(upbeat music) >> Hello friends and welcome back to theCUBE's Live coverage of AWS re:Invent 2022 from the Venetian Expo in Vegas, baby. This show is absolutely packed. Lisa Martin with Dave Vellante, Dave this is day two, but really full day one of our wall to wall coverage on theCUBE. We've had great conversations the last half day this morning already, we've been talking with a lot of companies, a lot of Amazonians and some Amazonians that have left and gone on to interesting more things, which is what we're going to talk about next. >> Well, I'm excited about this segment because it's a really interesting space. You've got a search company who's gotten into observability and security and through our ETR partner our research, we do quarterly research and Elastic off the charts. Obviously they're the public company, so you can see how well they're doing. But the spending momentum on this platform is very, very strong and it has been consistently for quite some time. So really excited to learn more. >> The voice of the customer speaking loudly, from Elastic, its Chief Product Officer joins us, Ken Exner. Ken, welcome to the program. Hi, thank you, good to be here. >> Dave Vellante: Hey Ken. >> So a lot of us know about Elastic from Elastic Search but it's so much more than that these days. Talk about Elastic, what's going on now? What's the current product strategy? What's your vision? >> Yeah. So people know Elastic from the ELK Stack, you know Elastic Search, Logstash, Kibana. Very, very popular open source projects. They've been used by millions of developers for years and years. But one of the things that we started noticing over the years is that people were using it for all kinds of different use cases beyond just traditional search. So people started using Elastic Search to search through operational data, search through logs, search through all kinds of other types of data just to find different answers. And what we started realizing is the customers were taking us into different spaces. They took us into log analytics they started building log management solutions. And we said, cool, we can actually help these customers by providing solutions that already do this for them. So it took us into observability, they took us into security, and we started building solutions for security and observability based on what customers were starting to do with the platform. So customers can still use the platform for any number of different use cases for how do you get answers added data or they can use our pre-built packaged solutions for observability and security. >> So you were a longtime Amazonian. >> I was. I was. >> Talk a little bit about some of the things that you did there and what attracted you to Elastic? 'Cause it's only been a couple months, right? >> I've been here three months, I think three months as of yesterday. And I was at AWS for 16 years. So I was there a long, long time. I was there pretty much from the beginning. I was hired as one of the first product managers in AWS. Adam Selipsky hired me. And it was a great run. I had a ton of fun, I learned a lot. But you know, after 16 years I was kind of itching to do something new and it was going to take something special because I had a great gig and enjoyed the team at AWS. But I saw in Elastic sort of a great foundational technology they had a lot of momentum, a huge community behind it. I saw the business opportunity where they were going. I saw, you know the business opportunity of observability and security. These are massive industries with tons of business problems. Customers are excited about trying to get more answers out of data about their operational environment. And I saw, you know, that customers were struggling with their operating environments and things were becoming increasingly complicated. We used to talk in AWS about, you know how customers want to move from monolithic applications to monoliths, but one of the secrets was that things were increasingly complicated. Suddenly people had all these different microservices they had all these different managed services and their operating environment got complicated became this constellation of different systems, all emitting data. So companies like Elastic were helping people find answers in that data, find the problems with their systems so helping tame that complexity. So I saw that opportunity and I said I want to jump on that. Great foundational technology, good community and building solutions that actually helped solve real problems. >> Right. >> So, before you joined you probably looked back, and said, let think about the market, what's happening in the market space. What were the big trends that you saw that sort of informed your decision? >> Well, just sort of the mountain of data that was sort of emerging. Adam Selipsky in his talk this morning began by talking about how data is just multiplying constant. And I saw this, I saw how much data businesses were drowning in. Operational data, security data. You know, if you're trying to secure your business you have all these different endpoints you have all these different devices, you have different systems that you need to monitor all tons of data. And companies like Elastic were helping companies sort of manage that complexity, helping them find answers in that. So, when you're trying to track intruders or trying to track you know, malicious activity, there's a ton of different systems you need to pay attention to. And you know, there's a bunch of data. It's different devices, laptops and phone devices and stuff that you need to pay attention to. And you find correlations across that to figure out what is going on in your network, what is going on in your business. And that was exciting to me. This is a company sort of tackling one of the hardest problems which is helping you understand your operating environment, helping you understand and secure your business. >> So everybody's getting into observability. >> Yep. >> Right, it's a very crowded space right now. First of all, you know it's like overnight it just became the hottest thing going. VCs were throwing money at it. Why was that and how were you guys different? >> Well, we began by focusing on log analytics because that was the core of what we were doing. But customers started using it beyond log analytics and started using it for APM and started using it for performance data. And what we realized is that we could do all this for customers. So we ended up, sort of overnight over the course of three years building that a complete observe observability suite. So you can do APM, you can do profiling, you can do tracing, sort of distributed tracing, you can do synthetic monitoring everything you want to do, wheel user wondering. >> Metrics? >> All of it, metrics, all of it. And you can use the same system for this. So this was sort of a powerful concept, not only is it the best in leading log system, it also provides everything you need for complete observability. And because it's based on this open platform you can extend it to a number of different scenarios. So this is important, a lot of the different observability companies provide you something that's sort of packaged and as long as you're trying to do what it wants to support, it's great. But with Elastic, you have this flexible data architecture that you can use for anything. So companies use it to monitor assembly lines, they use it to monitor dish networks, for example use it to not only manage their fleet of servers they also use it to manage all their devices. So 25 million desktop devices. So, you know, observability systems like that that can do a number of different scenarios, I think that's a powerful thing. It's not just about how do you manage your servers how do you manage the things that are simple. It's how do you manage anything? How do you get observability into anything. >> Multiple use cases. >> Sorry, when you say complete, okay you talked about all the different APM, log analytics tracing, metrics, and also end-to-end. >> Ken Exner: End-to-end, yeah. >> Could you talk about that component of complete? >> So, if you're trying to find an issue like you have some metric that goes into alarm. You want to have a metric system that has alarming. Once that metric goes in alarm you're going to want to dig into your log. So you're going to want it to take you to the area of your logs that has that issue. Once you gets to there, you're going to want to find the trace ID that takes you to your traces and looks at sort of profiling, distributed tracing