>> (bright music) >> Narrator: The Cube, presents Kubecon and Cloudnativecon, year of 2022, brought to you by Red Hat, the cloud native computing foundation and its ecosystem partners. >> Now what we're opening. Welcome to Valencia, Spain in Kubecon Cloudnativecon, Europe, 2022. I'm Keith Townsend, along with my host, Paul Gillin, who is the senior editor for architecture at Silicon angle, Paul. >> Keith you've been asking me questions all these last two days. Let me ask you one. You're a traveling man. You go to a lot of conferences. What's different about this one. >> You know what, we're just talking about that pre-conference, open source conferences are usually pretty intimate. This is big. 7,500 people talking about complex topics, all in one big area. And then it's, I got to say it's overwhelming. It's way more. It's not focused on a single company's product or messaging. It is about a whole ecosystem, very different show. >> And certainly some of the best t-shirts I've ever seen. And our first guest, Jim has one of the better ones. >> I mean a bit cockroach come on, right. >> Jim Walker, principal product evangelist at CockroachDB and Christian Huning, tech director of cloud technologies at Finleap Connect, a financial services company that's based out of Germany, now offering services in four countries now. >> Basically all over Europe. >> Okay. >> But we are in three countries with offices. >> So you're CockroachDB customer and I got to ask the obvious question. Databases are hard and started the company in 2015 CockroachDB, been a customer since 2019, I understand. Why take the risk on a four year old database. I mean that just sounds like a world of risk and trouble. >> So it was in 2018 when we joined the company back then and we did this cloud native transformation, that was our task basically. We had very limited amount of time and we were faced with a legacy infrastructure and we needed something that would run in a cloud native way and just blend in with everything else we had. And the idea was to go all in with Kubernetes. Though early days, a lot of things were alpha beta, and we were running on mySQL back then. >> Yeah. >> On a VM, kind of small setup. And then we were looking for something that we could just deploy in Kubernetes, alongside with everything else. And we had to stack and we had to duplicate it many times. So also to maintain that we wanted to do it all the same like with GitOps and everything and Cockroach delivered that proposition. So that was why we evaluate the risk of relatively early adopting that solution with the proposition of having something that's truly cloud native and really blends in with everything else we do in the same way was something we considered, and then we jumped the leap of faith and >> The fin leap of faith >> The fin leap of faith. Exactly. And we were not dissatisfied. >> So talk to me a little bit about the challenges because when we think of MySQL, MySQL scales to amazing sizes, it is the de facto database for many cloud based architectures. What problems were you running into with MySQL? >> We were running into the problem that we essentially, as a finTech company, we are regulated and we have companies, customers that really value running things like on-prem, private cloud, on-prem is a bit of a bad word, maybe. So it's private cloud, hybrid cloud, private cloud in our own data centers in Frankfurt. And we needed to run it in there. So we wanted to somehow manage that and with, so all of the managed solution were off the table, so we couldn't use them. So we needed something that ran in Kubernetes because we only wanted to maintain Kubernetes. We're a small team, didn't want to use also like full blown VM solution, of sorts. So that was that. And the other thing was, we needed something that was HA distributable somehow. So we also looked into other solutions back at the time, like Vitis, which is also prominent for having a MySQL compliant interface and great solution. We also got into work, but we figured, this is from the scale, and from the sheer amount of maintenance it would need, we couldn't deliver that, we were too small for that. So that's where then Cockroach just fitted in nicely by being able to distribute BHA, be resilient against failure, but also be able to scale out because we had this problem with a single MySQL deployment to not really, as it grew, as the data amounts grew, we had trouble to operatively keep that under control. >> So Jim, every time someone comes to me and says, I have a new database, I think we don't need it, yet another database. >> Right. >> What problem, or how does CockroachDB go about solving the types of problems that Christian had? >> Yeah. I mean, Christian laid out why it exists. I mean, look guys, building a database isn't easy. If it was easy, we'd have a database for every application, but you know, Michael Stonebraker, kind of godfather of all database says it himself, it takes seven, eight years for a database to fully gestate to be something that's like enterprise ready and kind of, be relied upon. We've been billing for about seven, eight years. I mean, I'm thankful for people like Christian to join us early on to help us kind of like troubleshoot and go through some things. We're building a database, it's not easy. You're right. But building a distributor system is also not easy. And so for us, if you look at what's going on in just infrastructure in general, what's happening in Kubernetes, like this whole space is Kubernetes. It's all about automation. How do I automate scale? How do I automate resilience out of the entire equation of what we're actually doing? I don't want to have to think about active passive systems. I don't want to think about sharding a database. Sure you can scale MySQL. You know, how many people it takes to run three or four shards of MySQL database. That's not automation. And I tell you what, this world right now with the advances in data how hard it is to find people who actually understand infrastructure to hire them. This is why this automation is happening, because our systems are more complex. So we started from the very beginning to be something that was very different. This is a cloud native database. This is built with the same exact principles that are in Kubernetes. In fact, like Kubernetes it's kind of a spawn of borg, the back end of Google. We are inspired by Spanner. I mean, this started by three engineers that worked at Google, are frustrated, they didn't have the tools, they had at Google. So they built something that was, outside of Google. And how do we give that kind of Google like infrastructure for everybody. And that's, the advent of Cockroach and kind of why we're doing, what we're doing. >> As your database has matured, you're now beginning a transition or you're in a transition to a serverless version. How are you doing that without disrupting the experience for existing customers? And why go serverless at all? >> Yeah, it's interesting. So, you know, serverless was, it was kind of a an R&D project for us. And when we first started on a path, because I think you know, ultimately what we would love to do for the database is let's not even think about database, Keith. Like, I don't want to think about the database. What we're building too is, we want a SQL API in the cloud. That's it. I don't want to think about scale. I don't want to think about upgrades. I literally like. that stuff should just go away. That's what we need, right. As developers, I don't want to think about isolation levels or like, you know, give me DML and I want to be able to communicate. And for us the realization of that vision is like, if we're going to put a database on the planet for everybody to actually use it, we have to be really, really efficient. And serverless, which I believe really should be infrastructure less because I don't think we should be thinking of just about service. We got to think about, how do I take the context of regions out of this thing? How do I take the context of cloud providers out of what we're talking about? Let's just not think about that. Let's just code against something. Serverless was the answer. Now we've been building for about a year and a half. We launched a serverless version of Cockroach last October and we did it so that everybody in the public could have a free version of a database. And that's what serverless allows us to do. It's all consumption based up to certain limits and then you pay. But I think ultimately, and we spoke a little bit about this at the very beginning. I think as ISVs, people who are building software today the serverless vision gets really interesting because I think what's on the mind of the CTO is, how do I drive down my cost to the cloud provider? And if we can basically, drive down costs through either making things multi-tenant and super efficient, and then optimizing how much compute we use, spinning things down to zero and back up and auto scaling these sort of things in our software. We can start to make changes in the way that people are thinking about spend with the cloud provider. And ultimately we did that, so we could do things for free. >> So, Jim, I think I disagree Christian, I'm sorry, Jim. I think I disagree with you just a little bit. Christian, I think the biggest challenge facing CTOs are people. >> True. >> Getting the people to worry about cost and spend and implementation. So as you hear the concepts of CoachDB moving to a serverless model, and you're a large customer how does that make you think or react to your people side of your resources? >> Well, I can say that from the people side of resources luckily Cockroach is our least problem. So it just kind of, we always said, it's an operator stream because that was the part that just worked for us, so. >> And it's worked as you have scaled it? without you having ... >> Yeah. I mean, we use it in a bit of a, we do not really scale out like the Cockroach, like really large. It's like, more that we use it with the enterprise features of encryption in the stack and our customers then demand. If they do so, we have the Zas offering and we also do like dedicated stacks. So by having a fully cloud native solution on top of Kubernetes, as the foundational layer we can just use that and stamp it out and deploy it. >> How does that translate into services you can provide your customers? Are there services you can provide customers that you couldn't have, if you were running, say, MySQL? >> No, what we do is, we run this, so the SAS offering runs in our hybrid private cloud. And the other thing that we offer is that we run the entire stack at a cloud provider of their choosing. So if they are an AWS, they give us an AWS account, we put it in there. Theoretically, we could then also talk about using the serverless variant, if they like so, but it's not strictly required for us. >> So Christian, talk to me about that provisioning process because if I had a MySQL deployment before I can imagine how putting that into a cloud native type of repeatable CICD pipeline or Ansible script that could be difficult. Talk to me about that. How CockroachDB enables you to create new onboarding experiences for your customers? >> So what we do is, we use helm charts all over the place as probably everybody else. And then each application team has their parts of services, they've packaged them to helm charts, they've wrapped us in a super chart that gets wrapped into the super, super chart for the entire stack. And then at the right place, somewhere in between Cockroach is added, where it's a dependency. And as they just offer a helm chart that's as easy as it gets. And then what the teams do is they have an inner job, that once you deploy all that, it would spin up. And as soon as Cockroach is ready it's just the same reconcile loop as everything. It will then provision users, set up database schema, do all that. And initialize, initial data sets that might be required for a new setup. So with that setup, we can spin up a new cluster and then deploy that stack chart in there. And it takes some time. And then it's done. >> So talk to me about life cycle management. Because when I have one database, I have one schema. When I have a lot of databases I have a lot of different schemas. How do you keep your stack consistent across customers? >> That is basically part of the same story. We have get offs all over the place. So we have this repository, we see the super helm chart versions and we maintain like minus three versions and ensure that we update the customers and keep them up to date. It's part of the contract sometimes, down to the schedule of the customer at times. And Cockroach nicely supports also, these updates with these migrations in the background, the schema migrations in the background. So we use in our case, in that integration SQL alchemy, which is also nicely supported. So there was also part of the story from MySQL to Postgres, was supported by the ORM, these kind of things. So the skill approach together with the ease of helm charts and the background migrations of the schema is a very seamless upgrade operations. Before that we had to have downtime. >> That's right, you could have online schema changes. Upgrading the database uses the same concept of rolling upgrades that you have in Kubernetes. It's just cloud native. It just fits that same context, I think. >> Christian: It became a no-brainer. >> Yeah. >> Yeah. >> Jim, you mentioned the idea of a SQL API in the cloud, that's really interesting. Why does such a thing not exist? >> Because it's really difficult to build. You know, SQL API, what does that mean? Like, okay. What I'm going to, where does that endpoint live? Is there one in California one on the east coast, one in Europe, one in Asia? Okay. And I'm asking that endpoint for data. Where does that data live? Can you control where data lives on the planet? Because ultimately what we're fighting in software today in a lot of these situations is the speed of light. And so how do you intelligently place data on this planet? So that, you know, when you're asking for data, when you're maybe home, it's a different latency than when you're here in Valencia. Does that data follow and move you? These are really, really difficult problems to solve. And I think that we're at that layer of, we're at this moment in time in software engineering, we're solving some really interesting, interesting things cause we are budding against this speed of light problem. And ultimately that's one of the biggest challenges. But underneath, it has to have all this automation like the ease at which we can scale this database like the always on resilient, the way that we can upgrade the entire thing with just rolling upgrades. The cloud native concepts is really what's enabling us to do things at global scale it's automation. >> Let's alk about that speed of light in global scale. There's no better conference for speed of light, for scale, than Kubecon. Any predictions coming out of the show? >> It's less a prediction for me and more of an observation, you guys. Like look at two years ago, when we were here in Barcelona at QCon EU, it was a lot of hype. It's a lot of hype, a lot of people walking around, curious, fascinated, this is reality. The conversations that I'm having with people today, there's a reality. There's people really doing, they're becoming cloud native. And to me, I think what we're going to see over the next two to three years is people start to adopt this kind of distributed mindset. And it permeates not just within infrastructure but it goes up into the stack. We'll start to see much more developers using, Go and these kind of the threaded languages, because I think that distributed mindset, if it starts at the chip all the way to the fingertip of the person clicking and you're distributed everywhere in between. It is extremely powerful. And I think that's what Finleap, I mean, that's exactly what the team is doing. And I think there's a lot of value and a lot of power in that. >> Jim, Christian, thank you so much for coming on the Cube and sharing your story. You know what we're past the hype cycle of Kubernetes, I agree. I was a nonbeliever in Kubernetes two, three years ago. It was mostly hype. We're looking at customers from Microsoft, Finleap and competitors doing amazing things with this platform and cloud native in general. Stay tuned for more coverage of Kubecon from Valencia, Spain. I'm Keith Townsend, along with Paul Gillin and you're watching the Cube, the leader in high tech coverage. (bright music)

(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)

>>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)

(soft music) >> Hey, welcome back to theCUBE's coverage from Miami of IFS Unleashed 2022, Lisa Martin here with you. We've had great conversations today with IFS execs, customers, partners. Our ecosystem is quite robust and quite strong. And we've had some alumni on, I've got another alumni who's back with me, Michael Ouissi, the group's COO of IFS. Michael, welcome back to theCUBE. >> Thanks for having us, my pleasure. >> It's great to be back in-person. >> Absolutely. >> It was great to walk into the keynote this morning and see a full room. I was talking with Darren Roos, your CEO earlier this morning and I said, it must have felt great to walk out on stage and actually see a sea of people and customers and partners who want to engage and get that relationship with IFS just turbocharged. >> Absolutely, I mean, it's been three years, we haven't had this buzz, this energy, and the opportunity to actually see all our customers and also show our customers who we are, how we are evolving and how we're becoming a different company over the past four years. >> And it's impressive what IFS has done in that timeframe. All the conversations I've had today, really reflect the strategy, the strong strategy and vision that this company has. But I was looking at some of the financials and saw that your first half of 2022, which ended in June, there was tremendous growth. ARR up 33%, I think they're recurring revenue is in the 70 percentile now. Lot of new customers, a lot of of trust that existing customers are showing to the company. >> Yeah, absolutely. Look, and I think the secret sauce is that we have focused on where our strengths are, we haven't gone astray, we haven't tried to actually capture growth in any other vertical. We are really very religious about where we're going and there, where we are going, we are going deep and we really are trying to be the best version of ourselves for our customers and for those customers' business transformation needs. >> Talk a little bit about that vertical specialization. It's something that we don't see very often but throughout all of my conversations today with your executives, IFS executives, with customers, with partners, that domain expertise, really the granularity of the domain expertise is really resonant that IFS has achieved that in those five key verticals in which you have such specialization. >> Yeah, look, I mean, I would love to take credit for having been the person who has done that, but IFS has over the past 35 years, really had this very strong focus. But what actually was important when you try to double a business in the space of four years, not to be tempted to go away from that but actually double down on exactly that and see the opportunity in those verticals and make sure that our customers actually are getting the attention and the functionality they deserve. >> Let's talk about customers. Over 10,000 customers right now. I was also in the keynote this morning where Christian Peterson was sharing that, in its first 18 months, IFS Cloud has over 400,000 users. So the growth is tremendous. The customer loyalty is ostensible in those verticals. Talk about customers and their influence on the company, the direction the technology goes, the evolution, that kind of stuff. >> Yeah, I mean, look, as I said, we are all about the depth of the functionality and that means that we need to listen to our customers, We need to listen what's going on in the industries. We also need to not just listen but we need to think forward. >> Yeah. >> We need to have some thought leadership on what we think is going to emerge and then test that with our customers again. So our customers are at the core of everything we do. When we engage with a customer, we start with trying to understand their business in depth. We've got our own methodology around that and we don't just try to push technology onto them, but we are trying to understand what are their business drivers and then actually try to apply technology to what enables them to deliver on those business transformation objectives they've got. >> What are some of the changes or the waves that you've seen, especially the last couple of years during the pandemic when we saw so many customers pivot, we need to transform digitally to stay alive, and then those that did that well enough to be competitive and to thrive, talk to me about some of the changes as the group's COO that you've seen. >> Yeah, so when you go back, I mean, there's two types of transformation, business and digital transformation but they are the same thing, they're just a different side of the coin. And when I talk about business transformation, what we're seeing a lot is, and there's this big buzzword overtization out there, but customers going service and customers trying to build an end to end business that is more viable, more sustainable, more successful in how they develop great moments of service for their customers, that is something we are seeing a lot. And during this business transformation, digital transformation has become a means to that end. And that is something where customers have matured a lot, where in the past we have seen a lot of the IOT, AI, machine learning, cloud, everything was a means or a purpose in itself and that has changed. It's now become actually a means to an end. It's become a means to actually deliver a business transformation and a business outcome that is meaningful for their customers. >> Has to be meaningful for their customers. I love how IFS talks about enabling your customers to deliver those moments of service. And when we think of, in our consumer lives, many of us flew here, and you think about what's the moment of service for an airline? Well, it's being able to get on that plan on time, have it leave on time and meet my expectations as a demanding consumer. But regardless if we're talking about aerospace, energy, manufacturing, engineering, the customers on the other end expect to have an integrated seamless experience that's not fragmented, that is able to deliver moments of service that then help drive up their revenue. So what IFS is doing is so embedded in what your customers are able to deliver to their customers. >> Yeah, absolutely. And look, if you look at all the things that have to come together to actually have a plane taken off at the right point in time or if you take any other examples, but there's so many things that need to go right. Crew scheduling, you need to have the right crew at the right point in time. You need to have them actually with the right experience to fly the right plane. You need to have airplane maintenance going right to have the plane available at the right point in time and no technical failures and so on and so forth. And we look at that as between customers, the people, and the assets that an organization has, you need to coordinate between all those dimensions in everything you do to make sure that this one moment of service where your plane takes off on time, you actually catch your connecting flight at the other end, that this actually is being delivered. And that's what drives us, that's what customers are driving into our product development, into how we embed AI, machine learning and so on in our technology to make it relevant to exactly that moment of service. >> That's what we as those consumers want. We want relevance, we want personalization, we want that relationship to know who we are and how to serve us best. Let's dig into the Jotun case study. He was going to join us, our CEO was going to join us, couldn't make it. Talk to me a little bit about Jotun, what type of business is it and then let's kind of start unpacking how they're leveraging IFS technology. >> Yeah, so Jotun is the seventh largest paints and coatings manufacturer in the world. And they've got obviously a home decoration part of the business, but they've got an industrial part of the business where one large part of the business is also a marines part. So they actually provide paints, coating, for all sorts of large ships and it's quite astonishing what you learn about that customer. I mean, we are now partnering with them for more than 20 years, so we are very intimate with that customer obviously. But when you see all of a sudden, three, four years ago, they started going onto a journey where they looked at apart from paint and coating, what actually can I provide to my customer in the marine industry to actually make their business more efficient, to actually make it easier for them to get a ship from A to B in an efficient way, in a timely way and so on. And they developed something called Hull Skating Solutions and those Hull Skating Solutions are integrating all sorts of weather data, all sorts of other data and provide them to the marine companies that actually then help them drive this... Well, actually get this ship in a more efficient way from A to B. And at the same time, also where there's predictions as to when you need to clean that ship, and they've got Hull Skating Solutions, which then actually clean the ship automatically as well. So it's quite an astonishing thing for a paints and coating manufacturer to then think about what do I need to know about my customer's business to provide that additional service to my customer? Great solution and great way of dealing with or delivering that great moment of service to their customers. >> Absolutely, the evolution of that business from paint manufacturing into the marine industry is not a stretch based on how you described it, but it's very innovative. How is IFS enabling them to do that and do it well? >> Well, one, they went on a modernization program for all their factories for all these kinds of things that they need to integrate then deliver to their customers. And we are in the central part in being that agile partner that actually delivers those technology solutions that enable them to, well, first of all think about that service, provide that service to their customers and make sure that they run a very efficient, very integrated version of IFS and can actually harmonize globally to make sure that wherever the customer is, they can deliver on that promise. >> Fantastic, let's talk a little bit about from your team's perspective, the go to market. We talked about the five verticals in which IFS specializes energy, aerospace and defense, engineering, manufacturing and there's one I'm missing. >> Utilities. >> Utilities, of course. >> Yeah. >> In terms of the domain expertise, are there vertical teams that are focused? I imagine that there are, talk to me a little bit about that specialization from that lens. So obviously, I mean, there are so many dimensions. There's our sales teams, there's our pre-sales teams, there's our industry teams which actually are working with the customers on receiving their feedback, on actually providing thought leadership and then organizing the feedback loop into our development teams who are providing these solutions then that hopefully our customers will cherish. So we are very specialized in that respect. We are driving the industry specialization. We've got a complete aerospace and defense business unit. We are in the market unit, specializing in the industries where we work in the various different territories with just those industry teams. We've got specialization in the pre-sales teams. So we take that really deep down and very seriously to make sure that whenever we talk to a customer, we also have the understanding and we have also got the curiosity to understand more of the customer's business, and that is something that is part of the IFS DNA. >> It's a differentiating part of IFS' DNA that not only having the domain expertise, and a lot of people talk about, well, we got to meet the customer where they are, wherever they are digitally, wherever they are in business transformation. But you're actually talking the customer's language. >> Yeah. >> By industry, which I would imagine really helps to not only solidify that relationship, but you actually get to really do a double click and get much more tightly connected with the customers and the outcomes that they're wanting to achieve so that those moments of service happen. >> Well, that's so true. And actually this is not just while we are selling to the customers, but it's actually throughout the whole life cycle of this application and the technology in Jotun's case more than two decades. And we've got a lot of customers who are actually that long with us because we don't run away once we've implemented a solution, but we actually stay close to it because first of all, we want to learn from our customers continuously. We want to actually give to our customers also what we are learning outside of the conversations we have with these customers. And we make sure that these customers continuously evolve how they think about their business, how they think about the application of our technology and then in turn, we can actually develop technology again, for their use cases. >> It's a flywheel. >> It's a complete flywheel and that creates loyalty. >> Yeah. >> That actually creates the longstanding relationships we have with many, many of our customers, yeah. >> I was speaking with a number of your executives, Marni Martin was here and we were talking about brand recognition and the loyalty, but that intimate customer knowledge that IFS really works hard to gain with its customers. 'Cause as consumers, we bleed into our business lives and we have very little tolerance, very little patients. I think that was one of the things in COVID that went away. People were just not tolerating this rapid change and we had no choice. But I don't know that patience is going to come back at the level in which we experienced it before COVID. So customers expect businesses and brands to know them and help anticipate what's next for me, how do I get there? And it sounds to me like IFS has really nailed that from a customer relationship perspective. >> As I said, I mean it's really part of our DNA and we try to preserve that culture while we're doubling our business and hopefully, doubling our business in the next three years again, because that is really the secret sauce to being that successful, and not only with our existing customers, but also with the net new customers. And we are driving almost 50% of our revenue, which is very, very much a benchmark in the industry from net new customers that we're winning while we're actually keeping or staying close to our existing customers and try to apply that knowledge to our net new customers. >> Yeah. >> But it's something that we absolutely have to preserve to be as successful as we've been in the past four years, also in the next four years. >> So coming off a great first half in the summer, when I teased Darren, "Any nuggets you want to say?" He said financials for Q3 are coming out in the next couple of weeks. And I said, I imagine that trajectory is up and to the right. >> Yeah. >> What are some of the things, Michael, that excite you for where you've seen this company go in your time there and the rocket ship that it seems to be on today? >> Yeah, look, I mean, what's amazing to me is... And if I look back, I joined four and a half years ago, and only the first one and a half years were under normal circumstances. >> Right. >> The other three years were a major pandemic, now a major war and recession and we've got all sorts of economic and macroeconomic headwinds. And what what impresses me about the company, about our customers, about our employees is the resilience we've got to just carry on with what we're doing. And I mean, I don't give too much away when I say we had a pretty good Q3 as well, and we are looking forward to a really good 2022 as a full year, and there are no excuses that actually the organization makes, it has just taken along. And we are facing the economic headwinds and we are going through that time hugely successful. And I'm very optimistic about the year and about 2023 as much. >> Fantastic, it's kind of hard to believe that calendar year 2023 is literally around the corner. But Michael, it's been great having you on theCUBE. Thank you for coming back, talking about what's going on at IFS from the overall COO's perspective, the customer synergies that IFS has, the work that you do to really get granular in those industries, it's impressive and congratulations on the success. We'll have to have you back next year to talk about what else is new. >> Thank you very much, Lisa. >> All right, my pleasure. >> Thank you. >> For Michael Ouissi, I'm Lisa Martin, you're watching theCUBE's coverage live from Miami on the show floor of IFS Unleashed. We'll be back with our final guest in just a minute. (soft music)

