>>Hey everyone. Welcome back to Las Vegas. It's the Cube live at AWS Reinvent 2022. This is our fourth day of coverage. Lisa Martin here with Paul Gillen. Paul, we started Monday night, we filmed and streamed for about three hours. We have had shammed pack days, Tuesday, Wednesday, Thursday. What's your takeaway? >>We're routed final turn as we, as we head into the home stretch. Yeah. This is as it has been since the beginning, this show with a lot of energy. I'm amazed for the fourth day of a conference, how many people are still here I am too. And how, and how active they are and how full the sessions are. Huge. Proud for the keynote this morning. You don't see that at most of the day four conferences. Everyone's on their way home. So, so people come here to learn and they're, and they're still >>Learning. They are still learning. And we're gonna help continue that learning path. We have an alumni back with us, Toron joins us, the CPO and co-founder of Dremeo. Tomer, it's great to have you back on the program. >>Yeah, thanks for, for having me here. And thanks for keeping the, the best session for the fourth day. >>Yeah, you're right. I like that. That's a good mojo to come into this interview with Tomer. So last year, last time I saw you was a year ago here in Vegas at Reinvent 21. We talked about the growth of data lakes and the data lake houses. We talked about the need for open data architectures as opposed to data warehouses. And the headline of the Silicon Angle's article on the interview we did with you was, Dremio Predicts 2022 will be the year open data architectures replace the data warehouse. We're almost done with 2022. Has that prediction come true? >>Yeah, I think, I think we're seeing almost every company out there, certainly in the enterprise, adopting data lake, data lakehouse technology, embracing open source kind of file and table formats. And, and so I think that's definitely happening. Of course, nothing goes away. So, you know, data warehouses don't go away in, in a year and actually don't go away ever. We still have mainframes around, but certainly the trends are, are all pointing in that direction. >>Describe the data lakehouse for anybody who may not be really familiar with that and, and what it's, what it really means for organizations. >>Yeah. I think you could think of the data lakehouse as the evolution of the data lake, right? And so, you know, for, for, you know, the last decade we've had kind of these two options, data lakes and data warehouses and, you know, warehouses, you know, having good SQL support, but, and good performance. But you had to spend a lot of time and effort getting data into the warehouse. You got locked into them, very, very expensive. That's a big problem now. And data lakes, you know, more open, more scalable, but had all sorts of kind of limitations. And what we've done now as an industry with the Lake House, and especially with, you know, technologies like Apache Iceberg, is we've unlocked all the capabilities of the warehouse directly on object storage like s3. So you can insert and update and delete individual records. You can do transactions, you can do all the things you could do with a, a database directly in kind of open formats without getting locked in at a much lower cost. >>But you're still dealing with semi-structured data as opposed to structured data. And there's, there's work that has to be done to get that into a usable form. That's where Drio excels. What, what has been happening in that area to, to make, I mean, is it formats like j s o that are, are enabling this to happen? How, how we advancing the cause of making semi-structured data usable? Yeah, >>Well, I think first of all, you know, I think that's all changed. I think that was maybe true for the original data lakes, but now with the Lake house, you know, our bread and butter is actually structured data. It's all, it's all tables with the schema. And, you know, you can, you know, create table insert records. You know, it's, it's, it's really everything you can do with a data warehouse you can now do in the lakehouse. Now, that's not to say that there aren't like very advanced capabilities when it comes to, you know, j s O and nested data and kind of sparse data. You know, we excel in that as well. But we're really seeing kind of the lakehouse take over the, the bread and butter data warehouse use cases. >>You mentioned open a minute ago. Talk about why it's, why open is important and the value that it can deliver for customers. >>Yeah, well, I think if you look back in time and you see all the challenges that companies have had with kind of traditional data architectures, right? The, the, the, a lot of that comes from the, the, the problems with data warehouses. The fact that they are, you know, they're very expensive. The data is, you have to ingest it into the data warehouse in order to query it. And then it's almost impossible to get off of these systems, right? It takes an enormous effort, tremendous cost to get off of them. And so you're kinda locked in and that's a big problem, right? You also, you're dependent on that one data warehouse vendor, right? You can only do things with that data that the warehouse vendor supports. And if you contrast that to data lakehouse and open architectures where the data is stored in entirely open formats. >>So things like par files and Apache iceberg tables, that means you can use any engine on that data. You can use s SQL Query Engine, you can use Spark, you can use flin. You know, there's a dozen different engines that you can use on that, both at the same time. But also in the future, if you ever wanted to try something new that comes out, some new open source innovation, some new startup, you just take it and point out the same data. So that data's now at the core, at the center of the architecture as opposed to some, you know, vendors logo. Yeah. >>Amazon seems to be bought into the Lakehouse concept. It has big announcements on day two about eliminating the ETL stage between RDS and Redshift. Do you see the cloud vendors as pushing this concept forward? >>Yeah, a hundred percent. I mean, I'm, I'm Amazon's a great, great partner of ours. We work with, you know, probably 10 different teams there. Everything from, you know, the S3 team, the, the glue team, the click site team, you know, everything in between. And, you know, their embracement of the, the, the lake house architecture, the fact that they adopted Iceberg as their primary table format. I think that's exciting as an industry. We're all coming together around standard, standard ways to represent data so that at the end of the day, companies have this benefit of being able to, you know, have their own data in their own S3 account in open formats and be able to use all these different engines without losing any of the functionality that they need, right? The ability to do all these interactions with data that maybe in the past you would have to move the data into a database or, or warehouse in order to do, you just don't have to do that anymore. Speaking >>Of functionality, talk about what's new this year with drio since we've seen you last. >>Yeah, there's a lot of, a lot of new things with, with Drio. So yeah, we now have full Apache iceberg support, you know, with DML commands, you can do inserts, updates, deletes, you know, copy into all, all that kind of stuff is now, you know, fully supported native part of the platform. We, we now offer kind of two flavors of dr. We have, you know, Dr. Cloud, which is our SaaS version fully hosted. You sign up with your Google or, you know, Azure account and, and, and you're up in, you're up and running in, in, in a minute. And then dral software, which you can self host usually in the cloud, but even, even even outside of the cloud. And then we're also very excited about this new idea of data as code. And so we've introduced a new product that's now in preview called Dr. >>Arctic. And the idea there is to bring the concepts of GI or GitHub to the world of data. So things like being able to create a branch and work in isolation. If you're a data scientist, you wanna experiment on your own without impacting other people, or you're a data engineer and you're ingesting data, you want to transform it and test it before you expose it to others. You can do that in a branch. So all these ideas that, you know, we take for granted now in the world of source code and software development, we're bringing to the world of data with Jamar. And when you think about data mesh, a lot of people talking about data mesh now and wanting to kind of take advantage of, of those concepts and ideas, you know, thinking of data as a product. Well, when you think about data as a product, we think you have to manage it like code, right? You have to, and that's why we call it data as code, right? The, all those reasons that we use things like GI have to build products, you know, if we wanna think of data as a product, we need all those capabilities also with data. You know, also the ability to go back in time. The ability to undo mistakes, to see who changed my data and when did they change that table. All of those are, are part of this, this new catalog that we've created. >>Are you talk about data as a product that's sort of intrinsic to the data mesh concept. Are you, what's your opinion of data mesh? Is the, is the world ready for that radically different approach to data ownership? >>You know, we are now in dozens of, dozens of our customers that are using drio for to implement enterprise-wide kind of data mesh solutions. And at the end of the day, I think it's just, you know, what most people would consider common sense, right? In a large organization, it is very hard for a centralized single team to understand every piece of data, to manage all the data themselves, to, you know, make sure the quality is correct to make it accessible. And so what data mesh is first and foremost about is being able to kind of federate the, or distribute the, the ownership of data, the governance of the data still has to happen, right? And so that is, I think at the heart of the data mesh, but thinking of data as kind of allowing different teams, different domains to own their own data to really manage it like a product with all the best practices that that we have with that super important. >>So we we're doing a lot with data mesh, you know, the way that cloud has multiple projects and the way that Jamar allows you to have multiple catalogs and different groups can kind of interact and share data among each other. You know, the fact that we can connect to all these different data sources, even outside your data lake, you know, with Redshift, Oracle SQL Server, you know, all the different databases that are out there and join across different databases in addition to your data lake, that that's all stuff that companies want with their data mesh. >>What are some of your favorite customer stories that where you've really helped them accelerate that data mesh and drive business value from it so that more people in the organization kind of access to data so they can really make those data driven decisions that everybody wants to make? >>I mean, there's, there's so many of them, but, you know, one of the largest tech companies in the world creating a, a data mesh where you have all the different departments in the company that, you know, they, they, they were a big data warehouse user and it kinda hit the wall, right? The costs were so high and the ability for people to kind of use it for just experimentation, to try new things out to collaborate, they couldn't do it because it was so prohibitively expensive and difficult to use. And so what they said, well, we need a platform that different people can, they can collaborate, they can ex, they can experiment with the data, they can share data with others. And so at a big organization like that, the, their ability to kind of have a centralized platform but allow different groups to manage their own data, you know, several of the largest banks in the world are, are also doing data meshes with Dr you know, one of them has over over a dozen different business units that are using, using Dremio and that ability to have thousands of people on a platform and to be able to collaborate and share among each other that, that's super important to these >>Guys. Can you contrast your approach to the market, the snowflakes? Cause they have some of those same concepts. >>Snowflake's >>A very closed system at the end of the day, right? Closed and very expensive. Right? I think they, if I remember seeing, you know, a quarter ago in, in, in one of their earnings reports that the average customer spends 70% more every year, right? Well that's not sustainable. If you think about that in a decade, that's your cost is gonna increase 200 x, most companies not gonna be able to swallow that, right? So companies need, first of all, they need more cost efficient solutions that are, you know, just more approachable, right? And the second thing is, you know, you know, we talked about the open data architecture. I think most companies now realize that the, if you want to build a platform for the future, you need to have the data and open formats and not be locked into one vendor, right? And so that's kind of another important aspect beyond that's ability to connect to all your data, even outside the lake to your different databases, no sequel databases, relational databases, and drs semantic layer where we can accelerate queries. And so typically what you have, what happens with data warehouses and other data lake query engines is that because you can't get the performance that you want, you end up creating lots and lots of copies of data. You, for every use case, you're