information. So a system that can do all of that end-to-end is a powerful solution. So it not only helps you track things end-to-end across the different signals that you're monitoring, but it actually helps you remediate more quickly. And the other thing that Elastic does that is unique is a lot of ML in this. So not only helping you find the information but surfacing things before you even know of them. So anomaly detection for example, helps you know about something before you even realize that there was an issue. So you should pay attention to this because it's anomalous. So a lot of systems help you find something if you know what to look for. But we're trying to help you not only find the things that you know to look for, but help you find the things that you didn't even think to know about. >> And it's fair to say one of your differentiators is you're open, open source. I mean, maybe talk about the ELK stack a little bit and how that plays. >> Yeah, well, so the great thing about this is we've extended that openness to both security and to observability. An example of this on the security side is all the detection rules that you use for looking for intrusion all the detection rules are open source and there's an entire community around this. So if you wanted to create a detection rule you can publish an open source, there's a bunch in GitHub you can benefit from what the community is doing as well. So in the world of security you want to be supported by the entire community, everyone looking for the same kind of issues. And there's an entire community around Elastic that is helping support these detection rules. So that approach, you know wanting to focus on community is differentiating for us. Not just, we got you covered as long you use things from us you can use it from the entire community. >> Well there implies the name Elastic. >> Yeah >> Talk a little bit about the influence that the customer has in the product roadmap and the direction. You've talked a little bit in the beginning about customers were leading us in different directions. It sounds very Amazonian in terms of following the customers where they go. >> It does, it actually does, it was one of the things that resonated for me personally is the journey that Elastic took to observability and security was customer led. So, we started looking at what customers were doing and realized that they were taking us into log analytics they were taking us into APM, they were taking us into these different solutions, and yeah, it is an Amazonian thing, so it resonated for me personally. And they're going to continue taking us in new places. Like we love seeing all the novel things that customers do with the platform and it's sort of one of the hallmarks of a great platform is you can have all kinds of novel things that, novel use cases for how people use your platform and we'll continue to see things and we may get taken into other solutions as well as we start seeing things emerge, like common patterns. But for now we're really excited about security and observability. >> So what do you see, so security's a big space, right? >> Yep. >> You see the optiv taxonomy and it makes your eyes bleed 'cause there's so many tools in there. Where do you fit in that taxonomy? How do you see and think about the security space and the opportunity for your customers? >> Yeah, so we began with logs in the security space as well. So SIEM, which is intrusion detection is based on aggregating a bunch of logs and helping you do threat hunting on those logs. So looking for patterns of malicious behavior or intrusion. So we started there and we did both detections as well as just ad hoc threat hunting. But then we started expanding into endpoint protection. So if we were going to have agents on all these different devices they were gathering logs, what if we also started providing remediation. So if you had malicious activity that was happening on one of the servers, don't just grab the information quarantine it, isolate it. So that took us into sort of endpoint protection or XDR. And then beyond that, we recently got into cloud security as well. So similar to observability, we started with logs but expanded to a full suite so that you can do everything. You can have both endpoint protection, you can have cloud security, all of it from one solution. >> Security is a very crowded market as well. What's your superpower? >> Ken Exner: What's our super power? >> Yeah. >> I think it, a lot of it is just the openness. It's the open platform, there's the community around it. People know and love the, the Elastic Search ELK stack and use it, we go into businesses all the time and they're familiar, their security engineers are using our product for searching through logs. So they're familiar with the product already and the community behind it. So they were excited about being able to use detection rules from other businesses and stay on top of that and be part of that community. The transparency of that is important to the customers. So if you're trying to be the most secure place, the most secure business, you want to basically invest in a community that's going to support that and not be alone in that. >> Right, absolutely, so much that rides on that. Favorite customer example that you think really articulates the value of Elastic, its openness, its transparency. >> Well, there's a customer Dish Media Dish Networks that's going to present here at re:Invent tomorrow at 1:45 at Mandalay Bay. I'm excited about their example because they use it to manage, I think it's 10 billion records a day across 25 million devices. So it illustrates the scale that we can support for managing observability for a company but also just sort of the unique use cases. We can use this for set top boxes for all their customers and they can track the performance that those customers are having. It's a unique case that a lot of vendors couldn't support but we can support because of the openness of the platform, the open data architecture that we have. So I think it illustrates the scale that we support, the elasticity, but also the openness of the data platform. >> Awesome and folks can catch that tomorrow, 1:45 PM at the Mandalay Bay. Last question for you, Ken, is you have a bumper sticker. >> Ken Exner: A bumper sticker? >> A bumper sticker you're going to put it on your fancy sexy new car and it's about elastic, what does it say? >> Helping you get answers out of data. So yeah. >> Love it, love it. Brilliant. >> Ken Exner: Thank you. >> Short and sweet. Ken, it's been a pleasure. >> It's been a pleasure being here, thank you. >> Thank you so much for sharing your journey with us as an Amazonian now into Elastic what Elastic is doing from a product perspective. We will keep our eyes peeled as Dave was saying. >> Ken Exner: Fantastic. >> The data show is really strong spending momentum so well done. >> Thank you very much, good to meet you. >> Our pleasure. For our guest and Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live enterprise and emerging tech coverage. (upbeat music)

(upbeat music) >> Dave Vellante: Okay. We're back with Mark Hill. who's the Director of IT Operations at Digital River. Mark. Welcome to the cube. Good to see you. Thanks for having me. I really appreciate it. >> Hey, tell us a little bit more about Digital River, people know you as a, a payment platform, you've got marketing expertise. How do you differentiate from other e-commerce platforms? >> Well, I don't think people realize it, but Digital River was founded about 27 years ago. Primarily as a one-stop shop for e-commerce right? And so we offered site development, hosting, order management, fraud, expert controls, tax, um, physical and digital fulfillment, as well as multilingual customer service, advanced reporting and email marketing campaigns, right? So it was really just kind of a broad base for e-commerce. People could just go there. Didn't have to worry about anything. What we found over time as e-commerce has matured, we've really pivoted to a more focused API offering, specializing in just our global seller services. And to us that means payment, fraud, tax, and compliance management. So our, our global footprint allows companies to outsource that risk management and expand their markets internationally, um very quickly. And with low cost of entry. >> Yeah. It's an awesome business. And, you know, to your point, you were founded way before there was such a thing as the modern cloud, and yet you're a cloud native business. >> Yeah. >> Which I think talks