in the end (Tony laughing) it's more stable, it's easier to manage, easier to maintain, and it's actually more efficient, which is the result of an MIT study from about 10 years ago, and still, we are not seeing this come to fruition in most business applications. >> And do you think it's going to require a new type of data platform database? Today, data's all far-flung. We see that's all over the clouds and at the edge. Today, you cache- >> We need a super cloud. >> You cache that data, you're throwing into memory. I mentioned, MySQL heat wave. There are other examples where it's a brute force approach, but maybe we need new ways of laying data out on disk and new database architectures, and just when we thought we had it all figured out. >> Well, without referring to disk, which to my mind, is almost like talking about cave painting. I think, that (Dave laughing) all the things that have been mentioned by all of us today are elements of what I'm talking about. In other words, the whole improvement of the data mesh, the improvement of metadata across the board and improvement of the ability to track data and judge its freshness the way we judge the freshness of a melon or something like that, to determine whether we can still use it. Is it still good? That kind of thing. Bringing together data from multiple sources dynamically and real-time requires all the things we've been talking about. All the predictions that we've talked about today add up to elements that can make this happen. >> Well, guys, it's always tremendous to get these wonderful minds together and get your insights, and I love how it shapes the outcome here of the predictions, and let's see how we did. We're going to leave it there. I want to thank Sanjeev, Tony, Carl, David, and Doug. Really appreciate the collaboration and thought that you guys put into these sessions. Really, thank you. >> Thank you. >> Thanks, Dave. >> Thank you for having us. >> Thanks. >> Thank you. >> All right, this is Dave Valente for theCUBE, signing off for now. Follow these guys on social media. Look for coverage on siliconangle.com, theCUBE.net. Thank you for watching. (upbeat music)

>> Prior to the pandemic, organizations were largely optimized for efficiency as the best path to bottom line profits. Many CIOs tell theCUBE privately that they were caught off guard by the degree to which their businesses required greater resiliency beyond their somewhat cumbersome disaster recovery processes. And the lack of that business resilience has actually cost firms because they were unable to respond to changing market forces. And certainly, we've seen this dynamic with supply chain challenges. And there's a little doubt we're also seeing it in the area of cybersecurity generally, and data recovery specifically. Over the past 30 plus months, the rapid adoption of cloud to support remote workers and build in business resilience had the unintended consequences of expanding attack vectors, which brought an escalation of risk from cybercrime. While security in the public cloud is certainly world class, the result of multicloud has brought with it multiple shared responsibility models, multiple ways of implementing security policies across clouds and on-prem. And at the end of the day, more, not less, . But there's a positive side to this story. The good news is that public policy, industry collaboration and technology innovation is moving fast to accelerate data protection and cybersecurity strategies with a focus on modernizing infrastructure, securing the digital supply chain, and very importantly, simplifying the integration of data protection and cybersecurity. Today, there's heightened awareness that the world of data protection is not only an adjacency to, but is becoming a fundamental component of cybersecurity strategies. In particular, in order to build more resilience into a business, data protection people, technologies and processes must be more tightly coordinated with security operations. Hello, and welcome to "The Future of Multicloud Data Protection" made possible by Dell in collaboration with theCUBE. My name is Dave Vellante and I'll be your host today. In this segment, we welcome into theCUBE two senior executives from Dell who will share details on new technology announcements that directly address these challenges. Jeff Boudreau is the President and General Manager of Dell's Infrastructure Solutions Group, ISG, and he's going to share his perspectives on the market and the challenges he's hearing from customers. And we're going to ask Jeff to double click on the messages that Dell is putting into the marketplace and give us his detailed point of view on what it means for customers. Now, Jeff is going to be joined by Travis Vigil. Travis is the Senior Vice-President of Product Management for ISG at Dell Technologies, and he's going to give us details on the products that are being announced today and go into the hard news. Now, we're also going to challenge our guests to explain why Dell's approach is unique and different in the marketplace. Thanks for being with us. Let's get right into it. (upbeat music) We're here with Jeff Boudreau and Travis Vigil, and we're going to dig into the details about Dell's big data protection announcement. Guys, good to see you. Thanks for coming in. >> Good to see you. Thank you for having us. >> You're very welcome. Alright, let's start off Jeff, with the high level. You know, I'd like to talk about the customer, what challenges they're facing? You're talking to customers all the time. What are they telling you? >> Sure, as you know, we spend a lot of time with our customers, specifically listening, learning, understanding their use cases, their pain points within their specific environments. They tell us a lot. No surprise to any of us that data is a key theme that they talk about. It's one of their most important assets. They need to extract more value from that data to fuel their business models, their innovation engines, their competitive edge. So, they need to make sure that that data is accessible, it's secure and its recoverable, especially in today's world with the increased cyber attacks. >> Okay, so maybe we could get into some of those challenges. I mean, when you talk about things like data sprawl, what do you mean by that? What should people know? >> Sure, so for those big three themes, I'd say, you have data sprawl, which is the big one, which is all about the massive amounts of data. It's the growth of that data, which is growing at unprecedented rates. It's the gravity of that data and the reality of the multicloud sprawl. So stuff is just everywhere, right? Which increases that surface as attack space for cyber criminals. >> And by gravity, you mean the data's there and people don't want to move it. >> It's everywhere, right? And so when it lands someplace, think Edge, Core or Cloud, it's there. And it's something we have to help our customers with. >> Okay, so it's nuanced 'cause complexity has other layers. What are those layers? >> Sure. When we talk to our customers, they tell us complexity is one of their big themes. And specifically it's around data complexity. We talked about that growth and gravity of the data. We talk about multicloud complexity and we talk about multicloud sprawl. So multiple vendors, multiple contracts, multiple tool chains, and none of those work together in this multicloud world. Then that drives their security complexity. So, we talk about that increased attack surface. But this really drives a lot of operational complexity for their teams. Think about we're lacking consistency through everything. So people, process, tools, all that stuff, which is really wasting time and money for our customers. >> So, how does that affect the cyber strategies and the, I mean, I've often said the Cisco, now they have this shared responsibility model. They have to do that across multiple clouds. Every cloud has its own security policies and frameworks and syntax. So, maybe you could double click on your perspective on that. >> Sure. I'd say the big challenge customers have seen, it's really inadequate cyber resiliency and specifically, they're feeling very exposed. And today as the world with cyber attacks being more and more sophisticated, if something goes wrong, it is a real challenge for them to get back up and running quickly. And that's why this is such a big topic for CEOs and businesses around the world. You know, it's funny. I said this in my open. I think that prior to the pandemic businesses were optimized for efficiency, and now they're like, "Wow, we have to actually put some headroom into the system to be more resilient." You know, are you hearing that? >> Yeah, we absolutely are. I mean, the customers really, they're asking us for help, right? It's one of the big things we're learning and hearing from them. And it's really about three things. One's about simplifying IT. Two, it's really helping them to extract more value from their data. And then the third big piece is ensuring their data is protected and recoverable regardless of where it is going back to that data gravity and that very, you know, the multicloud world. Just recently, I don't know if you've seen it, but the Global Data Protected, excuse me, the Global Data Protection Index. >> GDPI. >> Yes. Jesus. >> Not to be confused with GDPR. >> Actually, that was released today and confirms everything we just talked about around customer challenges. But also it highlights at an importance of having a very cyber, a robust cyber resilient data protection strategy. >> Yeah, I haven't seen the latest, but I want to dig into it. I think this, I've done this many, many years in a row. I'd like to look at the time series and see how things have changed. All right. At a high level, Jeff, can you kind of address why Dell, from your point of view is best suited? >> Sure. So, we believe there's a better way or a better approach on how to handle this. We think Dell is uniquely positioned to help our customers as a one stop shop, if you will, for that cyber resilient multicloud data protection solution and needs. We take a modern, a simple and resilient approach. >> What does that mean? What do you mean by modern? >> Sure. So modern, we talk about our software defined architecture. Right? It's really designed to meet the needs not only of today, but really into the future. And we protect data across any cloud and any workload. So, we have a proven track record doing this today. We have more than 1,700 customers that trust us to protect more than 14 exabytes of their data in the cloud today. >> Okay, so you said modern, simple and resilient. What do you mean by simple? >> Sure. We want to provide simplicity everywhere, going back to helping with the complexity challenge. And that's from deployment to consumption, to management and support. So, our offers will deploy in minutes. They are easy to operate and use, and we support flexible consumption models for whatever the customer may desire. So, traditional subscription or as a service. >> And when you talk about resilient, I mean, I put forth that premise, but it's hard because people say, "Well, that's going to cost us more. Well, it may, but you're going to also reduce your risk." So, what's your point of view on resilience? >> Yeah, I think it's something all customers need. So, we're going to be providing a comprehensive and resilient portfolio of cyber solutions that are secure by design. And we have some unique capabilities and a combination of things like built in immutability, physical and logical isolation. We have intelligence built in with AI part recovery. And just one, I guess fun fact for everybody is we have, our cyber vault is the only solution in the industry that is endorsed by Sheltered Harbor that meets all the needs of the financial sector. >> So it's interesting when you think about the NIST framework for cybersecurity. It's all about about layers. You're sort of bringing that now to data protection. >> Jeff: Correct. Yeah. >> All right. In a minute, we're going to come back with Travis and dig into the news. We're going to take a short break. Keep it right there. (upbeat music) (upbeat adventurous music) Okay, we're back with Jeff and Travis Vigil to dig deeper into the news. Guys, again, good to see you. Travis, if you could, maybe you, before we get into the news, can you set the business context for us? What's going on out there? >> Yeah. Thanks for that question, Dave. To set a little bit of the context, when you look at the data protection market, Dell has been a leader in providing solutions to customers for going on nearly two decades now. We have tens of thousands of people using our appliances. We have multiple thousands of people using our latest modern, simple PowerProtect Data Manager Software. And as Jeff mentioned, we have, 1,700 customers protecting 14 exabytes of data in the public clouds today. And that foundation gives us a unique vantage point. We talked to a lot of customers and they're really telling us three things. They want simple solutions. They want us to help them modernize. And they want us to add as the highest priority, maintain that high degree of resiliency that they expect from our data protection solutions. So, that's the backdrop to the news today. And as we go through the news, I think you'll agree that each of these announcements deliver on those pillars. And in particular, today we're announcing the PowerProtect Data Manager Appliance. We are announcing PowerProtect Cyber Recovery Enhancements, and we are announcing enhancements to our APEX Data Storage Services. >> Okay, so three pieces. Let's dig to that. It's interesting, appliance, everybody wants software, but then you talk to customers and they're like, "Well, we actually want appliances because we just want to put it in and it works." >> Travis: (laughs) Right. >> It performs great. So, what do we need to know about the appliance? What's the news there? >> Well, you know, part of the reason I gave you some of those stats to begin with is that we have this strong foundation of experience, but also intellectual property components that we've taken that have been battle tested in the market. And we've put them together in a new simple, integrated appliance that really combines the best of the target appliance capabilities we have with that modern, simple software. And we've integrated it from the, you know, sort of taking all of those pieces, putting them together in a simple, easy to use and easy to scale interface for customers. >> So, the premise that I've been putting forth for months now, probably well over a year, is that data protection is becoming an extension of your cybersecurity strategies. So, I'm interested in your perspective on cyber recovery. Your specific news that you have there. >> Yeah, you know, we are in addition to simplifying things via the appliance, we are providing solutions for customers no matter where they're deploying. And cyber recovery, especially when it comes to cloud deployments, is an increasing area of interest and deployment that we see with our customers. So, what we're announcing today is that we're expanding our cyber recovery services to be available in Google Cloud. With this announcement, it means we're available in all three of the major clouds and it really provides customers the flexibility to secure their data no matter if they're running on-premises, in Acolo, at the Edge, in the public cloud. And the other nice thing about this announcement is that you have the ability to use Google Cloud as a cyber recovery vault that really allows customers to isolate critical data and they can recover that critical data from the vault back to on-premises or from that vault back to running their cyber protection or their data protection solutions in the public cloud. >> I always invoke my favorite Matt Baker here. "It's not a zero sum game", but this is a perfect example where there's opportunities for a company like Dell to partner with the public cloud provider. You've got capabilities that don't exist there. You've got the on-prem capabilities. We could talk about Edge all day, but that's a different topic. Okay, so my other question Travis, is how does this all fit into APEX? We hear a lot about APEX as a service. It's sort of the new hot thing. What's happening there? What's the news around APEX? >> Yeah, we've seen incredible momentum with our APEX solutions since we introduced data protection options into them earlier this year. And we're really building on that momentum with this announcement being providing solutions that allow customers to consume flexibly. And so, what we're announcing specifically is that we're expanding APEX Data Storage Services to include a data protection option. And it's like with all APEX offers, it's a pay-as-you-go solution. Really streamlines the process of customers purchasing, deploying, maintaining and managing their backup software. All a customer really needs to do is specify their base capacity. They specify their performance tier. They tell us do they want a one year term or a three year term and we take it from there. We get them up and running so they can start deploying and consuming flexibly. And as with many of our APEX solutions, it's a simple user experience all exposed through a unified APEX Console. >> Okay, so it's, you're keeping it simple, like I think large, medium, small. You know, we hear a lot about T-shirt sizes. I'm a big fan of that 'cause you guys should be smart enough to figure out, you know, based on my workload, what I need. How different is this? I wonder if you guys could address this. Jeff, maybe you can start. >> Sure, I'll start and then- >> Pitch me. >> You know, Travis, you jump in when I screw up here. >> Awesome. >> So, first I'd say we offer innovative multicloud data protection solutions. We provide that deliver performance, efficiency and scale that our customers demand and require. We support as Travis said, all the major public clouds. We have a broad ecosystem of workload support and I guess the great news is we're up to 80% more cost effective than any of the competition. >> Dave: 80%? >> 80% >> Hey, that's a big number. All right, Travis, what's your point of view on this? >> Yeah, I think number one, end-to-end data protection. We are that one stop shop that I talked about, whether it's a simplified appliance, whether it's deployed in the cloud, whether it's at the Edge, whether it's integrated appliances, target appliances, software. We have solutions that span the gamut as a service. I mentioned the APEX Solution as well. So really, we can provide solutions that help support customers and protect them, any workload, any cloud, anywhere that data lives. Edge, Core to Cloud. The other thing that we hear as a big differentiator for Dell, and Jeff touched on on this a little bit earlier, is our Intelligent Cyber Resiliency. We have a unique combination in the market where we can offer immutability or protection against deletion as sort of that first line of defense. But we can also offer a second level of defense, which is isolation, talking about data vaults or cyber vaults and cyber recovery. And more importantly, the intelligence that goes around that vault. It can look at detecting cyber attacks. It can help customers speed time to recovery. And really provides AI and ML to help early diagnosis of a cyber attack and fast recovery should a cyber attack occur. And if you look at customer adoption of that solution, specifically in the cloud, we have over 1300 customers utilizing PowerProtect Cyber Recovery. >> So, I think it's fair to say that your portfolio has obviously been a big differentiator. Whenever I talk to your finance team, Michael Dell, et cetera, that end-to-end capability, that your ability to manage throughout the supply chain. We actually just did an event recently with you guys where you went into what you're doing to make infrastructure trusted. And so my take on that is you, in a lot of respects, you're shifting the client's burden to your R&D. now they have a lot of work to do, so it's not like they can go home and just relax. But that's a key part of the partnership that I see. Jeff, I wonder if you could give us the final thoughts. >> Sure. Dell has a long history of being a trusted partner within IT, right? So, we have unmatched capabilities. Going back to your point, we have the broadest portfolio. We're a leader in every category that we participate in. We have a broad deep breadth of portfolio. We have scale. We have innovation that is just unmatched. Within data protection itself, we are the trusted market leader. No if, ands or buts. We're number one for both data protection software in appliances per IDC and we were just named for the 17th consecutive time the leader in the Gartner Magic Quadrant. So, bottom line is customers can count on Dell. >> Yeah, and I think again, we're seeing the evolution of data protection. It's not like the last 10 years. It's really becoming an adjacency and really, a key component of your cyber strategy. I think those two parts of the organization are coming together. So guys, really appreciate your time. Thanks for coming. >> Thank you, sir. >> Dave. >> Travis, good to see you. All right, in a moment I'm going to come right back and summarize what we learned today, what actions you can take for your business. You're watching "The Future of Multicloud Data Protection" made possible by Dell in collaboration with theCUBE, your leader in enterprise and emerging tech coverage. Right back. >> Advertiser: In our data-driven world, protecting data has never been more critical. To guard against everything from cyber incidents to unplanned outages, you need a cyber resilient multicloud data protection strategy. >> It's not a matter of if you're going to get hacked, it's a matter of when. And I want to know that I can recover and continue to recover each day. >> It is important to have a cyber security and a cyber resiliency plan in place because the threat of cyber attack are imminent. >> Advertiser: PowerProtect Data Manager from Dell Technologies helps deliver the data protection and security confidence you would expect from a trusted partner and market leader. >> We chose PowerProtect Data Manager because we've been a strategic partner with Dell Technologies for roughly 20 years now. Our partnership with Dell Technologies has provided us with the ability to scale and grow as we've transitioned from 10 billion in assets to 20 billion. >> Advertiser: With PowerProtect Data Manager, you can enjoy exceptional ease of use to increase your efficiency and reduce costs. >> I'd installed it by myself, learn it by myself. It was very intuitive. >> While restoring your machine with PowerProtect Data Manager is fast, we can fully manage PowerProtect through the center. We can recover a whole machine in seconds. >> Instructor: Data Manager offers innovation such as transparent snapshots to simplify virtual machine backups, and it goes beyond backup and restore to provide valuable insights into protected data, workloads and VMs. >> In our previous environment, it would take anywhere from three to six hours a night to do a single backup of each VM. Now, we're backing up hourly and it takes two to three seconds with the transparent snapshots. >> Advertiser: With PowerProtect's Data Manager, you get the peace of mind knowing that your data is safe and available whenever you need it. >> Data is extremely important. We can't afford to lose any data. We need things just to work. >> Advertiser: Start your journey to modern data protection with Dell PowerProtect's Data Manager. Visit dell.com/powerprotectdatamanager >> We put forth the premise in our introduction that the worlds of data protection in cybersecurity must be more integrated. We said that data recovery strategies have to be built into security practices and procedures and by default, this should include modern hardware and software. Now, in addition to reviewing some of the challenges that customers face, which have been pretty well documented, we heard about new products that Dell Technologies is bringing to the marketplace that specifically address these customer concerns. And there were three that we talked about today. First, the PowerProtect Data Manager Appliance, which is an integrated system taking advantage of Dell's history in data protection, but adding new capabilities. And I want to come back to that in a moment. Second is Dell's PowerProtect Cyber Recovery for Google Cloud platform. This rounds out the big three public cloud providers for Dell, which joins AWS and Azure support. Now finally, Dell has made its target backup appliances available in APEX. You might recall, earlier this year we saw the introduction from Dell of APEX Backup Services and then in May at Dell Technologies World, we heard about the introduction of APEX Cyber Recovery Services. And today, Dell is making its most popular backup appliances available in APEX. Now, I want to come back to the PowerProtect Data Manager Appliance because it's a new integrated appliance and I asked Dell off camera, "Really what is so special about these new systems and what's really different from the competition?" Because look, everyone offers some kind of integrated appliance. So, I heard a number of items. Dell talked about simplicity and efficiency and containers and Kubernetes. So, I kind of kept pushing and got to what I think is the heart of the matter in two really important areas. One is simplicity. Dell claims that customers can deploy the system in half the time relative to the competition. So, we're talking minutes to deploy, and of course that's going to lead to much simpler management. And the second real difference I heard was backup and restore performance for VMware workloads. In particular, Dell has developed transparent snapshot capabilities to fundamentally change the way VMs are protected, which leads to faster backup and restores with less impact on virtual infrastructure. Dell believes this new development is unique in the market and claims that in its benchmarks, the new appliance was able to back up 500 virtual machines in 47% less time compared to a leading competitor. Now, this is based on Dell benchmarks, so hopefully these are things that you can explore in more detail with Dell to see if and how they apply to your business. So if you want more information, go to the Data Protection Page at dell.com. You can find that at dell.com/dataprotection. And all the content here and other videos are available on demand at theCUBE.net. Check out our series on the blueprint for trusted infrastructure, it's related and has some additional information. And go to siliconangle.com for all the news and analysis related to these and other announcements. This is Dave Vellante. Thanks for watching "The Future of Multicloud Protection" made possible by Dell, in collaboration with theCUBE, your leader in enterprise and emerging tech coverage. (upbeat music)