(soft electronic music) >> Hey, everyone. Welcome to Miami. I feel like I should be singing that song. Lisa Martin here live with theCUBE at IFS Unleashed. We've been here all day having great conversations with IFS executives, their customers, their partners, lots a... You can hear probably the buzz behind me at the vibe here. Lot of great folks, 1500 plus here. People are excited to be back and to see what IFS has been up to the last few years. I'm pleased to welcome back one of our alumni who was here with us last time we covered IFS, Marne Martin joins us. The president, Service Management, EAM and Global Industry at IFS. Marne, it's great to have you back on theCUBE. >> Yeah, I'm so happy to be here, and thanks for joining us in Miami. Last time it was Boston. >> That's right. >> So definitely much warmer climate this time. >> Much warmer. (Marne laughs) Yes, much warmer. And people here are just smiles on faces. People are excited to be back. There's... But I shouldn't elude that IFS slow down at all during the pandemic. You did not. I was looking at the first half, 2022 financials that came out over the summer and AR are up 33%. So much recurring revenue as well. So your... The business is doing incredibly well. You've pivoted beautifully during the pandemic. Customers are happy. There's a lot of customers here. You guys talk a lot about the moment of service. I love that. Talk to the audience about what that is, and how you're enabling your customers to deliver that to their customers. >> Definitely. So, you know, it's amazing when you have these inflection points and it's a good opportunity, world conference to world conference to celebrate that. We've grown a lot, and the number of customers we've brought in, in tier one global customers as well as in our variety of the various regions around the world and different industry verticals is amazing. And, you know, the participation is what's making IFS be a better company, a better technology vendor as we focus on these industries. So is understanding moment of service. You know, we talk a lot, and certainly CIOs and IT buyers will talk about technology, but putting the technology to work has to be meaningful, not only to the returns that go to shareholders, but what it matters, what matters to the end customers, of our customers. And when we started thinking about the new branding of IFS, because we also rebranded in this time, we thought, "How does that mission crystallize in what we're doing for our customers, and how do we really start put bringing technology to life?" And that is where moment of service came. So it's very rare in our world that you actually come up with a sort of slogan or an objective as a company that not only mobilizes what we do internally here at IFS, delivering great moments of service to our customers, but also that tells a story of the customers to the end customer. You know, service, an area that I work in a lot, it's very obvious that you... We all know when we get a great moment of service, or sometimes a bad moment of service. So if you talk to service organizations, field service organizations, they understand what a moment of service is. But it's also thinking about how we enable the people delivering that great moment of service. Not just like doing a survey or what have you, but what are the digital tools that help them to deliver better moments of service proactively. >> Right. >> One of my pet peeves was always that even like, if you have a voice of the customer program or what have you, that you may get that reactive feedback perhaps to a CMO in an organization, but the insights don't really get actioned. So here, across the line of business applications that we sell, ERP Service Management, EAM, ITSM, or ESM, we're really thinking about with that moment of service, the objective of putting the technology to work. How do we facilitate that alongside the business growth of our customers, but also how do we take the insights they get from their end customers into the business models as well as the functional design, what we develop. So moment of service has become, say the heart of IFS as well as a way of understanding our customers better. >> Really understanding them at much deeper level- >> Correct. Correct. >> And a lot of organizations. Give me some examples of some of the insights that IFS has gleaned from its customers. How you've brought them internally to really evolve the technology. >> So I think what's important is a lot of times technology vendors may say they know their customers, right? If you think about what technology vendor we know with the 360 view of the customer. You know, understanding the customer is a lot more than understanding their renewal date as a software vendor. >> Yeah. (laughs) >> So we have to really think about the moments of service on what matters most at that point of service, right? And it will vary certainly by industry, but there also will be certain things that are very much the same. Like for example, if we, as a customer, can have an asset or a piece of equipment that never breaks, we're a happier customer. If it does break, we, of course, want it to be fixed the first time someone shows up. So those are the obvious things. But how you then fix or manifest that into a different way of utilizing and implementing the technology. Thinking also about taking the operational insights that you have on driving, what we call preventative or predictive maintenance, or maximizing what's called a first time fixed resolution. You know, being able to marry best practices with at times artificial intelligence and machine learning information, with also the operational and personal insights of the people doing the work really enriches the quality of the insights you have around that moment of service and how to recreate a great moment of service, or lessen a poor moment of service. >> Yeah. >> And it also changes a view of what are often IT-driven projects into what's the user feedback that also matters most to enable that. You know, with the talent shortage that we're seeing, you know, customer expectations have only increased. >> Yes. >> So we all know, and customers want great moments of service, but how do we enable the frontline workers, whether they're field service workers or others, to deliver against these expectations when they might be harried, and you know, having to do a lot more work because of talent shortage. So we want to think about what their needs are in a way that's more focused towards delivering that moment of service, that great customer experience. And of course, that always feeds back into brand loyalty, selling more profits, but really getting into it. And you know, the advantage of IFS is that we understand the domain expertise to do things from a UI UX, a business process, but also thinking about how we're developing, to answer your question, the artificial intelligence machine learning. Even thinking about how you put IoT to work in ways that really matter, because there's a lot of money spent on IT projects that actually don't deliver great moments of service, let alone actual business value. >> Right. I love the vertical specialization that IFS has. I was interviewing Darren Roos, your CEO, a little bit earlier today and I said, "You know, we see so many companies... So many vendors, like some of your competitors in the ERP Space, which whom you're outgrowing or growing faster than, or horizontally focused. And the vertical specialization that he was kind of describing how long it's been here really allows IFS to focus on its core competencies. But another thing that I'm hearing throughout the interviews I'm having today, and you just said the same thing, is that you're not just, "We need to meet the customer where they are." Everyone talks about that. You've actually getting the... You're developing and fostering the domain expertise. >> Yes. >> So whether you're talking with an energy company, aerospace and defense company, manufacturing, there's that one to one knowledge within IFS and its customer, or based in that industry that it can only imagine is maybe part of what's leading to, you know, that big increase in ARR that I talked about, the recurring revenue being so high. That domain expertise seems to be a differentiator from my lens. >> Well, let's even talk about how people build relationships, right? You know, we're having a conversation, so we're already having a higher value relationship, right? And that comes through with how vendors engage with their customers. You know, when you have seen your executives like Darren and myself, and Michael and Christian, who still care and really focus on what is most impactful. What is that moment of service? I'm sure Darren talked about the great moment of service book that we just released. >> Yes. >> So understanding at a more visceral and may I say, intimate moment with the customers, what matters most to them. And really working with what are developing, what we call the digital dream team within these customers that understand enough of where they're going in the objective, enables us to do a better job. And it's also where then, it's not only how we're partnering in the sales process implementation in the conventional ways, but product management. What is the most meaningful? How can we prioritize what makes the most impact? Obviously, there's cool stuff we want to do too, but you know, we really think about understanding the verticals and understanding where they're going. And you see that, for example, we're an absolute leader in mobile workforce management specifically, where we have what's called real time optimization. Super hard to do. No one else does it anymore except us. Great. There's other things where you'd say that, "Hey, some of the other vendors talk about this, right?" APM as a performance management or other things, but because they lack the true vertical specialization and the use cases and the ease to put it in, the adoption rate is low. >> Yeah. >> So, you know, in that case, APM might not be something we do only, but if we can actually help commercialize this, something that has a great deal of value in a superior way in that focus verticals, that's what it means to have industry specialization. Because if you spread yourself too thin, you know then, you'll end up with an AI or machine learning platform or something like that that you know, most companies don't have five years to try and configure, build out a Watson or something like that. I mean, most companies in this day and age, with the requirements of competitive pressure and supply chain pressures have to be nimble and have to be getting results fast. So the closest with the customers, the domain expertise, the understanding of what matters most, helps us to be faster to the value outcomes that our customers needs. It helps us to be more focused in what we're developing and also how we're developing. And ultimately, that does benefit us that, you know, we want to make sure that we're not only leading today, but you know, staying ahead of the game in the next 5 to 10 years, which will help us to grow. You know, we're certainly not a small company anymore. We're at a billion in revenue looking to be 2 billion and eventually 5 billion in revenue. >> Okay. >> So that already, you know, puts us well beyond unicorn status into one of the very few. But, you know, we want to take a different track even of how a service now or a sales force or SAP or even, you know, to some degree workday grew by making sure that we remain focused on these key verticals and not lose our focus. And they're plenty big enough verticals for us to achieve our growth goals. >> Well the growth has been impressive, as I mentioned the ARR app in the first half, and I was chatting with Darren earlier as I said, and I said, "Can you gimme any nuggets for a second half?" I imagine the trajectory is up onto the right. And he alluded to the fact that things are going quite well, but the focus there that you have with customers. Also, you talked about this and I had several customers on the program today. Rolls-Royce was here. Aston Martin was here. And it's very obvious that there is a... There was a uniqueness about the relationship that I saw- >> Yes. >> Especially with Rolls-Royce that I thought was quite, I mean, you talked about kind of that customer intimacy and that personalization, which people used to tolerate fragmented experiences. We don't tolerate those anymore. >> No. >> Nobody has the patience for that. >> No. And it's also, you know, this business isn't easy for a lot of these customers to stay ahead, right? You know, especially if you think about a tier one customer that's at the top of their category. How did they continue to innovate? And Rolls Royce and Aston Martin are really cool customers. You know, but we're also thinking about, you know, what are the up-and-comers? Or you know, we also get customers that have come to us because they've started falling behind in their sector because they haven't been able to digitalize and grow forward. You know, we work a lot with SAP customers. Darren, of course, came from SAP. But in that ecosystem and especially in the areas I work in a lot with service management, SAP customers, you know, that are focusing on ERP, you know, SAP hasn't been a great enabler of service management for them. So the SAP customers have actually fallen behind. And the ability to come to a lot of these new type of digitally based value-based service offerings really make aftermarket service revenues a lifeblood of their company. So even there where, you know, we might have in a different ERP choice, we're able to provide what's really the missing link for these tier one companies that they can't get anywhere else. And we see this also, you know, you've obviously Salesforce and CRM. A lot of Salesforce CRM customers. Microsoft with Dynamics also primarily ERP. But the focus and the specialization that we have is rare in the industry, but it's so impactful. >> Yeah. >> And you know, I would even venture to say that there's not a tier one company that has a lot of aftermarket service revenue, or attention on service revenue, or even that is trying to monetize their connected asset or IoT investment that can ignore IFS. >> Yeah. >> Because we are unique enough in our focus verticals that if they want to continue growing and that is a cornerstone of their growth, their customer, their moment of service, then they definitely need to look at IFS. >> Absolutely. Does IFS care that it's not as well known of a brand? I mean, I mentioned you guys are growing. Maybe I didn't mention this, number three in ERP, you are growing faster than the top two biggest competitors, which you mentioned SAP, Oracle as well, but those implementations can be quite complex. Does IFS care that you're doing so well? Darren talked about where you're winning, how you're being competitive, where you went. Do they care about being a big name brand, or is that really kind of not as important nearly as delivering those moments of service? >> So, you know, it's a mirrored question that you asked me, and therefore, I'll give you a multifaceted answer. (Lisa laughs) You know, ERP, we're very proud to be a top three vendor and I think over time we'll continue to dislodge SAP and Oracle in ERP, where companies want to make a different ERP choice, or they're consolidating or whatever. I think already in field service management, we're by far the number one and will continue to be that. And you actually see a lot of our ERP competitors that are dropping down and you seem a... There's not really a lot of what I'd call best-of-breed options other than IFS as well. So... And then enterprise asset management, I really think the opportunity for IFS is how we put technology to work in some of these advanced capabilities in ways that can be automated that is, for example, in IBM Maximo or Watson or what have you haven't been able to be. And then you have some other best-of-breed EAM customers that have kind of not continued innovating and things like that. So the lines where we are really building the brand recognition with the largest companies in the world might be anchored for now more around field service management, enterprise asset management. But of course that brand recognition comes back into ERP. >> Yeah. >> And there will be, you know, as we continue to innovate, as people make ERP decisions every 5, 7, 10 years as those buying cycles are, then it's important that we're using the leadership positions we have. And especially, you know, thinking about these verticals where the asset centric service nature is paramount to them either to meet their moment of service, or to meet their aftermarket service revenue goals that we get the recognition of IFS as being the leader. And all the, you know... And this is where I'll go to the next layer of your question that building that is something I pride myself on and I'll say that we're building the IFS brand recognition at three different levels. >> Okay. >> There's the C-level and the board level, which I'd say my top participation in Darren's keynote this morning was more targeted to messages that would go, you know, "How are you a smarter digital business? How does IFS help you to be that?" >> Yeah. >> Okay. Then we have the operational or kind of the doers in a digital dream team that are below C-level, maybe VPs or directors or SVPs, that actually have the objective of bringing in the new business models, the operational change, the new technology, putting it to work. And there, you know, you have aspects of what do they need now versus how do they change and how do they continue innovating in a way that is easy as possible. >> Yeah. >> And then you definitely need to focus also on the people that are hands-on with those end customers. >> The practitioners. Yeah. >> The people that not only are told about the moment of service, but live the moment of service, right? The actual users in the field. Maybe the dispatchers, you know, the people that are doing the maintenance or the service or things like that. So the domain expertise in how we build the brand recognition has to be in all those three constituencies. We want to make sure that the CEO and the board members know who IFS is. We want to make sure that the operational leaders and the IT leaders who actually are delivering the project trust us to deliver. >> Right. >> And are confident in our ability to deliver with our ecosystem. And then we want to make sure that we're delighting those users of the software that they can deliver the moment of service, not just the business value that we all want from technology, but really that we're enabling them to have a solution that they love. That they can enjoy doing their job, or at least feel that they're doing their job in a way that's helpful to them. >> Right. >> And that ties into the end customers getting the moment of service that we all want. >> Absolutely. Well, very much aligned with what I heard today. It sounds like there's a rock solid strategy across the board at IFS and you... Congratulations on the work that you've done to help put that in place and how it's been evolving. I can only imagine that those second half numbers are going to be fantastic. So we'll have to have you back on the show next year (Marne laughs) to see what else is new. >> Yeah, I can't wait. It's an absolute pleasure and- >> Likewise. >> You know, and really, we're so passionate about what we do here. >> Yes. >> You know, I think just as a final note, as we grow, we want to make sure that doubling the company, doubling the number of customers, that our customers still feel that intimacy and that care. >> Yes. >> Right? >> Yes. >> That they can access senior executives that aren't clueless about their used cases and their vertical and actually have the ability to help them. You know, one of the things I pride myself on is that we... Okay, ideally people choose IFS in the first instance. We have successful projects and move on. Sometimes though, we're taking failed projects from other vendors. >> Yes, right. >> And what I pride myself on, and we all do here at IFS, is that we get those projects live, with those customers live. You know, we have the grit. We have the domain expertise, we see it through. And that even if customers have failed to get the business value or the transformation, you know, in the areas that we specialize at IFS, they can come here and we get it done. >> Right, you got a trusted partner. >> And that's something- Yes, and that, you know, I know every vendor says that- >> They do, but- >> But the reality is that we live it. >> Yeah. >> And it doesn't mean we're perfect. No vendor's perfect. But you know, we have the dedication and the focus and the domain expertise to get it done. And that's what's ultimately driving us into these leadership positions, changing how IFS is viewed. You know, we have people now that are coming to IFS that are saying, "IFS is the only choice in service management if you really want to do this work." And, you know, again, we have to keep earning it. But that's great. >> Exactly. Well, congratulations on all of that. That customer intimacy is a unique differentiator, and it's something that is... It's very... It's a flywheel, right? It's very synergistic. We appreciate your time and your insights for joining us on the program today. Thank you, Marne. >> Absolutely a pleasure. Thank you so much for coming. >> Mine as well. For Marne Martin, I'm Lisa Martin. No relation. (Marne laughs) You're watching theCUBE live from Miami at IFS Unleashed. I'll be back after a short break, so don't go too far. (soft electronic music) (soft electronic music continues)

>>Hey everyone. Welcome back to Miami. Lisa Martin here live with the Cube at IFS Unleashed 2022. We're so excited to be here. We just had a great conversation with Ifss, CEO of Darren Rouse. Now we've got another exciting conversation. F1 is here. You know how much I love f1. Christian Peterson joins us as well, the Chief Product Officer at ifs, and Sean Edwards IT business partner at Aston Martin. F1. Guys, it's great to have you on the program. Thank you for having >>Us. Thank you >>Very much. We were talking about F one. We probably could have an entire conversation just on that, but Christian, I wanna talk with you. It's been three years since the Cube has covered ifs obviously for obvious reasons during that time. So much momentum has happened. IFS cloud was launched about 18 months ago. Give our audience an o, a flavor of IFS, cloud and some of the milestones that you've hit in such a short time period. >>Yeah, I mean IFS cloud is really transformational in many ways. It's transformational for first and foremost for our customers in what enables them to do, but also transformational for us from a technology perspective, how we work and how we do everything. And at the end of the day, it has really surfaced, served around the the, the fact of what we need to do for our customers. And what we saw our customers often do back then, or any company, was they were out looking for EAP solutions or FSM Solutions or EAM Solutions or what have you. And then they were trying to stitch it all together and we, we said like, Hang on a second, these these traditional software s, those are some that I'm guilty. You know, there's some that we actually invented over the years together with analysts. So we invented EER P and we invented CRM and EAM and all these different things. >>But at the end of the day, customers really want a solution to what they are, they are what they're dealing with. And so in these conversations it became very clear that and very repeated conclusions from the conversations that customers wanted something that could manage and help them optimize the use of their assets. Regardless of what industry you're in, assets is such a key component. Either you are using your assets or you're producing assets. Second thing is really get the best use of of your people, your teams and your crew. How do you get the right people on the right job at the same time? How do you assemble the right crew with the right set of skills in the crew? Get them to the right people at the same time. So, and then the final thing is of course customers, you know all the things that you need to do to get customers to answer these ultimate questions, Will you buy from this company again? And they should say yes. That's the ultimate results of moments of service. So that's how we bring it all together and that's what we have been fast at work at. That's what IFS cloud is all about. >>And you, you talked about IFS cloud, being able to to help customers, orchestrate assets, people, customers, Aston Martin being one of those customers. Shawn, you came from ifs so you have kind of the backstory but just give the audience a little bit of, of flavor of your role at Aston Martin and then let's dig into the smart factory. >>Sure. So I previously worked at IFS as a manufacturing consultant. So my bread and butter is production planning in the ERP sector. So we, I Aston Martin didn't have an ERP system pre IFS or a legacy system that wasn't working for them and the team couldn't rely upon it. So what we did was bring IFS in. I was the consultant there and as IFS always preached customer first, well customer first did come and I jumped to support the team. So we've implemented a fully RP solution to manage the production control and the material traceability all the way through from design until delivery to track. And we've mo most recently implemented a warehouse solution at Trackside as well. So we are now tracking our parts going out with the garage. So that's a really exciting time for RFS. In terms of the smart factory, it's not built yet. >>We're we're supposed to move next year. So that's really exciting cause we're quadrupling our footprint. So going from quite a small factory spread out across the North Hampton Share countryside, we're going into one place quadruple in our footprint. And what we're gonna start looking at is using the technology we're implementing there. So enabling 5G to springboard our IFFs implementations going forward with the likes of Internet of things to connect our 15 brand new CMC machines, but also things like R F I D. So that comes with its own challenges on a Formula One car, but it's all about speed of data capture, single point of truth. And IFFs provides that >>And well, Formula One, the first word that comes to mind is speed. >>Absolutely. Second >>Word is crazy. >>We, we are very unique in terms of most customers Christian deals with, they're about speed but also about profit and efficiency. That doesn't matter to us. It is all about time. Time is our currency and if we go quicker in designing and manufacturing, which ifs supports ultimately the cargo quicker. So speed is everything. >>And and if we, if we think of of people, customers and assets at Asset Martin F one, I can't, I can't imagine the quantity of assets that you're building every race weekend and refactoring. >>Absolutely. So a Formula one car that drives out of the garage is made up of 13,000 car parts, most of which, 50% of which we've made in house. So we have to track that all the way through from the smallest metallic component all the way up to the most complex assembly. So orchestrating that and having a single point of truth for people to look at and track is what IFFs has provided us. >>Christian, elaborate on that a little bit in terms of, I mean, what you're facilitating, F1 is such a great example of of speed we talked about, but the fact that you're setting up the car every, every other weekend maybe sometimes back to back weeks, so many massive changes going on. You mentioned 50% of those 13,000 parts you manufacture. Absolutely. Talk about IFS as being a catalyst for that. >>I mean the, it's, it's fascinating with Formula One, but because as a technology geek like me, it's really just any other business on steroids. I mean we talk, we talk about this absolutely high tech, super high tech manufacturing, but even, even before that, the design that goes in with CFDs and how you optimize for different things and loose simulation software for these things goes into manufacturing, goes into wind tunnels and then goes on track. But guess what, when it's on track, it's an asset. It's an asset that streams from how many sensors are on the car, >>I think it's over 10,000 >>Sensors, over 10,000 sensors that streams maybe at 50 hertz or 50 readings. So every lap you just get this mountain of data, which is really iot. So I always say like F one if one did IOT before anybody invented the term. >>Absolutely. >>Yep. You know, F1 did machine learning and AI before anybody thought about it in terms of pattern recognition and things like that with the data. So that's why it's fascinating to work with an organization like that. It's the, it's the sophistication around the technologies and then the pace what they do. It's not that what they do is actually so different. >>It is, it absolutely isn't. We just have to do it really quickly. Really >>Quickly. Right. And the same thing when you talk about parts. I mean I was fascinated of a conversation with, with one of your designers that says that, you know, sometimes we are, we are designing a part and this, the car is now ready for production but the previous version of that part has not even been deployed on the car yet. So that's how quick the innovation comes through and it's, it's, it's fascinating and that's why we like the challenge that Esther Martin gives us because if we can, if we can address that, there's a lot of businesses we can make happy with that as far, >>So Sha I talk a little bit about this is, so we're coming up, there's what four races left in the 2022 season, but this is your busy time because that new car, the 23 car needs to be debuted in what February? So just a few months time? >>Absolutely. So it's a bit cancer intuitive. So our busiest time is now we're ramping up into it. So we co, we go into something called car build which is from December to December to February, which is our end point and there's no move in that point. The car has gotta go around that track in February. So we have got to make those 13,000 components. We've gotta design 'em, we've gotta make 'em and then we've gotta get 'em to the car in February for our moment of service. They said it on stage. Our moment of service as a manufacturing company is that car going around the track and we have to do it 24 times next year and we've gotta start. Well otherwise we're not gonna keep up. >>I'm just gonna ask you what a, what a moment, what's a moment of service in f1 and you're saying basically getting that >>Functional car >>On the track quickly, as quickly as possible and being able to have the technology underpinning that's really abstracting the complexity. >>Absolutely. So I would say our customer ultimately is the driver and the fans they, they need to have a fast car so they can sport it and they ultimately drive it around the track and go get first place and be competitive. So that is our moment of service to our drivers is to deliver that car 24 times next year. >>I imagine they might be a little demanding >>They are and I think it's gonna be exciting with Alonzo coming in, could the driver if we've gotta manage that change and he'll have new things that he wants to try out on a car. So adds another level of complexity to that. >>Well how influential are the drivers in terms some of the, the manufacturing? Like did they, are they give me kind of a a sense of how Alon Fernando Alanzo your team and ifs maybe collaborate, maybe not directly but >>So Alonzo will come in and suggest that he wants cars to work a certain way so he will feed back to the team in terms of we need this car, we need this car part to do this and this car part to do that. So then we're in a cycle when he first gets into the car in that February, we've then gotta turnaround car parts based off his suggestions. So we need to do that again really quickly and that's where IFS feeds in. So we have to have the release and then the manufacturer of the component completely integrated and that's what we achieve with IFFs and >>It needs to be really seamless. >>Absolutely. If, if we don't get it right, that car doesn't go out track so there's no moving deadline. >>Right. That's the probably one of the industries where deadlines do not move. Absolutely. We're so used to things happening in tech where things shift and change and reorgs, but this is one where the dates are set in their firm. >>Absolutely. And we have to do anything we can do to get that car on the track. So yeah, it's just a move. >>Christian, talk about the partnership a little bit from your standpoint in terms of how influential has Aston Martin F1 been in IFS cloud and its first 18 months. I was looking at some stats that you've already gotten 400,000 plus users in just a short time period. How influential are your customers in the direction and even the the next launch 22 R too? >>I mean our customers do everything plain and simple. That's that's what it is. And we have, we have a partnership, I think about every single customer as a partner of ours and we are partnering in taking technology to the next level in terms of, of the outputs and the benefits it can create for our customers. That's what it's all, all about. And I, I always think about these, these three elements I think I mentioned in our state as well. I think the partnership we have is a partnership around innovation. Innovation doesn't not only come from IFS or the technology partner, it comes from discussions, requirements, opportunities, what if like all these things. So innovation comes from everywhere. There's technology driven innovation, there's customer driven innovation, but that's part of the partnership. The second part of the partnership is inspiration. So with innovation you inspire. So when you innovate on something new that inspires new innovation and new thinking and that's again the second part of the partnership. And then the third part is really iterate and execute, right? Because it's great that we can now innovate and we can agree on what we need to do, but now we need to put it into products, put it in technology and put it into actual use. That's when the benefits comes and that's when we can start bringing the bell. >>And I think it's really intrinsically linked. I mean if you look at progress with Formula One teams and their innovation, it's all underpinned by our technology partners and that's why it's so important. The likes of Christian pushes the product and improves it and innovates it because then we can realize the benefits and ultimately save time and go faster. So it's really important that our, our partners and certainly inform one, push the boundaries and find that technology. >>And I think one of the things that we also find very, very important is that we actually understand our customers and can talk the language. So I think that was one of the key things in our engagement, Martin from the beginning is that we had a set of people that really understand Formula One felt it on their bodies and can have the conversation. So when the Formula One teams they say something, then we actually understand what we're talking about. So for instance, when we talk about, you know, track side inventory, well it's not that different from what a field service technician have in his van when he goes service. The only difference is when you see something happening on track, you'll see the parts manager go out to the pit lane with a tablet and say like, oh we need this, we need that, we need this and we need that. And then we'll go back and pick it and put it on the car and the car is service and maintain and off go. Absolutely. >>Yeah that speed always impresses me. >>It's unbelievable. >>Shannon, last question for you. From a smart factory perspective, you said you're moving in next year. What are some of the things that you are excited about that you think are really gonna be transformative but IFS is doing? >>So I think what I'm really excited about once we get in is using the technology they've already put in terms of 5G networks to sort of springboard that into a further IFS implementation. Maybe IFFs cloud in terms of we always struggle to keep the system up to date with, with what's physically happening so that the less data entry and the more automatic sort of data capture, the better it is for the formula on team cuz we improve our our single point of truth. So I'm really excited to look at the internet of things and sort of integrate our CNC machines to sort of feed that information back into ifs. But also the RFID technology I think is gonna be a game changer when we go into the new factory. So really >>Excited. Excellent. Well well done this year. We look forward to seeing Alonso join the team in 23. Fingers >>Crossed. >>Okay. Fingers crossed. Christian, Jeanette, it's been a pleasure to have you on the program. Thank you so much for sharing your insights and how ifs asked Martin are working together, how you really synergistically working together. We appreciate your time. >>Thank you very much for having us. Our >>Thanks for having us. And go Aston >>Woo go Aston, you already here first Lisa Martin, no relation to Aston Martin, but well, I wanna thank Christian Peterson and Shannon Edwards for joining me, talking about IFS and Aston Martin team and what they're doing at Speed and Scale. Stick around my next guest joins me in a minute. >>Thank you.