to the fact that, that incumbents can evolve. They can reinvent themselves from a technology perspective. I wonder if you could first paint a picture of, of how you use the cloud, you use AWS, you know, I'm sure you got S3 in there. Maybe we could talk about that a little bit. >> Yeah, exactly. So when I think of a cloud native business, you kind of go back to the history. Well, 27 years ago, there wasn't a cloud, right? There wasn't any public infrastructure. It was, we basically stood our own data center up in a warehouse. And so over our history, we've managed our own infrastructure and collocated data centers over time through acquisitions and just how things worked. You know those over 10 data centers globally. for us it was expensive, well from a software hardware perspective, as well as, you know, getting the operational teams and expertise up to up to speed too. So, and it was really difficult to maintain and ultimately not core to our business, right? Nowhere in our mission statement, does it say that we're our goal is to manage data centers? So, so about five years ago, we started the journey from our hosted into AWS. It was a hundred percent lift it and shift plan, and we were able to bleed that migration a little over two years, right. Amazon really just fit for us. It was a natural, a natural place for us to land and they made it really easy here for us to not to say it wasn't difficult, but, but once in the public cloud, we really adopted a cloud first vision. Meaning that we'll not only consume their infrastructure as the service, but we'll also purposely evaluate and migrate to software as a service. So I come from a database background. So an example would be migrating from self deployed and managed relational databases over to AWS RDS, relational database service. You know, you're able to utilize the backups, the standby and the patching tools. Automagically, you know, with a click of the button. And that's pretty cool. And so we moved away from the time consuming operational tasks and, and really put our resources into revenue and generate new products, you know, like pivoting to an API offering. I always like to say that we stopped being busy and started being productive. >> Ha ha. I love that. >> That's really what the cloud has done for us. >> Is that you mean by cloud native? I mean, being able to take advantage of those primitives and native API. So what does that mean for your business? >> Yeah, exactly. I think, well, the first step for us was just to consume the infrastructure right, in that, but now we're looking at targeted services that they have in there too. So, you know, we have our, our, our data stream of services. So log analytics, for example, we used to put it locally on the machine. Now we're just dumping into an S3 bucket and we're using Kinesis to consume that data, put it in Eastic and go from there. And none of the services are managed by Digital River. We're just utilizing the capabilities that AWS has there too. So. >> And as an e-commerce player, retail company, we were ever concerned about moving to AWS as a possible competitor, or did you look at other clouds? What can you tell us about that? >> Yeah. And, and so I think e-commerce has really matured, right? And so we, we got squeezed out by the Amazons of the world. It's just not something that we were doing, but we had really a good area of expertise with our global seller services. But so we evaluated Microsoft. We evaluated AWS as well as Google. And, you know, back when we did that, Microsoft was Windows-based. Google was just coming into the picture, really didn't fit for what we were doing, but Amazon was just a natural fit. So we made a business decision, right? It was financially really the best decision for us. And so we didn't really put our feelings into it, right? We just had to move forward and it's better than where we're at. And we've been delighted actually. >> Yeah. It makes sense. Best cloud, best, best tech. >> Yeah. >> Yeah. I want to talk about ChaosSearch. A lot of people describe it as a data lake for log analytics. Do you agree with that? You know, what does that, what does that even mean? >> Well, from, from our perspective, because they're self-managed solutions were costly and difficult to maintain, you know, we had older versions of self deployed using Splunk, other things like that, too. So over time, we made a conscious decision to limit our data retention in generally seven days. But in a lot of cases, it was zero. We just couldn't consume that, that log data because of the cost, intimidating in itself, because of this limit, you know, we've lost important data points use for incident triage, problem management, problem management, trending, and other things too. So ChaosSearch has offered us a manageable and cost-effective opportunity to store months, or even years of data that we can use for operations, as well as trending automation. And really the big thing that we're pushing into is an event driven architecture so that we can proactively manage our services. >> Yeah. You mentioned Elastic, I know I've talked to people who use the ELK Stack. They say you there's these exponential growth in the amount of data. So you have to cut it off at whatever. I think you said seven days or, or less you're saying, you're not finding that with, with ChaosSearch? >> Yeah. Yeah, exactly. And that was one of the huge benefits here too. So, you know, we were losing out if there was a lower priority incident, for example, and people didn't get to it until eight, nine days later. Well, all the breadcrumbs are gone. So it was really just kind of a best guess or the incident really wasn't resolved. We didn't find a root cause. >> Yeah. Like my video camera down there. My, you know, my other house, somebody breaks in and I don't find out for, for two weeks and then the video's gone. That kind of same thing. >> Yep So, so, so how do you, can you give us some more detail on how you use your data lake and ChaosSearch specifically? >> Yeah, yeah. Yep. And, and so there's, there's many different areas, but what we found is we were able to easily consolidate data from multiple regions, into a single pane of glass to our customers. So internally and externally, you know, it relieves us of that operational support for the data extract transformation load process, right? It offered us also a seamless transition for the users, who were familiar with ElasticSearch, right? It wasn't, it wasn't difficult to move over. And so all these are a lot of selling points, benefits. And, and so now that we have all this data that we're able to, to capture and utilize, it gives us an opportunity to use machine learning, predictive analysis. And like I said, you know, driving to an event driven architecture. >> Okay. >> So that's, that's really what it's offered. And it's, it's been a huge benefit. >> So you're saying that you can speak the language of Elastic. You don't have to move the data out of an S3 bucket and you can scale more easily. Is that right? >> Yeah, yeah, absolutely. And, so for us, just because we're running in multiple regions to drive more high availability, having that data available from multiple regions in a single pane of glass or a single way to utilize it, is a huge benefit as well. Just, you know, not to mention actually having the data. >> What was the initial catalyst to sort of rethink what you were doing with log analytics? Was it cost? Was it flexibility? Scale? >> There was, I think all of those went into it. One of the main drivers. So, so last year we had a huge project, so we have our ELK Stack and it's probably from a decade ago, right? And, you know, a version point oh two or something, you know, anyways, it's a very old, and we went through a whole project to get that upgraded and migrated over. And it was just, we found it impossible internally to do, right? And so this was a method for us to get out of that business, to get rid of the security risks, the support risk, and have a way for people to easily migrate over. And it was just a nightmare here, consolidating the data across regions. And so that was, that was a huge thing, but yeah, it was also been the cost, right? It was, we were finding it cheaper to use ChaosSearch and have more data available versus what we're doing currently in AWS. >> Got it. I wonder if you could, you could share maybe any stories that you have or examples that, that underscore the impact that this approach to analytics is having on your business, maybe your team's everyday activities, any, any