>>Hey guys. Welcome back to the Cubes coverage of Ansible Fast 2022. This is day two of our wall to wall coverage. Lisa Martin here with John Ferer. John, we're seeing this world where companies are saying if we can't automate it, we need to, The automation market is transforming. There's been a lot of buzz about that. A lot of technical chops here at Ansible Fest. >>Yeah, I mean, we've got a great guest here coming on Cuba alumni, Dean Newman, future room. He travels every event he's got. He's got his nose to the grindstone ear to the ground. Great analysis. I mean, we're gonna get into why it's important. How does Ansible fit into the big picture? It's really gonna be a great segment. The >>Board do it well, John just did my job for me about, I'll introduce him again. Daniel Newman, one of our alumni is Back Principal Analyst at Future and Research. Great to have you back on the cube. >>Yeah, it's good to join you. Excited to be back in Chicago. I don't know if you guys knew this, but for 40 years, this was my hometown. Now I don't necessarily brag about that anymore. I'm, I live in Austin now. I'm a proud Texan, but I did grow up here actually out in the west suburbs. I got off the plane, I felt the cold air, and I almost turned around and said, Does this thing go back? Yeah. Cause I'm, I've, I've grown thin skin. It did not take me long. I, I like the warm, Come on, >>I'm the saying, I'm from California and I got off the plane Monday. I went, Whoa, I need a coat. And I was in Miami a week ago and it was 85. >>Oh goodness. >>Crazy. So you just flew in. Talk about what's going on, your take on, on Ansible. We've talked a lot with the community, with partners, with customers, a lot of momentum. The flywheel of the community is going around and round and round. What are some of your perspectives that you see? >>Yeah, absolutely. Well, let's you know, I'm gonna take a quick step back. We're entering an era where companies are gonna have to figure out how to do more with less. Okay? We've got exponential data growth, we've got more architectural complexity than ever before. Companies are trying to discern how to deal with many different environments. And just at a macro level, Red Hat is one of the companies that is almost certainly gonna be part of this multi-cloud hybrid cloud era. So that should initially give a lot of confidence to the buying group that are looking at how to automate their environments. You're automating workflows, but really with, with Ansible, we're focused on automating it, automating the network. So as companies are kind of dig out, we're entering this recessionary period, Okay, we're gonna call it what it is. The first thing that they're gonna look at is how do we tech our way out of it? >>I had a wonderful one-on-one conversation with ServiceNow ceo, Bill McDermott, and we saw ServiceNow was in focus this morning in the initial opening session. This is the integration, right? Ansible integrating with ServiceNow. What we need to see is infrastructure automation, layers and applications working in concert to basically enable enterprises to be up and running all the time. Let's first fix the problems that are most common. Let's, let's automate 'em, let's script them. And then at some point, let's have them self resolving, which we saw at the end with Project Wisdom. So as I see it, automation is that layer that enterprises, boards, technologists, all can agree upon are basically here's something that can make our business more efficient, more profitable, and it's gonna deal with this short term downturn in a way that tech is actually gonna be the answer. Just like Bill and I said, let's tech our way out of it. >>If you look at the Red Hat being bought by ibm, you see Project Wisdom Project, not a product, it's a project. Project Wisdom is the confluence of research and practitioners kind of coming together with ai. So bringing AI power to the Ansible is interesting. Red Hat, Linux, Rel OpenShift, I mean, Red Hat's kind of position, isn't it? Kind of be in that right spot where a puck might be coming maybe. I mean, what do you think? >>Yeah, as analysts, we're really good at predicting the, the recent past. It's a joke I always like to make, but Red Hat's been building toward the future. I think for some time. Project Wisdom, first of all, I was very encouraged with it. One of the things that many people in the market probably have commented on is how close is IBM in Red Hat? Now, again, it's a $34 billion acquisition that was made, but boy, the cultures of these two companies couldn't be more different. And of course, Red Hat kind of carries this, this sort of middle ground layer where they provide a lot of value in services to companies that maybe don't use IBM at, at, for the public cloud especially. This was a great indication of how you can take the power of IBM's research, which of course has some of the world's most prolific data scientists, engineers, building things for the future. >>You know, you see things like yesterday they launched a, you know, an AI solution. You know, they're building chips, semiconductors, and technologies that are gonna power the future. They're building quantum. Long story short, they have these really brilliant technologists here that could be adding value to Red Hat. And I don't know that the, the world has fully been able to appreciate that. So when, when they got on stage and they kind of say, Here's how IBM is gonna help power the next generation, I was immediately very encouraged by the fact that the two companies are starting to show signs of how they can collaborate to offer value to their customers. Because of course, as John kind of started off with, his question is, they've kind of been where the puck is going. Open source, Linux hybrid cloud, This is the future. In the future. Every company's multi-cloud. And I said in a one-on-one meeting this morning, every company is going to probably have workloads on every cloud, especially large enterprises. >>Yeah. And I think that the secret's gonna be how do you make that evolve? And one of the things that's coming out of the industry over the years, and looking back as historians, we would say, gotta have standards. Well, with cloud, now people standards might slow things down. So you're gonna start to figure out how does the community and the developers are thinking it'll be the canary in the coal mine. And I'd love to get your reaction on that, because we got Cuban next week. You're seeing people kind of align and try to win the developers, which, you know, I always laugh cuz like, you don't wanna win, you want, you want them on your team, but you don't wanna win them. It's like a, it's like, so developers will decide, >>Well, I, I think what's happening is there are multiple forces that are driving product adoption. And John, getting the developers to support the utilization and adoption of any sort of stack goes a long way. We've seen how sticky it can be, how sticky it is with many of the public cloud pro providers, how sticky it is with certain applications. And it's gonna be sticky here in these interim layers like open source automation. And Red Hat does have a very compelling developer ecosystem. I mean, if you sat in the keynote this morning, I said, you know, if you're not a developer, some of this stuff would've been fairly difficult to understand. But as a developer you saw them laughing at jokes because, you know, what was it the whole part about, you know, it didn't actually, the ping wasn't a success, right? And everybody started laughing and you know, I, I was sitting next to someone who wasn't technical and, and you know, she kinda goes, What, what was so funny? >>I'm like, well, he said it worked. Do you see that? It said zero data trans or whatever that was. So, but if I may just really quickly, one, one other thing I did wanna say about Project Wisdom, John, that the low code and no code to the full stack developer is a continuum that every technology company is gonna have to think deeply about as we go to the future. Because the people that tend to know the process that needs to be automated tend to not be able to code it. And so we've seen every automation company on the planet sort of figuring out and how to address this low code, no code environment. I think the power of this partnership between IBM Research and Red Hat is that they have an incredibly deep bench of capabilities to do things like, like self-training. Okay, you've got so much data, such significant size models and accuracy is a problem, but we need systems that can self teach. They need to be able self-teach, self learn, self-heal so that we can actually get to the crux of what automation is supposed to do for us. And that's supposed to take the mundane out and enable those humans that know how to code to work on the really difficult and hard stuff because the automation's not gonna replace any of that stuff anytime soon. >>So where do you think looking at, at the partnership and the evolution of it between IBM research and Red Hat, and you're saying, you know, they're, they're, they're finally getting this synergy together. How is it gonna affect the future of automation and how is it poised to give them a competitive advantage in the market? >>Yeah, I think the future or the, the competitive space is that, that is, is ecosystems and integration. So yesterday you heard, you know, Red Hat Ansible focusing on a partnership with aws. You know, this week I was at Oracle Cloud world and they're talking about running their database in aws. And, and so I'm kind of going around to get to the answer to your question, but I think collaboration is sort of the future of growth and innovation. You need multiple companies working towards the same goal to put gobs of resources, that's the technical term, gobs of resources towards doing really hard things. And so Ansible has been very successful in automating and securing and focusing on very certain specific workloads that need to be automated, but we need more and there's gonna be more data created. The proliferation, especially the edge. So you saw all this stuff about Rockwell, How do you really automate the edge at scale? You need large models that are able to look and consume a ton of data that are gonna be continuously learning, and then eventually they're gonna be able to deliver value to these companies at scale. IBM plus Red Hat have really great resources to drive this kind of automation. Having said that, I see those partnerships with aws, with Microsoft, with ibm, with ServiceNow. It's not one player coming to the table. It's a lot of players. They >>Gotta be Switzerland. I mean they have the Switzerland. I mean, but the thing about the Amazon deal is like that marketplace integration essentially puts Ansible once a client's in on, on marketplace and you get the central on the same bill. I mean, that's gonna be a money maker for Ansible. I >>Couldn't agree more, John. I think being part of these public cloud marketplaces is gonna be so critical and having Ansible land and of course AWS largest public cloud by volume, largest marketplace today. And my opinion is that partnership will be extensible to the other public clouds over time. That just makes sense. And so you start, you know, I think we've learned this, John, you've done enough of these interviews that, you know, you start with the biggest, with the highest distribution and probability rates, which in this case right now is aws, but it'll land on in Azure, it'll land in Google and it'll continue to, to grow. And that kind of adoption, streamlining make it consumption more consumable. That's >>Always, I think, Red Hat and Ansible, you nailed it on that whole point about multicloud, because what happens then is why would I want to alienate a marketplace audience to use my product when it could span multiple environments, right? So you saw, you heard that Stephanie yesterday talk about they, they didn't say multiple clouds, multiple environments. And I think that is where I think I see this layer coming in because some companies just have to work on all clouds. That's the way it has to be. Why wouldn't you? >>Yeah. Well every, every company will probably end up with some workloads in every cloud. I just think that is the fate. Whether it's how we consume our SaaS, which a lot of people don't think about, but it always tends to be running on another hyperscale public cloud. Most companies tend to be consuming some workloads from every cloud. It's not always direct. So they might have a single control plane that they tend to lead the way with, but that is only gonna continue to change. And every public cloud company seems to be working on figuring out what their niche is. What is the one thing that sort of drives whether, you know, it is, you know, traditional, we know the commoditization of traditional storage network compute. So now you're seeing things like ai, things like automation, things like the edge collaboration tools, software being put into the, to the forefront because it's a different consumption model, it's a different margin and economic model. And then of course it gives competitive advantages. And we've seen that, you know, I came back from Google Cloud next and at Google Cloud next, you know, you can see they're leaning into the data AI cloud. I mean, that is their focus, like data ai. This is how we get people to come in and start using Google, who in most cases, they're probably using AWS or Microsoft today. >>It's a great specialty cloud right there. That's a big use case. I can run data on Google and run something on aws. >>And then of course you've got all kinds of, and this is a little off topic, but you got sovereignty, compliance, regulatory that tends to drive different clouds over, you know, global clouds like Tencent and Alibaba. You know, if your workloads are in China, >>Well, this comes back down at least to the whole complexity issue. I mean, it has to get complex before it gets easier. And I think that's what we're seeing companies opportunities like Ansible to be like, Okay, tame, tame the complexity. >>Yeah. Yeah, I totally agree with you. I mean, look, when I was watching the demonstrations today, my take is there's so many kind of simple, repeatable and mundane tasks in everyday life that enterprises need to, to automate. Do that first, you know? Then the second thing is working on how do you create self-healing, self-teaching, self-learning, You know, and, and I realize I'm a little broken of a broken record at this, but these are those first things to fix. You know, I know we want to jump to the future where we automate every task and we have multi-term conversational AI that is booking our calendars and driving our cars for us. But in the first place, we just need to say, Hey, the network's down. Like, let's make sure that we can quickly get access back to that network again. Let's make sure that we're able to reach our different zones and locations. Let's make sure that robotic arm is continually doing the thing it's supposed to be doing on the schedule that it's been committed to. That's first. And then we can get to some of these really intensive deep metaverse state of automation that we talk about. Self-learning, data replication, synthetic data. I'm just gonna throw terms around. So I sound super smart. >>In your customer conversations though, from an looking at the automation journey, are you finding most of them, or some percentage is, is wanting to go directly into those really complex projects rather than starting with the basics? >>I don't know that you're, you're finding that the customers want to do that? I think it's the architecture that often ends up being a problem is we as, as the vendor side, will tend to talk about the most complex problems that they're able to solve before companies have really started solving the, the immediate problems that are before them. You know, it's, we talk about, you know, the metaphor of the cloud is a great one, but we talk about the cloud, like it's ubiquitous. Yeah. But less than 30% of our workloads are in the public cloud. Automation is still in very early days and in many industries it's fairly nascent. And doing things like self-healing networks is still something that hasn't even been able to be deployed on an enterprise-wide basis, let alone at the industrial layer. Maybe at the company's on manufacturing PLAs or in oil fields. Like these are places that have difficult to reach infrastructure that needs to be running all the time. We need to build systems and leverage the power of automation to keep that stuff up and running. That's, that's just business value, which by the way is what makes the world go running. Yeah. Awesome. >>A lot of customers and users are struggling to find what's the value in automating certain process, What's the ROI in it? How do you help them get there so that they understand how to start, but truly to make it a journey that is a success. >>ROI tends to be a little bit nebulous. It's one of those things I think a lot of analysts do. Things like TCO analysis Yeah. Is an ROI analysis. I think the businesses actually tend to know what the ROI is gonna be because they can basically look at something like, you know, when you have an msa, here's the downtime, right? Business can typically tell you, you know, I guarantee you Amazon could say, Look for every second of downtime, this is how much commerce it costs us. Yeah. A company can generally say, if it was, you know, we had the energy, the windmills company, like they could say every minute that windmill isn't running, we're creating, you know, X amount less energy. So there's a, there's a time value proposition that companies can determine. Now the question is, is about the deployment. You know, we, I've seen it more nascent, like cybersecurity can tend to be nascent. >>Like what does a breach cost us? Well there's, you know, specific costs of actually getting the breach cured or paying for the cybersecurity services. And then there's the actual, you know, ephemeral costs of brand damage and of risks and customer, you know, negative customer sentiment that potentially comes out of it. With automation, I think it's actually pretty well understood. They can look at, hey, if we can do this many more cycles, if we can keep our uptime at this rate, if we can reduce specific workforce, and I'm always very careful about this because I don't believe automation is about replacement or displacement, but I do think it is about up-leveling and it is about helping people work on things that are complex problems that machines can't solve. I mean, said that if you don't need to put as many bodies on something that can be immediately returned to the organization's bottom line, or those resources can be used for something more innovative. So all those things are pretty well understood. Getting the automation to full deployment at scale, though, I think what often, it's not that roi, it's the timeline that gets misunderstood. Like all it projects, they tend to take longer. And even when things are made really easy, like with what Project Wisdom is trying to do, semantically enable through low code, no code and the ability to get more accuracy, it just never tends to happen quite as fast. So, but that's not an automation problem, That's just the crux of it. >>Okay. What are some of the, the next things on your plate? You're quite a, a busy guy. We, you, you were at Google, you were at Oracle, you're here today. What are some of the next things that we can expect from Daniel Newman? >>Oh boy, I moved Really, I do move really quickly and thank you for that. Well, I'm very excited. I'm taking a couple of work personal days. I don't know if you're a fan, but F1 is this weekend. I'm the US Grand Prix. Oh, you're gonna Austin. So I will be, I live in Austin. Oh. So I will be in Austin. I will be at the Grand Prix. It is work because it, you know, I'm going with a number of our clients that have, have sponsorships there. So I'll be spending time figuring out how the data that comes off of these really fun cars is meaningfully gonna change the world. I'll actually be talking to Splunk CEO at the, at the race on Saturday morning. But yeah, I got a lot of great things. I got a, a conversation coming up with the CEO of Twilio next week. We got a huge week of earnings ahead and so I do a lot of work on that. So I'll be on Bloomberg next week with Emily Chang talking about Microsoft and Google. Love talking to Emily, but just as much love being here on, on the queue with you >>Guys. Well we like to hear that. Who you're rooting for F one's your favorite driver. I, >>I, I like Lando. Do you? I'm Norris. I know it's not necessarily a fan favorite, but I'm a bit of a McLaren guy. I mean obviously I have clients with Oracle and Red Bull with Ball Common Ferrari. I've got Cly Splunk and so I have clients in all. So I'm cheering for all of 'em. And on Sunday I'm actually gonna be in the Williams Paddock. So I don't, I don't know if that's gonna gimme me a chance to really root for anything, but I'm always, always a big fan of the underdog. So maybe Latifi. >>There you go. And the data that comes off the how many central unbeliev, the car, it's crazy's. Such a scientific sport. Believable. >>We could have Christian, I was with Christian Horner yesterday, the team principal from Reside. Oh yeah, yeah. He was at the Oracle event and we did a q and a with him and with the CMO of, it's so much fun. F1 has been unbelievable to watch the momentum and what a great, you know, transitional conversation to to, to CX and automation of experiences for fans as the fan has grown by hundreds of percent. But just to circle back full way, I was very encouraged with what I saw today. Red Hat, Ansible, IBM Strong partnership. I like what they're doing in their expanded ecosystem. And automation, by the way, is gonna be one of the most robust investment areas over the next few years, even as other parts of tech continue to struggle that in cyber security. >>You heard it here. First guys, investment in automation and cyber security straight from two analysts. I got to sit between. For our guests and John Furrier, I'm Lisa Martin, you're watching The Cube Live from Chicago, Ansible Fest 22. John and I will be back after a short break. SO'S stick around.

(upbeat music) >> Welcome back to theCUBE, everyone. This is Lisa Martin, live in Miami. I'm at IFS Unleashed 2022. We've had a great day talking with IFS executives, customers, partners. We're going to be having another great conversation next. I have two guests here on set with me, Sarah Nicastro joins us, the founder Future Field of Service, and VP of Customer Engagement at IFS, and Roel Rentmeeters, the VP of Digital Transformation at Munters. Welcome to the program. >> Thanks for having us. >> So, here we are surrounded by about 1500 or so people. The buzz in here is, people are ready to come back. They're just ready to come back, have these conversations with their peers and their colleagues at IFS which is great to to see and to feel, right? Sarah, let's start with you, your role, founder Future of Field Service. Talk to me about what that is and what the genesis was. >> Yeah, absolutely. So, a lot of what I do is actually what you're doing and interviewing folks, creating content. I was in the media before I joined IFS, almost four years ago in service specifically. So service, you've probably heard a lot today about moment of service. Service is a huge focus area for IFS and Future of field service is thought leadership resource that IFS allowed me to come on board and create, not only for customers, but for the broader service community. So, I write articles related to service trends host a weekly podcast. Over time with the company as I got to engage with more and more customers, and there's so much value in them connecting with one another. You see that here, like you said, people are so excited to be together, but fostering those connections within our customer community, allowing them to get to know each other, share our best practices, as well as making sure that we're bringing the voice of customer always into IFS. So, that's what I do on the customer engagement side. >> I love it. The voice of the customer is invaluable. And of all the conversations that I've had today, it's so clear how strategic and strong the relationships are that IFS has with its customers. Roel, talk to us a little bit about Munters, you're a customer and talk about the relationship that you've established with IFS and the team. >> Yeah, with pleasure. So, Munters is a Swedish company. We are a global leader in sustainable air treatment solutions. So, think about deunification, cooling, but in big industrial applications. I am the VP of digital services or digital transformation. Prior to that, until very recently, I was a VP of services. And we started that standardization roadmap five years ago, six years ago. We work very closely with IFS. We're implementing a new apps version as an ERP for Munters. And so that servitization moving from additional services to outcome-based services has the digital aspect. So, my move is a natural flow with that. >> How long has Munters been in business? >> It's founded in 1955. >> Oh wow. >> It's a Swedish company, quite traditional still in their manufacturing and delivering services. But the shift is there. >> Talk to me about that shift and how IFS has been an accelerant of that. It's challenging for legacy businesses to evolve and transform. Obviously in this day and age, you don't have a choice. But talk to us about the digital transformation of the business so that you can deliver more to your customers and how IFS has been foundational to that. >> Yeah. So, so that servitization roadmap eventually it is something that our customers want. We captured it. Customers want remote management, they want connected devices, but that alone will not bring you servitization. You need to have your strong foundation in the back with a good process, a good system that can support that process. And that's where IFS came in for us. We are a long time IFS user, so, we are on the eighth version in Europe of app eight, but we are doing a new implementation to 10, and this way, a global implementation with clean data that needs to be cleansed, new processes, end to end processes. And so IFS is our partner to support us in this roadmap along with other developments and things IFS is doing, think about remote management, something we've implemented during COVID and that perfectly aligns with that road towards servitization. >> Yeah, I was just going to say Roel and I were on a panel discussion earlier today with two other customers, and all different industries, but when we said what is the focus of the business they all said servitization or outcomes based services. Me too. Me too, me too, right? So, it's a journey that a lot of our customers are on looking at how they differentiate through service, how they move away from being a provider of products or things, and someone that their customers can trust to provide peace of mind, uptime, outcomes, experiences, things like that. >> It's all about outcomes. And we're hearing more and more about servitization. It's not a new concept. The term is somewhat newer to some of these conversations. But we're seeing a lot of businesses especially in light of COVID pivot in that direction and they need a partner that they can trust like IFS to help them get there. Sarah, let's talk more about customer engagement. What are some of the different facets that need to be considered? You guys, IFS has expertise in five verticals which I love the vertical specialization there. But talk to us about some of those facets that make customer engagement successful. >> Yeah, so I think you're absolutely right. So we have our five industries that we focus heavily on, and that is where most of our customer engagement has and does reside, right? So each industry has its own group of customers that get together weigh in on how IFS is innovating, what they need from the company and their respective industries, etc. What I'm focused on, and probably a lot of it is just based on my background. I mentioned on the panel there was a lot of head nods and me-too, me-too. That's because there are also elements of innovation and change that are happening across industries that our customers care a lot about. So what I'm working on at the moment is introducing sort of another layer of customer engagement where we're also fostering those cross industry more innovation-centered conversations so that we can not only better understand what our customers are focused on there, but also allow them to connect and learn from one another. >> I love that. There's so much power and potential. Roel, talk to us about that from your perspective, the opportunity. You mentioned, Sarah, the panel that you guys were on earlier today, but talk to us about the opportunity that IFS is giving you to engage with your peers in other industries, but also for you to learn and get takeaways from them. That's got to be pretty unique from a technology partner perspective. >> That definitely is. And the Future of Field Service, it's one of those four where I think we share so much knowledge, not just while we are sitting together and having our talks with Sarah, also individually we connected with each other. Companies that are also Swedish based like Tetra Park, etc, So, there's kind of bonds that we can see. But it's true, we are learning from each other also because some are maybe a bit more advanced than others in this area. So we can learn, not just around how they do their processes, how they find technicians on the market which is very scarce today and very difficult. How do you retain them? But also, what are you experiencing during your implementation?? What is your partner that are... What are pitfalls that you have discovered since you were there? Would you go to cloud or would you still wait in APP 10? So we share that knowledge to each other and we learn a lot from each other, which is something I like. I also like the fact that IFS is a very customer-centric company, as we mentioned before, the fact that you have changed advisory boards where the voice of the customer is going to be important, where you can feed back or IFS feeds back trends and things they see going forward where we can also say, but, "Would it not be better that the user interface for a technician who just wants to do this and this and this is simpler than what you offer today. So, it's a win-win situation for both of us. >> It's a collaboration. >> Yeah, I like it. >> It should be. And I'm really passionate about what what I do, but to be on sessions with a group of customers and have them say, "I'm going to call you later because I want to know more about how you did this, or can we connect?" And to see those connections happen, it's great to have events like this and they have been on hold, but ideally happen every year or year and a half. But to keep those connections going continuously is really important to me. >> Well, the innovations that IFS can span from just those connections alone is infinite, right? I mean, your mind can wander with all of the different things that can come out of that. Sarah, talk a little bit more about... We often talk about the voice of the customer. It's incredibly powerful. I always think it's the most objective opinion, but one of the things that I think I was learning earlier today is it's not just about the voice of the customer. It's taking the insights from those customers into the company, into the development of the technologies to then be able to fuel customer-driven changes. Talk about that as a one of the focuses that IFS has. >> Yeah, I mean, not only we, but our customers are talking a lot more about outside in innovation, right? An inside out model does not work today. And so, that's really what the focus is. And there's so many parallels between what we're focused on, what our customers are focused on, right? And so, I think voice of the customer, it's always good to have a quantitative measure where you're doing surveys, you're understanding what is your NBS, how do your customers feel, are they satisfied, etc? But it's also very important to have more of a qualitative or more intimate forum to have those deeper discussions to really get into some of the details that, to Roel's point, can then influence. Okay, well, we haven't quite thought about it that way. The more you have those discussions, the more you can notice what those common challenges or opportunities are so that when you are putting effort into our own evolution and modernization, we can make sure that's geared toward the the impact our customers need. >> Right. That's critical. It's all about outcomes. Customers need to move faster and faster and faster these days, right? I think one of the things that was in very short supply during the pandemic was patients and tolerance. And I don't know that it's going to come back. I think we are... >> I've never had it personally. (Lisa and Sarah laugh) >> I had a little bit of it, but I think the consumerization of tech, we expect these experiences in our professional world to be as easy as going on Amazon and buying whatever we want. We also want the brands to know enough about us where it's not creepy, but make it personalized to some degree, have that intimate relationship with me that's good enough to get me the outcome that I'm looking for. We all have that in our personal lives, but it flows into our business lives as well. So you're dealing with customers that probably have gotten more demanding as a result. >> I think you're absolutely right. And at the same time, not all customers want to go into that entire outcome-based direction. So, but what I like about it is, if you can do outcome-based service, you can also accommodate those customers and the service they want without having the outcome, think about as a lay based service or those kind of things because your organization and your systems and your processes are ready to do this. It's actually part of it. So, that voice of the customer is for us important enough to know it's not one thing that we should create. It's not one service offering. It depends on what kind of customers you are. Look at data center customers for which we do a lot of cooling, they are scared to hell that that thing would be brought down because it would endanger their entire data center. They don't want to connect, but they want to have certain data that they can see inside their environment and that they can pass on to us. So, you need to accommodate all those things. So, your voice of customer is extremely important. >> You mentioned, Lisa, that we've been talking about servitization for quite a while, right? And it's because it involves so many layers of change within a business, right? And so, it's really more of a journey, a continuum. And to Roel's point, companies need to be able to address what their customers need at different points. Some may want to remain on a CapEx model and some may want to move to an outcomes model. We also need to be able to address what our customers need on a bit of a continuum, which is what we're working toward with IFS cloud, is being able to meet people where they are and give them what they need that can grow with them as they grow with their customers. >> And that's absolutely essential for a good partnership and that makes for those moments of service to happen at the end of the day to that end user, whether it's an airline or whatnot. IFS cloud, and we have a couple minutes left, but IFS cloud was launched only 18 months ago and I was in the keynote this morning and Christian was actually here on the show with me too, 400,000 plus users in 18 months, that's growing pretty quickly. What's been some of the feedback from the customer side, and we'll get your perspective, Roel, as well? >> I don't have cloud yet, so we are implementing APP 10. Why? Because we signed up with IFS two years ago. At that time it was not yet there. And we think now let's first do this and then we can move to cloud. But it's not that we will not move to cloud. It's something we will do eventually. I like the fact that IFS thinks of having everything in one rather than having the different pieces, which made it also for me personally very difficult to make a choice. Do I go for the standalone version of the field service, or do I take the one that is embedded in the ERP? What is the difference between those two? Is there functionalities that I'm going to miss if I choose one or the other? So, the fact that it will be all together, it makes it easier also to add on later on like customer service or the customer ports or all those kind of things. So, I like that concept. So, I'm very curious to hear from peers here that have done the implementation like the Tetre Pack, how's it going? What is their feeling? I'm very curious. >> Well, I imagine at this kind of event, you're going to learn just that. >> Yep. (Lisa chuckles) >> You were going to say something, Sarah. >> Yeah, I was just going to say, I think it's a really good point that you mentioned with all of the things we're used to in our consumer lives, we want simplicity. Having complex technology stacks is at odds with delivering simplicity to the customer, right? And so, so that's the goal really. I was just in a session before this with Yotin who's on the journey to Evergreen with IFS cloud. And it's really the idea of eliminating some of the manual effort that exists in maintaining a system, making it a lot easier and faster for organizations to adopt innovation that comes out and give them more agility really in focusing on meeting their customer needs instead of focusing on managing their technology. >> Absolutely. Nobody wants to be doing that. Thank you so much, both of you for joining me on the program today, talking about what IFS is doing, the Future of Field Service, how you're partnering, truly partnering with customers. It's impressive. We talked to a lot of vendors and a lot of customers and I definitely am seeing some unique differentiation here. So, thank you so much for sharing your insights with me today. >> Thanks, Lisa. >> Thank you. >> Appreciate it. For my guests, I'm Lisa Martin. You've been watching theCUBE live from Miami. We've been here all day. We thank you so much for watching. We will see you next time. (soft music)