creating a, you know, a pre-joy copy of that data, a pre aggregated version of that data. And you know, then you have to redirect all your data. >>You've got a >>Governance problem, individual things. It's expensive. It's expensive, it's hard to secure that cuz permissions don't travel with the data. So you have all sorts of problems with that, right? And so what we've done because of our semantic layer that makes it easy to kind of expose data in a logical way. And then our query acceleration technology, which we call reflections, which transparently accelerates queries and gives you subsecond response times without data copies and also without extracts into the BI tools. Cause if you start doing bi extracts or imports, again, you have lots of copies of data in the organization, all sorts of refresh problems, security problems, it's, it's a nightmare, right? And that just collapsing all those copies and having a, a simple solution where data's stored in open formats and we can give you fast access to any of that data that's very different from what you get with like a snowflake or, or any of these other >>Companies. Right. That, that's a great explanation. I wanna ask you, early this year you announced that your Dr. Cloud service would be a free forever, the basic DR. Cloud service. How has that offer gone over? What's been the uptake on that offer? >>Yeah, it, I mean it is, and thousands of people have signed up and, and it's, I think it's a great service. It's, you know, it's very, very simple. People can go on the website, try it out. We now have a test drive as well. If, if you want to get started with just some sample public sample data sets and like a tutorial, we've made that increasingly easy as well. But yeah, we continue to, you know, take that approach of, you know, making it, you know, making it easy, democratizing these kind of cloud data platforms and, and kinda lowering the barriers to >>Adoption. How, how effective has it been in driving sales of the enterprise version? >>Yeah, a lot of, a lot of, a lot of business with, you know, that, that we do like when it comes to, to selling is, you know, folks that, you know, have educated themselves, right? They've started off, they've followed some tutorials. I think generally developers, they prefer the first interaction to be with a product, not with a salesperson. And so that's, that's basically the reason we did that. >>Before we ask you the last question, I wanna just, can you give us a speak peek into the product roadmap as we enter 2023? What can you share with us that we should be paying attention to where Drum is concerned? >>Yeah. You know, actually a couple, couple days ago here at the conference, we, we had a press release with all sorts of new capabilities that we, we we just released. And there's a lot more for, for the coming year. You know, we will shortly be releasing a variety of different performance enhancements. So we'll be in the next quarter or two. We'll be, you know, probably twice as fast just in terms of rock qu speed, you know, that's in addition to our reflections and our career acceleration, you know, support for all the major clouds is coming. You know, just a lot of capabilities in Inre that make it easier and easier to use the platform. >>Awesome. Tomer, thank you so much for joining us. My last question to you is, if you had a billboard in your desired location and it was going to really just be like a mic drop about why customers should be looking at Drio, what would that billboard say? >>Well, DRIO is the easy and open data lake house and, you know, open architectures. It's just a lot, a lot better, a lot more f a lot more future proof, a lot easier and a lot just a much safer choice for the future for, for companies. And so hard to argue with those people to take a look. Exactly. That wasn't the best. That wasn't the best, you know, billboards. >>Okay. I think it's a great billboard. Awesome. And thank you so much for joining Poly Me on the program, sharing with us what's new, what some of the exciting things are that are coming down the pipe. Quite soon we're gonna be keeping our eye Ono. >>Awesome. Always happy to be here. >>Thank you. Right. For our guest and for Paul Gillin, I'm Lisa Martin. You're watching The Cube, the leader in live and emerging tech coverage.

>>Good morning. Welcome back to the cubes. Continuing coverage of AWS reinvent 2021. I'm Lisa Martin. We have two live sets here. We've got over a hundred guests on the program this week with our live sets of remote sets, talking about the next decade in cloud innovation. And I'm pleased to be welcoming back. One of our cube alumni timbers. She ran the founder and CPO of Jenny-O to the program. Tom is going to be talking about why 2022 is the year open data architectures surpass the data warehouse Timur. Welcome back to the >>Cube. Thanks for having me. It's great to be here. It's >>Great to be here at a live event in person, my goodness, sitting side by side with guests. Talk to me a little bit about before we kind of dig into the data lake house versus the data warehouse. I want to, I want to unpack that with you. Talk to me about what what's going on at Jemena you guys were on the program earlier this summer, but what are some of the things going on right now in the fall of 2021? >>Yeah, for us, it's a big year of, uh, a lot of product news, a lot of new products, new innovation, a company's grown a lot. We're, uh, you know, probably three times bigger than we were a year ago. So a lot of, a lot of new, new folks on the team and, uh, many, many new customers. >>It's good, always new customers, especially during the last 22 months, which have been obviously incredibly challenging, but I want to unpack this, the difference between a data lake and data lake house, but I love the idea of a lake house by the way, but talk to me about what the differences are similarities and how customers are benefiting. Sure. Yeah. >>I think you could think of the lake house as kind of the evolution of the lake, right? So we have, we've had data lakes for a while. Now, the transition to the cloud made them a lot more powerful and now a lot of new capabilities coming into the world of data lakes really make the, that whole kind of concept that whole architecture, much more powerful to the point that you really are not going to need a data warehouse anymore. Right. And so it kind of gives you the best of both worlds, all the advantages that we had with data lakes, the flexibility to use different processing engines, to have data in your own account and open formats, um, all those benefits, but also the benefits that you had with warehouses, where you could do transactions and get high performance for your, uh, BI workloads and things like that. So the lake house makes kind of both of those come together and gives you the, the benefits of both >>Elizabeth talk to me about from a customer lens perspective, what are some of the key benefits and how does the customer go about from say they've got data warehouses, data lakes to actually evolving to the lake house. >>You know, data warehouses have been around forever, right? And you know, there's, there's been some new innovation there as we've kind of moved to the cloud, but fundamentally there are very close and very proprietary architecture that gets very expensive quickly. And so, you know, with a data warehouse, you have to take your data and load it into the warehouse, right. You know, whether that's a, you know, Terra data or snowflake or any, any other, uh, you know, database out there, that's, that's what you do. You bring the data into the engine. Um, the data lake house is a really different architecture. It's one where you actually, you're having, you have data as its own tier, right? Stored in open formats, things like parquet files and iceberg tables. And you're basically bringing the engines to the data instead of the data to the engine. And so now all of a sudden you can start to take advantage of all this innovation that's happening on the same set of data without having to copy and move it around. So whether that's, you know, Dremio for high performance, uh, BI workloads and SQL type of analysis, a spark for kind of batch processing and machine learning, Flink for streaming. So lots of different technologies that you can use on the, on the same data and the data stays in the customer's own account, right? So S3 effectively becomes their new data warehouse. >>Okay. So it can imagine during the last 22 months of this scattered work from Eddie, and we're still in this work from anywhere environment with so much data being generated at the edge of the edge, expanding that bringing the engines to the data is probably now more timely than ever. >>Yeah. I think the, the growth in data, uh, you see it everywhere, right? That that's the reason so many companies like ourselves are doing so well. Right? It's, it's, there's so much new data, so many new use cases and every company wants to be data-driven right. They all want to be, you know, to, to democratize data within the organization. Um, you know, but you need the platforms to be able to do that. Right. And so, uh, that's very hard if you have to constantly move data around, if you have to take your data, you know, which maybe is landing in S3, but move it into, you know, subsets of it into a data warehouse. And then from there move, you know, substance of that into, you know, BI extracts, right? Tableau extracts power BI imports, and you have to create cubes and lots of copies within the data warehouse. There's no way you're going to be able to provide self-service and data democratization. And so really requires a new architecture. Um, and that's one of the main things that we've been focused on at Dremio, um, is really taking the, the, the lake house and the lake and making it, not just something that data scientists use for, you know, really kind of advanced use cases, but even your production BI workloads can actually now run on the lake house when you're using a SQL technology. Like, and then >>It's really critical because as you talked about this, you know, companies, every company, these days is a data company. If they're not, they have to be, or there's a competitor in the rear view mirror that is going to be able to take over what they're doing. So this really is really critical, especially considering another thing that we learned in the last 22 months is that there's no real-time data access is no longer, a nice to have. It's really an essential for businesses in any organization. >>I think, you know, we, we see it even in our own company, right? The folks that are joining the workforce now, they, they learn sequel in school, right. They, they, they don't want to report on their desk, printed out every Monday morning. They want access to the database. How do I connect my whatever tool I want, or even type sequel by hand. And I want access to the data and I want to just use it. Right. And I want the performance of course, to be fast because otherwise I'll get frustrated and I won't use it, which has been the status quo for a long time. Um, and that's basically what we're solving >>The lake house versus a data warehouse, better able to really facilitate data democratization across an organization. >>Yeah. Because there's a big, you know, people don't talk a lot about the story before the story, right. With, with a data warehouse, the data never starts there. Right. You typically first have your data in something like an S3 or perhaps in other databases, right. And then you have to kind of ETL at all into, um, into that warehouse. And that's a lot of work. And typically only a small subset of the data gets ETL into that data warehouse. And then the user wants to query something that's not in the warehouse. And somebody has to go from engineering, spend, you know, a month or two months, you know, respond to that ticket and wiring up some new ETL, uh, to get the data in. And so it's a big problem, right? And so if you can have a system that can query the data directly in S3 and even join it with sources, uh, outside of that things like your Oracle database, your, your SQL server database here, you know, Mongo, DB, et cetera. Well, now you can really have the ability to expose data to your, to your users within the company and make it very self-service. They can, they can query any data at any time and get a fast response time that that's, that's what they need >>At self-service is key there. Speaking of self-service and things that are new. I know you guys dromio cloud launched that recently, new SAS offering. Talk to me about that. What's going on there. Yeah. >>We want to stream your cloud. We, we spent about two years, um, working on that internally and, uh, really the goal was to simplify how we deliver all of the, kind of the benefits that we've had in our product. Right. Sub-second response times on the lake, a semantic layer, the ability to connect to multiple sources, but take away the pain of having to, you know, install and manage software. Right. And so we did it in a way that the user doesn't have to think about versions. They don't have to think about upgrades. They don't have to monitor anything. It's basically like running and using Gmail. Right? You log in, you, you get to use it, right. You don't have to be very sophisticated. There's no, not a lot of administration you have to do. Um, it basically makes it a lot, a lot simpler. >>And what's the adoption been like so far? >>It's been great. It's been limited availability, but we've been onboarding customers, uh, every week now. Um, many startups, many of the world's largest companies. So that's been, that's been really exciting actually. >>So quite a range of customers. And one of the things, it