metrics you can provide or even just anecdotal information. >> Yeah. Yeah. And, and I think, you know, one coming from an Oracle background here, so Digital River historically has been an Oracle shop, right? And we've been developing a reporting and analytics environment on Oracle and that's complicated and expensive, right? We had to use advance features in Oracle, like partitioning materialized views, and bring in other supporting software like Informatica, Hyperion, Sbase, right? And all of these required our large team with a wide set of expertise into these separate focus areas, right? And the amount of data that we were pushing at the ChaosSearch would simply have overwhelmed this legacy method for data analysis than a relational database, right? In that dimension, the human toll of, of the stress of supporting that Oracle environment, meant that a 24 by seven by 365 environment, you know, which requires little or no downtime. So, just that alone, it's a huge thing. So it's allowed us to break away from Oracle, it's allowed us to use new technologies that make sense to solve business solutions. >> I, you know, ChaosSearch is really interesting company to me. I'm sure like me, you see a lot of startups, I'm sure they're knocking on your door every day. And I always like to say, okay, where are they going after? Are they going after a big market? How are they getting product market fit? And it seems like ChaosSearch has really looked at, hard at log analytics and kind of maybe disrupting the ELK Stack. But I see, you know, other potential use cases, you know, beyond analyzing logs. I wonder if you agree, are there other use cases that you see in your future? >> Yeah, exactly. So I think there's, one area would be Splunk, for example, we have that here too. So we use Splunk versus, you know, flat file analysis or other ways to, to capture that data just because from a PCI perspective, it needs to be secured for our compliance and certification, right? So ChaosSearch allows us to do that. There's different types of authentication. Um, really a hodgepodge of authentication that we used in our old environment, but ChaosSearch has a more easily usable one, One that we could set up, one that can really segregate the data and allow us to satisfy our PCR requirements too. So, but Splunk, but I think really deprecating all of our ElasticSearch environments are homegrown ones, but then also taking a hard look at what we're doing with relational databases, right? 27 years ago, there was only relational databases; Oracle and Sequel Server. So we we've been logging into those types of databases and that's not, cost-effective, it's not supportable. And so really getting away from that and putting the data where it belongs and that was easily accessible in a secure environment and allowing us to, to push our business forward. >> Yep. When you say, where the data belongs, right? It sounds like you're putting it in the bit bucket, S3, leaving it there, because it's the the most cost-effective way to do it and then sort of adding value on top of it. That's, what's interesting about ChaosSearch to me. >> Yeah, exactly. Yup. Yup. Versus the high priced storage, you know, that you have to use for a relational database, you know, and not to mention that the standbys, the backups. So, you know, you're duplicating, triplicating all this data too in an expensive manner, so yeah. Yeah. >> Yeah. Copy. Create. Moving data around and it gets expensive. It's funny when you say about databases, it's true. But database used to be such a boring market. Now it's exploded. Then you had the whole no Sequel movement and Sequel, Sequel became the killer app. You know, it's like full circle, right? >> Yeah, exactly. >> Well, anyway, good stuff, Mark, really, really appreciate you coming on the Cube and, and sharing your perspectives. We'd love to have you back in the future. >> Oh yeah, no problem. Thanks for having me. I really appreciate it. (upbeat music) >> Okay. So that's a wrap. You know, we're seeing a new era in data and analytics. For example, we're moving from a world where data lives in a cloud object store and needs to be extracted, moved into a new data store, transformed, cleansed, structured into a schema, and then analyzed. This cumbersome and expensive process is being revolutionized by companies like ChaosSearch that leave the data in place and then interact with it in a multi-lingual fashion with tooling, that's familiar to analytic pros. You know, I see a lot of potential for this technology beyond just login analytics use cases, but that's a good place to start. You know, really, if I project out into the future, we see a trend of the global data mesh, really taking hold where a data warehouse or data hub or a data lake or an S3 bucket is just a discoverable node on that mesh. And that's governed by an automated computational processes. And I do see ChaosSearch as an enabler of this vision, you know, but for now, if you're struggling to scale with existing tools or you're forced to limit your attention because data is exploding at too rapid a pace, you might want to check these guys out. You can schedule a demo just by clicking the button on the site to do that. Or stop by the ChaosSearch booth at AWS Reinvent. The Cube is going to also be there. We'll have two sets, a hundred guests. I'm Dave Volante. You're watching the Cube, your leader in high-tech coverage.

(gentle music) >> Okay, we're back with Mark Hill who's the director of IT operations at Digital River. Mark, Welcome to "The Cube." Good to see you. >> Thanks for having me. I really appreciate it. >> Hey, tell us a little bit more about Digital River, people know you as a payment platform. >> You've got marketing expertise. >> Yeah. >> How do you differentiate from other e-commerce platforms? >> Well, I don't think people realize it, but Digital River was founded about 27 years ago primarily as a one-stop shop for e-commerce, right? And so we offered site development, hosting, order management, fraud, expert controls, tax, physical and digital fulfillment as well as multilingual customer service, advanced reporting and email marketing campaigns, right? So it was really just kind of a broad base for e-commerce. People could just go there. Didn't have to worry about anything. What we found over time as e-commerce has matured, we've really pivoted to a more focused API offering specializing in just a global seller services. And to us that means payment, fraud, tax and compliance management. So our global footprint allows companies to outsource that risk management and expand their markets internationally very quickly and with the low cost of entry. >> Yeah, it's an awesome business. And, you know, to your point, you were founded way before there was such a thing as the modern cloud, and yet you're a cloud native business. >> Yeah. >> Which I think talks to the fact that incumbents can evolve, they can reinvent themselves from a technology perspective. I wonder if you could first paint a picture of how you use the cloud, you use AWS, you know, I'm sure you got S3 in there. Maybe we could talk about that a little bit. >> Yeah, exactly. So when I think of a cloud native business, you kind of go back to the history. Well, 27 years ago, there wasn't a cloud, right? There wasn't any public infrastructure. We basically started our own data center up in a warehouse. And so over our history, we've managed our own infrastructure and co-located data centers over time through acquisitions and just how things works, you know, those are over 10 data centers globally for us. For us it was expensive, well from a software, hardware perspective, as well as, you know, getting the operational teams and expertise up to speed too. And it was really difficult to maintain and ultimately not core to our business, right? Nowhere in our mission statement does it say that our goal is to manage data centers. (laughing) So, about five years ago we started the journey from our host into AWS. It was a hundred percent lift and shift plan and we were able to complete that migration a little over two years, right? Amazon really just fit for us, it was a natural, a natural place for us to land in and they made it really easy here for us to, not to say it wasn't difficult, but once in the public cloud, we really adopted a cloud first vision, meaning that we'll not only consume their infrastructure as the service, but we'll also purposely evaluate and migrate to software as a service. So, I come from a database background. So an example would be migrating