>>Welcome back everyone to the cubes coverage here in Seattle, Washington for the Avis marketplace seller conference, part of the APN partner network merging with the marketplace to form the Amazon partner organization. I'm John furrier, host of the cube Walter Wall coverage today, Christian Gor cash, who is the VP of alliances at Kong Inc. Welcome to the cube. Thanks for coming on. >>Thank you. Thank you, John. Really glad to be here. Corke exactly. Yeah. It's awesome. >>So Kong we've been following you guys for while Docker Kong cube. You've been part of our cube conversation. Also part of our, our startup showcase fast growing startup, you know, working on stuff that everyone loves APIs. I mean, APIs are so popular now that they now a security concern, right? Yeah. So like it gets squat there everywhere. I won't say API sprawl, but APIs are the connections and that are, is the web. That is the cloud. Okay. Now with cloud native developers who are now in the front lines have taken over it, everyone knows DevOps dev SecOps is now the new it and it's the developers security and data they're below they're the new ops, right? So, so this is where microservices come in, open source service MES new automation is coming down the pike. That's super valuable to businesses as they look at cloud native architecture, what are you guys doing in there? Take a minute to explain Kong's value proposition, the hot products, and then why you're here. >>Yeah. So, you know, I joined Kong now or three years ago, you know, we were still just reaching our hundred employees, mark, which is very important, very startup, but even back then, you know, Kong was relatively well known in industry, you know, so we have one of the most, well the most popular open source project in API gateway area. So con API gateway, you know, we cross now 300 million downloads, even more important is just the scale it, which the product's been used. So between our open source community and enterprise customers, we are now crossing like 11 trillion transactions per month. Now just give you comparison. Like this is like 18, 19 times more than Netflix per month. You know? So for any company that has a technology that operates it at scale, you need to hit few things outta the park. You know, as he mentions cloud data developers, they want simplicity. You know, they want automation. They also want performance and scale and security, which are all critical, you know, to how Kong, you know, start as opensource project. Now, of course we have the whole suite of enterprise products. We also have our con service mesh offering as well as our cloud offerings. >>Yeah. And this is how open source is doing it now, obviously, you know, I, I still remember, I still tell the story to the young startups. Hey, I, there was proprietary software when I was in college. Open source is now everything. Now you've got, got cloud scale. So the dynamic between open source, which has become the software industry open source success doesn't mean it's it's game over. It's the beginning. The commercialization that you guys have gone through is super important. Trillions of transactions. Now you have enterprises working with you. What's the big advantage of the seller relationship that you have with Amazon? Why are customers using it? What are they buying it for? Give the pitch of con for the marketplace customer. >>Yeah, it's actually, we are relatively new in AWS marketplace. You know, so our first transaction that we ever done was actually in July and 2021. So we are just over a year, you know, that journey, you know, when I look what Chris gross talked today, he was talking about, you know, Hey, just publishing marketplace, not enough. You know, you need to understand what's your value proposition. You need to make sure your operations already, your sales is ready. Everything is, is set. And we kind of did this for the first year and a half is spend a lot of time improving our integration with AWS overall, all the first party services relevant to con we also understood, well, what does it take to kind of fine tune our value proposition? We have like three specific sales place. And you know, when we launch our flagship product con connect enterprise and got our first transaction, that was great milestone for, for star like Kong. But then what we've seen is just that work that we've done before really paid off. I mean right now, >>Like what we'll give example. >>Yeah. So, you know, we are focusing on as measure three sales place. Money is we are focused, specific on helping customers who are modernizing and, and their application going to the cloud. And you have a lot of these, you know, lifting shift and are rearchitect and modernized, but most of the attentions on the workloads, what about the connections? You know, so a monolith application had to authentic all the users understand wheres the network and so on. When you build those, when you now decouple this built like 1,000 thousand microservices, you don't want to repeat this for every microservice. So that's where K brings the whole suite from, you know, service match to the API gate to help manage the journey and really support this environment. And we spend a lot of time to just fine tune that message. So that customers understood where, you know, how can we help them on their journey beyond what, for instance, cloud native or AWS API gateway offers them. So we can really help them from day one on the journey and accelerate. And >>I think I it's a no, it's a no braining for a customer to buyer or to come into the marketplace and say, click, I'm gonna buy some data analytics services. I'm gonna buy gateway through Kong. But when they start getting into these microservices, this automation opportunity there, there's more behind the curtain for them with Kong. So I have to ask you with the keynote we heard from Chris, the leader of the marketplace. Now he said that he wants the ISVs to be more native in the cloud. That probably resonates with you. You, >>You guys well with con's relatively simple because we were built at cloud native, you know, so very briefly the whole story of Congo. This is before Ajo, our founders were actually running the, the very popular API exchange col mesh shape. And they had to build their own gateway just to handle the scale and was built on cloud native technologies. And then when everybody's calling you, what are you using to running? This are using PGS. And so else, no, we built ourselves, oh, how can we get our hands on? That's how con actually >>Came to. And that's how the big winners usually happen too. They start build their own, solve their own problem because it's a big scale problem. Exactly. No one's had that problem. >>Yeah. And what we have seen, especially what was very, you know, through, through the pandemic, what we have seen. And it's interesting, you know, being in a startup doing pandemic is like, whoa, will the life just shut down or what we're doing? You know? But actually what we have seen customers prioritize the new business capability. For instance, you have a large parental companies that overnight, they have to understand where the assets are. Yeah. Or banks who are like 45 days of, you know, approving process for the loans. They need to reduce it for a day or two. >>Yeah. And they're adding more developers, too, exactly. To build the modern application. So they need to have that infrastructure as code aspect. Correct. >>And they >>Need in place. >>Yeah. I need to like you have, you know, I don't think that many customers still have waterfall cycles, but they have, have pre pretty long developers development cycles. And now you need to, you know, do this multiple times a day. That's >>Interesting. We talked to a lot of cloud architects and C CIO C says, and you know, the executive just hire more developers take that hill, build. It just don't build a new app. It's not that easy boss. When, when the cloud architect says we have to be fully operationally ready with cloud native infrastructure's code. So with that, you're seeing a lot more enterprises come in now that are more savvy. They getting better. We're seeing Kubernetes more and more. You're seeing containerization. You're seeing that cloud native enterprise acceptance. What does that mean for you guys in the marketplace, as you look at the value proposition, how are you guys working with the marketplace today and where do you see customers buying in the future? >>Yeah, so we as mentioned, you know, we, we are now a year into that journey. We already seen tremendous benefits just in terms of reducing the friction. You know, the whole procurement, you know, you come as a startup with some, some of the largest companies in the world, they used to buy five, 10 billion in software and they have all these processes and you're like, well, but we only have like two people in finance. Sorry. How can you, and where marketplace can really, really helps us is, you know, improve this experience, both sides because they understand like we are fast moving company. They, they want us because of our speed and, and innovation that we, the product's strong. Yeah. They don't want us to get bogged down in all these pro procurement processes either. And so, so that's the first benefit. We also are working very hard to make sure that the customers can provision Kong in AWS and automate across the board. So essentially reducing their time to value dramatically. Yeah. And another thing that we found tremendously beneficial for us is a startup is the whole concept of a standard marketplace contract. Yeah. So instead of us coming with our little MSA or come like 50 page MSA from companies, we now have a middle ground. So we can just agree. You know, there's some differences, some specifics to qu software and it's tremendously reduced costs on both sides. >>Great. For you guys great for the buyers. Yeah. You get deployed services. They're not just buying, they're managing and deploying. Yeah, >>Exactly. Great. >>Quick, final question. Put a plugin for the company. What are you working on now? What's the big news. What's the con update? >>Well, that's an interesting part because I can't tell you because next week we have our con summit. Oh right. In San Francisco. The cubes not so 28, 20 ninth. Yeah. We, we we'll, I think we are gonna fix that in the future. But anyway, this is the first time after pandemic to do this in person, we have number of very exciting announcement, our Kong products, as well as you may hear some news about our AWS partnership, >>We like con we believe that DevOps has happened. Dev sec ops, whatever you gonna call it, dev is now the developers they're in the front lines. They're in the C I CD pipeline. They're shifting left. That's the new they took over it. That's what DevOps does. It's not a title. Now you have security and data ops behind the scenes. That's gonna be middleware. That's gonna have tons of microservices. So more, more, more action coming, all API based. >>Exactly. And the more, you know, the more complexity we can take away from that, the better we, you know, the >>Whole community. Thank you. Spending the time to come on the cube here at the, a us marketplace seller conference. What do you think about the APN merging with the marketplace formed the P the Amazon partner organization. Thumbs up, thumbs down. What's your heard? >>It's excellent. We have a great friend in AP, a great friend, us marketplace. Now both of them work together with huge. >>Fantastic. Yes. Thanks for okay. Cube coverage here in Seattle. I'm John furier APN marketplace together. APOs the new organization making it easier. Of course, we got all the coverage here. Thanks for watching.

>>Good afternoon, everyone. And welcome back to the VMware Explorer. 2022 live from San Francisco. Lisa Martin, here with Dave. Valante good to be sitting next to you, sir. >>Yeah. Yeah. The big set >>And we're very excited to be welcoming buck. One of our esteemed alumni Sanja poin joins us, the CEO and president of cohesive. Nice to see >>You. Thank you, Lisa. Thank you, Dave. It's great to meet with you all the time and the new sort of setting here, but first >>Time, first time we've been in west, is that right? We've been in north. We've been in south. We've been in Las Vegas, right. But west, >>I mean, it's also good to be back with live shows with absolutely, you know, after sort of the two or three or hiatus. And it was a hard time for the whole world, but I'm kind of driving a little bit of adrenaline just being here with people. So >>You've also got some adrenaline, sorry, Dave. Yeah, you're good because you are new in the role at cohesive. You wrote a great blog that you are identified. The four reasons I came to cohesive. Tell the audience, just give 'em a little bit of a teaser about that. >>Yeah, I think you should all read it. You can Google and, and Google find that article. I talked about the people Mohi is a fantastic founder. You know, he was the, you know, the architect of the Google file system. And you know, one of the senior Google executives was on my board. Bill Corrin said one of the smartest engineers. He was the true father of hyperconverge infrastructure. A lot of the code of Nutanix. He wrote, I consider him really the father of that technology, which brought computer storage. And when he took that same idea of bringing compute to secondary storage, which is really what made the scale out architect unique. And we were at your super cloud event talking about that, Dave. Yeah. Right. So it's a people I really got to respect his smarts, his integrity and the genius, what he is done. I think the customer base, I called a couple of customers. One of them, a fortune 100 customer. I, I can't tell you who it was, but a very important customer. I've known him. He said, I haven't seen tech like this since VMware, 20 years ago, Amazon 10 years ago and now Ko. So that's special league. We're winning very much in the enterprise and that type of segment, the partners, you know, we have HPE, Cisco as investors. Amazon's an investors. So, you know, and then finally the opportunity, I think this whole area of data management and data security now with threats, like ransomware big opportunity. >>Okay. So when you were number two at VMware, you would come on and say, we'd love all our partners and of course, okay. So you know, a little bit about how to work with, with VMware. So, so when you now think about the partnership between cohesive and VMware, what are the things that you're gonna stress to your constituents on the VMware side to convince them that Hey, partnering with cohesive is gonna gonna drive more value for customers, you know, put your thumb on the scale a little bit. You know, you gotta, you gotta unfair advantage somewhat, but you should use it. So what's the narrative gonna be like? >>Yeah, I think listen with VMware and Amazon, that probably their top two partners, Dave, you know, like one of the first calls I made was to Raghu and he knew about this decision before. That's the level of trust I have in him. I even called Michael Dell, you know, before I made the decision, there's a little bit of overlap with Dell, but it's really small compared to the overlap, the potential with Dell hardware that we could compliment. And then I called four CEOs. I was, as I was making this decision, Andy Jassey at Amazon, he was formerly AWS CEO sat Nadela at Microsoft Thomas cor at Google and Arvin Christian, IBM to say, I'm thinking about this making decision. They are many of the mentors and friends to me. So I believe in an ecosystem. And you know, even Chuck Robbins, who the CEO of Cisco is an investor, I texted him and said, Hey, finally, we can be friends. >>It was harder to us to be friends with Cisco, given the overlap of NSX. So I have a big tent towards everybody in our ecosystem with VMware. I think the simple answer is there's no overlap okay. With, with the kind of the primary storage capabilities with VSAN. And by the same thing with Nutanix, we will be friends and, and extend that to be the best data protection solution. But given also what we could do with security, I think this is gonna go a lot further. And then it's all about meet the field. We have common partners. I think, you know, sort of the narrative I talked about in that blog is just like snowflake was replacing Terada and ServiceNow replace remedy and CrowdStrike, replacing Symantec, we're replacing legacy vendors. We are viewed as the modern solution cloud optimized for private and public cloud. We can help you and make VMware and vs a and VCF very relevant to that part of the data management and data security continuum, which I think could end VMware. And by the way, the same thing into the public cloud. So most of the places where we're being successful is clearly withs, but increasingly there's this discussion also about playing into the cloud. So I think both with VMware and Amazon, and of course the other partners in the hyperscaler service, storage, networking place and security, we have some big plans. >>How, how much do you see this? How do you see this multi-cloud narrative that we're hearing here from, from VMware evolving? How much of an opportunity is it? How are customers, you know, we heard about cloud chaos yesterday at the keynote, are customers, do they, do they admit that there's cloud chaos? Some probably do some probably don't how much of an opportunity is that for cohesive, >>It's tremendous opportunity. And I think that's why you need a Switzerland type player in this space to be successful. And you know, and you can't explicitly rule out the fact that the big guys get into this space, but I think it's, if you're gonna back up office 365 or what they call now, Microsoft 365 into AWS or Google workspace into Azure or Salesforce into one of those clouds, you need a Switzerland player. It's gonna be hard. And in many cases, if you're gonna back up data or you protect that data into AWS banks need a second copy of that either on premise or Azure. So it's very hard, even if they have their own native data protection for them to be dual cloud. So I think a multi-cloud story and the fact that there's at least three big vendors of cloud in, in the us, you know, one in China, if include Alibaba creates a Switzerland opportunity for us, that could be fairly big. >>And I think, you know, what we have to do is make sure while we'll be optimized, our preferred cloud is AWS. Our control plane runs there. We can't take an all in AWS stack with the control plane and the data planes at AWS to Walmart. So what I've explained to both Microsoft and AWS is that data plane will need to be multi-cloud. So I can go to an, a Walmart and say, I can back up your data into Azure if you choose to, but the control plane's still gonna be an AWS, same thing with Google. Maybe they have another account. That's very Google centric. So that's how we're gonna believe the, the control plane will be in AWS. We'll optimize it there, but the data plane will be multicloud. >>Yeah. And that's what Mo had explained at Supercloud. You know, and I talked to him, he really helped me hone in on the deployment models. Yes. Where, where, where the cohesive deployment model is instantiating that technology stack into each cloud region and each cloud, which gives you latency advantages and other advantages >>And single code based same platform. >>And then bringing it, tying it together with a unified, you know, interface. That was he, he was, he was key. In fact, I, I wrote about it recently and, and gave him and the other 29 >>Quite a bit in that session, he went deep with you. I >>Mean, with Mohi, when you get a guy who developed a Google file system, you know, who can technically say, okay, this is technically correct or no, Dave, your way off be. So I that's why I had to >>Go. I, I thought you did a great job in that interview because you probed him pretty deep. And I'm glad we could do that together with him next time. Well, maybe do that together here too, but it was really helpful. He's the, he's the, he's the key reason I'm here. >>So you say data management is ripe for disrupt disruption. Talk about that. You talked about this Switzerland effect. That sounds to me like a massive differentiator for cohesive. Why is data management right for disruption and why is cohesive the right partner to do it? >>Yeah, I think, listen, everyone in this sort of data protection backup from years ago have been saying the S Switzerland argument 18 years ago, I was a at Veras an executive there. We used the Switzerland argument, but what's changed is the cloud. And what's changed as a threat vector in security. That's, what's changed. And in that the proposition of a, a Switzerland player has just become more magnified because you didn't have a sales force or Workday service now then, but now you do, you didn't have multi-cloud. You had hardware vendors, you know, Dell, HPE sun at the time. IBM, it's now Lenovo. So that heterogeneity of, of on-premise service, storage, networking, HyperCloud, and, and the apps world has gotten more and more diverse. And I think you really need scale out architectures. Every one of the legacy players were not built with scale out architectures. >>If you take that fundamental notion of bringing compute to storage, you could almost paralyze. Imagine you could paralyze backup recovery and bring so much scale and speed that, and that's what Mo invented. So he took that idea of how he had invented and built Nutanix and applied that to secondary storage. So now everything gets faster and cheaper at scale. And that's a disruptive technology ally. What snowflake did to ator? I mean, the advantage of snowflake is when you took that same concept data, warehousing is not a new concept it's existed from since Ralph Kimball and bill Inman and the people who are fathers of data warehousing, they took that to Webscale. And in that came a disruptive force toter data, right on snowflake. And then of course now data bricks and big query, similar things. So we're doing the same thing. We just have to showcase the customers, which we do. And when large customers see that they're replacing the legacy solutions, I have a lot of respect for legacy solutions, but at some point in time of a solution was invented in 1995 or 2000, 2005. It's right. For change. >>So you use snowflake as an example, Frank SL doesn't like when I say playbook, cuz I says, Dave, I'm a situational CEO, no playbook, but there are patterns here. And one of the things he did is to your point go after, you know, Terra data with a better data warehouse, simplify scale, et cetera. And now he's, he's a constructing a Tam expansion strategy, same way he did at ServiceNow. And I see you guys following a similar pattern. Okay. You get your foot in the door. Let's face it. I mean, a lot of this started with, you know, just straight back. Okay, great. Now it's extending into data management now extending to multi-cloud that's like concentric circles in a Tam expansion strategy. How, how do you, as, as a CEO, that's part of your job is Tam expansion. >>So yeah, I think the way to think about the Tam is, I mean, people say it's 20, 30 billion, but let me tell you how you can piece it apart in size, Dave and Lisa number one, I estimate there's probably about 10 to 20 exabytes of data managed by these legacy players of on-prem stores that they back up to. Okay. So you add them all up in the market shares that they respectively are. And by the way, at the peak, the biggest of these companies got to 2 billion and then shrunk. That was Verto when I was there in 2004, 2 billion, every one of them is small and they stopped growing. You look at the IDC charts. Many of them are shrinking. We are the fastest growing in the last two years, but I estimate there's about 20 exabytes of data that collectively among the legacy players, that's either gonna stay on prem or move to the cloud. Okay. So the opportunity as they replace one of those legacy tools with us is first off to manage that 20 X by cheaper, faster with the Webscale glass offer the cloud guys, we could tip that into the cloud. Okay. >>But you can't stop there. >>Okay. No, we are not doing just backup recovery. We have a platform that can do files. We can do test dev analytics and now security. Okay. That data is potentially at a risk, not so much in the past, but for ransomware, right? How do we classify that? How do we govern that data? How do we run potential? You know, the same way you did antivirus some kind of XDR algorithms on the data to potentially not just catch the recovery process, which is after fact, but maybe the predictive act of before to know, Hey, there's somebody loitering around this data. So if I'm basically managing in the exabytes of data and I can proactively tell you what, this is, one CIO described this very simply to me a few weeks ago that I, and she said, I have 3000 applications, okay. I wanna be prepared for a black Swan event, except it's not a nine 11 planes getting the, the buildings. >>It is an extortion event. And I want to know when that happens, which of my 3000 apps I recover within one hour within one day within one week, no later than one month. Okay. And I don't wanna pay the bad guys at penny. That's what we do. So that's security discussions. We didn't have that discussion in 2004 when I was at another company, because we were talking about flood floods and earthquakes as a disaster recovery. Now you have a lot more security opportunity to be able to describe that. And that's a boardroom discussion. She needs to have that >>Digital risk. O O okay, go ahead please. I >>Was just gonna say, ransomware attack happens every what? One, every 11, 9, 11 seconds. >>And the dollar amount are going up, you know, dollar are going up. Yep. >>And, and when you pay the ransom, you don't always get your data back. So you that's not. >>And listen, there's always an ethical component. Should you do it or not do it? If you, if you don't do it and you're threatened, they may have left an Easter egg there. Listen, I, I feel very fortunate that I've been doing a lot in security, right? I mean, I built the business at, at, at VMware. We got it to over a billion I'm on the board of sneak. I've been doing security and then at SAP ran. So I know a lot about security. So what we do in security and the ecosystem that supports us in security, we will have a very carefully crafted stay tuned. Next three weeks months, you'll see us really rolling out a very kind of disciplined aspect, but we're not gonna pivot this company and become a cyber security company. Some others in our space have done that. I think that's not who we are. We are a data management and a data security company. We're not just a pure security company. We're doing both. And we do it well, intelligently, thoughtfully security is gonna be built into our platform, not voted on. Okay. And there'll be certain security things that we do organically. There's gonna be a lot that we do through partnerships, this >>Security market that's coming to you. You don't have to go claim that you're now a security vendor, right? The market very naturally saying, wow, a comprehensive security strategy has to incorporate a data protection strategy and a recovery, you know, and the things that we've talking about Mount ransomware, I want to ask you, you I've been around a long time, longer than you actually Sanjay. So, but you you've, you've seen a lot. You look, >>Thank you. That's all good. Oh, >>Shucks. So the market, I've never seen a market like this, right? I okay. After the.com crash, we said, and I know you can't talk about IPO. That's not what I'm talking about, but everything was bad after that. Right. 