sounds like you want me to has grown itself during the pandemic. We've seen acceleration of, of that, of, of, uh, startups, of a lot of companies, of cloud adoption of migration. What are some, how have your customer conversations changed in the last 22 months as businesses and every industry kind of scrambled in the beginning to, to survive and now are realizing that they need to modernize, to thrive and to be competitive and to have competitive advantage. >>I think I've seen a few different trends here. One is certainly, there's been a lot of, uh, acceleration of movement to the cloud, right? With, uh, uh, you know, how different businesses have been impacted. It's required them to be more agile, more elastic, right. They don't necessarily know how much workload they're gonna have at any point in time. So having that flexibility, both in terms of the technology that can, you know, with Dremio cloud, we scale, for example, infinitely, like you can have, you know, one query a day, or you can have a thousand queries a second and the system just takes care of it. Right. And so that's really important to these companies that are going through, you know, being impacted in various different ways, right? You had the companies, you know, the Peloton and zooms of the world that were business was exploding. >>And then of course, you know, the travel and hospitality industries, and that went to zero, all of a sudden it's been recovering nicely, uh, you know, since then, but so that flexibility, um, has been really important to customers. I think the other thing is just they've realized that they have to leverage data, right? Because in parallel to this pandemic has been also really a boom in technology, right? And so every industry is being disrupted by new startups, whether it's the insurance industry, the financial services, a lot of InsureTech, FinTech, you know, different, uh, companies that are trying to take advantage of data. So if you, as a, as an enterprise are not doing that, you know, that's a problem. >>It is a problem. It's definitely something that I think every business and every industry needs to be very acutely aware of because from a competitive advantage perspective, you know, there's someone in that rear view mirror who is going to be focused on data. I have a real solid, modern data strategy. That's going to be able to take over if a company is resting on its laurels at all. So here we are at reinvent, they talked a lot about, um, I just came off of Adam psyllid speeds. So Lipsey's keynote. But talk to me about the jumbo AWS partnership. I know AWS its partner ecosystem is huge. You're one of the partners, but talk to me about what's going on with the partnership. How long have you guys been partners? What are the advantages for your customers? >>You know, we've been very close partners with AWS for, for a number of years now, and it kind of spans many different parts of AWS from kind of the, uh, the engineering organization. So very close relationship with the S3 team, the C2 team, uh, you know, just having dinner last night with, uh, Kevin Miller, the GM of S3. Um, and so that's kind of one side of things is really the engineering integration. You know, we're the first technology to integrate with AWS lake formation, which is Amazon's data lake security technology. So we do a lot of work together on kind of upcoming features that Amazon is releasing. Um, and then also they've been really helpful on the go-to-market side of things on the sales and marketing, um, whether it's, you know, blogs on the Amazon blog, where their sales teams actually promoting Dremio to their customers, um, uh, to help them be successful. So it's really been a good, good partnership. >>And there they are, every time I talked to somebody from Amazon, we always talk about their kind of customer first focus, their customer obsession sounds like you're, there's deep alignment on from the technical engineering perspective, sales and marketing. Talk to me a little bit about cultural alignment, because when you're going into customer conversations, I imagine they want to see one unified team. >>Yeah. You know, I think Amazon does have that customer first and obviously we do as well. And we, you know, we have to right as a, as a startup for us, you know, if a customer has a problem, the whole company will jump on that problem. Right. So that's where we call it customer obsession internally. Um, and I think that's very much what we've seen, you know, with, with AWS as well as the desire to make the customer successful comes before. Okay. How does this affect a specific Amazon product? Right? Because anytime a customer is, uh, you know, using Dremio on AWS, they're also consuming many different AWS services and they're bringing data into AWS. And so, um, I, I think for both of us, it's all about how do we solve customer problems and make them successful with their data in this case. Yup. >>Solving those customer problems is the whole reason that we're all here. Right. Talk to me a little bit about, um, as we have just a few more minutes here, we, when we hear terms like, future-proof, I always want to dig in with, with folks like yourself, chief product officers, what does it actually mean? How do you enable businesses to create these future-proof data architectures that are gonna allow them to scale and be really competitive? Sure. >>So yeah, I think many companies have been, have experienced. What's known as lock-in right. They, they invest in some technology, you know, we've seen this with, you know, databases and data warehouses, right? You, you start using that and you can really never get off and prices go up and you find out that you're spending 10 times more, especially now with the cloud data warehouses 10 times more than you thought you were going to be spending. And at that point it becomes very difficult. Right? What do you do? And so, um, one of the great things about the data lake and the lake house architecture is that the data stays stored in the customer's own account. Right? It's in their S3 buckets in source formats, like parquet files and iceberg tables. Um, and they can use many different technologies on that. So, you know, today the best technology for, for, you know, sequel and, you know, powering your, your mission critical BI is, is Dremio, but tomorrow they might be something else, right. >>And that customer can then take that, uh, uh, that company can take that new technology point at the same data and start using it right. That they don't have to go through some really crazy migration process. And, you know, we see that with Teradata data and Oracle, right? The, the, the old school vendors, um, that's always been a pain. And now it is with the, with the newer, uh, cloud data warehouses, you see a lot of complaints around that, so that the lake house is fundamentally designed. Especially if you choose open source formats, like iceberg tables, as opposed to say a Delta, like you're, you're really, you know, future-proofing yourself. Right. Um, >>Got it. Talk to me about some of the things as we wrap up here that, that attendees can learn and see and touch and feel and smell at the jumbo booth at this reinvent. >>Yeah. I think there's a, there's a few different things they can, uh, they can watch, uh, watch a demo or play around with the dremmel cloud and they can talk to our team about what we're doing with Apache iceberg. It's a iceberg to me is one of the more exciting projects, uh, in this space because, you know, it's just created by Netflix and apple Salesforce, AWS just announced support for iceberg with that, with their products, Athena and EMR. So it's really kind of emerging as the standard table format, the way to represent data in open formats in S3. We've been behind iceberg now for, for a while. And so that to us is very exciting. We're happy to chat with folks at the booth about that. Um, Nessie is another project that we created an source project for, uh, really providing a good experience for your data, where you have version control and branching, and kind of trying to reinvent, uh, data engineering, data management. So that's another cool project that there, uh, we can talk about at the booth. >>So lots of opportunity there for attendees to learn even thank you, Tomer for joining me on the program today, talking about the difference between a data warehouse data lake, the lake house, did a great job explaining that Jamil cloud what's going on and how you guys are deepening that partnership with AWS. We appreciate your time. Thank you. Thanks for having me. My pleasure for Tomer. She ran I'm Lisa Martin. You're watching the cube. Our coverage of AWS reinvent continues after this.

>> Narrator: From around the globe it's theCUBE with digital coverage of AWS reinvent 2020. Sponsored by Intel, AWS and our community partners. >> All right, you're continuing coverage of AWS reinvent 2020 virtual event. We get the pleasure of covering this show like no other AWS reinvent. We are pulling in from the other side of the world Tomer Levy, CEO of Logz.io. First time Cuber so we're going to ease them into it but it's going to be a great conversation. I'm Keith Townsend at CTO advisor. Tomer, welcome to the show. >> Keith, thank you for having me. I'm super excited to be here. >> You know what? We love having founders here on theCUBE. We have a long history of having deep conversations with builders and we're probably the show for builders. AWS reinvent is virtual. However, I think the spirit of re-invent is highlighted in companies like this. We've seen a lot of observability companies sprout up around the industry. AWS is a big, big magnet for these types of solutions. What's the assets Logz.io and how are you guys differentiating yourselves in this crowded space? >> Yeah, absolutely Keith you see observability is so fundamental to building applications on AWS that as companies develop more applications, they have to have solid observability. And we have a mission and our mission is to enable develop engineers and any engineer out there to use open source to run their observability. So when we were developers we wanted to use open source but we had to compromise on a proprietary solution. We decided to build the company so engineers can use the observability tools they're already using for logging, for metrics, for tracing, Whatever they're already using we want to enable them to use that at scale on AWS. So it's easy to use, it's super smart and the data is coordinated. And I think fundamentally it's what we're doing very differently in the market. There is no other company in the market today that takes the best open sources and bring them together as one super strong platform and we're proud to be that company. >> Well, when you say there's no other company doing open source the way that you guys are doing it, that really intrigues me especially as we look at this from the angle of Cooper Netties, the CEO of the leading virtualization company called Kubernetes, the doubts home of the internet. How do you see the intersection of opensource observability in kubernetes especially in the public cloud? >> Yeah, for sure. People say that kubernetes is almost the operating system of the future and why do people use kubernetes? They use it to make sure they can run multiple microservices. They can take their application which used to be a monolith and put it in a distributed way. So it becomes so much harder to monitor or to troubleshoot even to secure applications. So the way we built Logz.io was really designed for companies that are moving into the cloud, companies moving into kubernetes, into microservices and by having logs and metrics and traces all work together through the best open sources. I think we can help customers really get the visibility and just accelerate the software delivery. Just provide better service to their customers. >> So Levy, walk me through that journey. What is it like for a developer to come from their traditional open source roots and enter the cloud where they're melding public cloud services in AWS alongside their tools that they're using in observability. How do you help ease that transition? >> Yeah, absolutely Keith because one of the main drivers for companies adopting tools like Logz.io is actually the migration to AWS. So imagine now migration to a new ground, what do you have to think about first? Do I have the glasses? Can I see what's going on? Like when I see what's going on, I feel more confident. So if I'm now using, let's call it elk or using the open-source Grafana or using tools like Jaeger, which are all open sources too that we offer as part of our platform. So when I use these tools I'm using them to get visibility into my own application, my own infrastructure. So Logz.io faster transition to Logz.io is super easy. This is the whole notion of having an open source compatible platform. So I want to move to Loz.io, everything that worked with my open source currently still works with Logz.io but now when you move to the cloud Logz.io on AWS, we have a very strong relationship so all the services are automatically monitored. You have pre-configured dashboard, everything is interconnected so just when I jump into the AWS platform I immediately get visibility of my existing apps and of the AWS infrastructure. And that eventually helped me become confident, grow and deliver faster on AWS. >> So again this is a conference full of builders but you used the term devOps. We're starting to see a bleeding of DevOps and builders or operations and builders come together. One of the big trans and DevOps and observability is AI and machine learning. What are some of the features of AI and Machine Learning you guys are bringing to bear to this market? >> Yeah, listen