from self deployed and manage relational databases over to AWS RDS, relational database service. You know, you're able to utilize the backups, the standby and the patching tools auto magically, you know, with a click of a button. And that's pretty cool. And so we moved away from the time consuming operational task and really put our resources into revenue and generating the products, you know, like pivoting to an API offering. I always like to say that we stopped being busy and started being productive. (laughing) >> I love that. >> And that's really what the cloud has done for us. >> Is that what you mean by cloud native? I mean, being able to take advantage of those primitives and native API. So what does that mean for your business? >> Yeah, exactly. I think, well, the first step for us was just to consume the infrastructure, right? But now we're looking at targeted services that they have in there too. So, you know, we have our data stream of services. So log analytics, for example, we used to put it locally on the machine. Now we're just dumping into an S3 bucket the way you're using Kinesis to consume that data and put it in elastic and go from there. And none of the services are managed by Digital River. We're just realizing the capabilities that AWS has there too. >> And as an e-commerce player, retail company, were you ever concerned about moving to AWS as a possible competitor, or did you look at other clouds? What can you tell us about that? >> Yeah, and so, I think e-commerce is really mature, right? And so we got squeezed out by the Amazons of the world. It's just not something that we were doing, but we had really a good area of expertise with our global seller services. So we evaluated Microsoft, we evaluated AWS as well as Google and, you know, back when we did that, Microsoft was Windows-based. Google was just coming into the picture, really didn't fit for what we're doing, but Amazon was just a natural fit. So, we made a business decision, right? It was financially really the best decision for us. And so we didn't really put our feelings into it, right? We just had to move forward and it's better than where we're at and we've been delighted actually. >> Yeah, makes sense, best cloud, the best tech. >> Yeah. >> You know, I want to talk about Chaos Search. A lot of people describe it as a data lake for log analytics. Do you agree with that? You know, what does that even mean? >> Yeah, well, from our perspective because the self-managed solutions are costly and difficult to maintain. You know, we had older versions of self deployed using Splunk, other things like that too. So over time, we made a conscious decision to limit our data retention in generally seven days. But in a lot of cases, it was zero. We just couldn't consume that log data because of the cost, intimidating in itself, because of this limit, you know, we've lost important data points, use for incident triage problem management, trending and other things too. So, Chaos Search has offered us a manageable and cost-effective opportunity to store months or even years of data that we can use for operations as well as trending automation. And really the big thing that we're pushing into is in the event of an architecture so that we can proactively manage our services. >> Yeah, you mentioned elastic. So I know I've talked to people who use the Elk Stack. They say, yes, this is exponential growth in the amount of data. So you have to cut it off at whatever. I think you said seven days, >> Yeah. >> Or less, you're saying you're not finding that with Chaos Search? >> Yeah, yeah, exactly. And that was one of the huge benefits here too. So, you know, we we're losing out if there was, you know, a lower priority incident for example and people didn't get to it until eight, nine days later. Well, all the bread crumbs are gone. So it was really just kind of a best guess or the incident really wasn't resolved. We didn't find a root cause. >> Yeah, like my video camera's down you know, by your other house, is that when somebody breaks in, I don't find out for two weeks and then the video's gone, kind of like same thing. >> Yeah. >> So, how do you, can you give us some more detail on how you use your data lake and Chaos Search specifically? >> Yeah, yeah. Yep and so there's many different areas, but what we found is we were able to easily consolidate data from multiple regions into a single pane of glass to our customers. So internal and externally, you know, it really does serve that operational support for the data extract transformation load process, right? It offered us also a seamless transition for the users who were familiar with elastic search, right? It wasn't difficult to move over. And so all these are a lot of selling points benefits. And so now that we have all this data that we're able to capture and utilize, it gives us an opportunity to use machine learning, predictive analysis. And like I said, you know, driving to an event driven architecture. >> Okay. >> So that's really what is offered and it's been a huge benefit. >> So you're saying you can speak the language of elastic. You don't have to move the data out of an S3 bucket and you can scale more easily. Is that right? >> Yeah, yeah, absolutely. And it is so for us just because running in multiple regions to drive more high availability, having that data available from multiple regions in a single pane of glass or a single way to utilize it is a huge benefit as well, just to, you know, not to mention actually having the data. >> What was the initial catalyst to sort of rethink what you were doing with log analytics? Was it cost, was it flexibility scale? >> There was, I think all of those went into it. One of the main drivers, so last year we had a huge project, so we have our Elk Stack and it's probably from a decade ago, right? And, you know, a version point or two or something, you know, anyways, it's very old and we went through a whole project to get that upgraded and migrated over. And it was just, we found it impossible internally to do, right? And so this was a method for us to get out of that business, to get rid of the security risks and support risk and have a way for people to easily migrate over. And it was just a nightmare here consolidating the data across regions. And so that was a huge thing. But yeah, it has also been the cost, right? We're finding that cheaper to use Chaos Search and have more data available versus what we were doing currently in AWS. >> Got it, I wonder if you could share maybe any stories that you have or examples that underscore the impact that this approach to analytics, >> Yeah >> Is having on your business, maybe your team's everyday activities, any metrics you can provide, >> Yeah. >> Or even just anecdotal information? >> Yeah, yeah. And and I think, you know, one, coming from an Oracle background here, so Digital River historically has been an Oracle shop, right? And we've been developing a reporting and analytics environment on Oracle and that's complicated and expensive, right? We had to use advanced features in Oracle like partitioning materialized views and bringing other supporting software like Informatic, Hyperion, Essbase, right? And all of these require a large team with a wide set of expertise into the separate focus areas, right? And the amount of data that we were pushing at the KF search would simply have overwhelmed this legacy method for data analysis than a relational database, right? In that dimension, the human toll of the stress of supporting that Oracle environment than a 24 by seven by 365 environment, you know, which requires literal or no downtime. So just that alone, it was a huge thing. So, it's allowed us to break away from Oracle, it's allowed us to use new technologies that make sense to solve business solutions. >> You know, Chaos Search is just a really interesting company to me, I'm sure like me, you see a lot of startups. I'm sure they're knocking on your door every day. And I always like to say, "Okay, where are they going after? "Are they going after a big market? "How are they getting product market fit?" And it seems like Chaos Search has really looked that hard at log analytics and sort of maybe disrupting the Elk Stack. But I see, you know, other potential use cases, you know, beyond analyzing logs. I wonder if you agree, are there other use cases that you see in your future? >> Yeah, exactly. So, I think there's one area would be Splunk for example. We have that here too. So we use Splunk versus, you know, flat file analysis or other ways to capture that data just because from a PCI perspective, it needs to be secured for our compliance and certification, right? So Chaos Search allows us to do that. There's different types of authentication, really a hodgepodge of authentication that we used in our old environment, but Chaos Search has a more easily usable one, one that we could set up, one that can really segregate the data and allows to satisfy our PCR requirements too. But Splunk, I think really, deprecating all of our elastic search environments are homegrown ones, but then also taking a hard look at what we're doing with relational databases, right? 