The Cube Presents UI Path Forward five. Brought to you by UI Path. >>I Ready, Dave Ante with David Nicholson. We're back at UI Path forward. Five. We're getting ready for the big guns to come in, the two co CEOs, but we have a really special analyst panel now. We're excited to have Daniel Newman here. He's the Principal analyst at Future and Research. And Andy Dai, who's the Vice president and Principal Analyst at Constellation Research. Guys, good to see you. Thanks for making some time to come on the queue. >>Glad to be here. Always >>Good. So, >>Andy, you're deep into ai. You and I have been talking about having you come to our maor office. I'm, I'm really excited that we're able to meet here. What have you seen at the show so far? What are your big takeaways? You know, day one and a half? >>Yeah, well, so first of all, I'm d AI because my last name has AI and I >>Already talk about, >>So, but, but all jokes aside, there are a lot of good things I heard from the conference, right? I mean, one is the last two years because of the pandemic, the growth has been phenomenal for, for a lot of those robotic automation intelligent automation companies, right? So because the low hanging through position making processes have been already taken care of where they going to find the next growth spot, right? That was the question I was looking answers to. And they have some inverse, one good acquisition. They had intelligent document processing, but more importantly they're trying to move from detrimental rules based RPA automation into AI based, more probabilistic subjective decision making areas. That's a huge market, tons of money involved in it, but it's going to be a harder problem to solve. Love to see the execut. >>Well, it's also a big pivot for the, for the company. It started out as sort of a a point product and now is moving to, to platform. But to end of the macro is not in UI pass favor. It's not really in any, you know, tech company's favor, but especially, you know, a company that's going into a transition transitioning to go to market cetera. What are you seeing, what's your take on the macro? I mean, I know you follow the financial markets very closely. There's a lot of negative sentiment right now. Are you as negative as the sentiment? >>Well, the, the broad sentiment comes with some pretty good historical data, right? We've had probably one of the worst market years in multiple decades. And of course we're coming into a situation where all the, the factors are really not in our favor. You've got in interest rates climbing, you've got wildly high inflation, you've had a, you know, helicopters dumping money on the economy for a period of time. And we're, we're gonna get into this great reset is what I keep talking about. But, you know, I had the opportunity to talk to Bill McDermott recently on one of my shows and Bill's CEO of ServiceNow, in case anybody there doesn't know, but >>Former, >>Yeah, really well spoken guy. But you know, him and I kind of went back and forth and we came up with this kind of concept that we were gonna have to tech our way out of what's about to come. You can almost be certain recession is gonna come. But for companies like UiPath, I actually think there's a tremendous opportunity because the bottom line is companies are gonna be looking at their bottom line. A year ago it was all about growth a deal, like the Adobe Figma deal would've been, been lauded, people would've been excited. Now everybody's looking at going, how are they paying that price? Everybody's discounting the future growth. They're looking at the situation, say, what's gonna happen next? Well, bottom line is now they're looking at that. How profitable are we? Are you making money? Are you growing that bottom line? Are you creating earnings? We're >>Gonna come in >>Era, we're gonna come into an era where companies are gonna say, you know what? People are expensive. The inflationary cost of hiring is expensive. You know, what's less expensive? Investing in the cloud, investing in ai, investing in workflow and automation and things that actually enable businesses to expand, keep costs somewhat contained fixed costs, and scale their businesses and get themselves in a good position for when the economy turns to return to >>Grow. So since prior to the pandemic cloud containers, m l and RPA slash automation have been the big four that from a spending data standpoint have been above the line above all kind of the rest in terms of spending momentum up until last quarter, AI and RPA slash automation declined. So my question is, are those two areas discretionary or more discretionary than other technology investments you heard? >>Well, I, I think we're in a, a period where companies are, I won't say they've stopped spending, but you listened to Mark Benioff, you talked about the elongated sales cycle, right? I think companies right now are being very reflective and they're doing a lot of introspection. They're looking at their business and saying, We hired a lot of people. We hired really fast. Do we need to cut? Do we need to freeze? We've made investments in technology, are we getting a return on 'em? We all know that the analytics, whether it's you know, digital adoption platforms or just analytics in the business, say, What is all this money we've been spending doing for us and how productive are we? But I will tell you universally, the companies are looking at workflow automations that enable things. Whether that's onboarding customers, whether that's delivering experiences, whether that's, you know, full, you know, price to quote technologies, automate, automate, automate. By doing that, they're gonna bring down the cost, they're gonna control themselves as best as possible in a tough macro. And then when they come out of it, these processes are gonna be beneficiary in a, in a growth environment even more so, >>Andy UiPath rocketed to a leadership position, largely due to the, the product and the simplicity of the product relative to the competition. And then as you well know, they expanded into, you know, platform. So how do you see the competitive environment? A UI path is again focusing on that platform play Automation Anywhere couldn't get to public market. They had turnover at the go to market level. Chris Riley joined a lot of, lot of hope left Microsoft joined into the fray, obviously is having an impact that you're certainly seeing spending momentum around Microsoft. Then SAP service Now Salesforce, every software company the planet thinks they should get every dollar spent on software. You know, they, they see UI pass momentum and they say, Hey, we can, we can take some of that off the table. How do you see the competitive environment right now? >>So first of all, in in my mind, UI path is slightly better because of a couple of reasons. One, as you said, it's ease of use. >>They're able to customize it variable to what they want. So that's a real easy development advantage. And then the, when you develop the bots and equal, it takes on an average anywhere between two to maybe six weeks, generally speaking, in some industries regulated government might take more so that it's faster, quicker, easier than others in a sense. So people love using that. The second advantage of what they have in my mind is that not only they are available as a managed SA solution on, on cloud, on Azure Cloud, but also they have this version that you can install, maintain, manage any way you want, whether it's a public cloud or, or your own data center and so on so forth. That's not available with almost, not all of them have it, Few have it, but not all of the competitors have it. So they have an advantage there as well. Where it could become useful would be one of the areas that they haven't even expanded is the government. >>Government is the what, >>Sorry? The government. Yeah, related solutions, right? Defense, government, all of those areas when you go, which haven't even started for various reasons. For example, they're worried about laying off people, worried about cost, worried about automating things. There's a lot of hurdles to overcome. But once you overcome that, if you want to go there, nobody's going to use, or most of them will be very of using something on the cloud. So they have a solution for version variation of that. So they are set up to come to that next level. I mean, I don't know if you guys were at the keynote, the CEO talked about how their plans to go from 1 billion to 5 billion in ar. So they're set up to capture the market. But again, as you said, every big software company saw their momentum, they want to get into it, they want to compete with them. So >>Well, to get to 5 billion, they've gotta accelerate growth. I mean, if you do 20% cer over the next, you know, through the end of the decade, they don't quite get there. So they're gonna have to, you know, they lowered their forecast out of the high 20 or mid twenties to 18%. They're gonna have to accelerate that. And we've seen that before. We see it in cloud where cloud, you know, accelerates growth even though you got the lower large numbers. Go ahead Dave. >>Yeah, so Daniel, then how do we, how do we think of this market? How do we measure the TAM for total addressable market for automation? I mean, you know, what's that? What's that metric that shows how unautomated are we, how inefficient are we? Is there a, is there a 5% efficiency that can be gained? Is there a 40% efficiency that can be gained? Because if you're talking about, you know, how much much of the market can UI path capture, first of all, how big is the market? And then is UI path poised to take advantage of that compared to the actual purveyors of the software that people are interacting with? I'm interacting with an E R p, an ER P system that has built into it the ability to automate processes. Then why do I need 'EM UI path? So first, how do you evaluate TAM? Second, how do you evaluate whether UI Path is gonna have a chance in this market where RPAs built into the applications that we actually use? Yeah, >>I think that TAM is evolving, and I don't have it in front of me right now, but what I'll tell you about the TAM is there's sort of the legacy RPA tam and then there's what I would sort of evolve to call the IPA and workflow automation tam that is being addressed by many of these software companies that you asked in the competitive equation. In the, in the, in the question, what we're seeing is a world where companies are gonna say, if we can automate it, we will automate it. That's, it's actually non-negotiable. Now, the process in the ability to a arrive at automation at scale has long been a battle front within the nor every organization. We've been able to automate things for a long time. Why has it more been done? It's the same thing with analytics. There's been numerous studies in analytics that have basically shown companies that have been able to embrace, adopt, and implement analytics, have significantly better performances, better performances on revenue growth, better performances and operational cost management, better performances with customer experience. >>Guess what? Not everybody, every company can get to this. Now there's a couple of things behind this and I'm gonna, I'm gonna try to close my answer out cause I'm getting a little long winded here. But the first thing is automation is a cultural challenge in most organizations. We've done endless research on companies digitally transforming and automating their business. And what we've found is largely the technology are somewhat comparable. Meaning, you know, I, I've heard what he is saying about some of the advantages of partnership with Microsoft, very compelling. But you know what, all these companies that have automation offerings, whether it's you know, through a Salesforce, Microsoft, whether it's a specialized rpa like an Automation Anywhere or a UI path, their solutions can be deployed and successful. The company's ability to take the investment, implement it successfully and get buy in across the organization tends to always be the hurdle. An old CIO stat, 50% of IT projects fail. That stat is still almost accurate today. It's not 50% of technology is bad, but those failures are because the culture doesn't get behind it. And automation's a tricky one because there's a lot of people that feel on the outside rather than the inside of an automation transformation. >>So, Andy, so how do you think about the, to Dave's question, the SAPs the service nows trying to, you know, at least take some red crumbs off the table. They, they're gonna, they're gonna create these automation stove pipes, but in Automation Anywhere or, or UI path is a horizontal play, are they not? And so how do you think about that progression? Well, so >>First of all, all of this other companies, when they, they, whether it's a build, acquire, what have you, these guys already have what, five, seven years on them. So it's gonna be difficult for them to catch up with the Center of Excellence knowledge on the use cases, what they got to catch up with them. That's gonna be a lot of catch up. Just to give you an idea, Microsoft Power Automate has been there for a while, right? They're supposedly doing well as well, but they still choose to partner with the UiPath as well to get them to the next level. So there's going to be competition coming from all areas, but it's, it's about, you know, highlights. >>So, so who is the competition? Is it Microsoft chipping away an individual productivity? Is it a service now? Who's got a platform play? Is it themselves just being able to execute >>All plus also, but I think the, the most, I wouldn't say competition, but it's more people are not aware of what areas need to be automated, right? For example, one of the things I was talking about with a couple of customers is, so they have a automation hub where you can put the, the process and and task that need to be automated and then you prioritize and start working on it. And, and almost all of them that I speak to, they keep saying that most of the process and task identification that they need to do for automation, it's manual right now. So, which means it's limited, you have to go and execute it. When people find out and tell you that's what need to be fixed, you try to go and fix that. But imagine if there is a way, I mean the have solutions they're showcasing now if it becomes popular, if you're able to identify tasks that are very inefficient or or process that's very inefficient, automatically score them up saying that, you know what, this is what is going to be ROI and you execute on it. That's going to be huge. So >>I think ts right, there's no shortage of, of a market. I would, I would agree with you Rob Sland this morning talked about the progression. He sort of compared it to e R P of the early days. I sort of have a love hate with E R P cuz of the complexity of the implementation and the, and the cost. However, first of all, a couple points and I love to get your thoughts for you. If you went back, I know 25 years, you, you wouldn't have been able to pick SAP out of a lineup and say that's gonna be the leader in E R P and they ended up, you know, doing really, really well. But the more interesting angle is if you could have figured out the customers that were implementing e r p in, in a really high quality fashion, those are the companies that really did well. You buy their stocks, they really took off cuz they were killing their other industry competitors. So, fast forward to automation. Will automation live up to its hype and your opinion, will it be as transformative and will the, the practitioners of automation see the same type of uplift in their markets, in their market caps, in their competitiveness as did sort of the early adopters and the excellent adopters of brp? What are your thoughts? Well, >>I think it's an interesting comparison. Maybe answer it slightly different way. I think the future is that automation is a non-negotiable in every enterprise organization. I think if you're a large organization, we have absolutely filled our, our organizations with waste too much overhead, too much expense, too much technical debt and automation is an answer. This is the way we want to interact, right? We want a chat bot that actually gives us good answers that can answer on a Tuesday at 11:00 PM at night when we want to know if the right dog food, you know, and I'm saying that, you know, that's what we want. That's the outcome we want. And businesses have to be driven by the outcome. Here's what I'm not sure about, Dave, is we have an era where over the last three to five years, a lot of products have become companies and a lot of 'EM products became companies ended up in public markets. >>And so the RPA space is one of those areas that got this explosive amount of growth. And you look at it and there's two ways. Is this horizontally a business rpa or is this going to be something that's gonna be a target of those Microsofts and those SAPs and say, Look, we need hyper automation to be deeply integrated at the E R P crm, hcm SCM level. We're gonna build by this or we're gonna build this. And you're already hearing it in the partnerships, but this is how I think the story ends. I I think either the companies like UiPath get much bigger, they get much more rounded in their, in their offerings. Or you're gonna have a large company like a Microsoft come in and say, you know what? Buy it rather >>Than build can they can, they can, can this company, maybe not so much here, but can a company like Automation Anywhere stay acquisition? Well, >>I use the, I use the Service now as an, as a parallel because they're a company that I thought would always end up inside of a bigger company and now you're like, I think they're too big. I think they've they've dropped >>That, that chart. Yeah, they're acquisition proof. I would agree. But these guys aren't yet Nora's automation. They work for >>A while and it's not necessarily a bad thing. Sometimes getting bit bought is good, but what I mean is it's gonna be core and these big companies know it cuz they're all talking >>About, but as independent analysts, we want to see independent companies. >>I wanna see the right thing. >>It just makes it fun. >>The right thing >>Customers. Yeah, but you know, okay, Oracle buy more customers, more >>Customers. >>I'm kidding. Yeah, I guess it's the right thing. It just makes it more fun when you have really good independent competitors that >>We >>Absolutely so, and, and spend way more on r and d than these big companies who spend a lot more on stock buyback. But I know you gotta go. Thanks so much for spending some time, making time for Cube Andy. Great to see you. Good to see as well. All right, we are wrapping up day one, Dave Blan and Dave Nicholson live. You can hear the action behind us, forward in five on the Cube, right back.

(electronic music) (background party chatter) >> All right. Hello, everyone. Welcome to The Cube. Coming up, Bryan Talebi will be here with Ahura A.I? >> Ahura A.I. >> Ahura A.I. Bryan Talebi here with Ahura A.I. We are at The Cube post party networking event, special on the ground, extended coverage. Bryan, we were at The Futurist, not The Futurist Conference, The Future of Blockchain which was the Monaco Crypto Summit over at the Grimaldi Center. Now we're at the VIP gala, the prince is here, a lot of action's happening. You had a chance to look all the presentations we have all the heavy hitters here, kind of a movement going on, right? >> Absolutely. Well, first of all, I think it's absolutely amazing that Prince Albert II put this all together. He obviously understands the future and understands technology. It's absolutely brilliance. And Julio as well, I mean is incredible. So I take off my hat to all the people that put this event together and the speakers were brilliant. I mean, did you see all the speakers the technologies that they've built have the potential to radically transform billions of people's lives. >> It's interesting, you know, I've been covering crypto for a very long time and watched it emerge and then start exploding. And there's always been, and I saw this with the web too early on, legit versus not legit. And all early markets have the hype cycles go down and up, and you always kind of have that but now you're starting to see legitimate tie-in between physical digital assets where, and the confluence of the business value, societal value, government value, all across the spectrum. Every vertical, every use case is got a decentralized vibe going on right now because it's a forcing function. And, and here in Monaco, the price and the king they're leaning into it cause I think they see the future because they could answer their legacy. >> Yeah. Absolutely. And look, you're absolutely right about this because this downturn that we're facing, especially this new crypto winter, I think is the best thing that could possibly have happened to the crypto space because what it's doing is pushing out the let's call them the less than honest brokers within the crypto community, the people that were just in it for a buck, the pump and dumpers and so forth it's really pushing those folks out. And the companies that remain are the true technologists that aren't looking at crypto as just a speculative asset, but rather an underlying technology that can transform the way that we engage with the world in a decentralized way. >> Bryan, you know, we didn't mention in the intro but you also do investment. >> I do. >> You also have a lot of things going on. You got a great history, great pedigree of seeing the waves of innovation the best. That's something, an investment question, like are you in it for the money or are you in it for the make it happen mission? That becomes kind of like the probing question. Someone comes to the table, "Hey, I need some cash. We do funding." What's your exit strategy? "I want to make an exit in two years." Okay. You're out. (Bryan laughs) (John) But it's almost that easy now, right? >> Sure. >> (John) To figure out who's in it for the money. >> Sure. >> (John) Who's in it for the mission. Yeah, the mission's successful. You make a lot of money. >> That's exactly right. Look, one of my mentors once taught me is, money like power is only amassed in great amount if indirectly sought because money by itself is not intrinsically a motivator. And so, what we do at our AB+ Ventures, my venture capital fund, is we only invest, not only in companies that are impact driven and have the capacity to impact a billion people, but we invest in founders that are climbing their third or fourth mountain. So these are people who've already made their money. They either had a couple big exits at over a hundred million dollars or they became rock stars or they became astronauts. They did things where they achieved the highest levels of achievement. And now are building technologies because they believe that they're going to impact the world in a meaningful way. >> They kind of know it's important, right? They made some money, they've been successful. They have scar tissue and experience to apply almost I want to say for the legacy of it, but more for value. >> Yeah. >> For everybody. >> Absolutely. >> All right. So I got to ask about what your current venture, I know you got some good action going on. It's growing pretty good. As they say in golf, it's middle of the fairway. It's growing, got momentum. It's a turbine market. You probably has some offers on the table. I mean, I could imagine all the AI you got going on. Blockchain, very attracted. It's a hard problem, but it's the first inning. Not even. >> Yeah. >> What going on with the company? >> We're very early. Look, we've been building our technologies, the deep tech platform we've been building for four and a half years. There's a whole bunch of offers on the table to buy us. But look, the reality is right now is a fantastic hiring opportunity. There's a lot of amazing talent out there that now wants to come to us, which is great. Number one, number two, if you look back to the 2000 Dot-com bubble, what you saw is all of the companies that didn't really solve real problems went away and it left a more oxygen in the room for the companies that were really solving problems that needed to be solved. And those are now all trillion dollar companies. So, >> Well, Brian, you and I both got a little gray hair. So let's talk about the Dot-com bubble. The other thing, I'll add to that, by the way great commentary, is that everything that was like bullshit actually happened. People bought pet food online, >> Right. >> Groceries delivered to their house. So to your point, the things actually happen. See the visions and the aspirations were correct, timing and capital markets spree. >> Sure. >> Is there similarities going on in crypto? Is it the crypto winter, weeding out those pretenders? Is that what you're saying? >> Well, there's definitely a lot of similarities there but if you look at the example that you use, right, pets.com versus Amazon, people are still buying pet food online. I buy all my pet supplies for my two puppies online. However, if you look at the reason that Amazon works is because of their supply chain and the innovations that they created on being able to deliver anything to you within a day or two days in an extremely cost effective manner. It wasn't just because they had a website and they did some hand wavy stuff to say isn't this a good idea. You actually have to have the underlying operational capability and innovation from a technology standpoint to make it happen. And so, when we talk about crypto over the past number of years, and I've been in the crypto space for a long time, as you have there's been a lot of hand wavy stuff. There's been a lot of people like, "wouldn't this be a good idea?" but then you have the true operators that are able to find the underlying competitive advantages that actually make it work. And that's what I'm interested in. >> I'd love to get your thoughts on that. First of all, great point if you look at like, I was just commentating earlier I was asked the question what I think, and I said, well, I do a lot of lot of reporting and analysis on cloud computing. I watch what Amazon Web Service has done from many, many years ago. And all the followers now. Scale data, higher level services, they're all happening and it's creating a lot of value. Okay? That's going to come to crypto. And so, okay, the dots aren't connected there yet, but you've got this, but one of the things that has proven to be a success criteria, ecosystems. When you have enabling technology like DigitalBits, for instance, is kind the main powering of this ecosystem here, the value that's being created on top of it has to be a step function or multiple of the cost or operational cost to deploy the platform. Okay, so that's kind of in concert with everyone else. You product decentralized, what's your thoughts on that? Because now you have a lot of potential ecosystems that could connect together cause there's no one centralized ecosystem. >> (Bryan) Absolutely. >> But what is, what, how do you get that? How do you square that circle? So to speak. What's your take on that? How does ecosystems play into defi, decentralization, de-apps blockchain? >> So what you really talking about is interoperable, right? So again, if we use an analogy, if we look back to the late nineties, when Web 1.0 was really flourishing and then in the 2000s where everybody created their own websites, people went to the world wide web, but every company had their own website. They had their own social media platform. They had their entire Salesforce platform or what have you. So everyone had their entire separate organization. And so, I suspect that the future of crypto is going to be very similar, where there's going to be a bunch of different metaverses, a bunch of different ecosystems, but someone's going to come along, and I think there's a number of people on the back end that are actually working on this, Some of them are really brilliant, that are going to create an interoperable mechanism for people that jump from metaverse to metaverse from chain to chain in a completely easy experience from a user experience standpoint where you don't have to have a PhD in crypto, so to speak, that doesn't exist, but you don't have to have that level. >> Well, if you're working on crypto for the past five years you've got a PhD. >> Basically. >> The thesis is, you're still alive producing. (Brian laughs) Well, that's a good point. So I'm looking for like, this defacto enabler, right? Because TCP/IP was an example in the old days, you know, the levels of the stack that never, TCP/IP is part of the OSI model. It's just interconnect. That layer, nothing got above it, was open. It was just hard and top that TCP/IP the rest was all standard. Ethernet, token ring add that data layer and then cards. That worked, the industry could galvanize around that. I'm waiting for the crypto moment now, where, what is going to be that cloud (indistinct), Kubernetes and service matches and whatnot. What, is there anything on the horizon that you see that has that kind of coalescent ecosystem, let's get, if we all get behind this, we all win. Rather than chasing crumbs. >> Sure. >> You know, the bigger pie, rising tide, all that stuff. >> Well, so I think there's a really interesting analogy from a couple of hundred years ago on this. So most people don't realize that when the United States first had their railroad system which was the innovative infrastructure play at the time each state or each region had their own systems they had different size railroad. So what would happen if you were trying to ship a bunch of grain from one part of the country to the other you would take it by a train. You get to a train station, you'd have to take everything off, put it on a different train, on a different set of train tracks. You would go a couple states over. You'd have to do that again, go a couple states over. You have to do that again. Eventually what happened is the federal government came in and said, hey, we need to create a system of policies around one set of rules for all trains and all logistics across the country. And so, I do think there's a role for governments to come together, along with the operators and the companies to work collaboratively together to say, hey, what are the regulations? What are the rules of the road? How do we make sure we get all the scam artists out of the system? How do we create a system that actually works for everybody? Now, there's always dangers there, right? You have regulatory capture. Sometimes the government, oftentimes they're slow, they don't understand the technology. So they come down with a heavy hand. And so if it's done properly, and it's not just the United States alone, by the way, it's all the countries in the world. Now at this point, it's a global effort. >> There's money involved, too. >> Exactly. But if we are able to bring together people that are much smarter than me from the public and private sectors as well as the nonprofit sectors, together to come up with one set of rules I think that will enable crypto to massively expand across the entire globe. >> What are you passionate about right now? I know you got the investment fund for, you know, helping society and the planet, you get your project with your startup company, AI is in a hot area. What's going on? What's your top goals for the year? >> So there's two things. Number one, my company, Ahura A.I. is my baby. It's where I spend 70, 80 hours a week. We invent a technology that enables people to learn three to five times faster than traditional education. >> (John) Is that so? >> Because I believe that education is the first step. It's the first variable, that impacts all of the sustainable development goals, impacts the world in a very real way. >> And you're not wearing your UA pin. >> I'm not wearing my pin, I always point to it. >> I wanted to grab it, I saw it earlier. >> But then the second thing I'm super focused on is existential risk. Look, so I throw a lot of events where I bring together four categories of people, CEOs of impact driven companies, investors, whether they're VCs or billionaires or family offices, global experts, and celebrities that want to use their influence for good in the world. And one of the speakers that I had at one of my events is a guy at Stanford who runs their lab on existential risk and what he told the group, and what he told me, is according to Stanford and all the researchers, there's a one in six chance that we're all going to go extinct by 2050. One in six, that's a dice roll. And so to me, the most important thing I can do is bring people together that have capacity, have resources, have capabilities, to address these drivers of existential risk because selfishly, I don't want to live in a dystopian Hellscape. >> Exactly, yeah. Bryan, thanks for coming on. We're going to get back into dinner. Great to see you. >> Thank you very much. >> The Cube after dark, extended hours. Look at us, we're going the whole day. VIP gala, Prince Albert, the team, DigitalBits, The Cube, all here at the Yacht Club in Monaco. I'm John Furrier. Thanks for watching.