2008, 2000, everything was bad. I've never seen a market. That's half full, half empty, you know, snowflake beats and raises the stock, goes through the roof. Dev if it, if the area announced today, Mongo, DB, beat and Ray, that things getting crushed and, and after market never seen anything like this. It's so fed, driven and, and hard to protect. And, and of course, I know it's a marathon, you know, it's not a sprint, but have you ever seen anything like this? >>Listen, I walk worked through 18 quarters as COO of VMware. You've seen where I've seen public quarters there and you know, was very fortunate. Thanks to the team. I don't think I missed my numbers in 18 quarters except maybe once close. But we, it was, it's tough. Being a public company of the company is tough. I did that also at SAP. So the journey from 10 to 20 billion at SAP, the journey from six to 12 at VMware, that I was able to be fortunate. It's humbling because you, you really, you know, we used to have this, we do the earnings call and then we kind of ask ourselves, what, what do you think the stock price was gonna be a day and a half later? And we'd all take bets as to where this, I think you just basically, as a, as a sea level executive, you try to build a culture of beaten, raise, beaten, raise, beaten, raise, and you wanna set expectations in a way that you're not setting them up for failure. >>And you know, it's you, there's, Dave's a wonderful CEO as is Frank Salman. So it's hard for me to dissect. And sometimes the market are fickle on some small piece of it. But I think also the, when I, I encourage people say, take the long term view. When you take the long term view, you're not bothered about the ups and downs. If you're building a great company over the length of time, now it will be very clear over the arc of many, many quarters that you're business is trouble. If you're starting to see a decay in growth. And like, for example, when you start to see a growth, start to decay significantly by five, 10 percentage points, okay, there's something macro going on at this company. And that's what you won't avoid. But these, you know, ups and downs, my view is like, if you've got both Mongo D and snowflake are fantastic companies, they're CEOs of people I respect. They've actually kind of an, a, you know, advisor to us as a company, you knows moat very well. So we respect him, respect Frank, and you, there have been other quarters where Frank's, you know, the Snowflake's had a down result after that. So you build a long term and they are on the right side of history, snowflake, and both of them in terms of being a modern cloud relevant in the case of MongoDB, open source, two data technology, that's, you know, winning, I, I, we would like to be like them one day >>As, as the new CEO of cohesive, what are you most ask? What are you most anxious about and what are you most excited about? >>I think, listen, you know, you know, everything starts with the employee. You, I always believe I wrote my first memo to all employees. There was an article in Harvard business review called service profit chains that had a seminal impact on my leadership, which is when they studied companies who had been consistently profitable over a long period of time. They found that not just did those companies serve their customers well, but behind happy engaged customers were happy, engaged employees. So I always believe you start with the employee and you ensure that they're engaged, not just recruiting new employees. You know, I put on a tweet today, we're hiring reps and engineers. That's okay. But retaining. So I wanna start with ensuring that everybody, sometimes we have to make some unfortunate decisions with employees. We've, we've got a part company with, but if we can keep the best and brightest retained first, then of course, you know, recruiting machine, I'm trying to recruit the best and brightest to this company, people all over the place. >>I want to get them here. It's been, so I mean, heartwarming to come Tom world and just see people from all walks, kind of giving me hugs. I feel incredibly blessed. And then, you know, after employees, it's customers and partners, I feel like the tech is in really good hands. I don't have to worry about that. Cuz Mo it's in charge. He's got this thing. I can go to bed knowing that he's gonna keep innovating the future. Maybe in some of the companies I've worried about the tech innovation piece, but most doing a great job there. I can kind of leave that in his cap of hands, but employees, customers, partners, that's kind of what I'm focused on. None of them are for me, like a keep up at night, but there are are opportunities, right? And sometimes there's somebody you're trying to salvage to make sure or somebody you're trying to convince to join. >>But you know, customers, I love pursuing customers. I love the win. I hate to lose. So fortune 1000 global, 2000 companies, small companies, big companies, I wanna win every one of them. And it's not, it's not like, I mean, I know all these CEOs in my competitors. I texted him the day I joined and said, listen, I'll compete, honorably, whatever have you, but it's like Kobe and LeBron Kobe's passed away now. So maybe it's Steph Curry. LeBron, whoever your favorite athlete is you put your best on the court and you win. And that's how I am. That's nothing I've known no other gear than to put my best on the court and win, but do it honorably. It should not be the one that you're doing it. Unethically. You're doing it personally. You're not calling people's names. You're competing honorably. And when you win the team celebrates, it's not a victory for me. It's a victory for the team. >>I always think I'm glad that you brought up the employee experience and we're almost out of time, but I always think the employee experience and the customer experience are inextricably linked. This employees have to be empowered. They have to have the data that they need to do their job so that they can deliver to the customer. You can't do one without the other. >>That's so true. I mean, I, it's my belief. And I've talked also on this show and others about servant leadership. You know, one of my favorite poems is Brenda Naor. I went to bed in life. I dreamt that life was joy. I woke up and realized life was service. I acted in service was joy. So when you have a leadership model, which is it's about, I mean, there's lots of layers between me and the individual contributor, but I really care about that sales rep and the engineer. That's the leaf level of the organization. What can I get obstacle outta their way? I love skipping levels of going right. That sales rep let's go and crack this deal. You know? So you have that mindset. Yeah. I mean, you, you empower, you invert the pyramid and you realize the power is at the leaf level of an organization. >>So that's what I'm trying to do. It's a little easier to do it with 2000 people than I dunno, either 20, 20, 2000 people or 35,000 reported me at VMware. And I mean a similar number at SAP, which was even bigger, but you can shape this. Now we are, we're not a startup anymore. We're a midsize company. We'll see. Maybe along the way, there's an IP on the path. We'll wait for that. When it comes, it's a milestone. It's not the destination. So we do that and we are, we, I told people we are gonna build this green company. Cohesive is gonna be a great company like VMware one day, like Amazon. And there's always a day of early beginnings, but we have to work harder. This is kind of like the, you know, eight year old version of your kid, as opposed to the 18 year old version of the kid. And you gotta work a little harder. So I love it. Yeah. >>Good luck. Awesome. Thank you. Best of luck. Congratulations. On the role, it sounds like there's a tremendous amount of adrenaline, a momentum carrying you forward Sanjay. We always appreciate having you. Thank >>You for having in your show. >>Thank you. Our pleasure, Lisa. Thank you for Sanja poin and Dave ante. I'm Lisa Martin. You're watching the cube live from VMware Explorer, 2022, stick around our next guest. Join us momentarily.

>>Good afternoon, everyone. And welcome back to the Cube's day two coverage of VMware Explorer, 2022 live from San Francisco. Lisa Martin, here with Dave. Valante good to be sitting next to you, sir. >>Yeah, the big >>Set and we're very excited to be welcoming back. One of our esteemed alumni Sanja poin joins us, the CEO and president of cohesive. Nice to see >>You. Thank you, Lisa. Thank you, Dave. It's great to meet with you all the time and the new sort of setting here, but >>First time we've been in west, is that right? We've been in north. We've been in south. We've been in Las Vegas, right. But west >>Nice. Well, I mean, it's also good to be back with live shows with absolutely, you know, after sort of the two or three or high. And it was a hard time for the whole world, but I'm kind of driving a little bit of adrenaline just being here with people. So >>You've also got some adrenaline, sorry, Dave. Yeah, you're good because you are new in the role at cohesive. You wrote a great blog that you are identified. The four reasons I came to cohesive. Tell the audience, just give 'em a little bit of a teaser about that. >>Yeah, I think you should all read it. You can Google and, and Google find that article. I talked about the people Mohi is a fantastic founder. You know, he was the, you know, the architect of the Google file system. And you know, one of the senior Google executives who was on my board, bill Corrin said one of the smartest engineers. He was the true father of hyperconverge infrastructure. A lot of the code of Nutanix. He wrote, I consider him really the father of that technology, which brought computer storage. And when he took that same idea of bringing compute to secondary storage, which is really what made the scale out architect unique. And we were at your super cloud event talking about that, Dave. Yeah. Right. So it's a people I really got to respect his smarts, his integrity and the genius, what he is done. >>I think the customer base, I called a couple of customers. One of them, a fortune 100 customer. I, I can't tell you who it was, but a very important customer. I've known him. He said, I haven't seen tech like this since VMware, 20 years ago, Amazon 10 years ago. And now COER so that's special league. We're winning very much in the enterprise and that type of segment, the partners, you know, we have HPE, Cisco as investors, Amazon's an investors. So, you know, and then finally the opportunity, I think this whole area of data management and data security now with threats, like ransomware big opportunity. >>Sure. Okay. So when you were number two at VMware, you would come on and say, we'd love all our partners and of course, okay. So you know, a little bit about how to work with, with VMware. So, so when you now think about the partnership between cohesive and VMware, what are the things that you're gonna stress to your constituents on the VMware side to convince them that Hey, partnering with cohesive is gonna gonna drive more value for customers, you know, put your thumb on the scale a little bit. You know, you gotta, you gotta unfair advantage somewhat, but you should use it. So what's the narrative gonna be like? >>Yeah. I think listen with VMware and Amazon, that probably their top two partners, Dave, you know, like one of the first calls I made was to Raghu and he knew about this decision before. That's the level of trust I have in him. I even called Michael Dell, you know, before I made the decision, there's a little bit of an overlap with Dell, but it's really small compared to the overlap, the potential with Dell hardware that we could compliment. And then I called four CEOs. I was, as I was making this decision, Andy Jassy at Amazon, he was formerly AWS CEO sat Nadela at Microsoft Thomas cor at Google and Arvin Christian at IBM to say, I'm thinking about this making decision. They are many of the mentors and friends to me. So I believe in an ecosystem. And you know, even Chuck Robbins, who the CEO of Cisco is an investor, I texted him and said, Hey, finally, we can be friends. >>It was harder to us to be friends with Cisco, given the overlap of NEX. So I have a big tent towards everybody in our ecosystem with VMware. I think the simple answer is there's no overlap okay. With, with the kind of the primary storage capabilities with VSAN. And by the same thing with Nutanix, we will be friends and, and extend that to be the best data protection solution. But given also what we could do with security, I think this is gonna go a lot further. And then it's all about meet in the field. We have common partners. I think, you know, sort of the narrative I talked about in that blog is just like snowflake was replacing Terada and ServiceNow replace remedy and CrowdStrike, replacing Symantec, we're replacing legacy vendors. We are viewed as the modern solution cloud optimized for private and public cloud. We can help you and make VMware and VSAN and VCF very relevant to that part of the data management and data security continuum, which I think could enhance VMware. And by the way, the same thing into the public cloud. So most of the places where we're being successful is clearly withs, but increasingly there's this discussion also about playing into the cloud. So I think both with VMware and Amazon, and of course the other partners in the hyperscaler service, storage, networking place and security, we have some big plans. >>How, how much do you see this? How do you see this multi-cloud narrative that we're hearing here from, from VMware evolving? How much of an opportunity is it? How are customers, you know, we heard about cloud chaos yesterday at the keynote, are customers, do they, do they admit that there's cloud chaos? Some probably do some probably don't how much of an opportunity is that for cohesive, >>It's tremendous opportunity. And I think that's why you need a Switzerland type player in this space to be successful. And you know, and you can't explicitly rule out the fact that the big guys get into this space, but I think it's, if you're gonna back up office 365 or what they call now, Microsoft 365 into AWS or Google workspace into Azure or Salesforce into one of those clouds, you need a Switzerland player it's gonna be out. And in many cases, if you're gonna back up data or you protect that data into AWS banks need a second copy of that either on premise or Azure. So it's very hard, even if they have their own native data protection for them to be dual cloud. So I think a multi-cloud story and the fact that there's at least three big vendors of cloud in, in the us, you know, one in China, if include Alibaba creates a Switzerland opportunity for us, that could be fairly big. >>And I think, you know, what we have to do is make sure while we'll be optimized, our preferred cloud is AWS. Our control plane runs there. We can't take an all in AWS stack with the control plane and the data planes at AWS to Walmart. So what I've explained to both Microsoft and AWS is that data plane will need to be multicloud. So I can go to an a Walmart and say, I can back up your data into Azure if you choose to, but the control, plane's still gonna be an AWS, same thing with Google. Maybe they have another account. That's very Google centric. So that's how we're gonna play the, the control plane will be in AWS. We'll optimize it there, but the data plane will be multi-cloud. >>Yeah. And that's what Mo had explained at Supercloud. You know, and I talked to, he really helped me hone in on the deployment models. Yes. Where, where, where the cohesive deployment model is instantiating that technology stack into each cloud region and each cloud, which gives you latency advantages and other advantages >>And single code based same platform, >>And then bringing it, tying it together with a unified, you know, interface. That was he, he was, he was key. In fact, I, I wrote about it recently and, and gave him and the other 20, >>Quite a bit in that session. Yeah. So he went deep with you. I >>Mean, with Mohi, when you get a guy who developed a Google file system, you know, who can technically say, okay, this is technically correct or no, Dave, your way off be so I that's why I had to >>Go. I, I thought you did a great job in that interview because you probed him pretty deep and I'm glad we could do that together with him next time. Well, maybe do that together here too, but it was really helpful. He's the, he's the, he's the key reason I'm here. >>So you say data management is ripe for disrupt disruption. Talk about that. You talked about this Switzerland effect. That sounds to me like a massive differentiator for cohesive. Why is data management right. For disruption and why is cohesive the right partner to do it? >>Yeah, I think, listen, everyone in this sort of data protection backup from years ago have been saying the S Switzerland argument 18 years ago, I was a at Veras an executive there. We used the Switzerland argument, but what's changed is the cloud. And what's changed as a threat vector in security. That's, what's changed. And in that the proposition of a, a Switzerland player has just become more magnified because you didn't have a sales force or Workday service now then, but now you do, you didn't have multi-cloud. You had hardware vendors, you know, Dell, HPE sun at the time. IBM, it's now Lenovo. So that heterogeneity of, of on-premise service, storage, networking, HyperCloud, and, and the apps world has gotten more and more diverse. And I think you really need scale out architectures. Every one of the legacy players were not built with scale out architectures. >>If you take that fundamental notion of bringing compute to storage, you could almost paralyze. Imagine you could paralyze backup recovery and bring so much scale and speed that, and that's what Mo invented. So he took that idea of how he had invented and built Nutanix and applied that to secondary storage. So now everything gets faster and cheaper at scale. And that's a disruptive technology ally. What snowflake did to ator? I mean, the advantage of snowflake is when you took that same concept data, warehousing is not a new concept it's existed from since Ralph Kimble and bill Inman and the people who are fathers of data warehousing, they took that to Webscale. And in that came a disruptive force toter data, right? And snowflake. And then of course now data bricks and big query, similar things. So we're doing the same thing. We just have to showcase the customers, which we do. And when large customers see that they're replacing the legacy solutions, I have a lot of respect for legacy solutions, but at some point in time of a solution was invented in 1995 or 2000, 2005. It's right. For change. >>So you use snowflake as an example, Frank sluman doesn't like when I say playbook, cuz I says, Dave, I'm a situational. See you no playbook, but there are patterns here. And one of the things he did is to your point go after, you know, Terra data with a better data warehouse, simplify scale, et cetera. And now he's, he's a constructing a Tam expansion strategy, same way he did at ServiceNow. And I, you guys following a similar pattern. Okay. You get your foot in the door. Let's face it. I mean, a lot of this started with, you know, just straight back. Okay, great. Now it's extending into data management now extending to multi-cloud that's like concentric circles in a Tam expansion strategy. How, how do as, as a CEO, that's part of your job is Tam expansion. >>So yeah, I think the way to think about the Tam is, I mean, people say it's 20, 30 billion, but let me tell you how you can piece it apart in size, Dave and Lisa number one, I estimate there's probably about 10 to 20 exabytes of data managed by these legacy players of on-prem stores that they back up to. Okay. So you add them all up in the market shares that they respectively are. And by the way, at the peak, the biggest of these companies got to 2 billion and then shrunk. That was Verto when I was there in 2004, 2 billion, every one of them is small and they stopped growing. You look at the IDC charts. Many of them are shrinking. We are the fastest growing in the last two years, but I estimate there's about 20 exabytes of data that collectively among the legacy players, that's either gonna stay on prem or move to the cloud. Okay. So the opportunity as they replace one of those legacy tools with us is first off to manage that 20 X bike cheaper, faster with the Webscale, a glass or for the cloud guys, we could tip that into the cloud. Okay. >>But you can't stop there. >>Okay. No, we are not doing just back recovery. Right. We have a platform that can do files. We can do test dev analytics and now security. Okay. That data is potentially at a risk, not so much in the past, but for ransomware, right? How do we classify that? How do we govern that data? How do we run potential? You know, the same way you did antivirus some kind of XDR algorithms on the data to potentially not just catch the recovery process, which is after fact, but maybe the predictive act of before to know, Hey, there's somebody loitering around this data. So if I'm basically managing in the exabytes of data and I can proactively tell you what, this is, one CIO described this very simply to me a few weeks ago that I, and she said, I have 3000 applications, okay. I wanna be prepared for a black Swan event, except it's not a nine 11 planes hitting the, the buildings. >>It is an extortion event. And I want to know when that happens, which of my 3000 apps I recover within one hour within one day within one week, no lay than one month. Okay. And I don't wanna pay the bad guys of penny. That's what we do. So that's security discussions. We didn't have that discussion in 2004 when I was at another company, because we were talking about flood floods and earthquakes as a disaster recovery. Now you have a lot more security opportunity to be able to describe that. And that's a boardroom discussion. She needs to have that >>Digital risk. O O okay, go ahead please. I >>Was just gonna say, ransomware attack happens every what? One, every 11, 9, 11 seconds. >>And the dollar amount are going up, you know, dollar of what? >>Yep. And, and when you pay the ransom, you don't always get your data back. So you that's >>Not. And listen, there's always an ethical component. Should you do it or not do it? If you, if you don't do it and you're threatened, they may have left an Easter egg there. Listen, I, I feel very fortunate that I've been doing a lot in security, right? I mean, I built the business at, at, at VMware. We got it to over a billion I'm on the board of sneak. I've been doing security and then at SAP ran. So I know a lot about security. So what we do in security and the ecosystem that supports us in security, we will have a very carefully crafted stay tuned. Next three weeks months, you'll see us really rolling out a very kind of disciplined aspect, but we're not gonna pivot this company and become a cyber security company. Some others in our space have done that. I think that's not who we are. We are a data management and a data security company. We're not just a pure security company. We're doing both. And we do it well, intelligently, thoughtfully security is gonna be built into our platform, not bolted on, okay. And there'll be certain security things that we do organically. There's gonna be a lot that we do through partnerships, >>This security market that's coming to you. You don't have to go claim that you're now a security vendor, right? The market very naturally saying, wow, a comprehensive security strategy has to incorporate a data protection strategy and a recovery, you know, and the things we've talking about, Mount ransomware, I want to ask you, you know, I've been around a long time, longer than you actually Sanjay. So, but you you've, you've seen a lot. You look incredibly, >>Thank you. That's all good. Oh, >>Shocks. So the market, I've never seen a market like this, right? I okay. After the.com crash, we said, and I know you can't talk about IPO. That's not what I'm talking about, but everything was bad after that. Right. 