27 years ago, there was only relational databases, Oracle and SQL server. So we've been logging into those types of databases and that's not cost-effective, it's not supportable. And so really getting away from that and putting the data where it belongs and that is easily accessible in a secure environment and allowing us to push our business forward. >> And when you say where the data belongs, it sounds like you're putting it in the bit bucket S3, leaving it there, >> Yeah. >> And this is the most cost-effective way to do it and then sort of adding value on top of it. That's what's interesting about Chaos Search to me. >> Yeah, exactly, yup, yup versus the high price storage, you know, that you have to use for a relational database, you know, and not to mention the standbys, the backups. So, you know, you're duplicating, triplicating all this data in here too in expensive manner. So yeah. >> Yeah, copy creating, moving data around and it gets expensive. It's funny when you say about databases, it's true. But database used to be such a boring market now it's exploded. Then you had the whole no SQL movement and SQL became the killer app, you know, it's like full circle. (laughing) >> Yeah, yeah, exactly. >> Well, anyway, good stuff Mark, really, I really appreciate you coming on "The Cube" and sharing your perspectives. We'd love to have you back in the future. >> Oh yeah, yeah, no problem. Thanks for having me. I really appreciate it. >> Yeah, our pleasure. Okay, in a moment, I'll have some closing thoughts on getting more value out of your growing data lakes. You're watching "The Cube," you're leader in high-tech coverage. (gentle music)

(bright upbeat music) >> Hello everyone, and welcome to this exclusive Cube Conversation. We have the pleasure today to welcome, Wim Coekaerts, senior vice president of software development at Oracle. Wim, it's good to see you. How you been, sir? >> Good, it's been a while since we last talked but I'm excited to be here, as always. >> It was during COVID though and so I hope to see you face to face soon. But so Wim, since the Barron's Article declared Oracle a Cloud giant, we've really been sort of paying attention and amping up our coverage of Oracle and asking a lot of questions like, is Oracle really a Cloud giant? And I'll say this, we've always stressed that Oracle invests in R&D and of course there's a lot of D in that equation. And over the past year, we've seen, of course the autonomous database is ramping up, especially notable on Exadata Cloud@Customer, we've covered that extensively. We covered the autonomous data warehouse announcement, the blockchain piece, which of course got me excited 'cause I get to talk about crypto with Juan. Roving Edge, which for everybody who might not be familiar with that, it's an edge cloud service, dedicated regions that you guys announced, which is a managed cloud region. And so it's clear, you guys are serious about cloud. These are all cloud first services using second gen OCI. So, Oracle's making some moves but the question is, what are customers doing? Are they buying this stuff? Are they leaning into these new deployment models for the databases? What can you tell us? >> You know, definitely. And I think, you know, the reason that we have so many different services is that not every customer is the same, right? One of the things that people don't necessarily realize, I guess, is in the early days of cloud lots of startups went there because they had no local infrastructure. It was easy for them to get started in something completely new. Our customers are mostly enterprise customers that have huge data centers in many cases, they have lots of real estate local. And when they think about cloud they're wondering how can we create an environment that doesn't cause us to have two ops teams and two ways of managing things. And so, they're trying to figure out exactly what it means to take their real estate and either move it wholesale to the cloud over a period of years, or they say, "Hey, some of these things need to be local maybe even for regulatory purposes." Or just because they want to keep some data locally within their own data centers but then they have to move other things remotely. And so, there's many different ways of solving the problem. And you can't just say, "Here's one cloud, this is where you go and that's it." So, we basically say, if you're on prem, we provide you with cloud services on-premises, like dedicated regions or Oracle Exadata Cloud@Customer and so forth so that you get the benefits of what we built for cloud and spend a lot of time on, but you can run them in your own data center or people say, "No, no, no. I want to get rid of my data centers, I do it remotely." Okay, then you do it in Oracle cloud directly. Or you have a hybrid model where you say, "Some stays local, some is remote." The nice thing is you get the exact same API, the exact same way of managing things, no matter how you deploy it. And that's a big differentiator. >> So, is it fair to say that you guys have, I think of it as a purpose built club, 'cause I talk to a lot of customers. I mean, take an insurance app like Claims, and customers tell me, "I'm not putting that into the public cloud." But you're making a case that it actually might make sense in your cloud because you can support those mission critical applications with the exact same experience, same API, same... I can get, you know, take Rack for instance, I can't get, you know, real application clusters in an Amazon cloud but presumably I can get them in your cloud. So, is it fair to say you have a purpose built cloud specifically for the most demanding applications? Is that a right way to look at it or not necessarily? >> Well, it's interesting. I think the thing to be careful of is, I guess, purpose built cloud might for some people mean, "Oh, you can only do things if it's Oracle centric." Right, and so I think that fundamentally, Oracle cloud provides a generic cloud. You can run anything you want, any application, any deployment model that you have. Whether you're an Oracle customer or not, we provide you with a full cloud service, right? However, given that we know and have known, obviously for a long time, how our products run best, when we designed OCI gen two, when we designed the networking stack, the storage layer and all that stuff, we made sure that it would be capable of running our more complex environments because our advantage is, Oracle customers have a place where they can run Oracle the best. Right, and so obviously the context of purpose-built fits that model, where yes, we've made some design choices that allow us to run Rack inside OCI and allow us to deploy Exadatas inside OCI which you cannot do in other clouds. So yes, it's purpose built in that sense but I would caution on the side of that it sometimes might imply that it's unique to Oracle products and I guess one way to look at it is if you can run Oracle, you can run everything else, right? Because it's such a complex suite of products that if you can run that then it it'll support any other (mumbling). >> Right. Right, it's like New York city. You make it there, you can make it anywhere. If I can run the most demanding mission critical applications, well, then I can run a web app for instance, okay. I got a question on tooling 'cause there's a lot of tooling, like sometimes it makes my eyes bleed when I look at all this stuff and doesn't... Square the circle for me, doesn't autonomous, an autonomous database like Autonomous Linux, for instance, doesn't it eliminate the need for all these management tools? >> You know, it does. It eliminates the need for the management at the lower level, right. So, with the autonomous Linux, what we offer and what we do is, we automatically patch the operating system for you and make sure it's secure from a security patching point of view. We eliminate the downtime, so when we do it then