(gentle music) >> Welcome everyone to theCUBE's presentation of the AWS Startup Showcase. The theme is Data as Code; The Future of Enterprise Data and Analytics. This is the season two, episode two of the ongoing series of covering the exciting startups in the AWS ecosystem around data analytics and cloud computing. I'm your host, John Furrier. Today we're joined by great guests here. Three guests. Wen Phan, who's a Director of Product Management at Ahana, Satyam Krishna, Engineering Manager at Blinkit, and we have Akshay Agarwal, Senior Engineer at Blinkit as well. We're going to get into the relationship there. Let's get into. We're going to talk about how Blinkit's using open data lake, data house with Presto on AWS. Gentlemen, thanks for joining us. >> Thanks for having us. >> So we're going to get into the deep dive on the open data lake, but I want to just quickly get your thoughts on what it is for the folks out there. Set the table. What is the open data lakehouse? Why it is important? What's in it for the customers? Why are we seeing adoption around this because this is a big story. >> Sure. Yeah, the open data lakehouse is really being able to run a gamut of analytics, whether it be BI, SQL, machine learning, data science, on top of the data lake, which is based on inexpensive, low cost, scalable storage. And more importantly, it's also on top of open formats. And this to the end customer really offers a tremendous range of flexibility. They can run a bunch of use cases on the same storage and great price performance. >> You guys have any other thoughts on what's your reaction to the lakehouse? What is your experience with it? What's going on with Blinkit? >> No, I think for us also, it has been the primary driver of how as a company we have shifted our completely delivery model from us delivering in one day to someone who is delivering in 10 minutes, right? And a lot of this was made possible by having this kind of architecture in place, which helps us to be more open-source, more... where the tools are open-source, we have an open table format which helps us be very modular in nature, meaning we can pick solutions which works best for us, right? And that is the kind of architecture that we want to be in. >> Awesome. Wen, you know last time we chat with Ahana, we had a great conversation around Presto, data. The theme of this episode is Data as Code, which is interesting because in all the conversations in these episodes all around developers, which administrators are turning into developers, there's a developer vibe with data. And with opensource, it's software. Now you've got data taking a similar trajectory as how software development was with code, but the people running data they're not developers, they're administrators, they're operators. Now they're turning into DataOps. So it's kind of a similar vibe going on with branches and taking stuff out of and putting it back in, and testing it. Datasets becoming much more stable, iterating on machine learning algorithm. This is a movement. What's your guys reaction before we get into the relationships here with you guys. But, what's your reaction to this Data as Code movement? >> Yeah, so I think the folks at Blinkit are doing a great job there. I mean, they have a pretty compact data engineering team and they have some pretty stringent SLAs, as well as in terms of time to value and reliability. And what that ultimately translates for them is not only flexibility but reliability. So they've done some very fantastic work on a lot of automation, a lot of integration with code, and their data pipelines. And I'm sure they can give the details on that. >> Yes. Satyam and Akshay, you guys are engineers' software, but this is becoming a whole another paradigm where the frontline coding and or work or engineer data engineering is implementing the operations as well. It's kind of like DevOps for data. >> For sure. Right. And I think whenever you're working, even as a software engineer, the understanding of business is equally important. You cannot be working on something and be away from business, right? And that's where, like I mentioned earlier, when we realized that we have to completely move our stack and start giving analytics at 10 minutes, right. Because when you're delivering in 10 minutes, your leaders want to take decisions in your real-time. That means you need to move with them. You need to move with business. And when you do that, the kind of flexibility these softwares give is what enables the businesses at the end of the day. >> Awesome. This is the really kind of like, is there going to be a book called agile data warehouses? I don't think so. >> I think so. (laughing) >> The agile cloud data. This is cool. So let's get into what you guys do. What is Blinkit up to? What do you guys do? Can you take a minute to explain the company and your product? >> Sure. I'll take that. So Blinkit is India's biggest 10 minute delivery platform. It pioneered the delivery model in the country with over 10 million Indian shopping on our platform, ranging from everything: grocery staples, vegetables, emergency services, electronics, and much more, right. It currently delivers over 200,000 orders every day, and is in a hurry to bring the future of farmers to everyone in India. >> What's the relationship with Ahana and Blinkit? Wen, what's the tie in? >> Yeah, so Blinkit had a pretty well formed stack. They needed a little bit more flexibility and control. They thought a managed service was the way to go. And here at Ahana, we provide a SaaS managed service for Presto. So they engaged us and they evaluated our offering. And more importantly, we're able to partner. As a early stage startup, we really rely on very strong partners with great use cases that are willing to collaborate. And the folks at Blinkit have been really great in helping us push our product, develop our product. And we've been very happy about the value that we've been able to deliver to them as well. >> Okay. So let's unpack the open data lakehouse. What is it? What's under the covers? Let's get into it. >> Sure. So if bring up a slide. Like I said before, it's really a paradigm on being able to run a gamut of analytics on top of the open data lake. So what does that mean? How did it come about? So on the left hand side of the slide, we are coming out of this world where for the last several decades, the primary workhorse for SQL based processing and reporting and dashboarding use cases was really the data warehouse. And what we're seeing is a shift due to the trends in inexpensive scalable storage, cloud storage. The proliferation of open formats to facilitate using this storage to get certain amounts of reliability and performance, and the adoption of frameworks that can operate on top of this cloud data lake. So while here at Ahana, we're primarily focused on SQL workloads and Presto, this architecture really allows for other types of frameworks. And you see the ML and AI side. And like to Satyam's point earlier, offers a great amount of flexibility modularity for many use cases in the cloud. So really, that's really the lakehouse, and people like it for the performance, the openness, and the price performance. >> How's the open-source open side of it playing in the open-source? It's kind of open formats. What is the open-source angle on this because there's a lot of different approaches. I'm hearing open formats. You know, you have data stores which are a big part of seeing that. You got SQL, you mentioned SQL. There's got a mishmash of opportunities. Is it all coexisting? Is it one tool to rule the world or is it interchangeable? What's the open-source angle? >> There's multiple angles and I'll let definitely Satyam add to what I'm saying. This was definitely a big piece for Blinkit. So on one hand, you have the open formats. And what really the open formats enable is multiple compute engines to work on that data. And that's very huge. 'Cause it's open, you're not locked in. I think the other part of open that is important and I think it was important to Blinkit was the governance around that. So in particular Presto is governed by the Linux Foundation. And so, as a customer of open-source technology, they want some assurances for things like how's it governed? Is the license going to change? So there's that aspect of openness that I think is very important. >> Yeah. Blinkit, what's the data strategy here with lakehouse and you guys? Why are you adopting this type of architecture? >> So adding to what... Yeah, I think adding to Wen said, right. When we are thinking in terms of all these OpenStacks, you have got these open table formats, everything which is deployed over cloud, the primary reason there is modularity. It's as simple as that, right. You can plug and play so many different table formats from one thing to another based on the use case that you're trying to serve, so that you get the most value out of data. Right? I'll give you a very simple example. So for us we use... not even use one single table format. It's not that one thing solves for everything, right? We use both Hudi and Iceberg to solve for different use cases. One is good for when you're working for a certain data site. Icebergs works well when you're in the SQL kind of interface, right. Hudi's still trying to reach there. It's going to go there very soon. So having the ability to plug and play different formats based on the use case helps you to grow faster, helps you to take decisions faster because you now you're not stuck on one thing. They will have to implement it. Right. So I think that's what it is great about this data lake strategy. Keeping yourself cost effective. Yeah, please. >> So the enablement is basically use case driven. You don't have to be rearchitecturing for use cases. You can simply plug can play based on what you need for the use case. >> Yeah. You can... and again, you can focus on your business use case. You can figure out what your business users need and not worry about these things because that's where Presto comes in, helps you stitch that data together with multiple data formats, give you the performance that you need and it works out the best there. And that's something that you don't get to with traditional warehouse these days. Right? The kind of thing that we need, you don't get that. >> I do want to add. This is just to riff on what Satyam said. I think it's pretty interesting. So, it really allowed him to take the best-of-breed of what he was seeing in the community, right? So in the case of table formats, you've got Delta, you've got Hudi, you've got Iceberg, and they all have got their own roadmap and it's kind of organic of how these different communities want to evolve, and I think that's great, but you have these end consumers like Blinkit who have different maybe use cases overlapping, and they're not forced to pick one. When you have an open architecture, they can really put together best-of-breed. And as these projects evolve, they can continue to monitor it and then make decisions and continue to remain agile based on the landscape and how it's evolving. >> So the agility is a key point. Flexibility and agility, and time to valuing with your data. >> Yeah. >> All right. Wen, I got to get in to why the Presto is important here. Where does that fit in? Why is Presto important? >> Yeah. For me, it all comes down to the use cases and the needs. And reporting and dashboarding is not going to go away anytime soon. It's a very common use case. Many of our customers like Blinkit come to us for that use case. The difference now is today, people want to do that particular use case on top of the modern data lake, on top of scalable, inexpensive, low cost storage. Right? In addition to that, there's a need for this low latency interactive ability to engage with the data. This is often arises when you need to do things in a ad hoc basis or you're in the developmental phase of building things up. So if that's what your need is. And latency's important and getting your arms around the problems, very important. You have a certain SLA, I need to deliver something. That puts some requirements in the technology. And Presto is a perfect for that ideal use case. It's ideal for that use case. It's distributed, it's scalable, it's in memory. And so it's able to really provide that. I think the other benefit for Presto and why we're bidding on Presto is it works well on the data lakes, but you have to think about how are these organizations maturing with this technology. So it's not necessarily an all or nothing. You have organizations that have maybe the data lake and it's augmented with other analytical data stores like Snowflake or Redshift. So Presto also... a core aspect is its ability to federate or connect and query across different data sources. So this can be a permanent thing. This could also be a transitionary thing. We have some customers that are moving and slowly shifting their data portfolio from maybe all data warehouse into 80% data lake. But it gives that optionality, it gives that ability to transition over a timeframe. But for all those reasons, the latency, the scalability, the federation, is why Presto for this particular use case. >> And you can connect with other databases. It can be purpose built database, could be whatever. Right? >> Sure. Yes, yes. Presto has a very pluggable architecture. >> Okay. Here's the question for the Blinkit team? Why did you choose Presto and what led you to Ahana? >> So I'll take this better, over this what Presto sits well in that reach is, is how it is designed. Like basically, Presto decouples your storage with the compute. Basically like, people can use any storage and Presto just works as a query engine for them. So basically, it has a constant connectors where you can connect with a real-time databases like Pinot or a Druid, along with your warehouses like Redshift, along with your data lake that's like based on Hudi or Iceberg. So it's like a very landscape that you can use with the Presto. And consumers like the analytics doesn't need to learn the SQL or different paradigms of the querying for different sources. They just need to learn a single source. And, they get a single place to consume from. They get a single consumer on their single destination to write on also. So, it's a homologous architecture, which allows you to put a central security like which Presto integrates. So it's also based on open architecture, that's Apache engine. And it has also certain innovative features that you can see based on caching, which reduces a lot of the cost. And since you have further decoupled your storage with the compute, you can further reduce your cost, because now the biggest part of our tradition warehouse is a storage. And the cost goes massively upwards with the amount of data that you've added. Like basically, each time that you add more data, you require more storage, and warehouses ask you to write the data in their own format. Over here since we have decoupled that, the storage cost have gone down. It's literally that your cost that you are writing, and you just pay for the compute, and you can scale in scale out based on the requirements. If you have high traffic, you scale out. If you have low traffic, you scale in. So all those. >> So huge cost savings. >> Yeah. >> Yeah. Cost effectiveness, for sure. >> Cost effectiveness and you get a very good price value out of it. Like for each query, you can estimate what's the cost for you based on that tracking and all those things. >> I mean, if you think about the other classic Iceberg and what's under the water you don't know, it's the hidden cost. You think about the tooling, right, and also, time it takes to do stuff. So if you have flexibility on choice, when we were riffing on this last time we chatted with you guys and you brought it up earlier around, you can have the open formats to have different use cases in different tools or different platforms to work on it. Redshift, you can use Redshift here, or use something over there. You don't have to get locking >> Absolutely. >> Satyam & Akshay: Yeah. >> Locking is a huge problem. How do you guys see that 'cause sounds like here there's not a lot of locking. You got the open formats, and you got choice. >> Yeah. So you get best of the both worlds. Like you get with Ahana or with the Presto, you can get the best of the both worlds. Since it's cloud native, you can easily deploy your clusters very easily within like five minutes. Your cluster is up, you can start working on it. You can deploy multiple clusters for multiple teams. You get also flexibility of adding new connectors since it's open and further it's also much more secure since it's based on cloud native. So basically, you can control your security endpoints very well. So all those things comes in together with this architecture. So you can definitely go more on the lakehouse architecture than warehousing when you want to deliver data value faster. And basically, you get the much more high value out of your data in a sorted template. >> So Satyam, it sounds like the old warehousing was like the application person, not a lot of usage, old, a lot of latency. Okay. Here and there. But now you got more speed to deploy clusters, scale up scale down. Application developers are as everyone. It's not one person. It's not one group. It's whenever you want. So, you got speed. You got more diversity in the data opportunities, and your coding. >> Yeah. I think data warehouses are a way to start for every organization who is getting into data. I don't think data warehousing is still a solution and will be a solution for a lot of teams which are still getting into data. But as soon as you start scaling, as you start seeing the cost going up, as you start seeing the number of use cases adding up, having an open format definitely helps. So, I would say that's where we are also heading into and that's how our journey as well started with Presto as well, why we even thought about Ahana, right. >> (John chuckles) >> So, like you mentioned, one of the things that happened was as we were moving to the lakehouse and the open table format, I think Ahana is one of the first ones in the market to have Hudi as a first class citizen completely supported with all the things which are not even present at the time of... even with Presto, right. So we see Ahana working behind the scenes, improving even some of the things already over the open-source ecosystem. And that's where we get the most value out of Ahana as well. >> This is the convergence of open-source magic and commercialization. Wen, because you think about Data as Code, reminds me, I hear, "Data warehouse, it's not going to go away." But you got cloud scale or scale. It reminds me of the old, "Oh yeah, I have a data center." Well, here comes the cloud. So, doesn't really kill the data center, although Amazon would say that the data center's going to be eliminated. No, you just use it for whatever you need it for. You use it for specific use cases, but everyone, all the action goes to the cloud for scale. The same things happen with data, and look at the open-source community. It's kind of coming together. Data as Code is coming together. >> Yeah, absolutely. >> Absolutely. >> I do want to again to connect on another dot in terms of cost and that. You know, we've been talking a little bit about price performance, but there's an implicit cost, and I think this was also very important to Blinkit, and also why we're offering a managed service. So one piece of it. And it really revolves around the people, right? So outside of the technology, the performance. One thing that Akshay brought up and it's another important piece that I should have highlighted a little bit more is, Presto exposes the ability to interact your data in a widely adopted way, which is basically ANSI SQL. So the ability for your practitioners to use this technology is huge. That's just regular Presto. In terms of a managed service, the guys at Blinkit are a great high performing team, but they have to be very efficient with their time and what they manage. And what we're trying to do is provide leverage for them. So take a lot of the heavy lifting away, but at the same time, figuring out the right things to expose so that they have that same flexibility. And that's been the balancing point that we've been trying to balance at Ahana, but that goes back to cost. How do I total cost of ownership? And that not doesn't include just the actual querying processing time, but the ability for the organization to go ahead and absorb the solution. And what does it cost in terms of the people involved? >> Yeah. Great conversation. I mean, this brings up the question of back in the data center, the cloud days, you had the concept of an SRE, which is now popular, site reliability engineer. One person does all the clusters and manages all the scale. Is the data engineer the new SRE for data? Are we seeing a similar trajectory? Just want to get your reaction. What do you guys think? >> Yes, so I would say, definitely. It depends on the teams and the sizes of that. We are high performing team so each automation takes bits on the pieces of the architecture, like where they want to invest in. And it comes out with the value of the engineer's time and basically like how much they can invest in, how much they need to configure the architecture, and how much time it'll take to time to market. So basically like, this is what I would also highlight as an engineer. I found Ahana like the... I would say as a Presto in a cloud native environment, or I think so there's the one in the market that seamlessly scales and then scales out. And further, with a team of us, I would say our team size like three to four engineers managing cluster day in day out, conferring, tuning and all those things takes a lot of time. And Ahana came in and takes it off our plate and the hands in a solution which works out of box. So that's where this comes in. Ahana it's also based on open-source community. >> So the time of the engineer's time is so valuable. >> Yeah. >> My take on it really in terms of the data engineering being the SRE. I think that can work, it depends on the actual person, and we definitely try to make the process as easy as possible. I think in Blinkit's case, you guys are... There are data platform owners, but they definitely are aware of the pipelines. >> John: Yeah. >> So they have very intimate knowledge of what data engineers do, but I think in their case, you guys, you're managing a ton of systems. So it's not just even Presto. They have a ton of systems and surfacing that interface so they can cater to all the data engineers across their data systems, I think is the big need for them. I know you guys you want to chime in. I mean, we've seen the architecture and things like that. I think you guys did an amazing job there. >> So, and to adding to Wen's point, right. Like I generally think what DevOps is to the tech team. I think, what is data engineer or the data teams are to the data organization, right? Like they play a very similar role that you have to act as a guardrail to ensure that everyone has access to the data so the democratizing and everything is there, but that has to also come with security, right? And when you do that, there are (indistinct) a lot of points where someone can interact with data. We have... And again, there's a mixed match of open-source tools that works well, as well. And there are some paid tools as well. So for us like for visualization, we use Redash for our ad hoc analysis. And we use Tableau as well whenever we want to give a very concise reporting. We have Jupyter notebooks in place and we have EMRs as well. So we always have a mixed batch of things where people can interact with data. And most of our time is spent in acting as that guardrail to ensure that everyone should have access to data, but it shouldn't be exploited, right. And I think that's where we spend most of our time in. >> Yeah. And I think the time is valuable, but that your point about the democratization aspect of it, there seems to be a bigger step function value that you're enabling and needs to be talked out. The 10x engineer, it's more like 50x, right? If you get it done right, the enablement downstream at the scale that we're seeing with this new trend is significant. It's not just, oh yeah, visualization and get some data quicker, there's actually real advantages on a multiple with that engineering. So, and we saw that with DevOps, right? Like, you do this right and then magic happens on the edges. So, yeah, it's interesting. You guys, congratulations. Great environment. Thanks for sharing the insight Blinkit. Wen, great to see you. Ahana again with Presto, congratulations. The open-source meets data engineering. Thanks so much. >> Thanks, John. >> Appreciate it. >> Okay. >> Thanks John. >> Thanks. >> Thanks for having us. >> This season two, episode two of our ongoing series. This one is Data as Code. This is theCUBE. I'm John furrier. Thanks for watching. (gentle music)