I'm a big believer in AI. You know, the amount of data that companies like Logz.io have to ingest and our customers have to process. It's just something a human being cannot possibly understand. It's like billions and millions of lines of data. So this is where we bring machines to help humans. I'll give you one example, right? If you're a DevOps engineer and you see an issue in your logs, what do you do? You usually copy that and putting it into Google and you'll end up on stack overflow, maybe on GitHub, maybe on another website. What we have done is we've scraped the web and we have learned from any user on our platform. So we actually know which log line is important and which one is not. So when companies send a log line, our AI automatically scans it and says, "Hey, here are the billion log lines. No one cares about but here is one that you should really look at right now because either you know half a million people that were searching for it. There are 7,000 alerts on this and it just happened to you. Keith look, maybe you should jump in and look at that". This is where AI makes us just better operate or better DevOp people and not kind of try to replace us. >> So I'm a technical founder, you're a technical founder, theCUBE loves supporting founders. One of the advantages of being the CEO of your company is that you get to decide the culture and the mission of your company. Talk to me about the people side of your organization and how you're making a change for the better. >> Yeah, absolutely. You know, it is a privilege and to the privilege to start and come with a mission that you want to change something in the world and we were just two developers, a staff, my co-founder and myself having to use a product we didn't want to use and you know still really wanted to use an open source product. So we said let's build the company around that and this is kind of set the mission for the company as the company evolved, so is our mission. It evolves from logging to monitoring, to tracing and we also added a cloud SIEM solution all based on open source. So we're going to DevOps engineers and any engineers and we tag any engineer we tell them, "Hey, you can use the best open source tools in the cloud is one platform without compromising". And that's something that really is very differentiated today and I'm very humbled and excited to be part of this journey and I think the team at Logz.io is as well. >> You know I'm always intrigued about this journey to the cloud. Security is one of these things that intrigues me especially as we look at something as mature in the way open source. We often associate open source with public cloud, cloud native but open source is as old as technology itself. So there is a lot of practices that we bring from legacy, traditional infrastructures into the public cloud. So talk to me about that transition of security and security models? How does observability help to either take our existing tools and migrate them to the public cloud or adopt all new cloud native tools in the public cloud? >> Yeah, for sure. I think security is probably together with observability. One of the top priority that when you think about CTOs and VP of Engineering and CSOs, they're concerned about. So we've taken the observability path and bringing better glasses to our users and then on the security side there's a whole market called the SIEM market where companies look at detecting threats, investigating them and most of these tools were that companies use our legacy, incumbents and for design on their own premises world. And are not really a fit for the dynamic world of kubernetes and the cloud. And this is when we decided a couple of years ago to launch a product in that space and today this product is extremely successful. We have customers protecting their AWS environments across the board. So basically with one product for observability, you can with a single checkbox enable security and then you can detect threats. You can look at kind of the common pitfalls of AWS environment and how you can avoid them. And eventually when you see a threat, you can use our tool to investigate and find the root cause in a tool which was designed on AWS for AWS. And it's really designed for the kind of the native cloud environment rather than the on-premise as well. >> Now, is there an integration between the AI ML law of management and the threat management solutions from our observability perspective? >> Yeah, for sure. This is the beauty, it's all one data platform. So customers ship their data, loads, metrics and traces into one place and then we start to look at how can we provide more value on the data, right? How can we look at the logs from an operational perspective and tell you, "Hey, your production might be going down because of a production risks or maybe we can provide you threat intelligence". We can enrich the data and tell you, "Hey, we think you're undergoing an attack right now". So this is all done by users and it is all enraged by AI that provides more visibility, more enrichment of the data and just advice on where to look. >> So Tomer levy, CEO, founder of Logz.io. You're now a few belong. Thank you for joining the show. I hope you have a very successful AWS reinvent. Speaking of AWS reinvent, theCUBE's nonstop coverage of AWS reinvent continues. Watch some of the world's greatest builders, innovators get challenged on their vision and for us to understand and appreciate the work that's been done in this dynamic community. Continue to watch this coverage and more. Talk to you next interview on the CUBE's coverage, of AWS reinvent 2020. (soft music)

(bright upbeat music) >> Hey everyone. Welcome to this "CUBE Conversation" featuring Dremio. I'm your host, Lisa Martin. And I'm excited today to be joined by Mark Lyons the VP of product management at Dremio. Mark thanks for joining us today. >> Hey Lisa, thank you for having me. Looking forward to the top. >> Yeah. Talk to me about what's going on at Dremio. I had the chance to talk to your chief product officer Tomer Shiran in a couple months ago but talk to us about what's going on. >> Yeah, I remember that at re:Invent it's been an exciting few months since re:Invent here at Dremio and just in the new year we raised our Series E since then we ran into our subsurface event which we had over seven, 8,000 registrants and attendees. And then we announced our Dremio cloud product generally available including Dremio Sonar, which is SQL query engine and Dremio Arctic in public preview which is a better store for the lakehouse. >> Great. And we're going to dig into both of those. I saw that over 400 million raised in that Series E raising the valuation of Dremio to 2 billion. So a lot of growth and momentum going on at the company I'm sure. If we think about businesses in any industry they've made large investments in data warehouses, proprietary data warehouses. Talk to me about historically what they've been able to achieve, but then what some those bottlenecks are that they're running into. >> Yeah, for sure. My background is actually in the data warehouse space. I spent over the last eight, maybe close to 10 years and we've seen this shift go on from the traditional enterprise data warehouse to the data lake to the the last couple years is really been the time of the cloud data warehouse. And there's been a large amount of adoption of cloud data warehouses, but fundamentally they still come with a lot of the same challenges that have always existed with the data warehouse, which is first of all you have to load your data into it. So that data's coming from lots of different sources. In many cases, it's landing in a files in the data lake like a repository like S3 first. And then there's a loading process, right? An ETL process. And those pipelines have to be maintained and stay operational. And typically as the data warehouse life cycle of processing moves on the scope of the data that consumers get to access gets smaller and smaller. The control of that data gets tighter and change process gets heavier, and it goes from quick changes of adding a column or adding a field to a file to days if not weeks for businesses to modify their data pipelines and test new scenarios offer new features in the application or answer new questions that the business is interested you know, from an analytics standpoint. So typically we see the same thing even with these cloud data warehouses, the scope of the data shrinks, the time to get answers gets longer. And when new engines come along the same story we see, and this is going on right now in the data warehouse space there's new data that are coming and they say, well we're a thousand faster times faster than the last data warehouse. And then it's like, okay, great. But what's the process? The process is to migrate all your data to the new data warehouse, right? And that comes with all the same baggage. Again, it's a proprietary format that you load your data into. So I think people are ready for a change from that. >> People are not only ready for a change, but as every company has to become a data company these days and access to real time data is no longer a nice to have. It's absolutely essential. The ability to scale the ability to harness the value from as much data as possible and to do so fast is real really table stakes for any organization. How is Dremio helping customers in that situation to operationalize their data? >> Yeah, so that's why I was so intrigued and loved about Dremio when I joined three, four, five months back. Coming from the warehouse space, when I first saw the product I was just like, oh my gosh, this is so much easier for folks. They can access a larger scope of their data faster, which to your point, like is table stakes for all organizations these days they need to be able to analyze data sooner. Sooner is the better. Data has a halflife, right? Like it decays. The value of data decays over time. So typically the most valuable data is the newest data. And that all depends on what we're the industries we're talking about the types of data and the use cases, but it's always basically true that newer data is more valuable and they need to be able to analyze as much of it as possible. The story can't be, no, we have to wait weeks or months to get a new data source or the story can't be you know, that data that includes seasonality. You know, we weren't able to keep in the same location because it's too expensive to keep it in the warehouse or whatever. So for Dremio and our customers our story is simple, is leverage the data where it is so access data in all sorts of sources, whether it's a post press database or an S3 bucket, and don't move the data don't copy the data, analyze it in place. And don't limit the scope of the data you're trying to analyze. If you have new use cases you have additional data sets that you want to add to those use cases, just bring them in, into S3 and you are off to the races and you can easily analyze more data and give more power to the end user. So if there's a field that they want to calculate the simple change convert this miles field, the kilometers well, the end users should be empowered to just make a calculation on the data like that. That should not require an entire cycle through a data engineering team and a backlog and a ticket and pushing that to production and so forth which in many cases it does at many organizations. It's a lot of effort to make new calculations on the data or derive new fields, add a new column and so forth. So Dremio makes the data engineers life easier and more productive. It also makes the data consumers life much easier and happier, and they can just do their job without worrying about and waiting. >> Not only can they do their job but from a business, a high level perspective the business is probably has the opportunity to be far more competitive because it's got a bigger scope of data, as you mentioned, access to it more widely faster and those are only good things in terms of- >> More use cases, more experiments, right? So what I've seen a lot is like there's no shortage of ideas of what people can do with the data. And projects that might be able to be undertaken but no one knows exactly how valuable that will be. How whether that's something that should be funded or should not be funded. So like more use cases, more experiments try more things. Like if it's cheap to try these data problems and see if it's valuable to the business then that's better for the business. Ultimately the business will be more competitive. We'll be able to try more new products we'll be able to have better operational kind of efficiencies, lower risk all those things. >> Right. What about data governance? Talk to me about how the Lakehouse enables that across all these disparate data volumes. >> I think this is where things get really interesting with the Lakehouse concept relative to where we used to be with a data lake, which was a parking ground for just lots of files. And that came with a lot of challenges when you just had a lot of files out there in a data lake, whether that was HDFS, right. I do data lake back in the day or now a cloud storage object, storage data lake. So historically I feel like governance, access authentication, auditing all were extremely challenging with the data lake but now in the modern kind of lake in the modern lakehouse world, all those challenges have been solved. You have great everything from the front of the house with all and access policies and data masking everything that you would expect through commits and tables and transactions and inserts and updates and deletes, and auditing of that data able to see, well who made the changes to the data, which engine, which user when were they made and