2008, 2000, everything was bad. I've never seen a market. That's half full, half empty, you know, snowflake beats and raises the stock, goes through the roof. Dev if it, the area announced today, Mongo, DB, beat and Ray, that things getting crushed. And, and after market never seen anything like this. It's so fed, driven and, and hard to protect. And, and of course, I know it's a marathon, you know, it's not a sprint, but have you ever seen anything like this? >>Listen, I walk worked through 18 quarters as COO of VMware. You seen, I've seen public quarters there and you know, was very fortunate. Thanks to the team. I don't think I missed my numbers in 18 quarters except maybe once close. But we, it was, it's tough. Being a public company. Officer of the company is tough. I did that also at SAP. So the journey from 10 to 20 billion at SAP, the journey from six to 12 at VMware, that I was able to be fortunate. It's humbling because you, you really, you know, we used to have this, we do the earnings call and then we kind of ask ourselves, what, what do you think the stock price was gonna be a day and a half later? And we'd all take bets as to wear this. I think you just basically, as a, as a sea level executive, you try to build a culture of beaten, raise, beaten, raise, beaten, raise, and you wanna set expectations in a way that you're not setting them up for failure. >>And you know, it's you, there's, Dave's a wonderful CEO as is Frank movement. So it's hard for me to dissect. And sometimes the market are fickle on some small piece of it. But I think also the, when I, I encourage people say, take the long term view. When you take the long term view, you're not bothered about the ups and downs. If you're building a great company over the length of time, now it will be very clear over the arc of many, many quarters that you're business is trouble. If you're starting to see a decay in growth. And like, for example, when you start to see a growth, start to decay significantly by five, 10 percentage points, okay, there's something macro going on at this company. And that's what you won't avoid. But these, you know, ups and downs, my view is like, if you've got both Mongo, DIA and snowflake are fantastic companies, they're CEOs of people I respect. They've actually a kind of an, a, you know, advisor to us as a company, you knows mot very well. So we respect him, respect Frank, and you, there have been other quarters where Frank's, you know, the snowflakes had a down result after that. So you build a long term and they are on the right side of history, snowflake, and both of them in terms of being a modern cloud relevant in the case of MongoDB open source to data technology, that's, you know, winning, I, we would like to be like them one day >>As, as the new CEO of cohesive, what are you most, what are you most anxious about? And what are you most excited about? >>I think, listen, you know, you know, everything starts with the employee. You, I always believe I wrote my first memo to all employees. There was an article in Harvard business review called service profit chains that had a seminal impact on my leadership, which is when they studied companies who had been consistently profitable over a long period of time. They found that not just did those companies serve their customers well, but behind happy engaged customers were happy, engaged employees. So I always believe you start with the employee and you ensure that they're engaged, not just recruiting new employees. You know, I put on a tweet today, we're hiring reps and engineers. That's okay. But retaining. So I wanna start with ensuring that everybody, sometimes we have to make some unfortunate decisions with employees. We've, we've got a part company with, but if we can keep the best and brightest retained first, then of course, you know, recruiting machine, I'm trying to recruit the best and brightest to this company, people all over the place. >>I want to get them here. It's been, so I mean, heartwarming to come to world and just see people from all walks, kind of giving me hugs. I feel incredibly blessed. And then, you know, after employees, it's customers and partners, I feel like the tech is in really good hands. I don't have to worry about that. Cuz Mo it's in charge. He's got this thing. I can go to bed knowing that he's gonna keep innovating the future. Maybe in some of the companies, I would worried about the tech innovation piece, but most doing a great job there. I can kind of leave that in his cap of hands, but employees, customers, partners, that's kind of what I'm focused on. None of them are for me, like a keep up at night, but they're are opportunities, right? And sometimes there's somebody you're trying to salvage to make sure or somebody you're trying to convince to join. >>But you know, customers, I love pursuing customers. I love the win. I hate to lose. So fortune 1000 global, 2000 companies, small companies, big companies, I wanna win every one of 'em and it's not, it's not like, I mean, I know all these CEOs in my competitors. I texted him the day I joined and said, listen, I'll compete, honorably, whatever have you, but it's like Kobe and LeBron Kobe's passed away now. So maybe it's step Curry. LeBron, whoever your favorite athlete is you put your best on the court and you win. And that's how I am. That's nothing I've known no other gear than to put my best on the court and win, but do it honorably. It should not be the one that you're doing it. Unethically. You're doing it personally. You're not calling people's names. You're competing honorably. And when you win the team celebrates, it's not a victory for me, it's a victory for the team. >>I always think I'm glad that you brought out the employee experience and we're almost out of time, but I always think the employee experience and the customer experience are inextricably linked. This employees have to be empowered. They have to have the data that they need to do their job so that they can deliver to the customer. You can't do one without the other. >>That's so true. I mean, I, it's my belief. And I've talked also on this show and others about servant leadership. You know, one of my favorite poems is Brenda NA Tago. I went to bed in life. I dreamt that life was joy. I woke up and realized life was service. I acted in service was joy. So when you have a leadership model, which is it's about, I mean, there's lots of layers between me and the individual contributor, but I really care about that sales rep and the engineer. That's the leaf level of the organization. What can I get obstacle outta their way? I love skipping levels and going write that sales rep let's go and crack this deal. You know? So you have that mindset. Yeah. I mean, you, you empower, you invert the pyramid and you realize the power is at the leaf level of an organization. >>So that's what I'm trying to do. It's a little easier to do it with 2000 people than I dunno, either 20, 20, 2000 people or 35,000 reported me at VMware. And I mean a similar number at SAP, which was even bigger, but you can shape this. Now we are, we're not a startup anymore. We're a mid-size company. We'll see. Maybe along the way, there's an IP on the path. We'll wait for that. When it comes, it's a milestone. It's not the destination. So we do that and we are, we, I told people we are gonna build this green company. Cohesive is gonna be a great company like VMware one day, like Amazon. And there's always a day of early beginnings, but we have to work harder. This is kind of like the, you know, eight year old version of your kid, as opposed to the 18 year old version of the kid. And you gotta work a little harder. So I love it. Yeah. >>Good luck. Awesome. Thank you too. Best of luck. Congratulations on the role, it sounds like there's a tremendous amount of adrenaline, a momentum carrying you forward Sanja. We always appreciate having thank >>You for having in your show. >>Thank you. Our pleasure, Lisa. Thank you for Sanjay poin and Dave ante. I'm Lisa Martin. You're watching the cube live from VMware Explorer, 2022, stick around our next guest. Join us momentarily.

>>Welcome to this Q conversation. I'm Dave Nicholson. And today we are joined by Andrew ish and Chris Y Moran, both from Gentech. Andrew is the vice president of marketing. Chris John is the, uh, vice president of product engineering, gentlemen, welcome to the cube. >>Welcome David. Thanks for having us. Hey, >>David, thanks for having us on your show. >>Absolutely. Give us just, let's start out by, uh, giving us some background on, on Gentech. How would you describe to a relative coming over and asking you what you do for a living? What Genotech does? >>Well, I'll take a shot at that. I'm the marketing guy, David, but, uh, I think the best way to think of Genotech first and foremost is a software company. We, uh, we do a really good job of bringing together all of that physical security sensor network onto a platform. So people can make sense out of the data that comes from video surveillance, cameras, access control, reads, license plate recognition, cameras, and from a whole host of different sensors that can live out there in the world. Temperature, sensors, microwaves, all sorts of stuff. So we're a company that's really good at making sense of complex data from sensors. That's kind of, I think that's kind of what we >>Do and, and, and we focus specifically on like larger, complex, critical infrastructure type projects, whether they be airports, uh, large enterprise campuses and whatnot. So we're not necessarily your well known consumer type brand. >>So you mentioned physical, you mentioned physical security. Um, what about the intersection between physical security and, and cyber security who are, who are the folks that you work with directly as customers and where do they, where do they sit in that spectrum of cyber versus physical? >>So we predominantly work with physical security professionals and, uh, they typically are responsible for the security of a facility, a campus, a certain area. And we'll talk about security cameras. We'll talk about access control devices with card readers and, and, and locks, uh, intrusion detection, systems, fences, and whatnot. So anything that you would see that physically protects a facility. And, uh, what's actually quite interesting is that, you know, cybersecurity, we, we hear about cybersecurity and depressed all the time, right. And who's been hacked this week is typically like, uh, a headline that we're all like looking at, uh, we're looking for in the news. Um, so we actually do quite a lot of, I would say education work with the physical security professional as it pertains to the importance of cyber security in the physical security system, which in and of itself is an information system. Right. Um, so you don't wanna put a system in place to protect your facility that is full of cybersecurity holes because at that point, you know, your physical security systems becomes, uh, your weakest link in your security chain. Uh, the way I like to say it is, you know, there's no such thing as physical security versus cyber security, it's just security. Uh, really just the concept or a context of what threat vectors does this specific control or mechanism actually protects against >>Those seem to be words to live by, but are, are they aspirational? I mean, do you, do you see gaps today, uh, between the worlds of cyber and physical security? >>I mean, for sure, right? Like we, physical security evolved from a different part of the enterprise, uh, structure then did it or cyber security. So they, they come at things from a different angle. Um, so, you know, for a long time, the two worlds didn't really meet. Uh, but now what we're seeing, I would say in the last 10 years, Christian, about that, there's a huge convergence of cyber security with physical security. It, so information technology with operation technology really coming together quite tightly in the industry. And I think leading companies and sophisticated CISOs are really giving a big pitcher thought to what's going on across the organization, not just in cybersecurity. >>Yeah. I think we've come a long way from CCTV, which stands for closed circuit television, uh, which was typically like literally separated from the rest of the organization, often managed by the facilities, uh, part of any organization. Uh, and now we're seeing more and more organizations where this is converging together, but there's still ways to go, uh, to get this proper convergence in place. But, you know, we're getting there. >>How, how does Gentech approach its addressable market? Is this, is this a direct model? Uh, do you work with partners? What, what does that look like in your world? >>Well, we're a, we're a partner led company Gentech, you know, model on many friends is all about our partners. So we go to market through our integration channel. So we work with really great integrators all around the world. Um, and they bring together our software platform, which is usually forms the nucleus of sort of any O T security network. Uh, they bring that together with all sorts of other things, such as the sensor network, the cabling, all of that. It's a very complex multiplayer world. And also in that, you know, partnership ecosystem and Christian, this is more your world. We have to build deep integrations with all of these companies that build sensors, whether that's access, Bosch, Canon, uh, Hanoi, you know, we're, we're really working with them them. And of course with our storage and server partners >>Like Dell >>Mm-hmm <affirmative>. Yeah. So we have, we have like hundreds of, I would say ecosystem partners, right? Camera manufacturers, uh, access control reader, controller manufacturers, intrusion detection, manufacturers, late LIDAR radar, you know, the list goes on and on and on. And, and basically we bring this all together. The system integrator really is going to pick best of breed based on a specific end customer's I would say requirements and then roll out the system. According >>That's very interesting, you know, at, at Silicon angle on the cube, um, we've initiated coverage of this subject of the question, does hardware still matter? And, and you know, of course we're, we're approaching that primarily from kind of the traditional it, uh, perspective, but you said at the outset, you you're a software company mm-hmm <affirmative>, but clearly correct me if I'm wrong, your software depends upon all of these hardware components and as they improve, I imagine you can do things that maybe you couldn't do before those improvements. The first thing that comes to mind is just camera resolution. Um, you know, sort of default today is 4k, uh, go back five years, 10 years. I imagine that some of the sophisticated things that you can do today weren't possible because the hardware was lagging. Is that, is that a, is that a fair assessment? >>Oh, that's a fair assessment. Just going back 20 years ago. Uh, just VGA resolution on a security camera was like out of this world resolution, uh, even more so if it was like full motion, 30 images per second. So you typically have like, probably even like three 20 by 2 44 images per second, like really lousy resolution, just from a resolution perspective, the, the imagery sensors have, have really increased in terms of what they can provide, but even more so is the horsepower of these devices. Mm-hmm, <affirmative> now it's not uncommon to have, uh, pretty, pretty powerful Silicon in those devices now that can actually run machine learning models and you can actually do computer vision and analytics straight into the device. Uh, as you know, in some of the initial years, you would actually run this on kind of racks of servers in this data center. >>Now you can actually distribute those workloads across on the edge. And what we're seeing is, you know, the power that the edge provides is us as a software company, we have the opportunity to actually bring our workloads where it makes most sense. And in some cases we'll actually also have a ground station kind of in between the sensors and potentially the cloud, uh, because the use case just, uh, calls for it. Uh, just looking from a, from a, from a video security perspective, you know, when you have hundreds or thousands of cameras on an airport, it's just not economical or not even feasible in some cases to bring all that footage to the cloud even more so when 99% of that footage is never watched by anybody. So what's the point. Uh, so you just wanna provide the clips that, that actually do matter to the cloud and for longer term retention, you also want to be able to have sometimes more resilient systems, right? So what happens if the cloud disconnects, you can stop the operations of that airport or stop that operations of that, of that prison, right? It needs to continue to operate and therefore you need higher levels of resiliency. So you do need that hardware. So it's really a question of what it calls for and having the right size type of hardware so that you don't overly complexify the installation, uh, and, and actually get the job done. Are >>You comparing airports to prisons >>Christian? Well, nowadays they're pretty much prepared <laugh>, >>But I mean, this is exactly it, David, but I mean, this payload, especially from the video surveillance, like the, the workload that's going through to the, these ground stations really demands flexible deployment, right? So like we think about it as edge to cloud and, uh, you know, that's, what's really getting us excited because it, it gives so much more flexibility to the, you know, the C I S O and security professionals in places like prisons, airports, also large scale retail and banking, and, uh, other places, >>Universities, the list goes on and on and on, and >>On the flexibility of deployment just becomes so much easier because these are lightweight, you usually word deploying on a Linux box and it can connect seamlessly with like large scale head end storage or directly to, uh, cloud providers. It's, it's really a sophisticated new way of looking at how you architect out these networks. >>You've just given, you've just given a textbook example of why, uh, folks in the it world have been talking about hybrid cloud for, for, for such a long time, and some have scoffed at the idea, but you just, you just present a perfect use case for that combination of leveraging cloud with, uh, on-premises hardware and tracking with hardware advances, um, uh, on, on the subject of camera resolution. I don't know if you've seen this meme, but there's a great one with the, the first deep field image from the, from the, I was gonna say humble, the James web space telescope, uh, in contrast with a security camera F photo, which is really blurry of someone in your driveway <laugh>, uh, which is, which is, uh, sort of funny. The reality though, is I've seen some of these latest generation security cameras, uh, you know, beyond 4k resolution. And it's amazing just, you know, the kind of detail that you can get into, but talk about what what's, what's exciting in your world. What's, what's Gentech doing, you know, over the next, uh, several quarters that's, uh, particularly interesting what's on the leading edge of your, of your world. >>Well, I think right now what's on the leading edges is being driven by our end users. So the, so the, the companies, the governments, the organizations that are implementing our software into these complex IOT networks, they wanna do more with that data, right? It's not just about, you know, monitoring surveillance. It's not just about opening and closing doors or reading license plates, but more and more we're seeing organizations taking this bigger picture view of the data that is generated in their organizations and how they can take value out of existing investments that they've made in sensor networks, uh, and to take greater insight into operations, whether that can be asset utilization, customer service efficiency, it becomes about way more than just, you know, either physical security or cyber security. It becomes really an enterprise shaping O T network. And to us, that is like a massive, massive opportunity, uh, in the, in the industry today. >>Yeah. >>Now you're you're you're oh, go ahead. I'm sorry, Christian, go ahead. Yeah, >>No, it's, it's, it's good. But, you know, going back to a comment that I mentioned earlier about how it was initially siloed and now, you know, we're kind of discovering this diamond in the rough, in terms of all these sensors that are out there, which a lot of organizations didn't even know existed or didn't even know they had. And how can you bring that on kind of across the organizations for non-security related applications? So that's kind of one very interesting kind of, uh, direction that we're, that we've been undergoing for the last few years, and then, you know, security, uh, and physical security for that matter often is kind of the bastard step child. Doesn't get all the budget and, you know, there's lots of opportunities for, to help them increase and improve their operations, uh, as, as Andrew pointed out and really help bringing them into the 21st century. >>Yeah. >>And you're, you're headquartered in Montreal, correct? >>Yes. >>Yeah. So, so the reason, the reason why that's interesting is because, um, and, you know, correct me if I'm, if I'm off base here, but, but you're sort of the bridge between north America and Europe. Uh, and, and, uh, and so you sit at that nexus where, uh, you probably have more of an awareness of, uh, trends in security, which overlap with issues of privacy. Yeah. Where Europe has led in a lot of cases. Um, some of those European like rules are coming to north America. Um, is there anything in your world that is particularly relevant or that concerns you about north America catching up, um, or, or do those worlds of privacy and security not overlap as much as I might think they do? >>Ah, thank you. Any >>Thoughts? >>Absolutely not. No, no. <laugh> joking aside. This is, this is, this is, >>Leave me hanging >><laugh>, uh, this is actually core to our DNA. And, and, and we, we often say out loud how, like Europe has really paved the way for a different way, uh, of, of looking at privacy from a security setting, right. And they're not mutually exclusive. Right. You can have high security all while protecting people's privacy. And it's all of a question of ensuring that, you know, how you kind of, I would say, uh, ethically, uh, use said technology and we can actually put some safeguards in it. So to minimize the likelihood of there being abuse, right? There's, there's something that we do, which we call the privacy protector, which, you know, for all intents and purposes, it's not that complex of an idea. It's, it's really the concept of you have security cameras in a public space or a more sensitive location. And you have your security guards that can actually watch that footage when nothing really happens. >>You, you want to protect people's privacy in these situations. Uh, however, you still want to be able to provide a view to the security guard so they can still make out that, you know, there there's actually people walking around or there's a fight that broke out. And in the likelihood that something did happen, then you can actually view the overall footage. So, and with, with the details that the cameras that you had, you know, the super high mega pixel cameras that you have will provide. So we blur the images of the individuals. We still keep the background. And once you have the proper authorization, and this is based on the governance of the organization, so it can be a four I principle where it could be the chief security officer with the chief privacy officer need to authorize this footage to be kind of UN blurred. And at that point you can UN blur the footage and provide it to law enforcement for the investigation, for example. >>Excellent. I've got Andrew, if you wanted, then I, then I'm. Well, so I, I've a, I have a final question for you. And this comes out of a game that, uh, some friends and I, some friends of mine and I devised over the years, primarily this is played with strangers that you meet on airplanes as you're traveling. But the question you ask is in your career, what you're doing now and over the course of your careers, um, what's the most shocking thing <laugh> that people would learn from what, you know, what do you, what do you find? What's the craziest thing. When you go in to look at these environments that you see that people should maybe address, um, well, go ahead and start with you, Andrew. >>I, >>The most shocking thing you see every day in your world, >>It's very interesting. The most shocking thing I think we've seen in the industry is how willing, uh, some professionals are in our industry to install any kind of device on their networks without actually taking the time to do due diligence on what kind of security risks these devices can have on a network. Because I think a lot of people don't think about a security camera as first and foremost, a computer, and it's a computer with an IP address on a network, and it has a visual sensor, but we always get pulled in by that visual sensor. Right. And it's like, oh, it's a camera. No, it's a computer. And, you know, over the last, I would say eight years in the industry, we've spent a lot of time trying to sensitize the industry to the fact that, you know, you can't just put devices on your, your network without understanding the supply chain, without understanding the motives behind who's put these together and their track record of cybersecurity. So probably the weirdest thing that I've seen in my, um, you know, career in this industry is just the willingness of people not to take time to do due diligence before they hook something up on onto their corporate network where, you know, data can start leaking out, being exfiltrated by those devices and malevolent actors behind them. So gotta ask questions about what you put on your network. >>Christian, did he steal your, did he steal your thunder? Do you have any other, any other thoughts? >>Well, so first of all, there's things I just cannot say on TV. Okay. But you can't OK. >>You can't. Yeah, yeah, yeah. Saying that you're shocked that not everyone speaks French doesn't count. Okay. Let's just get, let's get past that, but, but go, but yeah, go ahead. Any thoughts? >>So, uh, you know, I, I would say something that I I've seen a lot and, and specifically with customers sometimes that were starting to shop for a new system is you'd be surprised by first of all, there's a camera, the likelihood of actually somebody watching it live while you're actually in the field of view of that camera is close to Neil first and foremost, second, there's also a good likelihood that that camera doesn't even record. It actually is not even functional. And, and I would say a lot of organizations often realize that, you know, that camera was not functioning when they actually knew do need to get the footage. And we've seen this with some large incidents, uh, very, uh, bad incidents that happened, uh, whether in the UK or in Boston or whatnot, uh, when they're, when law enforcement is trying to get footage and they realize that a lot of cameras actually weren't recording and, and, and goes back to Andrew's point in terms of the selection process of these devices. >>Yeah. Image resolution is important, like, because you need an, an image that it actually usable so that you can actually do something with it forensically, but you know, these cameras need to be recorded by a reliable system and, and should something happen with the device. And there's always going to be something, you know, power, uh, uh, a bird ate the lens. I don't know what it might be, or squirrel ate the wire. Um, and the camera doesn't work anymore. So you have to replace it. So having a system that provides, you know, you with like health insights in terms of, of, of if it's working or not is, is actually quite important. It needs to be managed like any it environment, right? Yeah. You have all these devices and if one of them goes down, you need to manage it. And most organizations it's fire and forget, I sign a purchase order. I bought my security system, I installed it. It's done. We move on to the next one and seven years later, something bad happens. And like, uhoh, >>It's not a CCTV system. It's a network. Yeah. Life cycle management counts. >>Well, uh, I have to say on that, uh, I'm gonna be doing some research on Canadian birds and squirrels. I, I had no idea, >>Very hungry. >>Andrew, Chris, John, thank you so much. Great conversation, uh, from all of us here at the cube. Thanks for tuning in. Stay tuned. The cube from Silicon angle media, we are your leader in tech coverage.