(upbeat music) >> Hey everyone. Welcome to theCUBE's presentation of the AWS Startup Showcase. This is Data as Code, The Future of Enterprise Data and Analytics. This is also season two, episode two of our ongoing series with exciting partners from the AWS ecosystem who are here to talk with us about data and analytics. I'm your host, Lisa Martin. Two guests join me, one, a cube alumni. Venkat Venkataramani is here CEO & Co-Founder of Rockset. Good to see you again. And Doug Moore, VP of cloud platforms at Command Alkon. You're here to talk to me about how Command Alkon implemented real time analytics in just days with Rockset. Guys, welcome to the program. >> Thanks for having us. >> Yeah, great to be here. >> Doug, give us a little bit of a overview of Command Alkon, what type of business you are? what your mission is? That good stuff. >> Yeah, great. I'll pref it by saying I've been in this industry for only three years. The 30 years prior I was in financial services. So this was really exciting and eye opening. It actually plays into the story of how we met Rockset. So that's why I wanted to preface that. But Command Alkon is in the business, is in the what's called The Heavy Building Materials Industry. And I had never heard of it until I got here. But if you think about large projects like building buildings, cities, roads anything that requires concrete asphalt or just really big trucks, full of bulky materials that's the heavy building materials industry. So for over 40 years Command Alkon has been the north American leader in providing software to quarries and production facilities to help mine and load these materials and to produce them and then get them to the job site. So that's what our supply chain is, is from the quarry through the development of these materials, then out to the to a heavy building material job site. >> Got it, and now how historically in the past has the movement of construction materials been coordinated? What was that like before you guys came on the scene? >> You'll love this answer. So 'cause, again, it's like a step back in time. When I got here the people told me that we're trying to come up with the platform that there are 27 industries studied globally. And our industry is second to last in terms of automation which meant that literally everything is still being done with paper and a lot of paper. So when one of those, let's say material is developed, concrete asphalt is produced and then needs to get to the job site. They start by creating a five part printed ticket or delivery description that then goes to multiple parties. It ends up getting touched physically over 50 times for every delivery. And to give you some idea what kind of scale it is there are over 330 million of these type deliveries in north America every year. So it's really a lot of favor and a lot of manual work. So that was the state of really where we were. And obviously there are compelling reasons certainly today but even 3, 4, 5 years ago to automate that and digitize it. >> Wow, tremendous potential to go nowhere but up with the amount of paper, the lack of, of automation. So, you guys Command Alkon built a platform, a cloud software construction software platform. Talk to me of about that. Why you built it, what was the compelling event? I mean, I think you've kind of already explained the compelling event of all the paper but give us a little bit more context. >> Yeah. That was the original. And then we'll get into what happened two years ago which has made it even more compelling but essentially with everything on premises there's really in a huge amount of inefficiency. So, people have heard the enormous numbers that it takes to build up a highway or a really large construction project. And a lot of that is tied up in these inefficiencies. So we felt like with our significant presence in this market, that if we could figure out how to automate getting this data into the cloud so that at least the partners in the supply chain could begin sharing information. That's not on paper a little bit closer to real time that we could make has an impact on everything from the timing it takes to do a project to even the amount of carbon dioxide that's admitted, for example from trucks running around and being delayed and not being coordinated well. >> So you built the connect platform you started on Amazon DynamoDB and ran into some performance challenges. Talk to us about the, some of those performance bottlenecks and how you found Venkat and Rockset. >> So from the beginning, we were fortunate, if you start building a cloud three years ago you're you have a lot of opportunity to use some of the what we call more fully managed or serverless offerings from Amazon and all the cloud vendors have them but Amazon is the one we're most familiar with throughout the past 10 years. So we went head first into saying, we're going to do everything we can to not manage infrastructure ourselves. So we can really focus on solving this problem efficiently. And it paid off great. And so we chose dynamo as our primary database and it still was a great decision. We have obviously hundreds of millions of billions of these data points in dynamo. And it's great from a transactional perspective, but at some point you need to get the data back out. And what plays into the story of the beginning when I came here with no background basically in this industry, is that, and as did most of the other people on my team, we weren't really sure what questions were going to be asked of the data. And that's super, super important with a NoSQL database like dynamo. You sort of have to know in advance what those usage patterns are going to be and what people are going to want to get back out of it. And that's what really began to strain us on both performance and just availability of information. >> Got it. Venkat, let's bring you into the conversation. Talk to me about some of the challenges that Doug articulated the, is industry with such little automation so much paper. Are you finding that still out there for in quite a few industries that really have nowhere to go but up? >> I think that's a very good point. We talk about digital transformation 2.0 as like this abstract thing. And then you meet like disruptors and innovators like Doug, and you realize how much impact, it has on the real world. But now it's not just about disrupting, and digitizing all of these records but doing it at a faster pace than ever before, right. I think this is really what digital transformation in the cloud really enable tools you do that, a small team in a, with a very very big mission and responsibility like what Doug team have been, shepherding here. They're able to move very, very, very fast, to be able to kind of accelerate this. And, they're not only on the forefront of digitizing and transforming a very big, paper-heavy kind of process, but real-time analytics and real time reporting is a requirement, right? Nobody's wondering where is my supply chain three days ago? Are my, one of the most important thing in heavy construction is to keep running on a schedule. If you fall behind, there's no way to catch up because there's so many things that falls apart. Now, how do you make sure you don't fall behind, realtime analytics and realtime reporting on how many trucks are supposed to be delivered today? Halfway through the day, are they on track? Are they getting behind? And all of those things is not just able to manage the data but also be able to get reporting and analytics on that is a extremely important aspect of this. So this is like a combination of digital transformation happening in the cloud in realtime and realtime analytics being in the forefront of it. And so we are very, very happy to partner with digital disruptors like Doug and his team to be part of this movement. >> Doug, as Venkat mentioned, access to real time data is a requirement that is just simple truth these days. I'm just curious, compelling event wise was COVID and accelerator? 'Cause we all know of the supply chain challenges that we're all facing in one way or the other, was that part of the compelling event that had you guys go and say, we want to do DynamoDB plus Rockset? >> Yeah, that is a fantastic question. In fact, more so than you can imagine. So anytime you come into an industry and you're going to try to completely change or revolutionize the way it operates it takes a long time to get the message out. Sometimes years, I remember in insurance it took almost 10 years really to get that message out and get great adoption and then COVID came along. And when COVID came along, we all of a sudden had a situation where drivers and the foreman on the job site didn't want to exchange the paperwork. I heard one story of a driver taping the ticket for signature to the foreman on a broomstick and putting it out his windows so that he didn't get too close. It really was that dramatic. And again, this is the early days and no one really has any idea what's happening and we're all working from home. So we launched, we saw that as an opportunity to really help people solve that problem and understand more what this transformation would mean in the long term. So we launched internally what we called Project Lemonade obviously from, make lemonade out of lemons, that's the situation that we were in and we immediately made some enhancements to a mobile app and then launched that to the field. So that basically there's now a digital acceptance capability where the driver can just stay in the vehicle and the foreman can be anywhere, look at the material say it's acceptable for delivery and go from there. So yeah, it made a, it actually immediately caused many of our customers hundreds to begin, to want to push their data to the cloud for that reason just to take advantage of that one capability >> Project lemonade, sounds like it's made a lot of lemonade out of a lot of lemons. Can you comment Doug on kind of the larger trend of real time analytics and logistics? >> Yeah, obviously, and this is something I didn't think about much either not knowing anything about concrete other than it was in my driveway before I got here. And that it's a perishable product and you've got that basically no more than about an hour and a half from the time you mix it, put it in the drum and get it to the job site and pour it. And then the next one has to come behind it. And I remember I, the trend is that we can't really do that on paper anymore and stay on top of what has to be done we'll get into the field. So a foreman, I recall saying that when you're in the field waiting on delivery, that you have people standing around and preparing the site ready to make a pour that two minutes is an eternity. And so, working a real time is all always a controversial word because it means something different to anyone, but that gave it real, a real clarity to mean, what it really meant to have real time analytics and how we are doing and where are my vehicles and how is this job performing today? And I think that a lot of people are still trying to figure out how to do that. And fortunately, we found a great tool set that's allowing us to do that at scale. Thankfully, for Rockset primarily. >> Venkat talk about it from your perspective the larger trend of real time analytics not just in logistics, but in other key industries. >> Yeah. I think we're seeing this across the board. I think, whether, even we see a huge trend even within an enterprise different teams from the marketing team to the support teams to more and more business operations team to the security team, really moving more and more of their use cases from real time. So we see this, the industries that are the innovators and the pioneers here are the ones for whom real times that requirement like Doug and his team here or where, if it is all news, it's no news, it's useless, right? But I think even within, across all industries, whether it is, gaming whether it is, FinTech, Bino related companies, e-learning platforms, so across, ed tech and so many different platforms, there is always this need for business operations. Some, certain aspects certain teams within large organizations to, have to tell me how to win the game and not like, play Monday morning quarterback after the game is over. >> Right, Doug, let's go back at you, I'm curious with connects, have you been able to scale the platform since you integrated with Rockset? Talk to us about some of the outcomes that you've achieved so far? >> Yeah, we have, and of course we knew and we made our database selection with dynamo that it really doesn't have a top end in terms of how much information that we can throw at it. But that's very, very challenging when it comes to using that information from reporting. But we've found the same thing as we've scaled the analytics side with Rockset indexing and searching of that database. So the scale in terms of the number of customers and the amount of data we've been able to take on has been, not been a problem. And honestly, for the first time in my career, I can say that we've always had to add people every time we add a certain number of customers. And that has absolutely not been the case with this platform. >> Well, and I imagine the team that you do have is far more, sorry Venkat, far more strategic and able to focus on bigger projects. >> It, is, and, you've amazed at, I mean Venkat hit on a couple of points that it's in terms of the adoption of analytics. What we found is that we are as big a customer of this analytic engine as our customers are because our marketing team and our sales team are always coming to us. Well how many customers are doing this? How many partners are connected in this way? Which feature flags are turned on the platform? And the way this works is all data that we push into the platform is automatically just indexed and ready for reporting analytics. So we really it's no additional ad of work, to answer these questions, which is really been phenomenal. >> I think the thing I want to add here is the speed at which they were able to build a scalable solution and also how little, operational and administrative overhead that it has cost of their teams, right. I think, this is again, realtime analytics. If you go and ask hundred people, do you want fast analytics on realtime data or slow analytics on scale data, people, no one would say give me slow and scale. So, I think it goes back to again our fundamental pieces that you have to remove all the cost and complexity barriers for realtime analytics to be the new default, right? Today companies try to get away with batch and the pioneers and the innovators are forced to solve, I know, kind of like address some of these realtime analytics challenges. I think with the platforms like the realtime analytics platform, like Rockset, we want to completely flip it on its head. You can do everything in real time. And there may be some extreme situations where you're dealing with like, hundreds of petabytes of data and you just need an analyst to generate like, quarterly reports out of that, go ahead and use some really, really good batch base system but you should be able to get anything, and everything you want without additional cost or complexity, in real time. That is really the vision. That is what we are really enabling here. >> Venkat, I want to also get your perspective and Doug I'd like your perspective on this as well but that is the role of cloud native and serverless technologies in digital disruption. And what do you see there? >> Yeah, I think it's huge. I think, again and again, every customer, and we meet, Command Alkon and Doug and his team is a great example of this where they really want to spend as much time and energies and calories that they have to, help their business, right? Like what, are we accomplishing trying to accomplish as a business? How do we enable, how do we build better products? How do we grow revenue? How do we eliminate risk that is inherent in the business? And that is really where they want to spend all of their energy not trying to like, install some backend software, administer build IDL pipelines and so on and so forth. And so, doing serverless on the compute side of that things like AWS lambda does and what have you. And, it's a very important innovation but that isn't, complete the story or your data stack also have to become serverless. And, that is really the vision with Rockset that your entire realtime analytics stack can be operating and managing. It could be as simple as managing a serverless stack for your compute environments like your APS servers and what have you. And so I think that is going to be a that is for here to stay. This is a path towards simplicity and simplicity scales really, really well, right? Complexity will always be the killer that'll limit, how far you can use this solution and how many problems can you solve with that solution? So, simplicity is a very, very important aspect here. And serverless helps you, deliver that. >> And Doug your thoughts on cloud native and serverless in terms of digital disruption >> Great point, and there are two parts to the scalability part. The second one is the one that's more subtle unless you're in charge of the budget. And that is, with enough effort and enough money that you can make almost any technology scale whether it's multiple copies of it, it may take a long time to get there but you can get there with most technologies but what is least scalable, at least that I as I see that this industry is the people, everybody knows we have a talent shortage and these other ways of getting the real time analytics and scaling infrastructure for compute and database storage, it really takes a highly skilled set of resources. And the more your company grows, the more of those you need. And that is what we really can't find. And that's actually what drove our team in our last industry to even go this way we reached a point where our growth was limited by the people we could find. And so we really wanted to break out of that. So now we had the best of both scalable people because we don't have to scale them and scalable technology. >> Excellent. The best of both worlds. Isn't it great when those two things come together? Gentlemen, thank you so much for joining me on "theCUBE" today. Talking about what Rockset and Command Alkon are doing together better together what you're enabling from a supply chain digitization perspective. We appreciate your insights. >> Great. Thank you. >> Thanks, Lisa. Thanks for having us. >> My pleasure. For Doug Moore and Venkat Venkatramani, I'm Lisa Martin. Keep it right here for more coverage of "theCUBE", your leader in high tech event coverage. (upbeat music)

(energetic music) >> Hello, welcome to the CUBE's coverage of Boomi's Out of This World event. I'm John Furrier, host of theCUBE. We've got two great guests here, Chris McNabb, CEO of Boomi, and Ed Macosky, SVP and Head of Products, talking about hyper automation and the future of connectivity. Gentlemen, thank you for coming on theCUBE, great to see you. >> John, it is great to see you again as well. Looking forward to the next in-person one. >> I miss the in-person events, you guys have had great events and a lot of action happening. Love the big news of going out on your own direction, big financing, change of control, all that good stuff happening, industries growing. Chris, this is a big move. You know, the industry is changing. Can you give us some context to, you know, what's going on in automation and connectivity, because iPaaS, which you guys have pioneered, have been a big part of Cloud and CloudScale, and now we're seeing next-generation things happening. Data, automation, edge, modern application development, all happening. Set some context, what's going on? >> Yeah John, listen, it's a great time to be in our space at this point in time. Our customers, at the end of the day, are looking to create what we announced at last year's thing, called Integrated Experiences, which is the combination of user engagement, more awesome connectivity, and making sure high quality data goes through that experience, and providing 21st century experiences. And we're right at the heart of that work. Our platform really drives all the services that are needed there. But what our customers really need and what we're here to focus on today, that this world is to make sure that we have the world's best cut connectivity capabilities, and process automation engagement of constituents to really do what they want to do, where they want to do it. >> So a lot of big moves happening, what's the story? Take us through the story. I mean, you guys have a transaction with big sum financing, setting up this intelligence connectivity and automation approach. Take us through the story, what happened? >> Yeah. So, you know, the lead business was sold outside of Dell and that deal closed. We are now owned by two top tier private equity firms, FP and TPG. That sale is completed and now we are ready to unleash the Boomi business on this market. I think it's a great, it's a great transaction for Dell, and it's a great transaction for FP, PTG but most specifically, it's really a world-class transaction for the Boomi business, the Boomi customer base, as well as the Boomi employee. So I really looked at this as a win-win-win and sets us up for really going after this one. >> Yeah, and there's a huge wave coming and you're seeing like the, the big wave coming. It's just like, no need to debate it. It's here. It's cloud 2.0, whatever you want to call it, it's scale. IT has completely figured out, that not only is replatforming the cloud, but you got to be in the cloud refactoring. This is driving the innovation. And, this is really I see where you guys are leading. So share with me what is hyper automation? What is that actually mean? >> So what hyper automation really is, is intelligent connectivity automation. So our customers have been doing this. It's very specifically related to taking workflows, taking automation within the business. That's been around for a long time anyway, but adding AI and ML to it. So, as you continue to automate your business, you're getting more and more steam, and you get more and more productivity out of the (mumbles) organization or productivity from the (mumbles). >> So Chris, tell us more about this hyper automation, because you guys have a large install base. Take us through some of the numbers of the customer base, and where the dots are connecting as they look at the new IT landscape as it transforms. >> Yeah. John, great question. You know, when I talk to, you know as many of our 18,000 customers worldwide as I can get to, you know, what they are saying very clearly is their IT news feed is getting more complicated, more distributed, more siloed, and it has more data. And as you work through that problem, what they're trying to accomplish, is they're trying to engage their constituents in a 21st century web, however they want, whether it be mobile web, portals, chat bots, old fashioned telephones. And in doing that, that complicated area is extraordinarily difficult. So that's the pervasive problem that Boomi is purpose-built to help solve. And our customers start out sometimes with just great connectivity. Hyper automation is where the real value comes in. That's where your constituents see a complete difference in how I inter-operate with (mumbles). >> So, first of all, I love the word hyper automation because it reminds me of hyper scale, which, you know, look at the Amazons and the cloud players. You know, that kind of game has kind of evolved. I mean, the old joke is what inning are we in, right? And, and I, to use a baseball metaphor, I think it's a doubleheader and game one is won by the cloud. Right? So, Amazon wins game one, game two is all about data. You guys, this is core to Boomi and I want to get your thoughts on this because data is the competitive advantage. But if you look at the pandemic and the stories that we're reporting on, and this reinvent specifically, that'll be a big story. The refactoring in the cloud is a big strategic effort, not just replatforming, refactoring in the cloud. So this is really where you guys are, I think, skating where the puck is. Am I getting it right, can you just share that vision? >> Yeah, John. From a vision perspective, I think the pandemic has really accelerated people's expectations. You know what we need to be more nimble, more flexible. And because they had a fair amount in the Cloud they have to understand what is the next tier, what is the next generation offerings that we put together tie together and connect. That is not only connecting systems, apps, databases, and clouds. You're connecting people, processes and devices. So we're going to have a great story here and out of this world about how we connect bio centric vest to a video system who a network monitoring hub to protect the officer's safety in Amsterdam in real-time. We can deploy officers to location all automatic. All decisions are automatic, all locations, cameras (mumbles) all automatically. And that's only possible, when we think about next generation technology that Boomi provides. Next generation capabilities by the other providers in that solution. >> Ed, before we get to the product announcements for the even, we'll get your reaction to that. I see in the cloud you can refactor, you got data, you got latency issues. These are all kind of go away when you start thinking about integrating it altogether. What's your reaction to refactoring as the next step? >> Yeah. So my regular, I mean, exactly what Chris said, but as our customers are moving to the cloud, they're not choosing any more, just one cloud. It is a multi-cloud it's multidimensional (mumbles), you got multi-cloud, you got hybrid cloud, you have edge devices, et cetera. And our technology just naturally puts this in the space to do that. And based on what we see with our customers, we actually have, we've connected over 189,000 different devices, application points, data endpoints, et cetera to people. And we're seeing that growth of 44% year on year. So, we're seeing that explosion in helping customers, and we just want to accelerate that, and help them react to these changes as quickly as they possibly can. And a lot of it doesn't require, you know, massive upload project technology. We've been lucky enough to be visionaries that with our deployment technology, being able to embrace this new environment that's coming up or we're right at the forefront of this (mumbles). >> Yeah. I love the intelligence saying, I love hyper automation. Okay, let's get into the product announcements of Out of This World event. What are some of the announcements, and share with us the key highlights. >> Yeah. So first and foremost, we've announced a vision in our tactic. So I talked about the 189,000 applications that we did data endpoints, et cetera, that our customers are picking today. And they're moving very, very rapidly with that and it's no longer about name, connections, and having these fixed auxiliary that connects to applications you need to be able to react intelligently, pick the next endpoint and connect very quickly and bring that into your ecosystem. So we've got this vision towards the connectivity service that we're working on that will basically normalize that connectivity across all of the applications that are plugging into Boomi's iPaaS ecosystem and allow customers to get up and running very quickly. So I'm really excited about that. The other thing we announced is Boomi event streams. So in order to complete this, we can't just, we've been on this EDA journey Event-Driven Architecture for the last couple of years, and embracing an open ecosystem. But we found that in order to go faster for our customers, it's very, very important that we bring this into Boomi's iPaaS platform. Our partnerships in this area are still very important for us. But there is an avenue that our customers are demanding that, "hey, bring us into your platform." And we need to move faster with this, and our new Boomi event streams will allow them to do that. We also recently just announced the Boomi Discover Catalog. So this is the, this is an ongoing vision us. We're, building up into a marketplace where customers and partners can all participate, whether it's inside of a customer's ecosystem or partners, or Boomi, et cetera, offering these quick onboarding solutions for their customers. So we will learn intelligently as people have these solutions to help customers onboard, and build, and connect to these systems faster. So that's kind of how they all come together for us In a hyper automation scenario the last thing too, is we are working on RPA as a last mile connectivity that's where we start RPAs today, you know, gone are going to be the days of having RPA at a desktop perspective where you have to have someone manually run that. Although its RPA our runtime technology extends the desktops anyway. So we are going to bring RPA technology into the IPaaS platform as we move forward here so that our customers can enjoy the benefits of that as well. >> That's real quick. It was going to ask about the fence stream. I love this RPA angle. Tell me more about how that impacts is that's that's what I think, pretty big what's the impact of when you bring robotic processes on our RPA into iPaaS, what's the, what's the impact of the customer? >> The impact of the customer is that we believe that customers can really enjoy true cloud when it comes to RPA technology today, most of the RPA technologies, like I said, are deployed at a desktop and they are, they are manually run by some folks. It helps speed up the business user and adds some value there. But our technology will surely bring it to the cloud and allow that connectivity of what an arm robotic process automation solution will be doing and can tap into the iPaaS ecosystem and extend and connect that data up into the cloud or even other operating systems that the customer (mumbles). >> Okay. So on the event streams that you did, you guys announced, obviously it's the best part of the embedded event driven architecture, You guys have been part of. What is, why is it important for customers? Can you just take a minute to explain why event streams and why event driven approaches are important. >> Because customers need access to the data real time. So, so there's two reasons why it's very important to the customers one is Event Driven Architectures are on the rise, in order to truly scale up an environment. If you're talking tens of millions of transactions, you need to have an Event Driven Architecture in place in order to manage that state. So you don't have any message loss or any of those types of things. So it's important that we continue to invest as we continue to scale on our customers and they scale up their environments with us. The other reason it is very important for us to bring it into our ecosystem, within our platform is that our customers enjoy the luxury of having an integrated experience themselves as they're building, you know, intelligent connectivity and automation solutions within our platform. So to ask a customer, to go work with a third party technology versus enjoying it in an integrated experience itself is why we want to bring it in and have them get their (mumbles) much faster. >> I really think you guys are onto something because it's a partnership world. Ecosystems are now everywhere. There's ecosystems, because everything's a platform now that's evolving from tools to platforms and it's not a one platform rules the world. This is the benefit of how the clouds emerging, almost a whole nother set of cloud capabilities. I love this vision and you start to see that, and you guys did talk about this thing called conductivity marketplace. And what is that? Is that a, is that a place where people are sharing instead of partnershipping? I know there's a lot of partners are connected with each other and they want to have it all automated. How does this all play in? Can you just quickly explain that? >> Yeah, so in the last year we launched and we actually launched open source community around connectors and that sort of thing we invested pretty heavily in RSDK. We see quite a big uptake in the ecosystem of them building specific connectors, as well as solution. And our partners were very excited about partnering with us and (mumbles) to markets and those sorts of things that they can offer solutions to their customers on a marketplace. So, so we are reacting to the popular demand that we have from our partners and customers where they say, Hey, we'd love to participate in this marketplace. We'd love to be able to work with you and publish solutions that we're delivering more customers. So, so we're, we're fulfilling that mission on behalf of our customers and partners. >> You know, Chris, when you look at the cloud native ecosystem at the high level, you're seeing opensource driving a big part of it, large enterprises, large customers are moving to that next level of modern application development. They're partnering, right? They're going to out, outsource and partner some, some edge components, maybe bring someone else over here, have a supplier everything's confide now in the cloud, AKA dev ops meets, you know, business logic. So this seems to be validated. How do you see this evolving? How does this iPaaS kind of environment just become the environment? I mean, it seems to me that that's what's happening. What's your reaction to the, to that trend? >> I think as iPaaS evolves we've extended the breadth of our iPaaS dramatically. We're not an integration platform. We're, we take the broadest definition of the word integration I guess I'll say it that way. You'll be integrating people. Connecting people is just as important as connecting cloud applications So, you know, that that's part one in terms of the vision of what it is two is going to be the importance of speed and productivity. It's critically important that people can figure out how to reconnect because endpoints are exploding. You have to connect these extraordinarily quickly infractions of the amount of time that it ever took and coding, code is just not the way that that works. You have to have it abstracted and you have to make it simpler, low-code, no-code environments, configuration based environments, make it simpler for more people outside of IT to actually use the solutions. So that's where these platforms become much more pervasive than the enterprise, solve a much bigger problem, and they solve it at speeds. So, you know, the vision for this is just to continue to accelerate that, you know, when we got started here, things used to take months and months, you know, it came down to weeks, it came down to days, it's in to hours. We're looking at seconds to define connectivity in an easy button, those get connected and get working. That's our vision for intelligent connectivity. >> Okay, so we're talking about hyper automation in the future context. That's the segment here? What is a feature conductivity? Take me through that. How does that evolve? I can see marketplace. I can see an ecosystem. I see people connecting with partners and applications and data. What is the future of connectivity? >> The vision, right? For connectivity, and they talk about our connectivity as a service, but you know, you have to think about it as connectivity instead of connectors, like an NBO, a thing that talks to it, and what we look at is like, you should be able to point to an endpoint, pick a cloud app, any cloud application.  You have an API. I should be able to automatically programmatically and dynamically, anytime I want go interrogate that, browse it in the button and I've established connectivity, and the amount of take, in the amount of time it's taken me to explain it, you should almost be able to work through it and be connected to that and talking to that endpoint, we're going to bring that kind of connectivity, that dynamic generated, automatic connectivity, in to our platform, and that's the vision >> And people connect to user from a product standpoint and this should be literally plug and play, so to speak, old, old term, but really seamlessly, automated play, automate and play kind of just connect. >> Yes, absolutely. And what Chris was talking, I was thinking about a customer to be named, but one of the, during one of the interviews coming up at Out of this World, the customer was describing to us today, already the capabilities that we have, where he is, a CTO was able to get an integration up and running before this team was able to write the requirements for the integration. So, so those are the types of things we're looking to continue add to, to add to. And we're also, you know, not asking our customers to make a choice. You can scale up and scale down. It's very important for our customers to realize whether the problem's really big or really small our platforms there to get it done fast and in a secure way. >> I see a lot of people integrating in the cloud with each other and themselves other apps, seeing huge benefits while still working on premise across multiple environments. So this kind of new operating models evolving, some people call it refactoring, whatever term you want to use. It's a change of, of a value creation, creates new value. So as you guys go out, Chris, take us through your vision on next steps. Okay. You're, you're going to be independent. You got the financing behind you. Dell got a nice deal. You guys are going forward. What's next for boomi? >> Well, listen John, we, we, you know, we couldn't be more excited having the opportunity to truly unleash, you know, this business out on the market and you know, our employees are super excited. Our customers are going to benefit. Our customers are going to get a lot more product innovation every single day, we are ready to put out 11 releases a year. There's literally a hundred different features we put in that product. We're looking to double down on that and really accelerate our path towards those things what we were talking about today. Engagement with our customers gets to get much better, you know, doubling down on customer success. People support people, PSL in the field gets us engaging our customers in so many different ways. There's so much more folks that when we partner with our customers, we care about their overall success, and this investment really gives us so many avenues now to double down on and making sure that their journey with us and their journey towards their success as a business and how we can help them. Some of them, we help them get there. >> You guys got a lot of trajectory and experience and knowledge in this industry I think. It's really kind of a great position to be in. And as you guys take on this next wave, Chris McNabb, CEO Boomi, Ed Macosky, SVP, head of projects, thanks for coming on the cube, and this is the cube coverage of Boomi's Out of This World. I'm John Furrier, your host. Thanks for watching. (upbeat music)