seeing the whole history of a table and not just one, not just a mess of files in a file store. So it's really come a long way. I feel like where the renaissance stage of the 2.0 data lakes or lakehouses as people call them. But basically what you're seeing is a lot of functionality from the traditional warehouse, all available in the lake. And warehouses had a lot of governance built in. And whether that is encryption and column access policies and row access policies. So only the right user saw the right data or some data masking. So that like the social security was masked out but the analyst knew it was a social security number. That was all there. Now that's all available on the lakehouse and you don't need to copy data into a data warehouse just to meet those type of requirements. Huge one is also deletes, right? Like I feel like deletes were one of the Achilles heels of the original data lake when there was no governance. And people were just copying data sets around modifying data sets for whatever their analytics use case was. If someone said, "Hey, go delete the right. To be forgotten GDPR." Now you've got Californias CCPA and others all coming online. If you said, go delete this per you know, this records or set of records from there from a lake original lake. I think that was impossible, probably for many people to do it with confidence, like to say that like I fully deleted this. Now with the Apache like iceberg cable format that is stores in the lakehouse architecture, you actually have delete functionality, right? Which is a key component that warehouses are traditionally brought to the table. >> That's a huge component from a compliance perspective. You mentioned GDPR, CCPA, which is going to be CPRA in less than a year, but there's so many other regulations data privacy regulations that are coming up that the ability to delete that is going to be table stakes for organizations, something that you guys launched. And we just have a couple minutes left, but you launched I love the name, the forever free data Lakehouse platform. That sounds great. Forever Free. Talk to me about what that really means is consisting of two products the Sonar and Arctic that you mentioned, but talk to me about this Forever Free data Lakehouse. >> Yeah. I feel like this is an amazing step forward in this, in the industry. And because of the Dremio cloud architecture, where the execution and data lives in the customer's cloud account we're able to basically say, hey, the Dremio software the Dremio service side of this platform is Forever Free for users. Now there is a paid tier but there's a standard tier that is truly forever free. Now that that still comes with infrastructure bills from like your cloud provider, right? So if you use AWS, you still have an S3 bill like for your data sets because we're not moving them. They're staying in your Amazon account in your S3 bucket. You still do still have to pay for right. The infrastructure, the EC2 and the compute to do the data analytics but the actual softwares is free forever. And there's no one else in our space offering that at in our space, everything's a free trial. So here's your $500 of credit. Come try my product. And what we're saying is with this kind of our unique architectural approach and this is what I think is preferred by customers too. You know, we take care of all the query planning all the engine management, all the administrative the platform, the upgrades fully available zero downtime platform. So they get all the benefits of SaaS as well as the benefits of maintaining control over their data. And because that data staying in their account and the execution of the analytics is staying in their account. We don't incur that infrastructure bill. So we can have a free forever tier a forever free tier of our platform. And we've had tremendous adoption. I think we announced this beginning of March first week of March. So it's not even the end of March. Hundreds and hundreds of signups and many customers actively are users actively on the platform now live querying their data >> Just kind of summarizes the momentum that Dremio we seeing. Mark, thank you so much. We're out of time, but thanks for talking to me- >> Thank you. >> About what's new at Dremio. What you guys are doing. Next time, we'll have to unpack this even more. I'm sure there's loads more we could talk about but we appreciate that. >> Yeah, this was great. Thank you, Lisa. Thank you. >> My pleasure for Mark Lyons. I'm Lisa Martin. Keep it right here on theCUBE your leader in high tech hybrid event coverage. (upbeat music)

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

>>from around the globe. It's the Cube with digital coverage of VM World 2020 brought to you by VM Ware and its ecosystem >>partners. Hello and welcome to the Cube. Special coverage of VM World 2020 Virtual I'm John for host of the Cube were stupid men Day volonte all doing interviews covering the virtual version of VM World. First time it's ever happened. We've been covering VM World for over 10 years, our 11th season with Cube at VM World. And of course, it's difference virtual. But we're doing our part. We're getting in the programs. We need to get the stories out and we got a great guest here. Submit to on who's the chief customer officer of the M where, uh, back to VM, where he ran the end user computing of which we covered air. Watch a lot of great announcements Submit. Great to see you. Thanks for coming on to the Q. Virtual >>John. Great to see you again. And great to be back on the Cube. >>So great to see you. And again I know you. You came in your back into the wheelhouse of VM ware. But as the theme of this show is putting the digital foundation for an unpredictable world. Also, with Covidien going virtual makes a lot of sense. However, VM Ware has been doing extremely well on the business performance side and making all the right tech moves we've been covering them to Cuba is well documented, the business models evolving. The performance is there. You are in a new role for VM, where its newly created chief customer officer tell us why you're back. Why this role? Why is it important? >>Yeah, great question, John. You know, I I joined the anywhere because we end where I look at sort of what bm where is trying to do all aligned with what customers want If you think about customers, they have been up until now, dabbling with cloud building sort of strategies on how to embrace Cloud, which applications will go to which parts off the cloud. And it has been something that has been more off slow RL strategy and with the multi cloud transition plan. Now, VM Ware provides to some extent this, you know, started out with operating system for the hardware, and it has evolved to provide operating system for the cloud it truly runs applications across multiple clouds. And with our partnerships with AWS Azure, Microsoft Google, we're able to sort of give our customers this multi cloud platform for them to run any application, whether that's traditional or modern, in a sort of unified operational fashion. Now this is a different subscription world for customers, right and customers in the world of cloud, especially when they're going into this kind of a transformational journey. Um, you know, it requires we anywhere to think slightly differently. It's not just the traditional cell implement support kind of customer model. You have really help them achieve their out, come over a period of time and then make them successful as they continue to sort of face the uncertainties off the multi cloud world. So So So Pat and Sanjay decided to create this new customer experience office and all different functions from success support digital engagement as well a czar insulting professional services. Tam's were put together so that we can offer integrated experiences to the customer. And that sounded exciting and, you know, we're making tons off interesting innovations there. Some announced that GM World and, uh, very much aligned with an objective to help our customers. >>E. I want to dig into the news and the announcement because I think there's a specific thing I'd like to drill into. But I want to get your thoughts submit because I think VM Ware and I thought to Sanjay about this as well as Pat. Clearly. Cooper Days is the dial tone of the Internet investment cloud Native Project. Monterey speaks to Multi cloud, totally get it. But Cove it has accelerated not only VM where every company, whether they're on the delivery side of it selling side or even consuming of the technology cloud, for instance, has forced the digital transformation. And it's catching some people off guard, right? So what are your thoughts? Because, you know, you have a value projects, you sell it to customers, you implement it, you support it. I mean, that >>was a >>nice grew swing for enterprise vendors like VM Ware. But now, with cove, it and all the digital transformation acceleration, it's causing a lot of people to be ready faster. How >>do you get >>that readiness? What do you bring to the table? What's your view on this? What's your reaction? Because people >>try to >>figure this out. It's confusing. >>I mean, I You know what it's it's very interesting. For example, I will give you an example. There's like, two extremes, and both of them are dealing with a very similar situation, all caused because of prove it. Okay, On one end of the spectrum, there are customers who are saying, Listen, our business is doing extremely well because of digital, and all of a sudden, uh, business needs this rapid agility, which can only be achieved through modern applications, and they're able to sort of move these applications because of elasticity of the cloud and leveraging multiple clouds. To do so is extremely important. If you're on one side of the spectrum on your business, where the business is doing extremely well, you have a percentage of the business that was coming from e commerce. All of a sudden that e commerce has accelerated. You know you can think off certain retailers, you know. Large scale retailers in that segment, and their their multi cloud journeys are accelerated, mostly because off just this surge in demand and change in capabilities that are needed to perform digital engagement with customers at a much much rapid pace, which are very difficult to do without leveraging multiple clouds. That's one extreme. The other extreme is, you know, I'll give you an example from large scale airlines and we all know in the travel hospitality airline business, this is extremely slow business for them, right at this point of time, and they're using the opportunity off this sort of time when things are slower to say, Okay, why don't we take this opportunity to fundamentally change our distilling it and truly embraced multi cloud while doing so? Because there is an opportunity to do so. The workload on the application than the infrastructure does not high little more technology reasons. A little bit more sort of a for downtime reason sort of go through the transformation faster. In other words, both ends of the spectrum. I'm seeing customers move the words sort of this destination fast it. And guess what? There is really no one at this stage outside of VM ware who can help them achieve that because otherwise you set a single voice. You know, there are their players who died. You tow their singular cloud solution and running. You know what I what I tell customers is multi cloud doesn't mean you are running two different architectures on two different clouds, right? That's not multi cloud. Multi cloud means running a singular architectures on multiple clouds, because that's when you get through governance and true operational scale and true experience and elasticity and control. And that's what we, um, where is all about? So we are now engaged with those conversations and helping customers at both the front end right when they're engaged with us at this stage. But we have also down tailored our service delivery and our success off offerings and are how we engage with customers digitally and sort of technically and through people. Uh, in once they start their journey with us, Um, and they sort of embark on leveraging the technology into multi cloud I want. So So that's the sort of shift that has occurred. >>Yeah, I want to unpack the offering in a second, but I want to stay in the customer experience for a minute. We've heard that cliche a customer experience. So digital transmission. Okay, it's actually happening now, and I totally agree with you, by the way there's there's the modernization trend. You just basically spoke to the spectrums. But it's about modernization. Okay, if you think modernization, you think business model business model is Hey, it's pretty light right now. I'm not a lot of people traveling. Let's retool, Let's modernize, Let's use our resource is and modernize our business, which is a lot of applications. It's everything up and down the stack. And then the companies that have a tailwind with Covic, who have had the epiphany and saying, If we don't building modern app or have modern APS in market, we're out of business. So there's a critical urgency to, uh, coming out of it with a growth strategy that's a business model transformation. Totally get that. That's where the customers are. So the question for you is okay. How do you talk to the customer that is saying, Hey, I'm building a modern app. We have to pivot, were forced to pivot whatever word you want to use force to survive. They're now they have to build a modern app. How do you guys support that customer? How does that customer? What does that customer need to be successful? >>Yeah, I mean, I think it starts with an architectural approach right. We bring to the customers and architectural approach