you don't have to restart applications. However, we don't know necessarily what the app is that is installed on top of it. You know, people can deploy their own applications, they can run third party applications, they can use it for development environments and so forth. So, there's sort of the core operating system layer and on the database side, you know, we take care of database patching and upgrades and storage management and all that stuff. So the same thing, if you run your own application inside the database, we can manage the database portion but we don't manage the application portion just like on the operating system. And so, there's still a management level that's required, no matter what, a level above that. And the other thing and I think this is what a lot of the stuff we're doing is based on is, you still have tons of stuff on-premises that needs full management. You have applications that you migrate that are not running Autonomous Linux, could be a Windows application that's running or it could be something on a different Linux distribution or you could still have some databases installed that you manage yourself, you don't want to use the autonomous or you're on a third-party. And so we want to make sure that we can address all of them with a single set of tools, right. >> Okay, so I wonder, can you give us just an overview, just briefly of the products that comprise into the cloud services, your management solution, what's in that portfolio? How should we think about it? >> Yeah, so it basically starts with Enterprise Manager on-premises, right? Which has been the tool that our Oracle database customers in particular have been using for many years and is widely used by our customer base. And so you have those customers, most of their real estate is on-premises and they can use enterprise management with local. They have it running and they don't want to change. They can keep doing that and we keep enhancing as you know, with newer versions of Enterprise Manager getting better. So, then there's the transition to cloud and so what we've been doing over the last several years is basically, looking at the things, well, one aspect is looking at things people, likes of Enterprise Manager and make sure that we provide similar functionality in Oracle cloud. So, we have Performance Hub for looking at how the database performance is working. We have APM for Application Performance Monitoring, we have Logging Analytics that looks at all the different log files and helps make sense of it for you. We have Database Management. So, a lot of the functionality that people like in Enterprise Manager mentioned the database that we've built into Oracle cloud, and, you know, a number of other things that are coming Operations Insights, to look at how databases are performing and how we can potentially do consolidation and stuff. So we've basically looked at what people have been using on-premises, how we can replicate that in Oracle cloud and then also, when you're in a cloud, how you can make make use of all the base services that a cloud vendor provides, telemetry, logging and so forth. And so, it's a broad portfolio and what it allows us to do with our customers is say, "Look, if you're predominantly on-prem, you want to stay there, keep using Enterprise Manager. If you're starting to move to Oracle cloud, you can first use EM, look at what's happening in the cloud and then switch over, start using all the management products we have in the cloud and let go of the Enterprise Manager instance on-premise. So you can gradually shift, you can start using more and more. Maybe you start with analytics first and then you start with insights and then you switch to database management. So there's a whole suite of possibilities. >> (indistinct) you mentioned APM, I've been watching that space, it's really evolved. I mean, you saw, you know, years ago, Splunk came out with sort of log analytics, maybe simplified that a little bit, now you're seeing some open source stuff come out. You're seeing a lot of startups come out, you saw Cisco made an acquisition with AppD and that whole space is transforming it seems that the future is all about that end to end visibility, simplifying the ability to remediate problems. And I'm thinking, okay, you just mentioned, you guys have a lot of these capabilities, you got Autonomous, is that sort of where you're headed with your capabilities? >> It definitely is and in fact, one of the... So, you know, APM allows you to say, "Hey, here's my web browser and it's making a connection to the database, to a middle tier" and it's hard for operations people in companies to say, hey, the end user calls and says, "You know, my order entry system is slow. Is it the browser? Is it the middle tier that they connect to? Is it the database that's overloaded in the backend?" And so, APM helps you with tracing, you know, what happens from where to where, where the delays are. Now, once you know where the delay is, you need to drill down on it. And then you need to go look at log files. And that's where the logging piece comes in. And what happens very often is that these log files are very difficult to read. You have networking log files and you have database log files and you have reslog files and you almost have to be an expert in all of these things. And so, then with Logging Analytics, we basically provide sort of an expert dashboard system on top of that, that allows us to say, "Hey! When you look at logging for the network stack, here are the most important errors that we could find." So you don't have to go and learn all the details of these things. And so, the real advantages of saying, "Hey, we have APM, we have Logging Analytics, we can tie the two together." Right, and so we can provide a solution that actually helps solve the problem, rather than, you need to use APM for one vendor, you need to use Logging Analytics from another vendor and you know, that doesn't necessarily work very well. >> Yeah and that's why you're seeing with like the ELK Stack it's cool, you're an open source guy, it's cool as an open source, but it's complicated to set up all that that brings. So, that's kind of a cool approach that you guys are taking. You mentioned Enterprise Manager, you just made a recent announcement, a new release. What's new in that new release? >> So Enterprise Manager 13.5 just got released. And so EM keeps improving, right? We've made a lot of changes over over the years and one of the things we've done in recent years is do more frequent updates sort of the cloud model frequent updates that are not just bug fixes but also introduce new functionality so people get more stuff more frequently rather than you know, once a year. And that's certainly been very attractive because it shows that it's a lively evolving product. And one of the main focus areas of course is cloud. And so a lot of work that happens in Enterprise Manager is hybrid cloud, which basically means I run Enterprise Manager and I have some stuff in Oracle cloud, I might have some other stuff in another cloud vendors environment and so we can actually see which databases are where and provide you with one consolidated view and one tool, right? And of course it supports Autonomous Database and Exadata in cloud servers and so forth. So you can from EM see both your databases on-premises and also how it's doing in in Oracle cloud as you potentially migrate things over. So that's one aspect. And then the other one is in terms of operations and automation. One of the things that we started doing again with Enterprise Manager in the last few years is making sure that everything has a REST API. So we try to make the experience with Enterprise Manager be very similar to how people work with a cloud service. Most folks now writing automation tools are used to calling REST APIs. EM in the early days didn't have REST APIs, now we're making sure everything works that way. And one of the advantages is that we can do extensibility without having to rewrite the product, that we just add the API clause in the agent and it makes it a lot easier to become part of the modern system. Another thing that we introduced last year but that we're evolving with more dashboards and so forth is the Grafana plugin. So even though Enterprise Manager provides lots of cool tools, a lot of cloud operations folks use a tool called Grafana. And so we provide a plugin that allows customers to have Grafana dashboards but the data actually comes out of Enterprise Manager. So that allows us to integrate EM into