>>Hello, welcome to the cubes coverage of Boomi's out of this world. I'm John for your host of the cube at two great guests here, Chris port, chief operating officer of Boomi and Mandy deli wall. Who's the chief marketing officer of Boomi, Chris Mandy. Great to see you. Thanks for coming on the cube. Appreciate it. >>Thank you for having us. >>This segment is really about the Boomi, uh, trend and customers, um, and the success you guys had obviously now on a new trajectory go to the next level. And you got a lot of trajectory and success. Chris, as the chief operating officer, we've talked many times about the customer base, uh, and growing poised perfectly for this next wave. Give us the update on the macro trends around your customer base and how Boomi's helping them and how you're, you're getting your growth. >>Absolutely. And John really look forward to seeing you soon later, yo, again, this is a great moment in time. We're now more than 18,000 customers, 800 partners globally. We've actually seen an acceleration of the business through the pandemic. Obviously people are trying to do more with less. So it's just an amazing time to see what our customers are doing. Obviously, an explosion of SAS applications. And when we started thinking about, you know, explosion of endpoints, explosion of data, and now you compound that with a labor sheet, which you know, I know if anyone's looking at movies hiring more than we've ever hired in our life. And obviously we're all seeing this in space. So now basically a high productivity, high time to value tool set like Boomi is an imperative. It's no longer a luxury. And we're seeing that accelerate where our customers you've heard Chris talking about 189,000 unique importance that we now connect to. That's the power of movie. You do that in minutes and that's happening every single day. So again, just extending our footprint, extending our customer, really taking advantage. We're seeing there are real tailwind for the business right now. So really excited. Are you excited to work with, >>You know, Chris, uh, Dave Volante, we're talking about, you know, how do you tell the next big breakout success is rogue usage, shadow it. When you have rogue users, that means there's some innovation happening and you guys have a lot of customers that are hiring because it's all new, it's all new innovation, Mandy. This is kind of like a marketing opportunity. It's like rogue is not a bad word here. There's new functionality. You guys are showing the market that you go with Boomi, you can get more value. And then new things just emerge. New positions, open up value is being created. It's kind of a sign of value. Not, not a negative. It's a positive. >>Yeah, absolutely. We give our customers innovate. They're looking to modernize, transform new business models, right? The world we live in today. And so there's really your choice. We abstract away that complexity. So our platform gives people the ability to go build quickly. And so that's really the thought leadership. >>You know, I love, I love Andy Jassy former CEO of AWS. Now the CEO of Amazon always said, uh, Chris, you know, you know, he's no compression algorithm for experience. And he always talked about Amazon being misunderstood. And then finally people go, oh my God, that's the flow. That's the formula of success. And then they're late to the game. A lot of similarities in the Boomi culture, uh, with his law under undifferentiated, heavy lifting, you guys take away and create net new opportunities. This is an operational opportunity for customers. What's your quick comment on that? >>I love the quote again, 26 billion minutes of working with our customers directly. That's a perfect way to put it. I mean, it's not, it's a mode. There's no substitute for that. Trying to bring that to bear every day. And again would just the imperative of being agile speed, time to value. I mean, Forrester did a study recently, you know, Boomi 65% faster in terms of building integration, manual coding, and more importantly, legacy middleware. And these are now just embarrass. They're not luxuries anymore. So again, you know, when we take the, you know, we bring the bear that 26 billion minutes, everything we do from a successful or which is now double more than double from a footprint, you know, over the last 12 to 18 months. And again, trying to build more and more people into that organization, but cumulating success, successes that part of our DNA. I mean, you know, the thousand plus people across the globe, it's what we think about every single day is how to make customers successful. And again, to your point, there's, there is no substitute for the experience of, >>You know, um, we've been covering Boomi for a long time, Mandy, you know that, and, and we kind of got the picture right away. And you mentioned Chris, some of those KPIs, those are real value points that you look to, but ultimately you guys are, have been successful. And I think one of the tell signs is customer customer value always have great customers. So customer success, this is a pass term SAS term. I I-PASS term is part of the, of the cloud. You have to have customer sets built in from the beginning. You guys always had that as part of your culture, customer success, organizations and operations. What's the update, Chris with customer it's customer success. >>Yeah. Again, I mean, you know, more than doubling the team over the last 18 months in building this even more into the DNA of Boomi overall, we've completely overhauled what we think is a world-class onboarding experience for both our new customers, as well as our existing customers. John, you brought it up, you know, call it road, call it whatever. I mean, we're existing customers every day when you give them the best onboarding experience too, so that they can accelerate their journey, which kind of gets into the Boomi person, our whole community, which when we were together last time, face to face, you wouldn't be seen. We weren't just two years ago, we're now over a hundred thousand members and part of our community growing every single day, incredibly excited about that because that brings the knowledge base to all of their experience. And again, it really brings what customers really want to interact in a digital way and the Boomi versus so, so much significantly the number of knowledge base articles, the number of marketplace type vehicles that our cohorts construct talking to each other about what they're doing is so much more than comms. >>We didn't do this year, but again, you know, the Boomi versus so vibrant now it's kind of a force multiplier for more importantly, how our customers are learning from each other. Yeah. And just to tag onto that, John, over 38% of our customers are publicly. There's a movement here, industry, average of averages are high. So the platform really sells itself and customers nowadays, we're very grateful for that. >>I think you guys are a great example of product market fit and go to market fit. As people look at these metrics, you gotta nail customer success, which from day one, you gotta have the usage metrics. You've gotta have the integration. Now you've got hyper automation. And as you start getting the ecosystem, Mandy, you've got a branding opportunity here. You got, you have, uh, ecosystem, which is another tale sign of success. When you start having that word of mouth. I remember when shadow, it was kind of like poo-pooed, but that was the road behaviors became the cloud. You starting to see you guys see this ecosystem, you've kind of crossed the chasm, create opportunity for your brand. What's your reaction. >>Yeah, absolutely. And we haven't done any brand work yet. Right? That's common. So, you know, we're just getting started. >>Okay. So I have to ask what this viral thing going on. That's going to go, boom, go Boomi it. So a lot of kind of double entendres there, it and boom, you know, everyone knows that icon on their text. Boom. You know, it's good. Things are booming. What's going on? He was the update go, boom. It Boomi is, >>Yeah. So it's go movie. And this was something that our customers brought to us during the pandemic. We didn't have much opportunity. Honestly, we were all sitting behind our computer screens. So we decided that we were going to start to hold wine conversations with customers, just to check in, see how they're doing, see how we can help and get them together to share a story of how they're handling disruptions to the business. So over the course of several months, talking to customers globally, I started to hear people say, well, I told my so-and-so because it'll get done. If you have a problem, doesn't matter what it is. And all of a sudden they crystallized for me like, you know what, this is a movement. And so this wasn't something the marketing team dropped up. This is something we heard from our and have taken it to market. Now our team members talk about it or customers are talking about it. And really, again, it's a Testament to the pervasiveness and capability platform. You start with the connect, but you're able to grow with us as your business changes and opportunities advisement. >>Well, you know, that's a really good indicator of, uh, net, net, net promoter score kind of vibe when people are giving you your marketing slogans, uh, from happy customers. So a really great congratulations to the whole team there. Can you give us some specific examples since you mentioned referenceable customers of customer examples and take me through some of the highlights in your opinion, that kind of show where this is going in terms of customer use case and value. >>Yeah. And I'll start with one that's very near and dear and obviously very relevant, right? There's there's been some press on Moderna here recently. Um, you know, they were in the race to find a cure for COVID-19. They were looking to bring on new employees and they couldn't bring them on onboard these people. So they leveraged the technology to do an integrated, uh, pursuit of driving customers onto their own to their employee platforms. So we ripped, it celebrated their onboarding cut that time in half. So they could actually start working on what matters. So then undifferentiated heavy lifting around the administrative tasks associated with getting my social security number, as well as other aspects that we all have joining a company that's automated, you can get to work faster. So that really helped improve drug development time and make a real difference in terms of getting the vaccine to market. >>So that's a net that's one tangible example, second example, customer of ours, uh, drink customer with net suite. They had to find different routes to market, right? And so they went direct to consumer. So they expanded their business through a global pandemic by leveraging Boomi technology and integrating commerce with their financial systems to be able to get to customers directly and also manage their Omni channel in a, in a new way. So again, innovator die. Right? Great. When you have another customer in India, that's a government, small country, citizens had to go in in-person together for their health ID cards. Well, offices are closed. Nobody's allowed to go be in person anymore. Within one week, they digitally transform. So they can disseminate healthcare cards in a critical time in a global pandemic to their citizens and have them get healthier. So three tangible examples of how we just in the last 18 months have been able to help these customers. >>So Chris, you guys have been operating a great business. Okay. Now you're on your own. You're independent. You got some great financing partners behind you, independent company, great trajectory building on that. A lot of economies of scale, you guys have built into it. Mandy, you've got great customers. Where's the next journey for you guys, take us through the operational growth strategy, uh, for Boomi. >>Well look, I mean, obviously we're on a hiring screen or hiring than we've ever done, and that's pervasive across the entire business, real focus on product engineering, who our go-to market, but we're also, you know, when you heard Chris, we're really redefining I-PASS. I mean, when I think about what I'm most excited about, it's a few things a we're violently aligned from kind of call it the chairman of the board to the newest team member. You know, we know what the opportunity is. We're all aligned, but as importantly, it's what we're doing from a product perspective. You know, when you've heard about intelligent connectivity, you've heard about automating connectivity, what we're doing from a discover perspective, EDA, everything we're doing in the marketplace, really accelerating what the adoption opportunities are for movie across the whole Boomi verse and across all of those new customers that we're acquiring and then ultimately seeing what they do. I mean, again, I, I, I love what Mandy says. I mean, it literally always, I feel so strongly about this within every single company in the world. I mean, it literally should be, no movie is because the opportunities are expansive and endless in terms of what we can do together. And that's what I'm excited about is really kind of unleashing this company on the world, see what we can do next. It was, we really think about this next iteration, >>Mandy, real quick to you, uh, when people say go Boomi it, when your customers say that, what does it mean to them? Why are they saying it? Take us through some of the psychology and some of the implications of, and the meaning of the word go Boomi from a customer perspective. >>Yeah. Great question. I think it's, first of all, it's a Testament of the trust, right? It's just going to work, right? So go get it done. It'll be fast. It'll be easy. It is not complex at all. Drag and drop visual interface. Just go make it happen and go move on to the next data is critical, right? It's the lifeblood of any organization or that backbone of connectivity that gives our customers confidence to go to work. >>Awesome stuff. Chris, final word for you. If you can just share in your opinion and be talking to your customers out there and future customers, what would you say to them as you guys go this next leg of the journey for Boomi? What would you say to them? >>Yeah, I would say come partner with us. Come on, understand what we can do for your business. Come understand what true intelligent, automated connects in Lightspeed in terms of how fast we can do that with you. And let's go explore the art of the possible because to me, that's >>Awesome, Chris. Great to see you, Amanda and great to see you virtually. Can't wait to see you in person and next event, uh, and congratulations on all the success and looking forward to covering the next leg of the journey of Boomi. Thanks for coming on. Okay. This is the cube coverage of Boomi's out of this world event. I'm John furrier hosted the cube. Thanks for watching.

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 semiconductors are the heart of technology innovation for decades technology improvements have marched the cadence of silicon advancements in performance cost power and packaging in the past 10 years the dynamics of the semiconductor industry have changed dramatically soaring factory costs device volume explosions fabulous chip companies greater programmability compressed time to tape out a lot more software content the looming presence of china these and other factors have changed the power structure of the semiconductor business chips today power every aspect of our lives and have led to a global semiconductor shortage that's been well covered but we've never seen anything like it before we believe silicon's success in the next 20 years will be determined by volume manufacturing capabilities design innovation public policy geopolitical dynamics visionary leadership and innovative business models that can survive the intense competition in one of the most challenging businesses in the world hello and welcome to this week's wikibon cube insights powered by etr in this breaking analysis it's our pleasure to welcome daniel newman in one of the leading analysts in the technology business and founder of futurum research daniel welcome to the program thanks so much dave great to see you thanks for having me big topic yeah i'll say i'm really looking forward to this and so here's some of the topics that we want to cover today if we have time changes in the semiconductor industry i've said they've been dramatic the shift to nofap companies we're going to talk about volume manufacturing those shifts that have occurred largely due to the arm model we want to cover intel and dig into that and what it has to do to to survive and thrive these changes and then we want to take a look at how alternative processors are impacting the world people talk about is moore's law dead is it alive and well daniel you have strong perspectives on all of this including nvidia love to get your thoughts on on that plus talk about the looming china threat as i mentioned in in the intro but daniel before we get into it do these topics they sound okay how do you see the state of the semiconductor industry today where have we come from where are we and where are we going at the macro level there are a lot of different narratives that are streaming alongside and they're not running in parallel so much as they're running and converging towards one another but it gradually different uh you know degrees so the last two years has welcomed a semiconductor conversation that we really hadn't had and that was supply chain driven the covid19 pandemic brought pretty much unprecedented desire demand thirst or products that are powered by semiconductors and it wasn't until we started running out of laptops of vehicles of servers that the whole world kind of put the semiconductor in focus again like it was just one of those things dave that we as a society it's sort of taken for granted like if you need a laptop you go buy a laptop if you needed a vehicle there'd always be one on the lot um but as we've seen kind of this exponentialism that's taken place throughout the pandemic what we ended up realizing is that semiconductors are eating the world and in fact the next industrial the entire industrial itself the complex is powered by semiconductor technology so everything we we do and we want to do right you went from a vehicle that might have had 50 or 100 worth of semiconductors on a few different parts to one that might have 700 800 different chips in it thousands of dollars worth of semi of semiconductors so you know across the board though yes you're dealing with the dynamics of the shortage you're dealing with the dynamics of innovation you're dealing with moore's law and sort of coming to the end which is leading to new process we're dealing with the foundry versus fab versus invention and product development uh situation so there's so many different concurrent semiconductor narratives that are going on dave and we can talk about any of them and all of them and i'm sure as we do we'll overlap all these different themes you know maybe you can solve this mystery for me there's this this this chip shortage and you can't invent vehicle inventory is so tight but yet when you listen to uh the the ads if the the auto manufacturers are pounding the advertising maybe they're afraid of tesla they don't want to lose their brand awareness but anyway so listen it's by the way a background i want to get a little bit academic here but but bear with me i want to introduce actually reintroduce the concept of wright's law to our audience we know we all know about moore's law but the earlier instantiation actually comes from theodore wright t.p wright he was this engineer in the airplane industry and the math is a little bit abstract to apply but roughly translated says as the cumulative number of units produced doubles your cost per unit declines by a fixed percentage now in airplanes that was around 15 percent in semiconductors we think that numbers more like 20 25 when you add the performance improvements you get from silicon advancements it translates into something like 33 percent cost cost declines when you can double your cumulative volume so that's very important because it confers strategic advantage to the company with the largest volume so it's a learning curve dynamic and it's like andy jassy says daniel there's no compression algorithm for experience and it definitely applies here so if you apply wright's law to what's happening in the industry today we think we can get a better understanding of for instance why tsmc is dominating and why intel is struggling any quick thoughts on that well you have to take every formula like that in any sort of standard mathematics and kind of throw it out the window when you're dealing with the economic situation we are right now i'm not i'm not actually throwing it out the window but what i'm saying is that when supply and demand get out of whack some of those laws become a little bit um more difficult to sustain over the long term what i will say about that is we have certainly seen this found um this fabulous model explode over the last few years you're seeing companies that can focus on software frameworks and innovation that aren't necessarily getting caught up in dealing with the large capital expenditures and overhead the ability to as you suggested in the topics here partner with a company like arm that's developing innovation and then and then um you know offering it uh to everybody right and for a licensee and then they can quickly build we're seeing what that's doing with companies like aws that are saying we're going to just build it alibaba we're just going to build it these aren't chip makers these aren't companies that were even considered chip makers they are now today competing as chip makers so there's a lot of different dynamics going back to your comment about wright's law like i said as we normalize and we figure out this situation on a global scale um i do believe that the who can manufacture the most will certainly continue to have significant competitive advantages yeah no so that's a really interesting point that you're bringing up because one of the things that it leads me to think is that the chip shortage could actually benefit intel i think will benefit intel so i want to introduce this some other data and then get your thoughts on this very simply the chart on the left shows pc shipments which peaked in in 2011 and then began at steady decline until covid and they've the pcs as we know have popped up in terms of volume in the past year and looks like they'll be up again this year the chart on the right is cumulative arm shipments and so as we've reported we think arm wafer volumes are 10x those of x86 volumes and and as such the arm ecosystem has far better cost structure than intel and that's why pat gelsinger was called in to sort of save the day so so daniel i just kind of again opened up this this can of worms but i think you're saying long term volume is going to be critical that's going to confer low cost advantages but in the in in the near to mid-term intel could actually benefit from uh from this chip shortage well intel is the opportunity to position itself as a leader in solving the repatriation crisis uh this will kind of carry over when we talk more about china and taiwan and that relationship and what's going on there we've really identified a massive gap in our uh in america supply chain in the global supply chain because we went from i don't have the stat off hand but i have a rough number dave and we can validate this later but i think it was in like the 30-ish high 30ish percentile of manufacturing of chips were done here in the united states around 1990 and now we're sub 10 as of 2020. so we we offshored almost all of our production and so when we hit this crisis and we needed more manufacturing volume we didn't have it ready part of the problem is you get people like elon musk that come out and make comments to the media like oh it'll be fixed later this year well you can't build a fab in a year you can't build a fab and start producing volume and the other problem is not all chips are the same so not every fab can produce every chip and when you do have fabs that are capable of producing multiple chips it costs millions of dollars to change the hardware and to actually change the process so it's not like oh we're going to build 28 today because that's what ford needs to get all those f-150s out of the lot and tomorrow we're going to pump out more sevens for you know a bunch of hp pcs it's a major overhaul every time you want to retool so there's a lot of complexity here but intel is the one domestic company us-based that has basically raised its hand and said we're going to put major dollars into this and by the way dave the arm chart you showed me could have a very big implication as to why intel wants to do that yeah so right because that's that's a big part of of foundry right is is get those volumes up so i want to hold that thought because i just want to introduce one more data point because one of the things we often talk about is the way in which alternative processors have exploded onto the scene and this chart here if you could bring that up patrick thank you shows the way in which i think you're pointing out intel is responding uh by leveraging alternative fat but once again you know kind of getting getting serious about manufacturing chips what the chart shows is the performance curve it's on a log scale for in the blue line is x86 and the orange line is apple's a series and we're using that as a proxy for sort of the curve that arm is on and it's in its performance over time culminating in the a15 and it measures trillions of operations per second so if you take the traditional x86 curve of doubling every 18 to 24 months that comes out roughly to about 40 percent improvement per year in performance and that's diminishing as we all know to around 30 percent a year because the moore's law is waning the orange line is powered by arm and it's growing at over a hundred percent really 110 per year when you do the math and that's when you combine the cpu the the the neural processing unit the the the xpu the dsps the accelerators et cetera so we're seeing apple use arm aws to you to your point is building chips on on graviton and and and tesla's using our list is long and this is one reason why so daniel this curve is it feels like it's the new performance curve in the industry yeah we are certainly in an era where companies are able to take control of the innovation curve using the development using the open ecosystem of arm having more direct control and price control and of course part of that massive arm number has to do with you know mobile devices and iot and devices that have huge scale but at the same time a lot of companies have made the decision either to move some portion of their product development on arm or to move entirely on arm part of why it was so attractive to nvidia part of the reason that it's under so much scrutiny that that deal um whether that deal will end up getting completed dave but we are seeing an era where we want we i said lust for power i talked about lust for semiconductors our lust for our technology to do more uh whether that's software-defined vehicles whether that's the smartphones we keep in our pocket or the desktop computer we use we want these machines to be as powerful and fast and responsive and scalable as possible if you can get 100 where you can get 30 improvement with each year and generation what is the consumer going to want so i think companies are as normal following the demand of consumers and what's available and at the same time there's some economic benefits they're they're able to realize as well i i don't want to i don't want to go too deep into nvidia arm but what do you handicap that that the chances that that acquisition actually happens oh boy um right now there's a lot of reasons it should happen but there are some reasons that it shouldn't i still kind of consider it a coin toss at this point because fundamentally speaking um you know it should create more competition but there are some people out there that believe it could cause less and so i think this is going to be hung up with regulators a little bit longer than we thought we've already sort of had some previews into that dave with the extensions and some of the timelines that have already been given um i know that was a safe answer and i will take credit for being safe this one's going to be a hard one to call but it certainly makes nvidia an amazing uh it gives amazing prospects to nvidia if they're able to get this deal done yeah i i agree with you i think it's 50 50. okay my i want to pose the question is intel too strategic to fail in march of this year we published this article where we posed that question uh you and i both know pat pretty well we talked about at the time the multi-front war intel is waging in a war with amd the arm ecosystem tsmc the design firms china and we looked at the company's moves which seemed to be right from a strategy standpoint the looking at the potential impact of the u.s government intel's partnership with ibm and what that might portend the us government has a huge incentive to make sure intel wins with onshore manufacturing and that looming threat from china but daniel is intel too strategic to fail and is pat gelsinger making the right moves well first of all i do believe at this current juncture where the semiconductor and supply chain shortage and crisis still looms that intel is too strategic to fail i also believe that intel's demise is somewhat overstated not to say intel doesn't have a slate of challenges that it's going to need to address long term just with the technology adoption curve that you showed being one of them dave but you have to remember the company still has nearly 90 of the server cpu market it still has a significant market share in client and pc it is seeing market share erosion but it's not happened nearly as fast as some people had suggested it would happen with right now with the demand in place and as high as it is intel is selling chips just about as quickly as it can make them and so we right now are sort of seeing the tam as a whole the demand as a whole continue to expand and so intel is fulfilling that need but where are they really too strategic to fail i mean we've seen in certain markets in certain uh process in um you know client for instance where amd has gained of course that's still x86 we've seen uh where the m1 was kind of initially thought to be potentially a pro product that would take some time it didn't take nearly as long for them to get that product in good shape um but the foundry and fab side is where i think intel really has a chance to flourish right now one it can play in the arm space it can build these facilities to be able to produce and help support the production of volumes of chips using arm designs so that actually gives intel and inroads two is it's the company that has made the most outspoken commitment to invest in the manufacturing needs of the united states both here in the united states and in other places across the world where we have friendly ally relationships and need more production capabilities if not in intel b and there is no other logical company that's us-based that's going to meet the regulator and policymakers requirements right now that is also raising their hand and saying we have the know-how we've been doing this we can do more of this and so i think pat is leaning into the right area and i think what will happen is very likely intel will support manufacturing of chips by companies like qualcomm companies like nvidia and if they're able to do that some of the market share losses that they're potentially facing with innovation challenges um and engineering challenges could be offset with growth in their fab and foundry businesses and i think i think pat identified it i think he's going to market with it and you know convincing the street that's going to be a whole nother thing that this is exciting um but i think as the street sees the opportunity here this is an area that intel can really lean into so i think i i think people generally would recognize at least the folks i talk to and it'll be interested in your thoughts who really know this business that intel you know had the best manufacturing process in in the world obviously that's coming to question but but but but for instance people say well intel's 10 nanometer you know is comparable to tsm seven nanometer and that's sort of overstated their their nanometer you know loss but but so so they they were able to point as they were able to sort of hide some of the issues maybe in design with great process and and i i believe that comes down to volume so the question i have then is and i think so i think patrick's pat is doing the right thing because he's going after volume and that's what foundry brings but can he get enough volume or does he need for inst for instance i mean one of the theories i've put out there is that apple could could save the day for intel if the if the us government gets apple in a headlock and says hey we'll back off on break up big tech but you got to give pat some of your foundry volume that puts him on a steeper learning curve do you do you worry sometimes though daniel that intel just even with like qualcomm and broadcom who by the way are competitors of theirs and don't necessarily love them but even even so if they could get that those wins that they still won't have the volume to compete on a cost basis or do you feel like even if they're numbered a number three even behind samsung it's good enough what are your thoughts on that well i don't believe a company like intel goes into a business full steam and they're not new to this business but the obvious volume and expansion that they're looking at with the intention of being number two or three these great companies and you know that's same thing i always say with google cloud google's not out to be the third cloud they're out to be one well that's intel will want to to be stronger if the us government and these investments that it's looking at making this 50 plus billion dollars is looking to pour into this particular space which i don't think is actually enough but if if the government makes these commitments and intel being likely one of the recipients of at least some of these dollars to help expedite this process move forward with building these facilities to make increased manufacturing very likely there's going to be some precedent of law a policy that is going to be put in place to make sure that a certain amount of the volume is done here stateside with companies this is a strategic imperative this is a government strategic imperative this is a putting the country at risk of losing its technology leadership if we cannot manufacture and control this process of innovation so i think intel is going to have that as a benefit that the government is going to most likely require some of this manufacturing to take place here um especially if this investment is made the last thing they're going to want to do is build a bunch of foundries and build a bunch of fabs and end up having them not at capacity especially when the world has seen how much of the manufacturing is now being done in taiwan so i think we're concluding and i i i correctly if i'm wrong but intel is too strategic to fail and and i i sometimes worry they can go bankrupt you know trying to compete with the likes of tsmc and that's why the the the public policy and the in the in the partnership with the u.s government and the eu is i think so important yeah i don't think bankruptcy is an immediate issue i think um but while i follow your train of thought dave i think what you're really looking at more is can the company grow and continue to get support where i worry about is shareholders getting exhausted with intel's the merry-go-round of not growing fast enough not gaining market share not being clearly identified as a leader in any particular process or technology and sort of just playing the role of the incumbent and they the company needs to whether it's in ai whether it's at the edge whether it's in the communications and service provider space intel is doing well you look at their quarterly numbers they're making money but if you had to say where are they leading right now what what which thing is intel really winning uh consistently at you know you look at like ai and ml and people will point to nvidia you look at you know innovation for um client you know and even amd has been super disruptive and difficult for intel uh of course you we've already talked about in like mobile um how impactful arm has been and arm is also playing a pretty big role in servers so like i said the market share and the technology leadership are a little out of skew right now and i think that's where pat's really working hard is identifying the opportunities for for intel to play market leader and technology leader again and for the market to clearly say yes um fab and foundry you know could this be an area where intel becomes the clear leader domestically and i think that the answer is definitely yes because none of the big chipmakers in the us are are doing fabrication you know they're they're all outsourcing it to overseas so if intel can really lead that here grow that large here then it takes some of the pressure off of the process and the innovation side and that's not to say that intel won't have to keep moving there but it does augment the revenue creates a new profit center and makes the company even more strategic here domestically yeah and global foundry tapped out of of sub 10 nanometer and that's why ibm's pseudonym hey wait a minute you had a commitment there the concern i have and this is where again your point is i think really important with the chip shortage you know to go from you know initial design to tape out took tesla and apple you know sub sub 24 months you know probably 18 months with intel we're on a three-year design to tape out cycle maybe even four years so they've got to compress that but that as you well know that's a really hard thing to do but the chip shortage is buying them time and i think that's a really important point that you brought out early in this segment so but the other big question daniel i want to test with you is well you mentioned this about seeing arm in the enterprise not a lot of people talk about that or have visibility on that but i think you're right on so will arm and nvidia be able to seriously penetrate the enterprise the server business in particular clearly jensen wants to be there now this data from etr lays out many of the enterprise players and we've superimposed the semiconductor giants in logos the data is an xy chart it shows net score that's etr's measure of spending momentum on the vertical axis and market share on the horizontal axis market share is not like idc market share its presence in the data set and as we reported before aws is leading the charge in enterprise architecture as daniel mentioned they're they're designing their own chips nitro and graviton microsoft is following suit as is google vmware has project monterey cisco is on the chart dell hp ibm with red hat are also shown and we've superimposed intel nvidia china and arm and now we can debate the position of the logos but we know that one intel has a dominant position in the data center it's got to protect that business it cannot lose ground as it has in pcs because the margin pressure it would face two we know aws with its annapurna acquisition is trying to control its own destiny three we know vmware has project monterey and is following aws's lead to support these new workloads beyond x86 general purpose they got partnerships with pansando and arm and others and four we know cisco they've got chip design chops as does hpe maybe to a lesser extent and of course we know ibm has excellent semiconductor design expertise especially when it comes to things like memory disaggregation as i said jensen's going hard after the data center you know him well daniel we know china wants to control its own destiny and then there's arm it dominates mobile as you pointed out in iot can it make a play for the data center daniel how do you see this picture and what are your thoughts on the future of enterprise in the context of semiconductor competition it's going to take some time i believe but some of the investments and products that have been brought to market and you mentioned that shorter tape out period that shorter period for innovation whether it's you know the graviton uh you know on aws or the aiml chips that uh with trainium and inferentia how quickly aws was able to you know develop build deploy to market an arm-based solution that is being well received and becoming an increasing component of the services and and uh products that are being offered from aws at this point it's still pretty small and i would i would suggest that nvidia and arm in the spirit of trying to get this deal done probably don't necess don't want the enterprise opportunity to be overly inflated as to how quickly the company's going to be able to play in that space because that would somewhat maybe slow or bring up some caution flags that of the regulators that are that are monitoring this at the same time you could argue that arm offering additional options in competition much like it's doing in client will offer new form factors new designs um new uh you know new skus the oems will be able to create more customized uh hardware offerings that might be able to be unique for certain enterprises industries can put more focus you know we're seeing the disaggregation with dpus and how that technology using arm with what aws is doing with nitro but what what these different companies are doing to use you know semiconductor technology to split out security networking and storage and so you start to see design innovation could become very interesting on the foundation of arm so in time i certainly see momentum right now the thing is is most companies in the enterprise are looking for something that's fairly well baked off the shelf that can meet their needs whether it's sap or whether it's you know running different custom applications that the business is built on top of commerce solutions and so intel meets most of those needs and so arm has made a lot of sense for instance with these cloud scale providers but not necessarily as much sense for enterprises especially those that don't want to necessarily look at refactoring all the workloads but as software becomes simpler as refactoring becomes easier to do between different uh different technologies and processes you start to say well arm could be compelling and you know because the the bottom line is we know this from mobile devices is most of us don't care what the processor is the average person the average data you know they look at many of these companies the same in enterprise it's always mattered um kind of like in the pc world it used to really matter that's where intel inside was born but as we continue to grow up and you see these different processes these different companies nvidia amd intel all seen as very worthy companies with very capable technologies in the data center if they can offer economics if they can offer performance if they can offer faster time to value people will look at them so i'd say in time dave the answer is arm will certainly become more and more competitive in the data center like it was able to do at the edge in immobile yeah one of the things that we've talked about is that you know the software-defined data center is awesome but it also created a lot of wasted overhead in terms of offloading storage and and networking security and that much of that is being done with general purpose x86 processors which are more expensive than than for instance using um if you look at what as you mentioned great summary of what aws is doing with graviton and trainium and other other tooling what ampere is doing um in in in oracle and you're seeing both of those companies for example particularly aws get isvs to write so they can run general purpose applications on um on arm-based processors as well it sets up well for ai inferencing at the edge which we know arms dominating the edge we see all these new types of workloads coming into the data center if you look at what companies like nebulon and pensando and and others are doing uh you're seeing a lot of their offloads are going to arm they're putting arm in even though they're still using x86 in a lot of cases but but but they're offloading to arm so it seems like they're coming into the back door i understand your point actually about they don't want to overplay their hand there especially during these negotiations but we think that that long term you know it bears watching but intel they have such a strong presence they got a super strong ecosystem and they really have great relationships with a lot of the the enterprise players and they have influence over them so they're going to use that the the the chip shortage benefits them the uh the relationship with the us government pat is spending a lot of time you know working that so it's really going to be interesting to see how this plays out daniel i want to give you the last word your final thoughts on what we talked about today and where you see this all headed i think the world benefits as a whole with more competition and more innovation pressure i like to see more players coming into the fray i think we've seen intel react over the last year under pat gelsinger's leadership we've seen the technology innovation the angstrom era the 20a we're starting to see what that roadmap is going to look like we've certainly seen how companies like nvidia can disrupt come into market and not just using hardware but using software to play a major role but as a whole as innovation continues to take form at scale we all benefit it means more intelligent software-defined vehicles it puts phones in our hands that are more powerful it gives power to you know cities governments and enterprises that can build applications and tools that give us social networks and give us data-driven experiences so i'm very bullish and optimistic on as a whole i said this before i say it again i believe semiconductors will eat the world and then you know you look at the we didn't even really talk about the companies um you know whether it's in ai uh like you know grok or grav core there are some very cool companies building things you've got qualcomm bought nuvia another company that could you know come out of the blue and offer us new innovations in mobile and personal computing i mean there's so many cool companies dave with the scale of data the uh the the growth and demand and desire for connectivity in the world um it's never been a more interesting time to be a fan of technology the only thing i will say as a whole as a society as i hope we can fix this problem because it does create risks the supply chain inflation the economics all that stuff ties together and a lot of people don't see that but if we can't get this manufacturing issue under control we didn't really talk about china dave and i'll just say taiwan and china are very physically close together and the way that china sees taiwan and the way we see taiwan is completely different we have very little control over what can happen we've all seen what's happened with hong kong so there's just so many as i said when i started this conversation we've got all these trains on the track they're all moving but they're not in parallel these tracks are all converging but the convergence isn't perpendicular so sometimes we don't see how all these things interrelate but as a whole it's a very exciting time love being in technology and uh love having the chance to come out here and talk with you i love the optimism and you're right uh that competition in china that's going to come from china as well xi has made it a part of his legacy i think to you know re-incorporate taiwan that's going to be interesting to see i mean taiwan ebbs and flows with regard to you know its leadership sometimes they're more pro i guess i should say less anti-china maybe that's the better way to say it uh and and and you know china's putting in big fab capacity for nand you know maybe maybe people look at that you know some of that is the low end of the market but you know clay christensen would say well to go take a look at the steel industry and see what happened there so so we didn't talk much about china and that was my oversight but but they're after self-sufficiency it's not like they haven't tried before kind of like intel has tried foundry before but i think they're really going for it this time but but now what are your do you believe that china will be able to get self-sufficiency let's say within the next 10 to 15 years with semiconductors yes i would never count china out of anything if they put their mind to it if it's something that they want to put absolute focus on i think um right now china vacillates between wanting to be a good player and a good steward to the world and wanting to completely run its own show the the politicization of what's going on over there we all saw what happened in the real estate market this past week we saw what happened with tech ed over the last few months we've seen what's happened with uh innovation and entrepreneurship it is not entirely clear if china wants to give the more capitalistic and innovation ecosystem a full try but it is certainly shown that it wants to be seen as a world leader over the last few decades it's accomplished that in almost any area that it wants to compete dave i would say if this is one of gigi ping's primary focuses wanting to do this it would be very irresponsible to rule it out as a possibility daniel i gotta tell you i i love collaborating with you um we met face to face just recently and i hope we could do this again i'd love to have you you back on on the program thanks so much for your your time and insights today thanks for having me dave so daniel's website futuram research that's three use in futurum uh check that out for termresearch.com uh the the this individual is really plugged in he's forward thinking and and a great resource at daniel newman uv is his twitter so go follow him for some great stuff and remember these episodes are all available as podcasts wherever you listen all you do is search for breaking analysis podcast we publish each week on wikibon.com and siliconangle.com and by the way daniel thank you for contributing your your quotes to siliconangle the writers there love you uh you can always connect on twitter i'm at divalanto you can email me at david.velante at siliconangle.com appreciate the comments on linkedin and don't forget to check out etr.plus for all the survey data this is dave vellante for the cube insights powered by etr be well and we'll see you next time you