>>And welcome to this cube conversation here in Palo Alto, California. I'm John furrier, host of the cube. We have a great guest coming in remotely from LA Christian Hernandez developer experienced lead at code fresh code fresh IO. Recently they were on our feature at a startup showcase series, season two episode one cloud data innovations, open source innovations, all good stuff, Christian. Thanks for coming on this cube conversation. >>Thank you. Thank you, John. Thank you for having me on, >>You know, I'm I was really impressed with code fresh. My met with the founders on here on the cube because GI ops AI, everything's something ops devs dev sec ops. You've got AI ops. You've got now GI ops, essentially operationalizing the software future is here and software's eating the world is, was written many years ago, but it's open source is now all. So all things software's open source and that's kind of a done deal. It's only getting better and better. Mainstream companies are contributing. You guys are on this wave of, of this open source tsunami and you got cloud scale. Automation's right there, machine learning, all this stuff is now the next gen of, of, of code, right? So you, your code fresh and your title is developer experience lead. What does that mean right now? What does it mean to be a developer experience lead? Like you make sure people having a good experience. Are you developing you figuring out the product? What does that mean? >>Yeah. That's and it's also part of the, the whole Debre explosion that's happening right now. I believe it's, you know, everyone's always asking, well, what, you know, what is developer advocate? What does that mean developer experience? What does that mean? So, so you, you kind of hit the nail on the head a little bit up there in, in the beginning, is that the, the experience of the developer when using a particular platform, right? Especially the code flash platform. That is my responsibility there at code fresh to enable, to enable end users, to enable partners, to enable, you know, anyone that wants to use the code fresh platform for their C I C D and get ops square flows. So that's, that's really my, my corner of the world is to make sure their experience is great. So that's, it's really what, what I'm here to do >>At food fresh. You know, one of the things I can say of my career, you've been kind of become a historian over time. When I was a developer back in the old days, it was simply you compiled stuff, you did QA on it. You packaged it out. You wanted out the door and you know, that was a workflow right now with the cloud. I was talking with your founders, you got new abstraction layers. Cloud has changed again again, open source. So newer things are coming, right? Like, like, like Kubernetes for instance is a great example that came out of the open source kind of the innovations. But that, and Hadoop, we were mentioning before he came on camera from a storage standpoint, kind of didn't make it because it was just too hard. Right. And it made the developer's job harder. And then it made the developer's requirements to be specialized. >>So you had kind of two problems. You had hard to use a lot of friction and then it required certain expertise when the developers just want to code. Right. So, so you have now the motion of, with GI ops, you guys are in the middle of kinda this idea of frictionless based software delivery with the cloud. So what's different now, can you talk about that specific point because no one wants to be, do hard work and have to redo things. Yeah. Shift left and all that good stuff. What's hard now, what do you guys solve? What's the, what's the friction that you're taking out what's to become frictionless. >>Yeah. Yeah. And you, you, you mentioned a very interesting point about how, you know, things that are coming out almost makes it seem harder nowadays to develop an application. You used to have it to where, you know, kind of a, sort of a waterfall sort of workflow where, you know, you develop your code, you know, you compile it. Right. You know, I guess back in the day, Java was king. I think Java still is, has a, is a large footprint out there where you would just compile it, deploy it. If it works, it works. Alright cool. And you have it and you kind of just move it along in its process. Whereas I think the, the whole idea of, I think Netflix came out with like the, the fail often fail fast release often, you know, the whole Atlassian C I C D thing, agile thing came into play. >>Where now it's, it's a little bit more complex to get your code out there delivered to get your code from one environment to the other environment, especially with the, the Avan of Kubernetes and cloud native architecture, where you can deploy and have this imutable infrastructure where you can just deploy and automate so quickly. So often that there needs to be some sort of new process now into place where to have a new process, like GI ops to where it'll, it it's frictionless, meaning that it's, it, it makes it that process a little easier makes that little, that comp that complex process of deploying onto like a cloud native architecture easier. So that way, as you said before, returning the developers to back to what they care about, mot, the most is just code. I just want to code. >>Yeah. You know, the other thing, cool thing, Christian, I wanna bring up and we'll get into some of the specifics around Argo specifically CD is that the community is responding as a kind of, it takes a village kind of mindset. People are getting into this just saying, Hey, if we can get our act together around some de facto workflows and de facto capabilities, everyone wins. It's a rising tide, floats all boats, kind of concept. CNCF certainly has been a big part of that. Even seen some of the big hyper scales getting behind it. But you guys are part of the founding members of the open get ups working group, Amazon Azure, GitHub, red hat Weaveworks and then a ton of contributors. Okay. So this is kind of cool. This means that there's like people behind this thing. Look, we gotta get here faster. What happened at co con this year? You guys had some news around Argo and you had some news around the hosted solution. Can you take a minute to explain two things, one the open community vibe, and then two, what you guys announced at Coon in Spain. >>Yeah. Yeah. So as far as open get ups, that was, you know, as you said before, code fresh was part of that, that founding committee. Right. Of, of group of people trying to figure out, define what get ups is. Right. We're trying to bring it beyond the, you know, the, the hype word, right beyond just like a marketing term to where we actually define what it actually is, because it is actually something that's out there that people are doing. Right. A lot of people, you know, remember that the, the Chick-fil-A story where it's like, they, they are completely doing, you know, this get ops thing, we're just now wanting, putting definition around it. So that was just amazing to see out at there in, in Cuban. And, but like you said, in QAN, we, you know, we're, we're, we're taking some of that, that acceleration that we see in the community to, and we, we announce our, our hosted get ops offering. >>Right. So hosted get ops is something that our customers have been asking for for a while. Many times when, you know, someone wants to use something like Argo CD, the, in, they install it on their cluster, they get up and running. And, but with, with all that comes like the feed and care of that platform, and, you know, not only just keeping the lights on, but also management security, you know, general maintenance, you know, all the things that, that come along with managing a system. And on top of that comes like the scale aspect of it. Right. And so with scale, so a lot of people go with like a hub and spoke others, go with like a fleet design in, in either case, right. There's, there's a challenge for the feet and care of it. Right. And so with code fresh coast of get ups, we take that management headache away. >>Right? So we, we take the, the, the management of, of Argo CD, the management of, of all of that, and kind of just offer Argo CD as a surface, right. Which offers, you know, allows users to, you know, let us take care of all the, of the get offs, runtime. And so they can concentrate on, you know, their application deployments. Right. And you also get things like Dora metrics, right. Integrated with the platform, you have the ability to integrate multiple CI providers, you know, like get hub actions or whatever, existing Jenkins pipelines. And really that, that code fresh platform becomes like your get ops platform becomes like, you know, your, your central view of the world of, of your, you know, get ups processes. >>Yeah. I mean, that whole single source of truth concept is really kind of needed. I gotta ask you though, with the popularity of the Argo CD on get ups internally, right. That's been clear, right. Kubernetes, the way that's going, it's accelerating fast. People want simple it's scaling, you got automation built in all that good stuff. What was the driver behind the hosted get up solution? Was it customer needs? Was it efficiency all the above? What was specifically and, and why would someone want to have the hosted versus say internal? >>Yeah. So it's, it was really driven by, you know, customer need been something that the customers have been asking for. And it's also been something that, you know, you, you, you have a process of developing an application to, you know, you know, a fleet of clusters in a traditional, you know, I keep saying traditional, get outs practice as if get outs are so old. And, you know, in, you know, when, when, when people first start out, they'll start, you know, installing Argo city on all these clusters and trying to manage that at scale it's, it's, it, it seemed like there was, you know, it it'd be nice if we can just like, be able to consume this as a service. So we don't have to like, worry about, you know, you know, best practices. We don't have to worry about security. We don't just, all of that is taken care of and managed by us at code fresh. So this is like something that, you know, has been asked for and, and something that, you know, we believe will accelerate, you know, developers into actually developing their, their applications. They don't have to worry about managing >>The platform. So just getting this right. Hosted, managed service by you guys on this one, >>Correct? Yes. >>Okay. Got it. All right. So let me, let me get in the Argo real quick, just to kind of just level set for the folks that are, are leaning into this and then kicking the tires. Where are we with Argo? What, why was it so popular? What did it do specifically? Did it just make it easier for developers to manage and monitor Kubernetes, keep 'em updated? What was the specific value behind Argo? Where, where, where did it come from and why is it so popular? >>Yeah, so Argo the Argo project, which is made up of, of a few tools, usually when people say Argo, they meet, they they're talking about Argo CD, but there's also Argo workflows, Argo events, Argo notifications. And, and like I said before, CD with that, and that is something that was developed internally at Intuit. Right? So for those of who don't know, Intuit is the company behind turbo tax. So for those, those of us in the us, we, we know, you know, we know that season all too well, the tax season. And so that was a tool that was developed internally. >>And by the way, Intuit we've done many years. They're very huge cloud adopters. They've been on that train from the day one. They've been, they've been driving a lot of cloud scale too. Sorry >>To interrupt. Yeah. And, and, and yeah, no, and, and, and also, you know, they, they were always open source first, right. So they've always had, you know, they developed something internally. They always had the, the intention of opensourcing it. And so it was really a tool that was born internally, and it was a tool that helped them, you know, get stuff done with Kubernetes. And that's kind of like the tagline they use for, for the Argo project is you need to get stuff done. They wanted their developers to focus less on deploying the application and more right. More than on writing the application itself. And so the, and so the Argo project is a suite of tools essentially that helps deploy onto Kubernetes, you know, using get ups as that, you know, that cornerstone in design, right in the design philosophy, it's so popular because of the ease of use and developer friendliness aspect of it. It's, it's, it's, it's meant to be simple right. In and simple in a, in a good sense of getting up and running, which attracted, you know, developers from, you know, all around the world. You know, other companies like red hat got into it as well. BlackRock also is, is a, is a big contributor, thousands of other independent contributors as well to the Argo project. >>Yeah. Christian, if you bring up a good point and I'm gonna go on a little tangent here, but I wanna get your reaction to something that Dave ante and I, and our cube team has been kind of riffing on lately. You mentioned, you know, Netflix earlier, you mentioned Intuit. There's a kind of a story that's been developing and, and with traction and momentum and trajectory over the past, say 10 years, the companies that went on the cloud, like Netflix into it, snowflake, snowflake, not so much now, but in terms of open source, they're all contributing lift. They're all contributing back to open source, but they're not cloud providers. Right. So you're seeing that kind of first generation, I's a massive contribution to open source. So open source been around for a while, remember the early days, and we'd all participate on projects, but now you have real companies building IP going open source first because they're on a hyperscale cloud, but they're not the cloud themselves. They took advantage of that. So there's kind of this cycle of flywheel of cloud to open source, not from the vendors themselves like Amazon, which services or Azure, but the people who rode their CapEx and built on that scale, feeding into the open source. And then coming back, this is kind of an interesting dynamic. What's your reaction to that? Do you see that? Yeah. Super cloud kind of vibe there. >>Yeah. Yeah. Well, and, and also it, it, I think it's, it's a, it's indicative that, you know, open source is not only, you know, a way to develop, you know, applications, a way to engineer, you know, your project, but also kind of like a strategic advantage in, in, in such a way. Right. You know, you, you see, you see companies like, like, like even like Microsoft has been going into, you know, open source, right. They they've been going to open source first. They made a, a huge pivot to, you know, using open source as, you know, like, like a, like a strategic direction for, for the company. And I think that goes back to, you know, a little bit for my roots, you know, I, I, I always, I always talk about, you know, I always talk about red hat, right. I always talk about, you know, I was, I was, I was in red hat previously and, you know, you know, red hat being, you know, the first billion dollar open source company. >>Right. I, we always joke is like, well, you know, internally, like we know you were a billion dollar company that sold free software. How, you know, how, how does that happen? But it's, it's, it's really, you know, built into the, built into being able to tap into those expert resources. Yeah. You know, people love using software. People love the software they love using, and they wanna improve it. Companies are now just getting out of their way. Yeah. You know, companies now, essentially, it's just like, let's just get out of the way. Let's let people work on, you know, what they wanna work on. They love the software. They wanna improve it. Let's let them, >>It's interesting. A lot of people love the clouds have all this power. If you think about what we are just riffing on and what you just said, the economics and the organic self-governing has always been the open source way where commercial value is enabled. If you play ball, right. Like, oh, red hat, for instance. And now you're seeing the community kind of be that arbiter of the cloud. So, Hey, if everyone can create value on say AWS or Azure, bring it to open source, everyone benefits across all clouds hope eventually. So the choice aspect comes in. So this community angle is huge. And I think it's changing a lot for the better. And I think this is where we're seeing a lot of that growth. And you guys have been the middle level with the Argo project and get ups specifically in that, in that sector. How have you seen that growth? What some dynamics have you seen power dynamics, organic? Is it governed well, whats some of the, the successes, what are some of the challenges? Can you share your thoughts on the community's growth around get ops and Argo project? >>Yeah, yeah. Yeah. So I've been, you know, part of some of these communities, right? Like the, the open, get, get ops community, the Argos community pretty much from the beginning and, and seeing it developed from an idea to, you know, having all these contributors, having, you know, the, the, the buzzword come out of it, you know, the get ups and it be that being the, you know, having it, you know, all over the, you know, social media, all over LinkedIn, all over all, all these, all these different channels, you know, I I've seen things like get ops con, right. So, you know, being part of the, get ops open, get ops community, you know, one of the things we did was we did get ops con it started as a meetup, you know, couple years ago. And now, you know, it was a, you know, we had an actual event at Cuan in Los Angeles. >>You know, we had like, you know, about 50 people there, but then, you know, Cuan in Valencia this past Cuan we had over 200 people, it was a second largest co-located events in, at Cuan. So that just, just seeing that community and, you know, from a personal standpoint, you know, be being part of that, that the, the community being the, the event chair, right. Yeah. Being, being one of the co-chairs was a, was a moment of pride for me being able to stand up there and just seeing a sea of people was like, wow, we just started with a handful of people at a meetup. And now, you know, we're actually having conferences and, and, and speaking of conference, like the Argo community as well, we put in, you know, we put on a virtual only event on Argo con last year. We're gonna do it in person today. You know, this year. >>Do you have a date on that? Do you have a date on that Argo con 22? >>Two? Yeah, yeah, yeah. Argo con September 19th, 2022. So, you know, mark your calendars, it it's, you know, it's a multi-day event, you know, it's, it's part of something else that I've seen in the community where, you know, first we're talk talking about these meetups. Now we're doing multi-day events. We're, you know, in talks of the open, get ups, you know, get ups can also make that a multi-day event. There's just so many talks in so many people that want to be involved in network that, you know, we're saying, well, we're gonna need more days because there's just so many people coming to these events, you know, in, in, you know, seeing these communities grow, not just from like the engineering standpoint, but also from the end user standpoint, but also from the people that are actually doing these things. And, you know, seeing some of these use cases, seeing some of the success, seeing some of the failures, right? Like people love listening to those talks about postmortems, I think are part of my favorite talks as well. So seeing that community grow is, is, you know, on a personal level, it's, it's a point >>It's like CSI for software developers. You want to curious about >>Exactly >>What happened. You know, you know, it's interesting, you mentioned about the, the multiple events at Coon. You know, the vibe that's going on is a very festival vibe, right? You have organic groups coming together. I remember when they had just started doing the day zero programs. Now you have like, almost like multiple stages of content at these events. It feels like, like a Coachella vibe or some sort of like festival vibe, like a lot of things going on and you, and if you pick your kind of area, but you can move around, I find that the kind of the format de Azure I think is going well these days. What do you think about that? >>Yeah, yeah. No, for sure. It's and, and, and I love that that analogy of Coachella, it does feel like, you know, it's, there's something for everyone and you can find what you like, and you'll find a little, you know, a little group, right. A little click of, of, of people that's probably the wrong term to use, but you know, you, you find, you know, you, you know, like-minded people and, you know, passionate about the same thing, right? Like the security guys, they, you know, you see them all clump together, right? Like you see like the, the developer C I CD get ops guys, we all kind of clump together and start talking, you know, about everything that we're doing. And it's, that's, that's, I think that's really something special that coupon, you know, some, you know, it's gotten so big that it's almost impossible to fit everything in a, in a week, because unless there's just so much to do. And there's so much that that interests, you know, someone, but it's >>A code, a code party is what we call it. It's a code party. Yeah. >>It's, it's a code party for sure. For >>Sure. Nerd nerd Fest on, on steroids. Hey, I gotta get, I wanna wrap this up and give you the final word, Christian. Thanks for coming on. Great insight, great conversation. There's a huge, you guys are in the middle of a hot area, obviously large scale data growth. Kubernetes is scaling beautifully and making it easier at managed services. What people want machine learning's kicking in and, and you get automation building in all favoring, the developer and C I CD pipeline and all that good stuff. People want to learn more. Can you take a minute to put the plug in for code fresh on the certification? How do I get involved? Where are you? Is there levels if I want to jump in and get trained and get fluent on code fresh, can you share commentary and, and, and what the status is? >>Yeah, yeah, for sure. So code fresh is offering a free certification, right? For get ups or Argo CD and get ops. The first of it's kind for Argo CD, first of it's kind for get ops is you can actually go get certified with Argo CD and get ops. You know, we there level one is out right now. You can go take that code, fresh.io/certification. It's out there, sign up, you know, you, you don't, you don't need to pay anything, right. It's, it's something it's a, of a free course. You could take level two is coming soon. Right? So level two is coming soon in the next few months, I believe I don't wanna quote a specific day, but soon because I, but soon I, it it's soon, soon as in, as in months. Right? So, you know, we're, we're counting that down where you can not only level one cert level certification, but a level, two more advanced certification for those who have been using Argo for a while, they can still, you know, take that and be, you know, be able to get, you know, another level of certification for that. So also, you know, Argo con will be there. We're, we're part of the programming committee for Argo con, right? This is a community driven event, but, you know, code fresh is a proud diamond sponsor. So we'll be there. >>Where's it located up to us except for eptember 19th multiday or one day >>It's a, it's a multi-day event. So Argo con from 19, 19 20 and 21 in a mountain view. So it'll be in mountain view in the bay area. So for those of you who are local, you can just drive in. Great. >>I'm write that down. I'll plug it. I'll put in the show notes. >>Awesome. Awesome. Yeah. And you will be there so you can talk to me, you can talk to anyone else at code, fresh talking about Argo CD, you know, find, find out more about hosted, get ups code, fresh.io. You know, you can find us in the Argo project, open, get ups community, you know, we're, we're, we're deep in the community for both Argo and get ups. So, you know, you can find us there as well. >>Well, let's do a follow up in when you're in town, so's only a couple months away and getting through the summer, it's already, I can't believe events are back. So it's really great to see face to face in the community. And there was responding. I mean, co con in October, I think that was kind of on the, that was a tough call and then get to see your own in Spain. I couldn't make it. Unfortunately, I had got COVID came down with it, but our team was there. Open sources, booming continues to go. The next level, new power dynamics are developing in a great way. Christian. Thanks for coming on, sharing your insights as the developer experience lead at code fresh. Thanks so much. >>Thank you, John. I appreciate it. >>Okay. This is a cube conversation. I'm John feer, host of the cube. Thanks for watching.