across multiple clouds that helped them when they go for their existing applications or new modern applications conforming toe, one operating model and one architectures. Because in this in this time, you know, customers have many critical line of business applications. This airline customer I was talking about, they have 600 applications that are quite critical. They sort of segment them out on which one they will truly modernize because of the business model modernization like you mentioned and which ones they will live with, the way they are for multiple reasons and how it starts with connecting them with a unified architect chair and a unified operating model is how we start with customers. Okay. And that is where the power off the younger comes in. Because, like I said, it becomes this architectural operating system for for the customers to run and adopt multiple clouds. >>You gotta be the chief customer officer. You're the quarterback. You're the one in charge of making sure customers were happy. Okay? And they get what they need. And again, there's different aspects of it. What do you guys announcing it? VM World 2020 virtual, um, that people should pay attention thio around servicing customers in this new subscription and SAS world. >>Yeah, I think besides the technology announcements in terms off modern, sort off, multi cloud platform, the architectural with Project Monterey from the customer experience side, we did announcement to announcements. One was for customers embarking on a journey. We want to make sure that customers get everything they need to be successful on the journey on an ongoing basis. Some off these journeys for large customers, John can take not just sort of three months, but three years because they're dealing with various applications. So for that we announced two pretty simple and easy to embrace offerings. One is AP navigator. AP Navigator enables customers to quickly assess which applications I have to be, you know, on one end, you know, rewritten, completely rewritten and on the other end simply sort of re hosted. Okay, and there are multiple options in between, and we call them as a five, our model with customers, and we guide customers through our own assessment and working with customers on how to sort of segment their applications and use a common architectures across all of them that we can then help and it and secondly, toe help them with. We announced something called Success 3 60 Success 3 60 is Our Mechanism Toe guide and help customers on an ongoing basis for a success plan with continuous, sort off adoption guidance designed workshops as well as providing they're dedicated support that customers need for embracing multiple cloud across all the cloud. With this architectural this way, customers get assured that they're able to get the right up front sort of assessment on applications and ongoing success. Okay, And that's sort of what we announced within customer experience side. And we have been able all of this available two people you know there are critical for large scale engagements, but also digital, you know, just like our customers are innovating with digital. We innovated with our own digital environment, and we brought it all together with something called customer Connect, all available with one single digital experience that's mobile friendly, alert driven, search driven. You know, all the AI that's needed at this point of time in terms of engaging with customers with proactive notifications and guidance in terms of how they're doing with success built into a singular experience so that they can engage with us, and we can engage with them to make them successful. >>And so it's people in technology you guys are bringing to the table. What can customers expect? Because, you know, as they've worked with the M where you've always had great technical support outside its have been a technology driven company. Um, but as you start getting into SAS, you're starting to get into the business model transformation. How do you guys impacting the customers and how you go to market and how you, uh, service your customer base? >>Yeah, I think there are two elements What customers can expect one. They don't have to stand up and engagement and experience mortal completely separate for a small set of applications on a completely different you know, cloud architectures. They could just fit and build a single experience off dealing with the M, where, as a mechanism to enable all of their applications to be hosted, regardless of which cloud there in Uh huh Sandvik they do it at their own pace, right? As then when they're ready for applications. Secondly, and more importantly, for the business model transformation side. We have a model where we continue to show them the value realization. Okay, because these are true business model transformations. At this stage, there is lot off investment that's coming into I P while at the same time, the rest off the business is doing belt type. So there is a continuous pressure on Earth. Customers are I t. That is the champion for the customers, and they're working with developers in line of business teams, and they have to continue to show how what they're investing into as a singular platform or in architecture is going to deliver some kind of a value on an ongoing basis. So we have delivered on an ongoing basis rip boards and feed back and continuous sort of information back to the customers so that they can take back to their businesses on all the investments they're making now are ongoing basis what value the business is getting, because at the end of the day in this, this is probably the first time in the where I I t is probably getting the least belt tightening in the case off sort of an economic downturn, and in fact, it is being looked at as a way to invest out off the downturn. Right? So they're going to be, in a way where there sometimes even going into the boardroom and showing not just governance, but also sort of the investments they made, what kind of value they they got. So those are the two things were providing seamless and at at pace move toe multi cloud with a common experience and second, ongoing value realization that they can communicate whoever they need. Toe >>submit. You know, we've been following VM where for many me personally of persons that was founded. But with the Cube since 2010 star 11th year, You know, we've been critical of times and pointing out the obvious and in some cases, not so obvious successes and challenges. Um and so we've seen the completeness of vision evolved and pat, certainly. You know, he he held the line and he did the right things. And then he executed. So, you know, as you look at the emerald, we're now been complimentary on some of the moves. Certainly on the technology side that you guys have made and then we again we've talked about this many times on the Cube. So complete in this, uh, vision check. Okay, this is wholesome. Michael Dell issues, but gave talks about that. So good vision complete executed business performance is there. But as you talk about sass and subscription, your ability to execute is going to be a key variable and things like the Gartner Magic quadrant for the areas you're competing in. Multi cloud talk about how you guys just set up financially to support that personnel. What is your organization gonna do? Can you share your vision? How you going to be able to execute customers success programs as this uncertainty around multi cloud continues to become reality and things are changing. >>Yeah, I think a couple of things firstly, you know, to be absolutely candid, you know, the pace at which the customers are going to the new multi cloud models is faster now than it was nine months ago. We just discussed that. Okay, so I wouldn't I would be misrepresenting if I said we always were ready for this kind of the case. We're also adjusting and innovating at this stage as fast as possible. The good news is that we were headed in the right direction. Okay, if we were headed in the wrong direction, it would have been much, much harder. Okay. Secondly, I think there is a very strong leadership, the leadership team. I mean, at the end of the day, it's vision, leadership, team investment, the components and, of course, diligence to execute that comes in for the execution. To me vision and the direction was always very, very strong. It motivated me to join the anywhere for this important mission. Second and many other exact. If second the leadership team is as strong as they get, the four team is extremely strong. We have strong leadership team leadership from Pat Michael, of course, as well as Sanjay Rgu Rajiv. Everyone provides strong leadership and then third, you asked about sort of the financial element. You know, they're The company continues to perform quite well, right? We have core businesses that some critical for customers to use as technologies to enable them, you know, to come out off this sort off economic issue we're facing and they're facing. So as a result, you know, financially, we're in a good position to be able to invest back into the business and Secondly, we have made now we've always, always been extremely strong on the technology front. Okay, now with Sanjay and packed sort of saying that we're going to be extremely strong in terms of customer experience front because the world of subscription, the world of cloud, the world off the SAS requires not just great technology but also a great customer experience. So we're seeing tremendous in a continued sort of support financially in terms of investing into the customer experience, from both getting the right set of people offerings as well as technology. So I believe we have all three things. Having said that, you know, some of these things that we're investing in. They need a lot of work, and I'm. While I'm proud of what we have accomplished, I truly believe you know the best is yet to come, and the right investments that we're making are going to continue to sort of enhance our offerings both through people as well as technology. But there's work to be done. You >>know, it's all about, you know, having the consume ability of the technology thio, the value proposition of VM ware and also also is a company being um, open and easy to work with and consumable that way. So I think this is a great time. Certainly. Product wise. Business wise, You guys do extremely well. Congratulations on your new role on the senior leadership is the chief customer officer of VM Ware will be following the stories of your customers. So I really appreciate you taking the time. >>Thank you. Thank you so much, John. Excited to be back. Great >>to have you back on the queue here. VM world coverage of 2020 virtual. I'm John for this. The host of Cube Virtual. Check us out cube dot Net. And also our new cube 3 65 where it's our new modern application for virtual events. Of course, we want to continue to tell the most important stories and cover all the key people making it happen. Submit. Thank you for coming on. This is the Cube. Thanks for watching

>> Announcer: Live from Las Vegas it's theCUBE covering Veritas Vision 2017. Brought to you by Veritas. (upbeat techno music) >> Everybody this is theCUBE, the leader in live tech coverage. And we're here covering Veritas Vision. The hashtag is Vtas, v-t-a-s vision. Little bit of a funny hashtag so make sure you get that one right if you want to follow all of the action. I'm Dave Vellante with my co-host this week Stu Miniman. Michelle VanAmburg is here. She's the Director of Global Alliances for Veritas. And she's joined by Daniel Witteveen who is the Vice President of Global Portfolio Resiliency Services at IBM. Folks, thanks for coming on theCUBE. >> Thanks for having us. >> Thank you for having us. >> Michelle, let's start with you. Alliances are a fundamental component of Veritas' strategy. You got to make friends with a lot of different people. What's your general philosophy around alliances? Let's start there. >> Yeah, well specially with IBM, we've had a long term alliance starting back in 2004, around backup and managed services. It's evolved into a very strategic alliance with IBM providing both internal IT support to migrate our key applications into their Bluemix and IBM cloud infrastructure. And then also, evolving the managed service around backup strategically moving into the cloud. We announced something in March to work on backup in the cloud with IBM as part of their Bluemix services. So, each and every partner in alliances has specific strengths and weaknesses. And I think with IBM we're maximizing our partnership around their strengths and that's the services and their play in the enterprise market. We both have about 86% overlap among those customers. >> So, I mean, this is interesting, Daniel, I mean IBM big technology company, huge product portfolio, some of the products competitive with Veritas, but you're part of the services organization so you've got to have the customer's interest first. You guys are sort of technology agnostic generally as a services professional. So, what's your philosophy with regard, maybe I just laid it out, but with regards specifically to data protection and back up? >> So, you said exactly right. We measure ourselves against the business outcomes for our clients. And that truly is vendor agnostic. But when you take a partnership like Veritas, and if you saw the keynotes this morning, they were talking about the leader in the Magic Quadrant for the last several years. IBM's also been the leader in resiliency and in security. So, that's an unparalleled partnership that you can't get from anywhere else. You've got a services firm that can take their software, provide a high-valued outcome to their clients, our clients or mutual clients, and