>> From around the globe it's theCube. Presenting Future Cloud. One event, a world of opportunities. Brought to you by Cisco. >> We're here with Vikas Ratna, who's the director of product management for ECS at Cisco and James Leach is the director of business development for UCS at Cisco as well. We're going to talk about computing in the age of hybrid cloud. Welcome gentlemen, great to see you. >> Thank you. >> Thank you. >> Vikas let's start with you and talk a little bit about computing architectures. We know that they're evolving, they're supporting new data intensive and other workloads, especially as high-performance workload requirements, what's Cisco's point of view on all this? And specifically, I'm interested in your thoughts on fabrics, I mean, it's kind of your wheelhouse, you've got accelerators, What are the workloads that are driving these evolving technologies and how is it impacting customers? What are you seeing? >> Sure, Dave. First of all, very excited to be here today. You're absolutely right. The pace of innovation and foundational platform ingredients have just been phenomenal in recent years. The fabric, accelerators, the drives, the processing power, the core density all have been evolving at just an amazing pace and the pace will only pick up further, but ultimately it is all about applications and the way applications leverage those innovations. And we do see applications evolving quite rapidly. The new classes of applications are evolving to absorb those innovations and deliver much better business values, very, very exciting times, Dave, but talking about the impact on the customers, well these innovations have helped them pretty positively. We do see significant challenges in the data center with a point product based approach of delivering these platform innovations to the applications. What has happened is these innovations today are being packaged as point products to meet the needs of a specific application. And as you know, the different applications have their different needs. Some applications need more tributes, others need more memory, yet others need, you know, more cores. Some need different kinds of fabrics. As a result, if you walk into a data center today, it is pretty common to see many different point products in the data center. This creates a manageability challenge. Imagine the aspect of managing, you know, several different form factors, one you, to you, purpose-built servers or the variety of, you know, blade form factor. You know, this reminds me of the situation we had before smartphones arrived. You remember the days when you, when we used to have a GPS device for navigation system, a cool music device for listening to the music, a phone device for making a call, camera for taking the photos. Right? And we were all excited about it. It's when the smartphones arrived that we realized all those cool innovations could be delivered in a much simpler, much convenient, and easy to consume it through one device and, you know, and that could completely transform our experience. So we see the customers who are benefiting from these innovations to have a way to consume those things in a much more simplistic way than they are able to do it today. >> And I like, look, it's always been about the applications, but to your point, the applications are now moving at a much faster pace. The customer experience is, expectation, is way escalated. And when you combine all these, I love your analogy there Vikas, because when you combine all these capabilities, it allows us to develop new applications, new capabilities, new customer experiences. So that's the, I always say, the next 10 years, they ain't going to be like the last. And James, public cloud obviously is heavily influencing compute design and customer operating models. You know, it's funny, when the public cloud first hit the market, everyone, we were swooning about oh, low cost, standard off-the-shelf servers, you know, and storage devices, but it quickly became obvious that customers needed more. So I wonder if you could comment on this. How are the trends that we've seen from the hyperscalers, how are they filtering into on-prem infrastructure and maybe, you know, maybe there's some differences there as well that you could address? >> Absolutely. So, you know, I'd say first of all, quite frankly, you know, public cloud has completely changed the expectations of how our customers want to consume compute, right? So customers, especially in a public cloud environment, they've gotten used to, or, you know, come to accept that they should consume from the application out, right? They want a very application-focused view, a services-focused view of the world. They don't want to think about infrastructure, right? They want to think about their application. They want to move outward, right? So, this means that the infrastructure basically has to meet the application where it lives. So what that means for us is that, you know, we're taking a different approach. We've decided that, you know, we're not going to chase this, you know, single pane of glass view of the world, which, you know, frankly our customers don't want. They don't want a single pane of glass. What they want is a single operating model. They want an operating model that's similar to what they can get with the public cloud, but they want it across all of their cloud options. They want it across private cloud, across hybrid cloud options, as well. So what that means is they don't want to just consume infrastructure services. They want all of their cloud services from this operating model. So that means that they may want to consume infrastructure services for automation orchestration, but they also need Kubernetes services. They also need virtualization services. They may need Terraform, workload optimization. All of these services have to be available from within the operating model, a consistent operating model, right? So it doesn't matter whether you're talking about private cloud, hybrid cloud, anywhere, where the application lives doesn't matter. What matters is that we have a consistent model, that we think about it from the application out, and frankly, I'd say, you know, this has been the stumbling block for private cloud. Private cloud is hard, right? This is why it hasn't been really solved yet. This is why we had to take a brand new approach. And frankly, it's why we're super excited about X Series and intersight as that, you know, operating model that fits the hybrid cloud better than anything else we've seen. >> This is a Cube first, first time's a technology vendor has ever said that it's not about a single pane of glass because I've been hearing for decades we're going to deliver a single pane of glass. It's going to be seamless and it never happens. It's like a single version of the truth. It's aspirational. And it's just not reality. So can we stay on the X Series for a minute, James, maybe in this context, but in the launch that we saw today, it was like a fire hose of announcements. So, how does the X Series fit into the strategy with intersight, and hybrid cloud in this operating model that you're talking about? >> Right. So, I think it goes hand-in-hand, right? The two pieces go together very well. So we have, you know, this idea of a single operating model that is definitely, you know, something that our customers demand, right? It's what we have to have, but at the same time we need to solve the problems Vikas was talking about before, we need a single infrastructure to go along with that single operating model. So no longer do we need to have silos within the infrastructure that give us different operating models or different sets of benefits, when you want infrastructure that can kind of do all of those configurations, all those applications. And then, you know, the operating model is very important because that's where we abstract the complexity that could come with just throwing all that technology at the infrastructure. So that, you know, this is, you know, the way that we think about it is the data center is not centered, right? It's no longer centered. Applications live everywhere. Infrastructure lives everywhere. And, you know, we need to have that consistent operating model, but we need to do things within the infrastructure as well to take full advantage, right? So we want all the SaaS benefits of a CICD model of, you know, the intersight can bring, we want all of that, you know, proactive recommendation engine with the power of AI behind it, we want the connected support experience. We want all of that, but we want to do it across a single infrastructure. And we think that that's how they tie together. That's why one or the other doesn't really solve the problem, but both together. That's why we're here. That's why we're super excited. >> So Vikas, I make you laugh a little bit. When I was an analyst at IDC, I was a bit deep into infrastructure, And then when I left, I was doing, I was working with application development heads. And like you said, infrastructure, it was just a roadblock, but it was so the tongue-in-cheek is when Cisco announced UCS a decade ago, I totally missed it. I didn't understand it. I thought it was Cisco getting into the traditional server business. And it wasn't until I dug in that I realized that your vision was really to transform infrastructure deployment and management. And change the model. It was like, okay, I got that wrong. But, so let's talk about the, the ecosystem and the joint development efforts that are going on there. X Series, how does it fit into this converged infrastructure business that you've built and grown with partners? You've got storage partners like NetApp and Pure. You got ISV partners in the ecosystem. We see Cohesity, it's been a while since we hung out with all these companies at the Cisco live, hopefully next year, but tell us what's happening in that regard. >> No, absolutely. I'm looking forward to seeing you in the Cisco live next year, Dave. Absolutely. You brought up a very good point. UCS is about the ecosystem that it brings together. It's about making our customers bring up the entire infrastructure, from the core foundational hardware all the way to the application level so that they can all go off and running pretty quick. That converse infrastructure has been one of the cornerstones of our strategy, as you pointed out, in the last decade. And I'm very glad to share that conversed infrastructure continues to be a very popular architecture for several enterprise applications even today. In fact, it is the preferred architecture for mission critical applications, where performance, resiliency, latency, are the critical requirements. They are almost de facto standards for large scale deployments of virtualize and business critical databases and so forth. With X Series, with our partnerships, with our restorative partners, those architectures will absolutely continue and will get better. But in addition, it's a hybrid cloud world. So we are now bringing in the benefits of conversed infrastructure to the world of hybrid cloud. We'll be supporting the hybrid cloud applications now with the CA infrastructure that we have built together with our strong partnership with the store as partners to tell you with the same benefits to the new age applications as well. >> Yeah and that's what customers want, they want that cloud operating model. Right? Go ahead, please. >> I was just going to say, you know, that the CA model will continue to thrive. It will transition out, it will expand the use cases now for the newer use cases that we were beginning to see, Dave, absolutely. >> Great. Thank you for that. And James, like I said earlier today, we heard this huge announcement, a lot of parts to it. And we heard, you know, KD talk about this initiative is, it's really computing built for the next decade. I mean, I like that because it shows some vision and that you've got, you know, a roadmap, that you've thought through the coming changes in workloads and infrastructure management and some of the technology that you can take advantage of beyond just the, you know, one or two product cycles. So, but I want to understand what you've done here specifically that you feel differentiates you from other competitive architectures in the industry. >> Sure. You know, that's a great question. number one. Number two, I'm frankly a little bit concerned at times for customers in general, for our customers, customers in general, because if you look at what's in the market, right? These rinse and repeat systems that were effectively just rehashes of the same old design, right? That we've seen since before 2009 when we brought UCS to market, these are what we're seeing over and over and over again, that's not really going to work anymore, frankly. And I think that people are getting lulled into a false sense of security by seeing those things continually put in the market. We've rethought this from the ground up because frankly, you know, future-proofing starts now, right? If you're not doing it right today, future-proofing isn't even on your radar because you're not even, you're not even today-proofed. So we've rethought the entire chassis, the entire architecture, from the ground up. Okay. If you look at other vendors, if you look at other solutions in the market, what you'll see is things like, you know management inside the chassis. That's a great example. Daisy chaining them together. Like, who needs that? Who wants that? Like, that kind of complexity is, first of all, it's ridiculous. Second of all, if you want to manage across clouds you have to do it from the cloud, right? It's just common sense. You have to move management where it can have the scale and the scope that it needs to impact, you know, your entire domain, your world, which is much larger now than it was before. We're talking about true hybrid cloud here. Right? So, we had to, you know, solve certain problems that existed in the traditional architecture. You know, I can't tell you how many times I heard you know, talk about, you know, the mid plane is a great example. Well, you know, the mid plane in a chassis is a limiting factor. It limits us on how much we can connect or how much bandwidth we have available to the chassis. It limits us on air flow and other things. So how do you solve that problem? Simple. Just get rid of it. Like we just, we took it out, right? It's now no longer a problem. We designed an architecture that doesn't need it. It doesn't rely on it, no forklift upgrades. So as we start moving down the path of needing liquid cooling, or maybe we need to take advantage of some new high performance, low latency fabrics. We can do that with almost no problem at all, right? So we don't have any forklift upgrades. Park your forklift on the side. You won't need it anymore because you can upgrade granularly. You can move along as technologies come into existence that maybe don't even exist today. They may not even be on our radar today to take advantage of but I like to think of these technologies. You know, they're really important to our customers. These are, you know, we can call them disruptive technologies. The reality is that we don't want to disrupt our customers with these technologies. We want to give them these technologies so they can go out and be disruptive themselves, right? And this is the way that we've designed this, from the ground up, to be easy consume and to take advantage of what we know about today and what's coming in the future that we may not even know about. So we think this is a way to give our customers that ultimate capability, flexibility, and future-proofing. >> I like that phrase, true hybrid cloud. It's one that we've used for years. But to me, this is all about that horizontal infrastructure that can support that vision of what true hybrid cloud is. You could support the mission critical applications. You can develop on the system and you can support a variety of workloads. You're not locked into, you know, one narrow stovepipe. And that does have legs. Vikas and James, thanks so much for coming on the program. Great to see you. >> Thank you, we appreciate the time. >> Thank you. >> And thank you for watching. This is Dave Volante for theCube, the leader in digital event coverage. (uplifting music)