(upbeat music) >> Hello, everyone. Welcome to the theCUBE's presentation of the AWS Startup Showcase. The theme, this showcase is MarTech, the emerging cloud scale customer experiences. Season two of episode three, the ongoing series covering the startups, the hot startups, talking about analytics, data, all things MarTech. I'm your host, John Furrier, here joined by Christian Wiklund, founder and CEO of unitQ here, talk about harnessing the power of user feedback to empower marketing. Thanks for joining us today. >> Thank you so much, John. Happy to be here. >> In these new shifts in the market, when you got cloud scale, open source software is completely changing the software business. We know that. There's no longer a software category. It's cloud, integration, data. That's the new normal. That's the new category, right? So as companies are building their products, and want to do a good job, it used to be, you send out surveys, you try to get the product market fit. And if you were smart, you got it right the third, fourth, 10th time. If you were lucky, like some companies, you get it right the first time. But the holy grail is to get it right the first time. And now, this new data acquisition opportunities that you guys in the middle of that can tap customers or prospects or end users to get data before things are shipped, or built, or to iterate on products. This is the customer feedback loop or data, voice of the customer journey. It's a gold mine. And it's you guys, it's your secret weapon. Take us through what this is about now. I mean, it's not just surveys. What's different? >> So yeah, if we go back to why are we building unitQ? Which is we want to build a quality company. Which is basically, how do we enable other companies to build higher quality experiences by tapping into all of the existing data assets? And the one we are in particularly excited about is user feedback. So me and my co-founder, Nik, and we're doing now the second company together. We spent 14 years. So we're like an old married couple. We accept each other, and we don't fight anymore, which is great. We did a consumer company called Skout, which was sold five years ago. And Skout was kind of early in the whole mobile first. I guess, we were actually mobile first company. And when we launched this one, we immediately had the entire world as our marketplace, right? Like any modern company. We launch a product, we have support for many languages. It's multiple platforms. We have Android, iOS, web, big screens, small screens, and that brings some complexities as it relates to staying on top of the quality of the experience because how do I test everything? >> John: Yeah. >> Pre-production. How do I make sure that our Polish Android users are having a good day? And we found at Skout, personally, like I could discover million dollar bugs by just drinking coffee and reading feedback. And we're like, "Well, there's got to be a better way to actually harness the end user feedback. That they are leaving in so many different places." So, you know what, what unitQ does is that we basically aggregate all different sources of user feedback, which can be app store reviews, Reddit posts, Tweets, comments on your Facebook ads. It can be better Business Bureau Reports. We don't like to get to many of those, of course. But really, anything on the public domain that mentions or refers to your product, we want to ingest that data in this machine, and then all the private sources. So you probably have a support system deployed, a Zendesk, or an Intercom. You might have a chatbot like an Ada, or and so forth. And your end user is going to leave a lot of feedback there as well. So we take all of these channels, plug it into the machine, and then we're able to take this qualitative data. Which and I actually think like, when an end user leaves a piece of feedback, it's an act of love. They took time out of the day, and they're going to tell you, "Hey, this is not working for me," or, "Hey, this is working for me," and they're giving you feedback. But how do we package these very messy, multi-channel, multiple languages, all over the place data? How can we distill it into something that's quantifiable? Because I want to be able to monitor these different signals. So I want to turn user feedback into time series. 'Cause with time series, I can now treat this the same way as Datadog treats machine logs. I want to be able to see anomalies, and I want to know when something breaks. So what we do here is that we break down your data in something called quality monitors, which is basically machine learning models that can aggregate the same type of feedback data in this very fine grained and discrete buckets. And we deploy up to a thousand of these quality monitors per product. And so we can get down to the root cause. Let's say, passive reset link is not working. And it's in that root cause, the granularity that we see that companies take action on the data. And I think historically, there has been like the workflow between marketing and support, and engineering and product has been a bit broken. They've been siloed from a data perspective. They've been siloed from a workflow perspective, where support will get a bunch of tickets around some issue in production. And they're trained to copy and paste some examples, and throw it over the wall, file a Jira ticket, and then they don't know what happens. So what we see with the platform we built is that these teams are able to rally around the single source of troop or like, yes, passive recent link seems to have broken. This is not a user error. It's not a fix later, or I can't reproduce. We're looking at the data, and yes, something broke. We need to fix it. >> I mean, the data silos a huge issue. Different channels, omnichannel. Now, there's more and more channels that people are talking in. So that's huge. I want to get to that. But also, you said that it's a labor of love to leave a comment or a feedback. But also, I remember from my early days, breaking into the business at IBM and Hewlett-Packard, where I worked. People who complain are the most loyal customers, if you service them. So it's complaints. >> Christian: Yeah. >> It's leaving feedback. And then, there's also reading between the lines with app errors or potentially what's going on under the covers that people may not be complaining about, but they're leaving maybe gesture data or some sort of digital trail. >> Yeah. >> So this is the confluence of the multitude of data sources. And then you got the siloed locations. >> Siloed locations. >> It's complicated problem. >> It's very complicated. And when you think about, so I started, I came to Bay Area in 2005. My dream was to be a quant analyst on Wall Street, and I ended up in QA at VMware. So I started at VMware in Palo Alto, and didn't have a driver's license. I had to bike around, which was super exciting. And we were shipping box software, right? This was literally a box with a DVD that's been burned, and if that DVD had bugs in it, guess what it'll be very costly to then have to ship out, and everything. So I love the VMware example because the test cycles were long and brutal. It was like a six month deal to get through all these different cases, and they couldn't be any bugs. But then as the industry moved into the cloud, CI/CD, ship at will. And if you look at the modern company, you'll have at least 20 plus integrations into your product. Analytics, add that's the case, authentication, that's the case, and so forth. And these integrations, they morph, and they break. And you have connectivity issues. Is your product working as well on Caltrain, when you're driving up and down, versus wifi? You have language specific bugs that happen. Android is also quite a fragmented market. The binary may not perform as well on that device, or is that device. So how do we make sure that we test everything before we ship? The answer is, we can't. There's no company today that can test everything before the ship. In particular, in consumer. And the epiphany we had at our last company, Skout, was that, "Hey, wait a minute. The end user, they're testing every configuration." They're sitting on the latest device, the oldest device. They're sitting on Japanese language, on Swedish language. >> John: Yeah. >> They are in different code paths because our product executed differently, depending on if you were a paid user, or a freemium user, or if you were certain demographical data. There's so many ways that you would have to test. And PagerDuty actually had a study they came out with recently, where they said 51% of all end user impacting issues are discovered first by the end user, when they serve with a bunch of customers. And again, like the cool part is, they will tell you what's not working. So now, how do we tap into that? >> Yeah. >> So what I'd like to say is, "Hey, your end user is like your ultimate test group, and unitQ is the layer that converts them into your extended test team." Now, the signals they're producing, it's making it through to the different teams in the organization. >> I think that's the script that you guys are flipping. If I could just interject. Because to me, when I hear you talking, I hear, "Okay, you're letting the customers be an input into the product development process." And there's many different pipelines of that development. And that could be whether you're iterating, or geography, releases, all kinds of different pipelines to get to the market. But in the old days, it was like just customer satisfaction. Complain in a call center. >> Christian: Yeah. >> Or I'm complaining, how do I get support? Nothing made itself into the product improvement, except for slow moving, waterfall-based processes. And then, maybe six months later, a small tweak could be improved. >> Yes. >> Here, you're taking direct input from collective intelligence. Okay. >> Is that have input and on timing is very important here, right? So how do you know if the product is working as it should in all these different flavors and configurations right now? How do you know if it's working well? And how do you know if you're improving or not improving over time? And I think the industry, what can we look at, as far as when it relates to quality? So I can look at star ratings, right? So what's the star rating in the app store? Well, star ratings, that's an average over time. So that's something that you may have a lot of issues in production today, and you're going to get dinged on star ratings over the next few months. And then, it brings down the score. NPS is another one, where we're not going to run NPS surveys every day. We're going to run it once a quarter, maybe once a month, if we're really, really aggressive. That's also a snapshot in time. And we need to have the finger on the pulse of product quality today. I need to know if this release is good or not good. I need to know if anything broke. And I think that real time aspect, what we see as stuff sort of bubbles up the stack, and not into production, we see up to a 50% reduction in time to fix these end user impacting issues. And I think, we also need to appreciate when someone takes time out of the day to write an app review, or email support, or write that Reddit post, it's pretty serious. It's not going to be like, "Oh, I don't like the shade of blue on this button." It's going to be something like, "I got double billed," or "Hey, someone took over my account," or, "I can't reset my password anymore. The CAPTCHA, I'm solving it, but I can't get through to the next phase." And we see a lot of these trajectory impacting bugs and quality issues in these work, these flows in the product that you're not testing every day. So if you work at Snapchat, your employees probably going to use Snapchat every day. Are they going to sign up every day? No. Are they going to do passive reset every day? No. And these things are very hard to instrument, lower in the stack. >> Yeah, I think this is, and again, back to these big problems. It's smoke before fire, and you're essentially seeing it early with your process. Can you give an example of how this new focus or new mindset of user feedback data can help customers increase their experience? Can you give some examples, 'cause folks watching and be like, "Okay, I love this value. Sell me on this idea, I'm sold. Okay, I want to tap into my prospects, and my customers, my end users to help me improve my product." 'Cause again, we can measure everything now with data. >> Yeah. We can measure everything. we can even measure quality these days. So when we started this company, I went out to talk to a bunch of friends, who are entrepreneurs, and VCs, and board members, and I asked them this very simple question. So in your board meetings, or on all hands, how do you talk about quality of the product? Do you have a metric? And everyone said, no. Okay. So are you data driven company? Yes, we're very data driven. >> John: Yeah. Go data driven. >> But you're not really sure if quality, how do you compare against competition? Are you doing as good as them, worse, better? Are you improving over time, and how do you measure it? And they're like, "Well, it's kind of like a blind spot of the company." And then you ask, "Well, do you think quality of experience is important?" And they say, "Yeah." "Well, why?" "Well, top of fund and growth. Higher quality products going to spread faster organically, we're going to make better store ratings. We're going to have the storefronts going to look better." And of course, more importantly, they said the different conversion cycles in the product box itself. That if you have bugs and friction, or an interface that's hard to use, then the inputs, the signups, it's not going to convert as well. So you're going to get dinged on retention, engagement, conversion to paid, and so forth. And that's what we've seen with the companies we work with. It is that poor quality acts as a filter function for the entire business, if you're a product led company. So if you think about product led company, where the product is really the centerpiece. And if it performs really, really well, then it allows you to hire more engineers, you can spend more on marketing. Everything is fed by this product at them in the middle, and then quality can make that thing perform worse or better. And we developed a metric actually called the unitQ Score. So if you go to our website, unitq.com, we have indexed the 5,000 largest apps in the world. And we're able to then, on a daily basis, update the score. Because the score is not something you do once a month or once a quarter. It's something that changes continuously. So now, you can get a score between zero and 100. If you get the score 100, that means that our AI doesn't find any quality issues reported in that data set. And if your score is 90, that means that 10% will be a quality issue. So now you can do a lot of fun stuff. You can start benchmarking against competition. So you can see, "Well, I'm Spotify. How do I rank against Deezer, or SoundCloud, or others in my space?" And what we've seen is that as the score goes up, we see this real big impact on KPI, such as conversion, organic growth, retention, ultimately, revenue, right? And so that was very satisfying for us, when we launched it. quality actually still really, really matters. >> Yeah. >> And I think we all agree at test, but how do we make a science out of it? And that's so what we've done. And when we were very lucky early on to get some incredible brands that we work with. So Pinterest is a big customer of ours. We have Spotify. We just signed new bank, Chime. So like we even signed BetterHelp recently, and the world's largest Bible app. So when you look at the types of businesses that we work with, it's truly a universal, very broad field, where if you have a digital exhaust or feedback, I can guarantee you, there are insights in there that are being neglected. >> John: So Chris, I got to. >> So these manual workflows. Yeah, please go ahead. >> I got to ask you, because this is a really great example of this new shift, right? The new shift of leveraging data, flipping the script. Everything's flipping the script here, right? >> Yeah. >> So you're talking about, what the value proposition is? "Hey, board example's a good one. How do you measure quality? There's no KPI for that." So it's almost category creating in its own way. In that, this net new things, it's okay to be new, it's just new. So the question is, if I'm a customer, I buy it. I can see my product teams engaging with this. I can see how it can changes my marketing, and customer experience teams. How do I operationalize this? Okay. So what do I do? So do I reorganize my marketing team? So take me through the impact to the customer that you're seeing. What are they resonating towards? Obviously, getting that data is key, and that's holy gray, we all know that. But what do I got to do to change my environment? What's my operationalization piece of it? >> Yeah, and that's one of the coolest parts I think, and that is, let's start with your user base. We're not going to ask your users to ask your users to do something differently. They're already producing this data every day. They are tweeting about it. They're putting in app produce. They're emailing support. They're engaging with your support chatbot. They're already doing it. And every day that you're not leveraging that data, the data that was produced today is less valuable tomorrow. And in 30 days, I would argue, it's probably useless. >> John: Unless it's same guy commenting. >> Yeah. (Christian and John laughing) The first, we need to make everyone understand. Well, yeah, the data is there, and we don't need to do anything differently with the end user. And then, what we do is we ask the customer to tell us, "Where should we listen in the public domain? So do you want the Reddit post, the Trustpilot? What channels should we listen to?" And then, our machine basically starts ingesting that data. So we have integration with all these different sites. And then, to get access to private data, it'll be, if you're on Zendesk, you have to issue a Zendesk token, right? So you don't need any engineering hours, except your IT person will have to grant us access to the data source. And then, when we go live. We basically build up this taxonomy with the customers. So we don't we don't want to try and impose our view of the world, of how do you describe the product with these buckets, these quality monitors? So we work with the company to then build out this taxonomy. So it's almost like a bespoke solution that we can bootstrap with previous work we've done, where you don't have these very, very fine buckets of where stuff could go wrong. And then what we do is there are different ways to hook this into the workflow. So one is just to use our products. It's a SaaS product as anything else. So you log in, and you can then get this overview of how is quality trending in different markets, on different platforms, different languages, and what is impacting them? What is driving this unitQ Score that's not good enough? And all of these different signals, we can then hook into Jira for instance. We have a Jira integration. We have a PagerDuty integration. We can wake up engineers if certain things break. We also tag tickets in your support system, which is actually quite cool. Where, let's say, you have 200 people, who wrote into support, saying, "I got double billed on Android." It turns out, there are some bugs that double billed them. Well, now we can tag all of these users in Zendesk, and then the support team can then reach out to that segment of users and say, "Hey, we heard that you had this bug with double billing. We're so sorry. We're working on it." And then when we push fix, we can then email the same group again, and maybe give them a little gift card or something, for the thank you. So you can have, even big companies can have that small company experience. So, so it's groups that use us, like at Pinterest, we have 800 accounts. So it's really through marketing has vested interest because they want to know what is impacting the end user. Because brand and product, the lines are basically gone, right? >> John: Yeah. >> So if the product is not working, then my spend into this machine is going to be less efficient. The reputation of our company is going to be worse. And the challenge for marketers before unitQ was, how do I engage with engineering and product? I'm dealing with anecdotal data, and my own experience of like, "Hey, I've never seen these type of complaints before. I think something is going on." >> John: Yeah. >> And then engineering will be like, "Ah, you know, well, I have 5,000 bugs in Jira. Why does this one matter? When did it start? Is this a growing issue?" >> John: You have to replicate the problem, right? >> Replicate it then. >> And then it goes on and on and on. >> And a lot of times, reproducing bugs, it's really hard because it works on my device. Because you don't sit on that device that it happened on. >> Yup. >> So now, when marketing can come with indisputable data, and say, "Hey, something broke here." And we see the same with support. Product engineering, of course, for them, we talk about, "Hey, listen, you you've invested a lot in observability of your stack, haven't you?" "Yeah, yeah, yeah." "So you have a Datadog in the bottom?" "Absolutely." "And you have an APP D on the client?" "Absolutely." "Well, what about the last mile? How the product manifests itself? Shouldn't you monitor that as well using machines?" They're like, "Yeah, that'd be really cool." (John laughs) And we see this. There's no way to instrument everything, lowering the stack to capture these bugs that leak out. So it resonates really well there. And even for the engineers who's going to fix it. >> Yeah. >> I call it like empathy data. >> Yup. >> Where I get assigned a bug to fix. Well, now, I can read all the feedback. I can actually see, and I can see the feedback coming in. >> Yeah. >> Oh, there's users out there, suffering from this bug. And then when I fix it and I deploy the fix, and I see the trend go down to zero, and then I can celebrate it. So that whole feedback loop is (indistinct). >> And that's real time. It's usually missed too. This is the power of user feedback. You guys got a great product, unitQ. Great to have you on. Founder and CEO, Christian Wiklund. Thanks for coming on and sharing, and showcase. >> Thank you, John. For the last 30 seconds, the minute we have left, put a plug in for the company. What are you guys looking for? Give a quick pitch for the company, real quick, for the folks out there. Looking for more people, funding status, number of employees. Give a quick plug. >> Yes. So we raised our A Round from Google, and then we raised our B from Excel that we closed late last year. So we're not raising money. We are hiring across go-to-markets, engineering. And we love to work with people, who are passionate about quality and data. We're always, of course, looking for customers, who are interested in upping their game. And hey, listen, competing with features is really hard because you can copy features very quickly. Competing with content. Content is commodity. You're going to get the same movies more or less on all these different providers. And competing on price, we're not willing to do. You're going to pay 10 bucks a month for music. So how do you compete today? And if your competitor has a better fine tuned piano than your competitor will have better efficiencies, and they're going to retain customers and users better. And you don't want to lose on quality because it is actually a deterministic and fixable problem. So yeah, come talk to us if you want to up the game there. >> Great stuff. The iteration lean startup model, some say took craft out of building the product. But this is now bringing the craftsmanship into the product cycle, when you can get that data from customers and users. >> Yeah. >> Who are going to be happy that you fixed it, that you're listening. >> Yeah. >> And that the product got better. So it's a flywheel of loyalty, quality, brand, all off you can figure it out. It's the holy grail. >> I think it is. It's a gold mine. And every day you're not leveraging this assets, your use of feedback that's there, is a missed opportunity. >> Christian, thanks so much for coming on. Congratulations to you and your startup. You guys back together. The band is back together, up into the right, doing well. >> Yeah. We we'll check in with you later. Thanks for coming on this showcase. Appreciate it. >> Thank you, John. Appreciate it very much. >> Okay. AWS Startup Showcase. This is season two, episode three, the ongoing series. This one's about MarTech, cloud experiences are scaling. I'm John Furrier, your host. Thanks for watching. (upbeat music)

>> From theCUBE studios in Palo Alto in Boston, bringing you data driven insights from theCUBE and ETR. This is "Breaking Analysis" with Dave Vellante. >> Snowflake Summit 2022 underscored that the ecosystem excitement which was once forming around Hadoop is being reborn, escalated and coalescing around Snowflake's data cloud. What was once seen as a simpler cloud data warehouse and good marketing with the data cloud is evolving rapidly with new workloads of vertical industry focus, data applications, monetization, and more. The question is, will the promise of data be fulfilled this time around, or is it same wine, new bottle? Hello, and welcome to this week's Wikibon CUBE Insights powered by ETR. In this "Breaking Analysis," we'll talk about the event, the announcements that Snowflake made that are of greatest interest, the major themes of the show, what was hype and what was real, the competition, and some concerns that remain in many parts of the ecosystem and pockets of customers. First let's look at the overall event. It was held at Caesars Forum. Not my favorite venue, but I'll tell you it was packed. Fire Marshall Full, as we sometimes say. Nearly 10,000 people attended the event. Here's Snowflake's CMO Denise Persson on theCUBE describing how this event has evolved. >> Yeah, two, three years ago, we were about 1800 people at a Hilton in San Francisco. We had about 40 partners attending. This week we're close to 10,000 attendees here. Almost 10,000 people online as well, and over over 200 partners here on the show floor. >> Now, those numbers from 2019 remind me of the early days of Hadoop World, which was put on by Cloudera but then Cloudera handed off the event to O'Reilly as this article that we've inserted, if you bring back that slide would say. The headline it almost got it right. Hadoop World was a failure, but it didn't have to be. Snowflake has filled the void created by O'Reilly when it first killed Hadoop World, and killed the name and then killed Strata. Now, ironically, the momentum and excitement from Hadoop's early days, it probably could have stayed with Cloudera but the beginning of the end was when they gave the conference over to O'Reilly. We can't imagine Frank Slootman handing the keys to the kingdom to a third party. Serious business was done at this event. I'm talking substantive deals. Salespeople from a host sponsor and the ecosystems that support these events, they love physical. They really don't like virtual because physical belly to belly means relationship building, pipeline, and deals. And that was blatantly obvious at this show. And in fairness, all theCUBE events that we've done year but this one was more vibrant because of its attendance and the action in the ecosystem. Ecosystem is a hallmark of a cloud company, and that's what Snowflake is. We asked Frank Slootman on theCUBE, was this ecosystem evolution by design or did Snowflake just kind of stumble into it? Here's what he said. >> Well, when you are a data clouding, you have data, people want to do things with that data. They don't want just run data operations, populate dashboards, run reports. Pretty soon they want to build applications and after they build applications, they want build businesses on it. So it goes on and on and on. So it drives your development to enable more and more functionality on that data cloud. Didn't start out that way, you know, we were very, very much focused on data operations. Then it becomes application development and then it becomes, hey, we're developing whole businesses on this platform. So similar to what happened to Facebook in many ways. >> So it sounds like it was maybe a little bit of both. The Facebook analogy is interesting because Facebook is a walled garden, as is Snowflake, but when you come into that garden, you have assurances that things are going to work in a very specific way because a set of standards and protocols is being enforced by a steward, i.e. Snowflake. This means things run better inside of Snowflake than if you try to do all the integration yourself. Now, maybe over time, an open source version of that will come out but if you wait for that, you're going to be left behind. That said, Snowflake has made moves to make its platform more accommodating to open source tooling in many of its announcements this week. Now, I'm not going to do a deep dive on the announcements. Matt Sulkins from Monte Carlo wrote a decent summary of the keynotes and a number of analysts like Sanjeev Mohan, Tony Bear and others are posting some deeper analysis on these innovations, and so we'll point to those. I'll say a few things though. Unistore extends the type of data that can live in the Snowflake data cloud. It's enabled by a new feature called hybrid tables, a new table type in Snowflake. One of the big knocks against Snowflake was it couldn't handle and transaction data. Several database companies are creating this notion of a hybrid where both analytic and transactional workloads can live in the same data store. Oracle's doing this for example, with MySQL HeatWave and there are many others. We saw Mongo earlier this month add an analytics capability to its transaction system. Mongo also added sequel, which was kind of interesting. Here's what Constellation Research analyst Doug Henschen said about Snowflake's moves into transaction data. Play the clip. >> Well with Unistore, they're reaching out and trying to bring transactional data in. Hey, don't limit this to analytical information and there's other ways to do that like CDC and streaming but they're very closely tying that again to that marketplace, with the idea of bring your data over here and you can monetize it. Don't just leave it in that transactional database. So another reach to a broader play across a big community that they're building. >> And you're also seeing Snowflake expand its workload types in its unique way and through Snowpark and its stream lit acquisition, enabling Python so that native apps can be built in the data cloud and benefit from all that structure and the features that Snowflake is built in. Hence that Facebook analogy, or maybe the App Store, the Apple App Store as I propose as well. Python support also widens the aperture for machine intelligence workloads. We asked Snowflake senior VP of product, Christian Kleinerman which announcements he thought were the most impactful. And despite the who's your favorite child nature of the question, he did answer. Here's what he said. >> I think the native applications is the one that looks like, eh, I don't know about it on the surface but he has the biggest potential to change everything. That's create an entire ecosystem of solutions for within a company or across companies that I don't know that we know what's possible. >> Snowflake also announced support for Apache Iceberg, which is a new open table format standard that's emerging. So you're seeing Snowflake respond to these concerns about its lack of openness, and they're building optionality into their cloud. They also showed some cost op optimization tools both from Snowflake itself and