provide it in the cloud. And that could be our cloud, that could be another provider's cloud. Very significant for our clients. >> So, every time we go to these shows you hear about digital transformation. And it's an important topic but sometimes putting meat on the bones is hard. So, let's try to do that. I presume you're hearing this same thing from your joint customers. We got to become a digital business. You hear that from the top. So, what does that mean to your customers? What does it mean to become a digital business? >> So, for me I think a lot of people say that in the context of a one time event. We have to go through digital transformation. >> Voilà! >> Yeah, or suddenly, "Whoo-hoo! We're there!" (laughter) And that's a big, wide definition of what that could mean. I think it's continual transformation. It's innovation. That's a buzz word to me that says, okay, yeah this creates the conversation that's a door opener. But we really have to talk about evolving transformation, cognitive learning, using IBM Watson, always making us better. It's not laying out here's what we're doing and walk away. It has to be continual. >> Can you add anything to that, Michelle? What are your thoughts on digital? We think digital means data. >> Michelle: Mmm-hmm. >> You guys, all we heard this morning is how you're the sort of center of the data universe. What are you hearing from customers on digital? >> Well, I think we're all, including us, Veritas internally struggling with the same thing, right? How do you get there? How do you save cost over time? And how do you keep your business running with all the governance and compliance regulations that are coming down, like GDPR? So, there are a lot of challenges coming out of a lot of these organizations. And I think it takes not only somebody that's the leader in technology, like Veritas, but then it takes somebody who's the system integrator who is monitoring the outcomes for their customers over time. If you look at all the large accounts that IBM manages, we have a huge play for Veritas technology and use of those products in those accounts. So, I think it takes more than just a point, product, or a point in time like Daniel mentioned. It really takes an evolution over time, and a solid plan that can be, again, flexible as GDPR regulations come down the pike. How do we move with the times? How do we manage those outcomes for our customers to be cost effective so that we can keep their business and grow it too. >> Daniel, did you want to comment on that one? >> Yeah, I mean, we mentioned GDPR which I think is kind of the biggest event. It's going to be the Y2K of 2018, right? It's massively significant. But if you throw that under the compliance bucket, we really think about what does that mean for our clients and protecting our clients with those compliance requirements. When you look at IBM and Veritas, our partnership has extensively talked about, Bill Coleman was talking this morning about meeting with the two largest banks. IBM covers 75% of the top 35 banks. We get regulation. That's our job. Customers look for us to lead that example. We have 80% of the Fortune 100 across multiple industries. So, when you combine these technologies together, you combine that regulation overlay, which we have to know not just for one customer but across all of our customers. It's really unmatched. >> So, in addition to kind of the governance piece, what about security? It's been something in my whole career. Used to get a lot of lip service. Today, it's board level discussion. Everybody's handling it. Resiliency services have to believe covers that as well as kind of traditional BCDR type activity. >> Yeah, we define that under cyber resiliency. And that is really going from everything from direct protection all the way to outage to recovery. And I think a lot of customers are struggling with that. We did a study with Ponemon Institute back in May, and 68 of their respondents said they lacked actually reliable foundational way to recover against a cyber attack. And when you really think about it everyone's been in the news over the last several months. You have to respond to that very differently than a hurricane outage or what people think of a disaster recovery which I struggle with that name because it's really any kind of outage. So, cyber resiliency is key. In fact, we have a session tomorrow at 12:30 specifically, talking about our combined approach against cyber resiliency starting from threat protection deterrence. But more importantly when the outage occurs how do you make sure you're actively responding? You're not out for hours, days, and months. You're really, truly out for minutes. >> Michelle, anything around ransomware, the cyber resiliency piece? How does Veritas look at partnering with companies like IBM for these solutions? >> Since we've broken off from Symantec, and we had a lot of security and data protection that was combined, we really look for our partners, like IBM, to to provide a lot of that security specific services around our product. So, one of the things that Daniel had developed, is the cyber resilience offer that we are looking to our joint customers to provide specifically a short engagement around that to help them. So, really, we are starting to look to our partners to offer that security service. >> So, I'm a little bit of an industry historian, mainly cause I'm old. (Michelle laughs) And so, when I look back 1983 when Veritas got started, and we heard today that Veritas has been a leader in the Magic Quadrant for 15 years. So, you had the the PC era, which changed backup when the pendulum swung from mainframe mini to PC. And then obviously clients server evolved that and then virtualization business change that. So, you saw backup evolve, and obviously Veritas stayed with that as a leader throughout. Now, we come to digital business and cloud. And when you think of digital business and cloud, I'm interested in the impacts that it's having on data protection. I think of distributed data, analytics, edge computing, the cloud itself. Whole different set of technologies and processes and skillsets to manage data protection. So, I wonder if you could bring that back to the customer. How are they re-architecting their businesses around, specifically, the data protection side of the business. >> So, I think the first, and we saw this with virtualization we saw it with storage area networks. And we saw it with cloud. The first instinct and the first sales point is well, then I don't need DR. I don't need backup. And it's kind of this false sense of or "I have an SLA, so I'm covered." Which an SLA is just a penalty. It doesn't mean you're covered at all, right? So, we've seen that at every kind of hurdle in our business. But then what we've seen, when you saw storage and virtualization is probably a perfect example, When it's more consolidated, your risk is a lot more condensed. So, before you could have one server outage. You might never have known. But now you have an entire virtual system SAN or even a cloud. We've seen that in the press just being out. It's much more significant. So, customers are taking a lot more serious look at how they're architecting those solutions, making sure their not reliant on one of those consolidated entities. Do I have my data in the cloud? Do I have a way to have that data out of the cloud? Can I run in this cloud, maybe that cloud, on-prem, hybrid IT? Hear that a lot from IBM. But how can I diversify? Which is a very different way of architecting solutions when you've just had client server. >> Stu: Right. Okay, anything you could add to that Michelle, just in terms of what customers are asking you? And specifically, how it might relate to some of your partnerships. >> Michelle: Yeah. >> Maybe, no offense, but broader even than IBM. >> Yeah, from a broader perspective we're seeing all the cloud providers in the market, and we're partnering with all of them at Veritas. Each one of them has their strength. And if you look across our partners, and I've been integral in some of our accounts. Some of them are doing things just as simple as snapshots. They don't have a way to index. They have a hard time recovering. Things like that. Our customers are really on that high end. So, as Daniel mentioned, we have a lot of overlap in the Fortune 1,000. And they are looking for ways to recover their data like they did on-prem but they're moving to the cloud. So, our solutions together, with IBM, are really those heavy-duty enterprise solutions that allow them to have the data recovery, same times RTO, RPO. And also, the disaster recovery programs and the security around those high-end applications that have all the compliance around them. So, from my point of view, IBM's a key partner in that space to allow those highly regulated customers to have the same type of data protection. >> So historically, you guys are in the insurance business. It's a great business, no question. And I always ask, is data an asset or a liability? And the answer is both. But if you had the value pie. Clearly, the pendulum is swinging and things are evolving. Is data still more of a liability in your world than it is an asset? >> Daniel: So, our CEO said it best, data is the new natural resource. So, data is the number one important thing within the customer environment. Without it you don't have intelligence. You don't have machine learning. You don't have predictive outage. You don't have sales force automation. All that is reliant on data. So, it's more critical. Where you could argue it becomes a liability is when you have to be compliant and you have to have that data for the next number of years. A lot of people like to promote backup success. Well, that's nice if you can back it up but can you restore it? Can you make that data active? So, that's where it can be treated as a liability but there's no way I would say it's a liability over an asset. It's absolutely the number one asset in a business. >> Stu: You would Agree, I presume? >> Yeah, I would agree. And we always use the iceberg analogy. The data that you really need is just at the tip of the iceberg above the water. And then you have all this data hidden under the water. How do you make that secure, and understand what you have? And so, I think the analytics, and some of the data protection, and the tiering, the understanding what you readily need available versus what can be archived and stored in the lower cost tier is really important. >> So, where do you guys want to take this relationship? When you sit down ... Give us a little inside baseball here. Where do you see this going over the next 18 to 24 months? >> Daniel: It's only going to be stronger. A lot of conversations in the works about doing a lot more strategic relationships together. I'll leave it as that. We've been very healthy partners for over 11 years, you mentioned 2004 timeframe, I think. We have folks on my development team that are a integral part of Veritas' product offering. Very important to the feedback loop. And vice versa the managed service. So, I think that's going to get tighter. I think that's going to expand just beyond backup. And I'm really looking forward to those possibilities. >> Yep. >> Michelle? So, I'm really excited about our cloud partnership that we announced in March. I see IBM as a key to allowing Veritas to leap into that market, and to provide the enterprise strength solutions. And just really excited about our future. >> Stu: Great. All right, well thank you very much. Good luck with your partnership. >> Michelle: Thank you. >> Daniel: Excellent. >> All right, keep it right there, everybody. We'll be back with our next guest. We're live at Veritas Vision 2017 in Las Vegas. This is theCUBE. Be right back. >> Daniel: Excellent >> Michelle: Awesome, guys. (upbeat techno music)