>>from around the globe it's the >>cube >>presenting >>Future Cloud one event. A >>world of >>opportunities >>brought to you by Cisco. We're here with Dejoy Pandey a VP of emerging tech and incubation at Cisco. V. Joy. Good to see you welcome. >>Good to see you as well. Thank you Dave and pleasure to be here. >>So in 2020 we kind of had to redefine the notion of agility when it came to digital business or you know organizations, they had to rethink their concept of agility and business resilience. What are you seeing in terms of how companies are thinking about their operations in this sort of new abnormal context? >>Yeah I think that's a great question I think what what we're seeing is that pretty much the application is the center of the universe and if you think about it the application is actually driving brand recognition and the brand experience and the brand value. So the example I like to give is think about a banking app uh recovered that did everything that you would expect it to do. But if you wanted to withdraw cash from your bank you would actually have to go to the ATM and punch in some numbers and then look at your screen and go through a process and then finally withdraw cash. Think about what that would have, what that would do in a post pandemic era where people are trying to go contact less. And so in a situation like this the digitization efforts that all of these companies are going through and the modernization of the automation is what is driving brand recognition, brand trust and brand experience. >>Yeah. So I was gonna ask you when I heard you say that, I was gonna say well but hasn't it always been about the application? But it's different now, isn't it? So I wonder if you talk more about how the application is experience is changing? Yes. As a result of this new digital mandate. But how should organizations think about optimizing those experiences in this new world? >>Absolutely. And I think, yes, it's always been about the application, but it's becoming the center of the universe right now because all interactions with customers and consumers and even businesses are happening through that application. So if the application is unreliable or if the application is not available is untrusted insecure, uh, there's a problem. There's a problem with the brand with the company and the trust that consumers and customers have with our company. So if you think about an application developer, the weight he or she is carrying on their shoulders is tremendous because you're thinking about rolling features quickly to be competitive. That's the only way to be competitive in this world. You need to think about availability and resiliency, like you pointed out and experience, you need to think about security and trust. Am I as a customer or consumer willing to put my data in that application? So velocity availability, security and trust and all of that depends on the developer. So the experience, the security, the trust, the feature velocity is what is driving the brand experience now. >>So are those two tensions that say agility and trust, you know, zero trust used to be a buzzword now, it's a mandate. But are those two vectors counter posed? Can they be merged into one and not affect each other? Does the question makes sense? Right? Security usually handcuffs my speed. But how do you address that? >>Yeah, that's a great question. And I think if you think about it today, that's the way things are. And if you think about this developer, all they want to do is run fast because they want to build those features out and they're going to pick and choose a purpose and services that matter to them and build up their app and they want the complexities of the infrastructure and security and trust to be handled by somebody else is not that they don't care about it, but they want that abstraction so that is handled by somebody else. And typically within an organization we've seen in the past where there's friction between Netapp, Succop cited hopes and the cloud platform teams and the developer on one side and these these frictions and these meetings and toil actually take a toll on the developer and that's why companies and apps and developers are not as agile as they would like to be. So I think, but it doesn't have to be that way. So I think if there was something that would allow a developer to pick and choose, discover the apis that they would like to use, connect those api is in a very simple manner and then be able to scale them out and be able to secure them and in fact not just secure them during the run time when it's deployed, we're right off the back when the fire up that I'd and start developing the application, wouldn't that be nice? And as you do that, there is a smooth transition between that discovery connectivity and ease of consumption and security with the idea cops, netapp psych ops teams and see source to ensure that they are not doing something that the organization won't allow them to do in a very seamless manner. >>I want to go back and talk about security but I want to add another complexity before we do that. So for a lot of organizations in the public cloud became a staple of keeping the lights on during the pandemic. But it brings new complexities and differences in terms of latency security, which I want to come back to deployment models etcetera. So what are some of the specific networking challenges that you've seen with the cloud? Native architecture is how are you addressing those? >>Yeah. In fact, if you think about cloud, to me that is a that is a different way of seeing a distributed system. And if you think about a distributed system, what is at the center of the distributed system is the network. So my my favorite comment here is that the network is the wrong time for all distribute systems and modern applications. And that is true because if you think about where things are today, like you said, there's there's cloud assets that a developer might use in the banking example that I gave earlier. I mean if you want to build a contact less app so that you get verified, a customer gets verified on the app. They walk over to the ATM and they were broadcast without touching that ATM. In that kind of an example, you're touching the mobile Rus, let's say, Ohio escapees, you're touching Cloud API is where the back end might sit, you're touching on primary purpose, maybe it's an oracle database or a mainframe even where transactional data exists, you're touching branch pipes were the team actually exists and the need for consistency when you withdraw cash and you're carrying all of this and in fact there might be customer data sitting in Salesforce somewhere. So it's cloud API is a song premise branch, it's ass is mobile and you need to bring all of these things together and over time you will see more and more of these API is coming from various as providers. So it's not just cloud providers but saAS providers that the developer has to use. And so this complexity is very very real and this complexity is across the wide open internet. So the application is built across this wide open internet. So the problems of discovery ability, the problems of being able to simply connect these apis and manage the data flow across these apis. The problems of consistency of policy and consumption because all of these areas have their own nuances and what they mean, what the arguments mean and what the A. P. I. Actually means. How do you make it consistent and easy for the developer? That is the networking problem. And that is a problem of building out this network, making traffic engineering easy making policy easy, making scale out, scale down easy, all of that our networking problems. And so we are solving those problems. Uh Francisco >>Yeah the internet is the new private network but it's not so private. So I want to go back to security. I often say that the security model of building a moat, you dig the moat, you get the hardened castle that's just outdated now that the queen is left her castle. I always say it's dangerous out there. And the point is you touched on this? It's it's a huge decentralized system and with distributed apps and data, that notion of perimeter security, it's just no longer valid. So I wonder if you could talk more about how you're thinking about this problem and you definitely address some of that in your earlier comments. But what are you specifically doing to address this? And how do you see it evolving? >>Yeah, I mean that that's that's a very important point. I mean I think if you think about again the wide open internet being the wrong time for all modern applications, what is perimeter security in this uh in this new world? I mean it's to me it boils down to securing an API because again, going with that running example of this contact lists cash withdrawal feature for a bank. The FBI wherever it sits on tram branch sas cloud, IOS android doesn't matter that FBI is your new security perimeter and the data object that is trying to access is also the new security perimeter. So if you can secure ap to ap communication and P two data object communication, you should be good. So that is the new frontier. But guess what? Software is buggy? Everybody's software not saying Cisco software, everybody's Softwares buggy. Uh software is buggy, humans are not reliable and so things mature, Things change, Things evolve over time. So there needs to be defense in depth. So you need to secure at the API layer had the data object layer, but you also need to secure at every layer below it so that you have good defense and depth if any layer in between is not working out properly. So for us that means ensuring ap to ap communication, not just during long time when the app has been deployed and is running, but during deployment and also during the development life cycle. So as soon as the developer launches an ID, they should be able to figure out that this API is security uses reputable. It has compliant, it is compliant to my my organization's needs because it is hosted, let's say from Germany and my organization wants a P is to be used only if they are being hosted out of Germany. So compliance needs and and security needs and reputation. Is it available all the time? Is it secure and being able to provide that feedback all the time between the security teams and the developer teams in a very seamless real time manner? Yes, again, that's something that we're trying to solve through some of the services that we're trying to produce in SAN Francisco. >>Yeah, I mean those that layered approach that you're talking about is critical because every layer has, you know, some vulnerability and so you you've got to protect that with some depth in terms of thinking about security, how should we think about where where Cisco's primary value add is, I mean it's parts of the interview has a great security business. Is growing business. Is it your intention to to to to add value across the entire value chain? I mean obviously you can't do everything so you've got a partner but so has the we think about Cisco's role over the next I'm thinking longer term over the over the next decade. >>Yeah, I mean I think so. We do come in with good strength from the runtime side of the house. So if you think about the security aspects that we haven't played today, uh there's a significant set of assets that we have around user security around around uh with with do and password less. We have significant assets in random security. I mean the entire portfolio that Cisco brings to the table is I don't run time security. The security checks aspects around posture and policy that will bring to the table. And as you see, Cisco evolve over time, you will see us shifting left. I mean I know it's an overused term, but that is where security is moving towards. And so that is where api security and data security are moving towards. So learning what we have during runtime. Because again, runtime is where you learn what's available and that's where you can apply all of the M. L. And I models to figure out what works what doesn't taking those learnings, Taking those catalogs, taking that reputation database and moving it into the deployment and development life cycle and making sure that that's part of that entire they have to deploy to runtime chain is what you will see Cisco do overtime. >>That's fantastic phenomenal perspective video. Thanks for coming on the cube. Great to have you and look forward to having you again. >>Absolutely. Thank you. Pleasure to be here. >>This is Dave Volonte for the cube. Thank you for watching. Mhm. >>Mhm mm.

(upbeat music) >> Narrator: From around the globe, it's theCUBE. Presenting Future Cloud. One event, a world of opportunities. Brought to you by Cisco. >> Okay. We're here with Thomas Scheibe, who's the vice president of Product Management, aka VP of all things Data Center Networking, STN, cloud, you name it in that category. Welcome Thomas, good to see you again. >> Hey, same here. Thanks for having me on. >> Yeah, it's our pleasure. Okay. Let's get right into observability. When you think about observability, visibility, infrastructure monitoring, problem resolution across the network, how does cloud change things? In other words, what are the challenges that networking teams are currently facing as they're moving to the cloud and trying to implement hybrid cloud? >> Yeah. (scoffs) Yeah. Visibility as always is very, very important and it's quite frankly, it's not just, it's not just the networking team, it's actually the application team too, right? And as you pointed out, the the underlying impetus to what's going on here is the, the data center is wherever the data is, and I think we said this a couple years back. And really what happens the, the applications are going to be deployed in different locations, right? Whether it's in a public cloud, whether it's on-prem and they're built differently, right? They're built as micro servers, so they might actually be distributed as well at the same application. And so what that really means is you need, as an operator as well as actually a user, a better visibility, "where are my pieces?", and you need to be able to correlate between where the app is and what the underlying network is, that is in place in these different locations. So you have actually a good knowledge why the app is running so fantastic or sometimes not. So I think that's, that's really the problem statement. What, what we're trying to go after with observability. >> Okay. Let's, let's double click on that. So, so a lot of customers tell me that you got to stare at log files until your eyes bleed, then you've got to bring in guys with lab coats who have PhDs to figure all this stuff out. >> Thomas: Yeah. >> So you just described, it's getting more complex, but at the same time, you have to simplify things. So how, how are you doing that? >> Correct. So what we basically have done is we have this fantastic product that is called ThousandEyes. And so what this does is basically (chuckles) as the name which I think is a fantastic, fantastic name. You have these sensors everywhere and you can have a good correlation on links between if I run a from a site to a site, from a site to a cloud, from the cloud to cloud. And you basic can measure what is the performance of these links? And so what we're, what we're doing here is we're actually extending the footprint of the ThousandEyes agent, right? Instead of just having a, an inversion machine of clouds we are now embedding them with the Cisco network devices, right? We announced this was the Catalyst 9000. And we're extending this now to our 8000 Catalyst product line for the for the SD-WAN products, as well as to the data center products, in Nexus line. And so what you see is, is you know, a half a thing, you have ThousandEyes. You get a million insights and you get a billion dollar off improvements for how your applications run. And this is really the, the power of tying together the footprint of what a network is with the visibility, what is going on. So you actually know the application behavior that is attached to this network. >> I see. So, okay. So as the cloud evolves, it expands, it connects, you're actually enabling ThousandEyes to go further, not just confined within a single data center location but out to the network across clouds, et cetera. >> Thomas: Correct. >> Wherever the network is you're going to have a ThousandEyes sensor and you can bring this together and you can quite frankly pick, if you want to say, Hey I have my application in public cloud provider A domain one, and I have another one in domain two I can do monitor that link. I can also monitor, I have a user that has a campus location or a branch location. I kind of put an agent there and then I can monitor the connectivity from that branch location all the way to the, let's say, corporation's data center or headquarter or to the cloud. And I can have these probes and just the, have visibility in saying, Hey, if there's a performance I know where the issue is. And then I obviously can use all the other tools that we have to address those. >> All right, let's talk about the cloud operating model. Everybody tells us that, you know, it's really the change in the model that drives big numbers in terms of ROI. And I want you to maybe address how you're bringing automation and DevOps to this world of hybrid and specifically, how is Cisco enabling IT organizations to move to a cloud operating model as that cloud definition expands? >> Yeah, no, that's that's another interesting topic beyond the observability. So it really, really what we're seeing, and this is going on for, I want to say couple of years now it's really this transition from operating infrastructure as a networking team, more like a service like what you would expect from a cloud provider, right? This is really around the networking team offering services like a cloud provided us. And that's really what the meaning is of cloud operating model, right? Where this is infrastructure running your own data center where that's linking that infrastructure was whatever runs on the public cloud is operating it like a cloud service. And so we are on this journey for a while. So one of the examples um that we have, we're moving some of the control software assets that customers today can deploy on-prem to an instance that they can deploy in a, in a cloud provider and just basically instantiate things there and then just run it that way. Right? And so the latest example for this is what we have, our Identity Service Engine that is now unlimited availability, available on AWS and will become available mid this year, both on AWS and Azure, as a service. You can just go to Marketplace, you can load it there and now increase. You can start running your policy control in the cloud managing your access infrastructure in your data center, in your campus, wherever you want to do it. And so that's just one example of how we see our Customers Network Operations team taking advantage of a cloud operating model and basically deploying their, their tools where they need them and when they need them. >> Dave: So >> What's the scope of I, I hope I'm saying it right, ISE, right? I.S.E, I think it's um, you call it ISE. What's the scope of that? Like for instance, to an effect my, or even, you know address, simplify my security approach? >> Absolutely. That's now coming to what is the beauty of the product itself? Yes. What you can do is really is, a lot of people talking about is, how do I get to a Zero Trust approach to networking? How do I get to a much more dynamic, flexible segmentation in my infrastructure, again, whether this was only campus access as well as the data center and ISE helps you there. You can use it as a pawn to define your policies and then inter-connect from there, right. In this particular case, we would, instead of ISE in a cloud as a software, alone, you now can connect and say, Hey, I want to manage and program my network infrastructure and my data center or my campus going to the respective controller, whether it's DNA Center for campus or whether it's the, the ACI policy controller. And so yes, what you get as an effect out of this is a very elegant way to automatically manage ,in one place, "what is my policy", and then drive the right segmentation in your network infrastructure. >> Yeah. Zero Trust. It was..Pre pandemic it was kind of a buzzword, now it's become a mandate. I, I wonder if we could talk about- >> Thomas: - Yes >> Yeah, right. I mean, so- >> Thomas: -Pretty much. >> I wondered if we could talk about cloud native apps. You got all these developers that are working inside organizations, they're maintaining legacy apps they're connecting their data to systems in the cloud. They're sharing that data. These developers, they're rapidly advancing their skillsets. How is Cisco enabling its infrastructure to support this world of cloud native, making infrastructure more responsive and agile for application developers? >> Yeah. So you were going to the talk we saw was the visibility. We talked about the operating model how our network operates actually want to use tools going forward. Now the next step to this is, it's not just the operator. How do they actually, where do they want to put these tools? Or how they interact with this tools? As well as quite frankly, as how let's say, a DevOps team, or application team or a cloud team also wants to take advantage of the programmability of the underlying network. And this is where we're moving into this whole cloud native discussion, right. Which has really two angles. So it's the cloud native way, how applications are being built. And then there is the cloud native way, how you interact with infrastructure, right? And so what we have done is we're A, putting in place the on-ramps between clouds, and then on top of it, we're exposing for all these tools APIs that can be used and leveraged by standard cloud tools or cloud-native tools, right? And one example or two examples we always have. And again, we're on this journey for a while, is both Ansible script capabilities that access from RedHat as well as Hashi Terraform capabilities that you can orchestrate across infrastructure to drive infrastructure automation. And what, what really stands behind it is what either the networking operations team wants to do or even the app team. They want to be able to describe the application as a code and then drive automatically or programmatically instantiation of infrastructure needed for that application. And so what you see us doing is providing all these capability as an interface for all our network tools, right. Whether this is ISE, what I just mentioned, whether this is our DCN controllers in the data center whether these are the controllers in the, in the campus for all of those, we have cloud-native interfaces. So operator or a DevOps team can actually interact directly with that infrastructure the way they would do today with everything that lives on the cloud or with everything how they built the application. >> Yeah, this is key. You can't even have the conversation of of Op cloud operating model that includes and comprises on-prem without programmable infrastructure. So that's, that's very important. Last question, Thomas, are customers actually using this? You made the announcement today. Are there, are there any examples of customers out there doing this? >> We do have a lot of customers out there that are moving down the path and using the Cisco High-performance Infrastructure both on the compute side, as well as on the Nexus side. One of the costumers, and this is like an interesting case, is Rakuten. Rakuten is a large telco provider, a mobile 5G operator in Japan and expanding, and as in different countries. And so people, some think, "Oh cloud" "You must be talking about the public cloud provider" "the big three or four". But if you look at it, there's a lot of the telco service providers are actually cloud providers as well and expanding very rapidly. And so we're actually very proud to work together with Rakuten and help them build high performance data center infrastructure based on HANA Gig and actually for a gig to drive their deployment to its 5G mobile cloud infrastructure, which is which is where the whole the whole world, which frankly is going. And so it's really exciting to see this development and see the power of automation visibility together with the High-performance infrastructure becoming a reality on delivering actually, services. >> Yeah, some great points you're making there. Yes, you have the big four clouds, they're enormous but then you have a lot of actually quite large clouds telcos that are either proximate to those clouds or they're in places where those hyper-scalers may not have a presence and building out their own infrastructure. So, so that's a great case study. Thomas.Hey, great having you on. Thanks much for spending some time with us. >> Yeah, same here. I appreciate it. Thanks a lot. >> All right. And thank you for watching everybody. This is Dave Vellante for theCUBE, the leader in tech event coverage. (upbeat music)

>>From around the globe. It's the cube present a future cloud one event, a world of opportunities brought to you by Cisco. >>Okay. We're here with Thomas Shabbat. Who's the vice president of product management, AKA VP of all things, data center, networking, SDN cloud, you name it in that category. Welcome Thomas. Good to see you again. >>Hey Sam. Yes. Thanks for having me on. >>Yeah, it's our pleasure. Okay. Let's get right into observability. When you think about observability visibility, infrastructure monitoring, problem resolution across the network, how does cloud change thing? In other words, what are the challenges that networking teams are currently facing as they're moving to the cloud and trying to implement hybrid cloud? >>Yeah. Yeah. Uh, visibility as always is very, very important. And it's perfect. It's not just, it's not just the network team is actually the application team too. Right. And as you pointed out, the, the underlying impetus to what's going on here is the data center is wherever the data is. And I think we set as a couple of years back and really what happens, the, the applications are going to be deployed, uh, in different locations, right? Whether it's in a public cloud, whether it's on prem, uh, and they're built differently, right? They are built as microservices. They might actually be distributed as well at the same application. And so what that really means is you need as an operator as well as actually a user, a bit of visibility where I, my pieces and you need to be able to correlate between where the Apres and what the underlying network is. That is a place at these different locations. So you have actually a good knowledge why the app is running so fantastic or sometimes not. So I think that's, that's really the problem statement, uh, what, what we tried to go after was the observability. >>Okay. Let's double click on that. So, so a lot of customers telling me that you got to stare at log files until your eyes bleed. And then you've got to bring in guys with lab coats who have PhDs to figure all this stuff out. So you just described, it's getting more complex, but at the same time, you have to simplify things. So how are you doing that? >>Correct. So what we basically have done is we have this fantastic product that is called thousand eyes. And so what does DAS is basically as the name, which I think is a fantastic, uh, fantastic name. You have these sensors everywhere. Um, and you can have a good correlation on, uh, links between if I run a, a site to a site from a site to a cloud, from a cloud to cloud, and you basically can measure what is the performance of these links? And so what we're, what we're doing here is we're actually extending the footprint of these thousand eyes agent, right. Instead of just having them, uh, in Virgin material clouds, we are now embedding them with the Cisco network devices, right. We announced this was the catalyst of 9,000. And we're extending this now to our, um, uh, 8,000 catalyst product line for the, for the sun products, as well as to the data center products, the next line. Um, and so what you see is, is there a half a thing you have sounds nice, you get a million insights and you get a billion dollar off improvements, uh, for how your applications run. And this is really, um, the, the power of tying together, the footprint of what a network is with the visibility, what is going on. So you actually know the application behavior that is attached to this network. >>I see. So, okay. So as the cloud evolves, it expands, it connects, you're actually enabling thousand eyes to go further, not just confined within a single data center location, but out to the network across clouds, et cetera, >>Correct. Wherever the network is, you're going to have a thousand eyes sensor and you can bring this together and you can quite frankly pick, if you want to say, Hey, I have my application in public cloud provider, a, uh, domain one, and I have another one domain, two, I can do monitor that link. I can also monitor, I have a user that has a campus location or branch location. I kind of put an agent there and then I can monitor the connectivity from that branch location, all the way to the let's say, corporations, that data center or headquarter, or to the cloud. And I can have these probes and just to be, have visibility and saying, Hey, if there's a performance, I know where the issue is. And then I obviously can use all the other sorts that we have to address those. >>All right, let's talk about the cloud operating model. Everybody tells us that, you know, it's, it's really the change in the model that drives big numbers in terms of ROI. And I want you to maybe address how you're bringing automation and dev ops to this world of, of hybrid and specifically, how is Cisco enabling it organizations to move to a cloud operating model as that cloud definition expands? >>Yeah, no, that's, that's another interesting topic beyond the observability. So really, really what we're seeing. And this has gone on for, uh, I want to say couple of years now, it's really this transition from, uh, operating infrastructure as a network and team more like a service, like what you would expect from a cloud provider, right? This is really around the network team, offering services like a cloud provided us. And that's really what the meaning is of cloud operating model, right? Where this is infrastructure running in your own data center, whether that's linking that infrastructure was whatever runs on the public cloud is operating at like a cloud service. And so we are on this journey for a while. So one of the examples, um, that we have removing some of the control software assets that customers today can deploy on prem, uh, to, uh, an instance that they can deploy in a, in a cloud provider and just basically instantiate saying, stay, and then just run it that way. >>Right? And so the latest example for this is what we have our identity service engine that is now unlimited availability available on AWS. And we will become available mid this year. Also data, we, as a visual, as a service, you can just go to marketplace, you can load it there and now increase. You can start running your policy control in a cloud, managing your X's infrastructure in your data center and your, uh, wherever you want to do it. And so that's just one example of how we see, uh, our customers' network operations team taking advantage of a cloud operating model, or basically deploying their, their tools where they need them and when they need them. So >>What's the scope of, I hope I'm saying it right, ice, right. ISC. I think they call it ice. What's the scope of that? Like for instance, 10 an effect my, or even, you know, address simplify my security approach. >>Absolutely. That's now coming to, what is the beauty of the product itself? Yes. Uh, what you can do is really is like, there's a lot of people talking, what I, how do I get to a zero trust approach to networking? How do I get to a much more dynamic, flexible segmentation in my infrastructure, again, whether this is on only campus X, as well as the data center and ice helps you there, you can use this as a point to, to find your policies and then any connect from there, right? In this particular case, we would instead ice in a cloud as a software, uh, load you now can connect and say, Hey, I want to manage and program my network infrastructure and my data center, or my campus going to the respect of controller with it's DNA center for campus, or whether does this, the, uh, ACI policy controller. And so, yes, what'd you get as an effect out of this is a very elegant way to automatically manage in one place. What does my policy, and then drive the right segmentation in your network infrastructure. Okay. >>Zero trust. It was pre pandemic. It was kind of a buzzword. Now it's become a mandate. I, I wonder if we could talk about yet, right. I mean, so I wonder, could talk about cloud native apps. Uh, you got all these developers that are working inside organizations, they're maintaining legacy apps, they're connecting their data to systems in the cloud. They're sharing that data. These developers they're rapidly advancing their skillsets. How is Cisco enabling its infrastructure to support this world of cloud native making infrastructure more responsive and agile for application developers? >>Yeah. So you were going to, the talk we saw was the visibility. We talked about the operating model, how our network operates, actually want to use tools going forward. Now the next step to visits, it's not just the operator. How do they actually, where do they want to put these tools? All they, how they interact with this tools as well as quite frankly, is how let's say a dev ops team on application team or a cloud team also wants to take advantage off the programmability of the underlying network. And this is where we moving into this whole cloud native discussion, right. Which has really two angles to, is the cloud native way, how applications are being built. And then there is the cloud native way, how you interact with infrastructure, right? And so what we have done as we're putting in place, the on-ramps between clouds, uh, and then on top of it, we're exposing for all these tools, API APIs that can be used and leveraged by standard cloud tools or, uh, uh, cloud native tools, right? >>And one example or two examples we always have. And again, we're on this journey for a while is, uh, both Ansible, uh, script capabilities, uh, that access from red hat, as well as, uh, Hashi Terraform capabilities that you can orchestrate across infrastructure to drive infrastructure automation. And what, what really stands behind it is what either the networking operations team wants to do, or even the app team. They want to be able to describe the application as a code and then drive automatically or programmatically in sedation of infrastructure needed for that application. And so what you see us doing is providing all these, uh, capability as an interface for all our network tools, right? Whether this is ice. What I just mentioned, whether this is our, uh, DCN controllers in the data center, uh, whether these are the controllers in the, uh, in the campus for all of those, we have cloud native interfaces. So, uh, operator or a dev ops team can actually interact directly with that infrastructure the way they would do today with everything that lives in the cloud, or was everything, how they built the application, >>You can't even have the conversation of, of op cloud operating model that includes and comprises on-prem without programmable infrastructure. So that's, that's very important. Last question, Thomas are customers actually using this? They made the announcement today. Are there any examples of customers out there doing this? >>We, we do have a lot of customers out there, um, that are moving down a path and using the D D Cisco high-performance infrastructure, also on the compute side, as well as on the next site. Uh, one of the customers, uh, and this is like an interesting case, is the Rakuten, uh, record in is a large type of provider, um, uh, mobile 5g operator, uh, in Japan and expanding and as in different countries. Uh, and so people, something, Oh, cloud, you must be talking about the public cloud provider, the big, the big three or four. Uh, but if you look at it as a lot of the tackles service providers are actually cloud providers as well and expanding very rapidly. And so we're actually very, um, proud to work together was, was Rakuten and in help them building a high performance, uh, data center infrastructure based on how they gig and actually phone a gig, uh, to drive their deployment to it's a 5g mobile cloud infrastructure, which is, which is, um, where the whole, the whole world where traffic is going. And so it's really exciting to see these development and see the power of automation, visibility, uh, together with the high performance infrastructure, becoming reality and delivering actually, uh, services. Yes. >>Some great points you're making there, but yes, you have the big four clouds are enormous, but then you have a lot of actually quite large clouds, telcos that are either proximate to those clouds or they're in places where those hyperscalers may not have a presence and building out their own infrastructure. So, so that's a great case study, uh, Thomas, Hey, great. Having you on. Thanks so much for spending some time with us. >>Yeah. The same here. I appreciate it. Thanks a lot. >>Thank you for watching everybody. This is Dave Volante for the cube, the leader in tech event coverage.

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