from the ecosystem, notably Capital One which launched a software business on top of Snowflake focused on optimizing cost and eventually the rollout data management capabilities, and all kinds of features that Snowflake announced that the show around governance, cross cloud, what we call super cloud, a new security workload, and they reemphasize their ability to read non-native on-prem data into Snowflake through partnerships with Dell and Pure and a lot more. Let's hear from some of the analysts that came on theCUBE this week at Snowflake Summit to see what they said about the announcements and their takeaways from the event. This is Dave Menninger, Sanjeev Mohan, and Tony Bear, roll the clip. >> Our research shows that the majority of organizations, the majority of people do not have access to analytics. And so a couple of the things they've announced I think address those or help to address those issues very directly. So Snowpark and support for Python and other languages is a way for organizations to embed analytics into different business processes. And so I think that'll be really beneficial to try and get analytics into more people's hands. And I also think that the native applications as part of the marketplace is another way to get applications into people's hands rather than just analytical tools. Because most people in the organization are not analysts. They're doing some line of business function. They're HR managers, they're marketing people, they're sales people, they're finance people, right? They're not sitting there mucking around in the data, they're doing a job and they need analytics in that job. >> Primarily, I think it is to contract this whole notion that once you move data into Snowflake, it's a proprietary format. So I think that's how it started but it's usually beneficial to the customers, to the users because now if you have large amount of data in paket files you can leave it on S3, but then you using the Apache Iceberg table format in Snowflake, you get all the benefits of Snowflake's optimizer. So for example, you get the micro partitioning, you get the metadata. And in a single query, you can join, you can do select from a Snowflake table union and select from an iceberg table and you can do store procedure, user defined function. So I think what they've done is extremely interesting. Iceberg by itself still does not have multi-table transactional capabilities. So if I'm running a workload, I might be touching 10 different tables. So if I use Apache Iceberg in a raw format, they don't have it, but Snowflake does. So the way I see it is Snowflake is adding more and more capabilities right into the database. So for example, they've gone ahead and added security and privacy. So you can now create policies and do even cell level masking, dynamic masking, but most organizations have more than Snowflake. So what we are starting to see all around here is that there's a whole series of data catalog companies, a bunch of companies that are doing dynamic data masking, security and governance, data observability which is not a space Snowflake has gone into. So there's a whole ecosystem of companies that is mushrooming. Although, you know, so they're using the native capabilities of Snowflake but they are at a level higher. So if you have a data lake and a cloud data warehouse and you have other like relational databases, you can run these cross platform capabilities in that layer. So that way, you know, Snowflake's done a great job of enabling that ecosystem. >> I think it's like the last mile, essentially. In other words, it's like, okay, you have folks that are basically that are very comfortable with Tableau but you do have developers who don't want to have to shell out to a separate tool. And so this is where Snowflake is essentially working to address that constituency. To Sanjeev's point, and I think part of it, this kind of plays into it is what makes this different from the Hadoop era is the fact that all these capabilities, you know, a lot of vendors are taking it very seriously to put this native. Now, obviously Snowflake acquired Streamlit. So we can expect that the Streamlit capabilities are going to be native. >> I want to share a little bit about the higher level thinking at Snowflake, here's a chart from Frank Slootman's keynote. It's his version of the modern data stack, if you will. Now, Snowflake of course, was built on the public cloud. If there were no AWS, there would be no Snowflake. Now, they're all about bringing data and live data and expanding the types of data, including structured, we just heard about that, unstructured, geospatial, and the list is going to continue on and on. Eventually I think it's going to bleed into the edge if we can figure out what to do with that edge data. Executing on new workloads is a big deal. They started with data sharing and they recently added security and they've essentially created a PaaS layer. We call it a SuperPaaS layer, if you will, to attract application developers. Snowflake has a developer-focused event coming up in November and they've extended the marketplace with 1300 native apps listings. And at the top, that's the holy grail, monetization. We always talk about building data products and we saw a lot of that at this event, very, very impressive and unique. Now here's the thing. There's a lot of talk in the press, in the Wall Street and the broader community about consumption-based pricing and concerns over Snowflake's visibility and its forecast and how analytics may be discretionary. But if you're a company building apps in Snowflake and monetizing like Capital One intends to do, and you're now selling in the marketplace, that is not discretionary, unless of course your costs are greater than your revenue for that service, in which case is going to fail anyway. But the point is we're entering a new error where data apps and data products are beginning to be built and Snowflake is attempting to make the data cloud the defacto place as to where you're going to build them. In our view they're well ahead in that journey. Okay, let's talk about some of the bigger themes that we heard at the event. Bringing apps to the data instead of moving the data to the apps, this was a constant refrain and one that certainly makes sense from a physics point of view. But having a single source of data that is discoverable, sharable and governed with increasingly robust ecosystem options, it doesn't have to be moved. Sometimes it may have to be moved if you're going across regions, but that's unique and a differentiator for Snowflake in our view. I mean, I'm yet to see a data ecosystem that is as rich and growing as fast as the Snowflake ecosystem. Monetization, we talked about that, industry clouds, financial services, healthcare, retail, and media, all front and center at the event. My understanding is that Frank Slootman was a major force behind this shift, this development and go to market focus on verticals. It's really an attempt, and he talked about this in his keynote to align with the customer mission ultimately align with their objectives which not surprisingly, are increasingly monetizing with data as a differentiating ingredient. We heard a ton about data mesh, there were numerous presentations about the topic. And I'll say this, if you map the seven pillars Snowflake talks about, Benoit Dageville talked about this in his keynote, but if you map those into Zhamak Dehghani's data mesh framework and the four principles, they align better than most of the data mesh washing that I've seen. The seven pillars, all data, all workloads, global architecture, self-managed, programmable, marketplace and governance. Those are the seven pillars that he talked about in his keynote. All data, well, maybe with hybrid tables that becomes more of a reality. Global architecture means the data is globally distributed. It's not necessarily physically in one place. Self-managed is key. Self-service infrastructure is one of Zhamak's four principles. And then inherent governance. Zhamak talks about computational, what I'll call automated governance, built in. And with all the talk about monetization, that aligns with the second principle which is data as product. So while it's not a pure hit and to its credit, by the way, Snowflake doesn't use data mesh in its messaging anymore. But by the way, its customers do, several customers talked about it. Geico, JPMC, and a number of other customers and partners are using the term and using it pretty closely to the concepts put forth by Zhamak Dehghani. But back to the point, they essentially, Snowflake that is, is building a proprietary system that substantially addresses some, if not many of the goals of data mesh. Okay, back to the list, supercloud, that's our term. We saw lots of examples of clouds on top of clouds that are architected to spin multiple clouds, not just run on individual clouds as separate services. And this includes Snowflake's data cloud itself but a number of ecosystem partners that are headed in a very similar direction. Snowflake still talks about data sharing but now it uses the term collaboration in its high level messaging, which is I think smart. Data sharing is kind of a geeky term. And also this is an attempt by Snowflake to differentiate from everyone else that's saying, hey, we do data sharing too. And finally Snowflake doesn't say data marketplace anymore. It's now marketplace, accounting for its application market. Okay, let's take a quick look at the competitive landscape via this ETR X-Y graph. Vertical access remembers net score or spending momentum and the x-axis is penetration, pervasiveness in the data center. That's what ETR calls overlap. Snowflake continues to lead on the vertical axis. They guide it conservatively last quarter, remember, so I wouldn't be surprised if that lofty height, even though it's well down from its earlier levels but I wouldn't be surprised if it ticks down again a bit in the July survey, which will be in the field shortly. Databricks is a key competitor obviously at a strong spending momentum, as you can see. We didn't draw it here but we usually draw that 40% line or red line at 40%, anything above that is considered elevated. So you can see Databricks is quite elevated. But it doesn't have the market presence of Snowflake. It didn't get to IPO during the bubble and it doesn't have nearly as deep and capable go-to market machinery. Now, they're getting better and they're getting some attention in the market, nonetheless. But as a private company, you just naturally, more people are aware of Snowflake. Some analysts, Tony Bear in particular, believe Mongo and Snowflake are on a bit of a collision course long term. I actually can see his point. You know, I mean, they're both platforms, they're both about data. It's long ways off, but you can see them sort of in a similar path. They talk about kind of similar aspirations and visions even though they're quite in different markets today but they're definitely participating in similar tam. The cloud players are probably the biggest or definitely the biggest partners and probably the biggest competitors to Snowflake. And then there's always Oracle. Doesn't have the spending velocity of the others but it's got strong market presence. It owns a cloud and it knows a thing about data and it definitely is a go-to market machine. Okay, we're going to end on some of the things that we heard in the ecosystem. 'Cause look, we've heard before how particular technology, enterprise data warehouse, data hubs, MDM, data lakes, Hadoop, et cetera. We're going to solve all of our data problems and of course they didn't. And in fact, sometimes they create more problems that allow vendors to push more incremental technology to solve the problems that they created. Like tools and platforms to clean up the no schema on right nature of data lakes or data swamps. But here are some of the things that I heard firsthand from some customers and partners. First thing is, they said to me that they're having a hard time keeping up sometimes with the pace of Snowflake. It reminds me of AWS in 2014, 2015 timeframe. You remember that fire hose of announcements which causes increased complexity for customers and partners. I talked to several customers that said, well, yeah this is all well and good but I still need skilled people to understand all these tools that I'm integrated in the ecosystem, the catalogs, the machine learning observability. A number of customers said, I just can't use one governance tool, I need multiple governance tools and a lot of other technologies as well, and they're concerned that that's going to drive up their cost and their complexity. I heard other concerns from the ecosystem that it used to be sort of clear as to where they could add value you know, when Snowflake was just a better data warehouse. But to point number one, they're either concerned that they'll be left behind or they're concerned that they'll be subsumed. Look, I mean, just like we tell AWS customers and partners, you got to move fast, you got to keep innovating. If you don't, you're going to be left. Either if your customer you're going to be left behind your competitor, or if you're a partner, somebody else is going to get there or AWS is going to solve the problem for you. Okay, and there were a number of skeptical practitioners, really thoughtful and experienced data pros that suggested that they've seen this movie before. That's hence the same wine, new bottle. Well, this time around I certainly hope not given all the energy and investment that is going into this ecosystem. And the fact is Snowflake is unquestionably making it easier to put data to work. They built on AWS so you didn't have to worry about provisioning, compute and storage and networking and scaling. Snowflake is optimizing its platform to take advantage of things like Graviton so you don't have to, and they're doing some of their own optimization tools. The ecosystem is building optimization tools so that's all good. And firm belief is the less expensive it is, the more data will get brought into the data cloud. And they're building a data platform on which their ecosystem can build and run data applications, aka data products without having to worry about all the hard work that needs to get done to make data discoverable, shareable, and governed. And unlike the last 10 years, you don't have to be a keeper and integrate all the animals in the Hadoop zoo. Okay, that's it for today, thanks for watching. Thanks to my colleague, Stephanie Chan who helps research "Breaking Analysis" topics. Sometimes Alex Myerson is on production and manages the podcasts. Kristin Martin and Cheryl Knight help get the word out on social and in our newsletters, and Rob Hof is our editor in chief over at Silicon, and Hailey does some wonderful editing, thanks to all. Remember, all these episodes are available as podcasts wherever you listen. All you got to do is search Breaking Analysis Podcasts. I publish each week on wikibon.com and siliconangle.com and you can email me at David.Vellante@siliconangle.com or DM me @DVellante. If you got something interesting, I'll respond. If you don't, I'm sorry I won't. Or comment on my LinkedIn post. Please check out etr.ai for the best survey data in the enterprise tech business. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching, and we'll see you next time. (upbeat music)

(upbeat music) >> Welcome back to Vegas, baby. Lisa Martin here with theCUBE. We are live at Caesar's Forum covering Snowflake Summit 22. This is day two of our wall to wall coverage on theCUBE you won't want to miss. We've got an exciting customer story to talk to you about next with Novartis and Snowflake. Please welcome two guests to theCUBE. Loïc Giraud, Global head digital delivery, Novartis. I hope I got the name right. >> Yes. Hi, thank you. >> I did my best. >> Absolutely. >> Lisa: (laughs) Jesse Cugliotta also joins us. Global Industry Lead, Healthcare and Life Sciences at Snowflake. Welcome with theCUBE, gentlemen. >> Thank you for having us. Good morning. >> So it was great to hear Novartis is a household word now, especially with what's gone on in the last two years. I had a chance to see the Keynote yesterday, heard Novartis mention in terms of a massive outcome that Snowflake is delivering that we're going to get to. But Loic talk to us about Novartis global 500 organization. You rank among the world's top companies investing in R&D, the massive portfolio and you're reaching nearly 800 million patients worldwide. That's huge, but there's been a lot of change in the healthcare and life sciences industry, especially recently. Talk to us about the industry landscape. What are you seeing? >> As you described, Novartis is one of the top life science company in the world. We are number three. We operate in 150 countries, and we have almost 120,000 employees. Our purpose is actually to reimagine medicine for the use of data science and technology and to extend people's life. And we really mean it. I think, as you mentioned, we treat eight or 9 million patient per year with our drugs. We expect to treat more than a billion patients in near time soon. Over the last few years, especially during COVID, our digital transformation help us to accelerate the drug discovery and then the commiseration of our drug to markets. As it was mentioned in the Keynote yesterday, we have actually been able to reduce our time to market. It used to take us up to 12 years and cost around 1.2 billion to discover and commercialize drug. And now we've actually use of technology like Snowflake, we have been able to reduce by two to three years, which ultimately is a benefit for our patients. >> Absolutely. Well, we're talking about life and death situations. Talk about... You mentioned Novartis wants to reimagine medicine. What does that look like? Where is data in that and how is Snowflake an enabler of reimagining medicine? >> So data is core for our asset, is a core of enterprise process. So if you look at our enterprise, we are using data from the research, for drug development, in manufacturing process, and how do we market and sell our product through HCPs and distribute it to reach our patients. If you build through our digital transformation we have created this integrated data ecosystem, where Snowflake is a core component. And through that ecosystem, we are able to identify compounds and cohorts, perform clinical trials, and engage HCPs and HGOs so that can prescribe drugs to serve our patient needs. >> Jesse, let's bring you into the conversation. Snowflake recently launched its healthcare and life sciences data cloud. I believe that was back in March. >> It was. >> Just a couple of months ago. Talk to us about the vertical focus. Talk to us about what this healthcare and life sciences data cloud is aiming to help customers like Novartis achieve. >> Well, as you mentioned there, Snowflake has made a real pivot to kind of focus on the various different industries that we serve in a new way. I think historically, we've been engaged in really, all of the industries across the major sectors where we participate today. But historically we've been often engaging with the office of IT. And there was a recognition as a company that we really need to be able to better speak the language of our customers in with our respective industries. So the entire organization has really made a pivot to start to build that capability internally. That's part of the team that I support here at Snowflake. And with respect to healthcare and life sciences, that means being able to solve some of the challenges that Loic was just speaking about. In particular, we're seeing the industry evolve in a number of ways. You bring up clinical research in the time that it takes to actually bring a drug to market. This is a big one that's really changed a lot over the last couple of years. Some of the reasons are obvious and other ones are somewhat opportunistic. When we looked at what it takes to get a drug to market, there's several stages of clinical research that have to be participated in, and this can often take years. What we saw in the last couple of years, is that all of a sudden, patients didn't want to physically participate in those anymore, because there was fear of potential infection and being in a healthcare facility. So the entire industry realized that it needed to change in terms of way that it would engage with patients in that context. And we're now seeing this concept of decentralized clinical research. And with that, becomes the need to potentially involve many different types of organizations beyond the traditional pharma, their research partners, but we're starting to see organizations like retail pharmacies, like big box retailers, who have either healthcare delivery or pharmaceutical arms actually get involved in the process. And of course, one of the core things that happens here is that everyone needs a better way to collaborate and share data amongst one another. So bringing this back to your original question, this concept of being able to do exactly that is core to the healthcare and the life sciences data cloud. To be able to collaborate and share data amongst those different types of organizations. >> Collaboration and data sharing. It seems to me to be a differentiator for Snowflake, in terms of being able to deliver secure, governed powerful analytics and data sharing to customers, partners to the ecosystem. You mentioned an example of the ecosystem there and how impactful to patients' lives, that collaboration and data sharing can be. >> That's absolutely right. It's something that if you think about all of the major challenges that the industry has had historically, whether it is high costs, whether it are health inequities, whether it is physicians practicing defensive medicine or repeat testing, what's core to each one of these things is kind of the inability to adequate collaborate and share data amongst all of the different players. So the industry has been waiting for the capability or some sort of solution to be able to do this, I think for a long, long time. And this is probably one of the most exciting parts of the conversations that we have with our customers, is when they realize that this is possible. And not only that it's possible within our platform, but that most of the organizations that they work with today are also Snowflake customers. So they realize that everyone's already here. It's just a matter of who else can we work with and how do we get started? >> Join the party. >> Exactly. >> Loic talk to us about Novartis's data journey. I know you guys have been, I believe using Snowflake since 2017 pre pandemic. But you had a largely on-premises infrastructure. Talk to us about the decision of Novartis to go to the cloud, do it securely and why you chose to partner with Snowflake. >> So when we started our journey in 2018, I think the ambition that our CEO, was to transform all enterprise processes for the use of digital tech. And at the core of this digital tech is data foundation. So we started with a large program called Formula One, which aim to integrate all our internal and external data asset into an integrated platform. And for that, I think we've built this multicloud and best upgrade platform, where Snowflake is a core component. And we've been able to integrate almost 1,000 data asset, internal and external for the platform to be able to accelerate the use of data to create insight for our users. In that transformation, we've realized that Snowflake could be a core component because of the scalability and the performance with large dataset. And moreover, when Snowflake started to actually open collaboration for their marketplace, we've been able to integrate new data set that are publicly available at the place that we could not do on ourself, on our own. So that is a core component of what we are trying to do. >> Yeah, and I think that's a great example of really what we're talking about here is that, he's mentioning that they're going out to our marketplace to be able to integrate data more easily with some of the vendors there. And that is kind of this concept of the healthcare and life sciences data cloud realized, where all of a sudden, acquiring and bringing data in and making it ready for analysis becomes much faster, much easier. We continually see more and more vendors coming to us saying, I get it now, I want in. Who else can I work with in this space? So I think that's a perfect example of how this starts to become real for folks. >> Well, it sounds like the marketplace has been an enabler, Loic, of the expansion of use cases. You've grown this beyond drug development. I read that you're developing new products and services for healthcare providers to personalize treatments for patients, which we all are demanding patients. We want that personalized care. But talk about the marketplace as a facilitator of those expanding use cases that Snowflake is powering. >> Yes. That's right. I mean we have currently almost 65 use cases in production and we are in advanced progress for over 200 use cases and they go across all our business sector. So if you look at drug development, we are monitoring our clinical trials using Snowflake. If you look at our omnichannel marketing, we are looking at personalization of information with our HCPs and HGOs using snowflake. If you look at our manufacturing process, we are looking at yet management, freight optimization, inventory, insight. So almost across all the industry sectors that we have, I think we are using the platforms to be able to deliver faster information to our users. >> And that's what we all want. Faster information. I think in the pandemic we learned that access to real time data in every industry wasn't a nice to have. That was a- >> Necessity. >> Absolute necessity. >> Yeah. >> And made the difference for companies that survived and thrived and those that didn't. That's something that we learned. But we also learned that the volume of data just continues to proliferate. Loic, you've been in the industry a couple of decades. What do you see? And you've got, obviously this great foundation now with Snowflake. You've got 65 use cases you said in production. What's the future of the data culture in healthcare and life sciences from your perspective? >> So my perspective. It is time now we give the access to our business technologies to be able to be self-sufficient using digital product. We need to consumerize digital technology so they can be self-sufficient. The amount of problems that we have to solve, and we can now solve with new technology has never been there. And I think where in the past, where in the next few years that you will see an accelerated generation of insight and an accelerated process of medicine by empowering the business technologies to use a technology that like Snowflake and over progress. >> What are your thoughts Loic, of some of the, obviously a lot of news coming out yesterday from Snowflake, we mentioned standing room only in the Keynote. This I believe is north of 10,000 attendees. People are ready to engage in person with Snowflake, but some of the news coming out, what is your perspective? You've been a partner of theirs for a while. What do you see from Snowflake in terms of the news, the volume of customers it's adding, all that good stuff? >> I must say I was blown away yesterday when Frank was talking about the ramp up of customers using Snowflake. But also, and I think in Benoit and Christian, and they talk about the innovation. When you look at native application or you look at hybrid tables, we saw a thing there. And the expansion of the marketplace by monetization application, that is something that is going to accelerate the expansion, not only on the company, but the integration and the utilization of customers. And to Jesse's point, I think that it is key that people collaborate using the platform. I think we want to collaborate with suppliers and providers and they want to collaborate with us. But we want to have a neutral environment where we can do that. And Snowflake can be that environment. >> And do it securely, right? Security is absolutely- >> Of course. I mean that's really table stake for this industry. And I think the point that you just made Loic, is very important, is that, the biggest question that we're often asked by our customers is who else is a customer within this industry that I can collaborate with? I think as Loic here will attest to, one of the challenges within life sciences in particular is that it is a highly regulated industry. It is a highly competitive industry, and folks are very sensitive about referenceability. So about things like logo usage. So to give some ideas here, people often have no idea that we're working with 28 of the top 50 global pharma today, working with seven of the top 12 global medical device companies today. The largest CROs, the largest distributors. So when I say that the party is here, they really are. And that's why we're so excited to have events like these, 'cause people can physically introduce themselves to one another and meet, and actually start to engage in some of these more collaborative discussions that they've been waiting for. >> Jesse, what's been some of the feedback that you've heard the last couple of days on the healthcare and life sciences data cloud? You've obviously finally gotten back to engaging with customers in person. But what are some of the things, feed on this street have said that you've thought, we made the absolute right decision on this pivot? >> Yeah, well I think some of it speaks to the the point I was just speaking about, is that they had no idea that so many of their peers were actually working with Snowflake already and that how mature their implementations have actually been. The other thing that folks are realizing is that, a lot of the technologies that serve this ecosystem, whether they're in the health tech space, whether they're clinical management or commercial engagement or supply chain planning technologies, those companies are also now pivoting to Snowflake, where they're either building a part or the entirety of their platform on top of ours. So it offers this great way to start to collaborate with the ecosystem through some of those capabilities that we spoke about. And that's driving new use cases in commercial, in supply chain, in pharmacovigilance, in clinical operations. >> Well, I think you just sum up beautifully why the theme of this conference is the world of data collaboration. >> Yes, absolutely. >> The potential there, that Snowflake is unleashing to the world is I think is what's captivating to me. That you just scratch on the surface about connecting and facilitating this collaboration and this data sharing in a secure way across industries. Loic, last question for you. Take us home with what is next for Novartis. You've done a tremendous amount of digitalization. 65 use cases in production with Snowflake. What's next for the company? >> See, I think that in next year's to come, open collaboration with the ecosystem, but also personalization. If you look at digital medicine and access to patient's informations, I think this is probably the next revolution that we are entering into. >> Excellent. And of course those demanding patients aren't going to want anything slower or less information. Guys, thank you for joining me on the program talking about the Novartis-Snowflake collaboration. The partnership, the outcomes that you're achieving and how this is really dramatically impacting the lives of hundreds of millions of people. We appreciate your time and your insights. >> Thank you for having us. This was fun. >> My pleasure. >> Thank you. >> For my guests, I'm Lisa Martin. You're watching theCUBE. This is live from Las Vegas, day two of our coverage of Snowflake Summit 22. I'll be right back with my next guest, so stick around. (upbeat music)