>> Announcer: Live from New York City. It's theCUBE. Covering Lenovo Transform 2017. Brought to you by Lenovo. >> Welcome back to theCUBE's coverage of Lenovo Transform. I'm your host Rebecca Knight, along with my co-host Stu Miniman. We are joined by Kamran Amini. He is the General Manager, Server and Storage Business Unit, here at Lenovo. Thanks so much. >> Thank you for having me. >> Welcome back to theCUBE, I should say. (Kamran laughs) >> Thank you. >> So today we've heard a lot about the largest product portfolio data storage product portfolio launch in Lenovo history. >> Kamran: Umhmm. Can you put this in perspective for us, though, in terms of the customer and why is this meaningful for the customer? >> Absolutely, so one of the key things with the entire Think System Portfolio, we started three years ago. A clean sheet and really listening to our clients, listening to our channel partner. What are their challenges with IT? Outside of wanting performance and everything else? How can we simplify their experience, from the buying experience, to life cycle management of the products, simplify part purchases. So a couple of things we did was common building blocks. So, the majority of the Think System Server Portfolio have common power supplies that go across. One of the things customer asked us was you have too many power supplies, right? I'm buying a part, I have to decide which server you have, and what form factor goes in. Now, we have one common across the board. Same thing with management software, we provide one look, and one feel experience for our clients. The whole philosophy of our Think System was start clean, deliver what customers are really valuing around IT and be able to help accelerate and future-proof the technology for them. As they're evolving their workloads and applications, as they're moving to Flash technologies, how do we provide that flexibility? And that's really the foundation of the Think System. >> Yeah, so, Kamran, there was discussion in the keynote this morning, it's about harnessing the intelligence revolution and AI. Can you connect the dots for us as to how that fits into servers, and specifically this launch the new Skylake Chipset? >> Absolutely, so, of course with the new scalable xenon processor, you're getting tremendous increase in performance. And I think when you look at AI and machine learning, there's the aspect that requires acceleration applications, and there's still computing happening on the CPU aspect of the AI machine learning. And you're seeing more the analytics and big data coming into this play. So that's really where we're leveraging the foundational excellence we have with our analytic platforms, and also looking at big data. And bring in with the accelerator's platforms to drive that end to end view around artificial intelligence. And that's where the Think System Portfolio is really shining. It's bringing that end to end view from a client perspective for all their purpose to drive the AI platform environments. >> One of the things we keep hearing about is Lenovo being number one in customer satisfaction, number one in reliability. Can you talk about how you make that happen? How do you ensure that you are as reliable as you come to be known to be? >> Yeah, so one of the things with Lenovo is we listen. If you're not listening to your clients and understand where they're going, what their challenges are, it's hard to be able to adapt. And one of the things you'll see from a reliability perspective, we believe even as you think about the future of software defined, that foundational server is going to be, it has to be reliable. You're getting away from the legacy thinking of redundancy of infrastructure to running everything on a server base. So now that server has to truly deliver five nines. So, we design stuff. A lot of people think x86 is a commodity space. My background is engineering, and I think you can do different styles of engineering. And our engineer team is a great team that thinks about how do we take the Intel processor technology, build a platform around it to be able to have the highest reliability? And, of course, with the highest reliability, it also leads to customers basically having gooder customer engagement, customer satisfaction. So they sort of go hand in hand, right? And that's where we try to continue drive innovation. As you heard from Curt in the main tent, our purpose is not to let go of that, but figure out how we can continuously drive improvement in our reliability. Ideally, I like to have six nines if I can in the server one day. But that's the foundation from an engineering aspect, and innovation that's leading into the actual platforms and offerings for our clients. >> Kamran, can you bring us inside what your customers are asking for? You talked about massive amounts of data, there's so many choices out there, I hear. You look in the AI space, it's like, oh, there's the public cloud with their GPUs and TPUs, versus moving to more distributed architectures internally. What kind of feedback are you getting from your customers, and what are they excited about that they can do this year that they couldn't do next? >> So I think a lot of >> Stu: Last. >> customers will love to have purpose-driven platforms. And I think, if you look at the market today, there's plenty of servers out there by a variety of different vendors. The challenge for customers is some customers are very price performance sensitive. And you know, sometimes they get siloed into I have to buy the expensive thing, even though my application might not require Flash, might not require GPUs. So if you look at the Think System Portfolio, we really focused on the segments of clients. All the way from SMB to large enterprises. And how are they actually using it? What's their purchasing philosophy? And build the platforms that accommodate that segment, plus the capabilities inside those platforms. So you'll see, for example, our mainstream two socket server where it has full capability with GPU, NVMe capabilities, future Intel technology built-in, versus we have our value line really focused around customers that are looking for really SMB environment. Give me that price performance that fits my budget friendly environment. And then you also see places like dense optimized platforms, really driving innovation around our HPC but also being leveraged around hyper-converg platforms and general purpose consolidations. And finally, we do believe that the big data analytics platforms are going to be mainstream one day. They're sitting in your backend of your center running your mission critical but they're becoming more and more relevant today. As you see AI happening. More and more stuff is going to go on those backend system to drive the analytics. And that's where we believe we're positioned very well in the portfolio we're delivering across the 14 servers. >> So what will it take for big data to really become an important part of they way companies do business. There is a deluge of data right now. And we're still trying to figure out how to, what to do with it, how to slice it and dice it. And how to, how to make improvements based on it. What will it take do you think? >> I think you're seeing a lot of ISP that we're doing traditionally. Traditional analytics are bring big data into the analytics. So that's their first movement, that the ISPs are merging those two environments together. The next thing is for people like Lenovo be able to deliver the infrastructure platform that actually can leverage that environment. Big data requires a lot of storage. And you'll see in our next gen analytics system, we almost quadruple the amount of storage you have in that platform because we know more and more is going to go from a storage perspective, and analytic and memory database environment. So it's really looking how the ISPs are looking in this challenge and building the right platform that actually leverage those those ISP solutions. >> Kamran, I loved how you were talking about some of the applications because when I talk to customers, it's that spectrum of application they have that they're struggling. Everything from building new microservices-based architecture to I've got my ERP solution, sitting back there. How do you help customers with that portfolio to modernize their infrastructure, optimize what they're doing and stay agile. >> Well, part of that is actually our service organization. It's really sitting and listening to understanding where the customer wants to go. Sometimes I think a lot of companies approach customers by saying here's what I have and try and force feed that offering into the customer environment. We actually are leveraging our professional service and consulting services to get a better idea. What does the customer want to do today but moving into tomorrow. And what platform or solutions will actually benefit the client from server storage or networking or even our engineers solutions that we have at Lenovo. >> When you're thinking about, when you're hearing the customer feedback, and trying to anticipate what the customer needs tomorrow, is there any area that worries you in particular that the customer may be have have a blind spot for? It could be about data storage or it could be about internet of things or cloud computing. What keeps you up at night? >> I think a lot of it is, to be personal, is around cloud. I think cloud initially provides a value prop around, for public cloud economics. But I think what we're seeing is a lot of customers have that philosophy of clouds but I think as they start looking into the actual deployment and how you manage that environment, the economics evolves. So what keeps me awake is, making sure that clients understand our story. Understand what Lenovo can bring into the table both for what their traditional IT needs, but also their next gen IT. Plus have establish for them a private cloud environment and tie into hybrid environment as well. We want to make sure our clients understand and drive the best value. One of things I always tell my clients is, look, if I could sell you one less server, but you're getting more benefit, I'm here to consult you in that way. I want to make sure the result that you see is what we want to achieve. And that's what we're focused on. And to me, that's what keeps me up is making sure our clients understand the journey as they want to go to cloud and what's the right path for them. >> Kamran, it's been about three years since Lenovo acquired the x86 business. Give us, as you look back, what surprised you in those three years. The keynote this morning, Y Y said, we wouldn't be able to think 18 months ago where we are today. So, what's changed the most, what surprised you the most about the journey with x86? >> So I did come from system X as part of the acquisition. And to be very frank, I think one of things that was stated in the keynote today was, the agility that Lenovo acts on. It's okay to make a mistake. As long as you quickly react and fix the mistake. And I think what I've noticed in the three years I've been here Lenovo now is, one, the culture is very flat. Everyone is empowered to make a decision. There's no hierarchical decision making. Of course, there's always the president. There's always the CEO. But people are empowered to make decisions that's beneficial for our clients. And we're seeing a huge focus around customer experience. It's not just a organizationally, it's not just a individual KPIs. It's really looking from end to end of our business. How can we transform our customer experience? To drive a better experience for our customers. And I think that's, with Lenovo being that agile of a company. I had great service years at, 17 years at IBM, very successful. But because of the size of the company and the different structures of the company, a lot of clients didn't feel we could adjust their needs immediately. And I think with Lenovo you're seeing a lot more faster agility. From our supply chain to how customers get quotes. From a product perspective and support. Those are all the things that I see slightly different, and we've been transforming as we've been going. Enhancing those capabilities. And we've learned through our mistakes through the last three years. It hasn't been any mistakes that we haven't came out with. But we constantly learn and try enhance as we go forward. And I'm very excited going into this year. Especially with these announcements that we're going to be driving a lot more enhancements and how our customers see Lenovo as a data center provider. >> A lot have been made about the fact that this is, Thinkpad and x86 25th year anniversary. Which seems amazing, really. >> Mmhmm. >> Now that these products are in their sort of adulthood so to speak, what do you think we should expect in terms performance and in terms of approach. Just because they are now, they've fully worked out the kinks of the youth and their adolescence. >> Yeah so if you look at, for example, in the server business, and the server portfolio Think System, from just gen to gen, literally, this is three years ago, two three years ago. You're going to see customers be able to run 150% more VDI, users. And that drives a better economics, dollar per user. So just from a gen to gen you're seeing tremendous platform improvements. And that's where I think, we're going to see customers. Customer, I think are going to see driving more and faster applications. I think we're going to see huge adoption of Flash within the server technology. And therefore, I think you're going to see where software define and server generation we're delivering come together very nicely. Where we believe that, my personal belief, you're going to see a lot more customers moving away from a traditional storage array to now software defined or all Flash software define environments. Where they're leveraging a commodity server base with huge amount of performance capabilities and software on top to deliver the business value. >> Kamran, where do you think we're going to be, next year but then also 10 years down the road. As you talk about the pace of business, change is incredible aren't they now. Can you predict a little bit into the future? (Kamran laughs) >> About what we're going to, I know it's a tough one. >> Kamran: I wish I could predict. I think you're going to see a lot of different applications coming together. I think you're going to see AI being a key factor to drive and generate a lot of information with machine learning. And being able to take that information and figure out how you drive business agility. I think you're going to see retail driving AI aggressively. I think you're already seeing automotive industry driving machine learning and everything else into their cars. So for us, it's very exciting as an IT provider. Were we see an evolution happening and eventually another revolution happening in IT, I think in the next 10, 15 years. You're going to see I think more dense platforms because you're going to drive more density with the nut form factor. I think you're going to see a lot more powerful systems. And I think you're going to see software becoming more relevant. And I think that the legacy status goal is going to eventually be gone I think. I think legacy, 10 years from now, legacy is going to be considered software defined I believe. >> Great. Bold predictions. (Rebecca laughs) >> Predictions. (Kamran laughs) >> Well, Kamran Amini, thank you so much for joining us. It's always a pleasure having you on the show. >> Kamran: Thank you for having me. >> I'm Rebecca Knight for Stu Miniman. We will have more from theCUBE at Lenovo Transform just after this. (upbeat music)