a more cloudy world in a cloud environment. I think the other important part is making sure that again, Enterprise Manager has sort of a cloud feel to it. So when you do patching and upgrades, it's near zero downtime which basically means that we do all the upgrades for you without having to bring EM down. Because even though it's a management tool, it's used for operations. So if there were downtime for patching Enterprise Manager for an hour, then for that hour, it's a blackout window for all the monitoring we do. And so we want to avoid that from happening, so now EM is upgrading, even though all the events are still happening and being processed, and then we do a very short switch. So that help our operations people to be more available. >> Yes. I mean, I've been talking about Automated Operations since, you know, lights out data centers since the eighties back in (laughs). I remember (indistinct) data center one-time lights out there were storage tech libraries in there and so... But there were a lot of unintended consequences around, you know, automated ops, and so people were sort of scared to go there, at least lean in too much but now with all this machine intelligence... So you're talking about ops automation, you mentioned the REST APIs, the Grafana plugins, the Cloud feel, is that what you're bringing to the table that's unique, is that unique to Oracle? >> Well, the integration with Oracle in that sense is unique. So one example is you mentioned the word migration, right? And so database migration tends to be something, you know, customers obviously take very serious. We go from one place, you have to move all your data to another place that runs in a slightly different environment. And so how do you know whether that migration is going to work? And you can't migrate a thousand databases manually, right? So automation, again, it's not just... Automation is not just to say, "Hey, I can do an upgrade of a system or I can make sure that nothing is done by hand when you patch something." It's more about having a huge fleet of servers and a huge fleet of databases. How can you move something from one place to another and automate that? And so with EM, you know, we start with sort of the prerequisite phase. So we're looking at the existing environment, how much memory does it need? How much storage does it use? Which version of the database does it have? How much data is there to move? Then on the target side, we see whether the target can actually run in that environment. Then we go and look at, you know, how do you want to migrate? Do you want to migrate everything from a sort of a physical model or do you want to migrate it from a logical model? Do you want to do it while your environment is still running so that you start backing up the data to the target database while your existing production system is still running? Then we do a short switch afterwards, or you say, "No, I want to bring my database down. I want to do the migrate and then bring it back up." So there's different deployment models that we can let our customers pick. And then when the migration is done, we have a ton of health checks that can validate whether the target database will run through basically the exact same way. And then you can say, "I want to migrate 10 databases or 50 databases" and it'll work, It's all automated out of the box. >> So you're saying, I mean, you've looked at the prevailing way you've done migrations, historically you'd have to freeze the code and then migrate, and it would take forever, it was a function of the number of lines of code you had. And then a lot of times, you know, people would say, "We're not going to freeze the code" and then they would almost go out of business trying to merge the two. You're saying in 2021, you can give customers the choice, you can migrate, you could change the, you know, refuel the plane while you're in midair? Is that essentially what you're saying? >> That's a good way of describing it, yeah. So your existing database is running and we can do a logical backup and restore. So while transactions are happening we're still migrating it over and then you can do a cutoff. It makes the transition a lot easier. But the other thing is that in the past, migrations would typically be two things. One is one database version to the next, more upgrades than migration. Then the second one is that old hardware or a different CPU architecture are moving to newer hardware in a new CPU architecture. Those were sort of the typical migrations that you had prior to Cloud. And from a CIS admin point of view or a DBA it was all something you could touch, that you could physically touch the boxes. When you move to cloud, it's this nebulous thing somewhere in a data center that you have no access to. And that by itself creates a barrier to a lot of admins and DBA's from saying, "Oh, it'll be okay." There's a lot of concern. And so by baking in all these tests and the prerequisites and all the dashboards to say, you know, "This is what you use. These are the features you use. We know that they're available on the other side so you can do the migration." It helps solve some of these problems and remove the barriers. >> Well that was just kind of same same vision when you guys came up with it. I don't know, quite a while ago now. And it took a while to get there with, you know, you had gen one and then gen two but that is, I think, unique to Oracle. I know maybe some others that are trying to do that as well, but you were really the first to do that and so... I want to switch topics to talk about security. It's hot topic. You guys, you know, like many companies really focused on security. Does Enterprise Manager bring any of that over? I mean, the prevailing way to do security often times is to do scripts and write, you know, custom security policy scripts are fragile, they break, what can you tell us about security? >> Yeah. So there's really two things, you know. One is, we obviously have our own best security practices. How we run a database inside Oracle for our own world, we've learned about that over the years. And so we sort of baked that knowledge into Enterprise Manager. So we can say, "Hey, if you install this way, we do the install and the configuration based on our best practice." That's one thing. The other one is there's STIG, there's PCI and they're ShipBob, those are the main ones. And so customers can do their own way. They can download the documentation and do it manually. But what we've done is, and we've done this for a long time, is basically bake those policies into Enterprise Manager. So you can say, "Here's my database this needs to be PCI compliant or it needs to be HIPAA compliant and you push a button and then we validate the policies in those documents or in those prescript described files. And we make sure that the database is combined to that. And so we take that manual work and all that stuff basically out of the picture, we say, "Push this button and we'll take care of it." >> Now, Wim, but just quick sidebar here, last time we talked, it was under a year ago. It was definitely during COVID and it's still during COVID. We talked about the state of the penguin. So I'm wondering, you know, what's the latest update for Linux, any Linux developments that we should be aware of? >> Linux, we're still working very hard on Autonomous Linux and that's something where we can really differentiate and solve a problem. Of course, one of the things to mention is that Enterprise Manager can can do HIPAA compliance on Oracle Linux as well. So the security practices are not just for the database it can also go down to the operating system. Anyway, so on the Autonomous Linux side, you know, management in an Oracle Cloud's OS management is evolving. We're spending a lot of time on integrating log capturing, and if something were to go wrong that we can analyze a log file on the fly and send you a notification saying, "Hey, you know there was this bug and here's the cause." And it was potentially a fix for it to Autonomous Linux and we're putting a lot of effort into that. And then also sort of IT/operation management where we can look at the different applications that are running. So you're running a web server on a Linux environment or you're running some Java processes, we can see what's running. We can say, "Hey, here's the CPU utilization over the past week or the past year." And then how is this evolving? Say, if something suddenly spikes we can say, "Well, that's normal, because every Monday morning at 10 o'clock there's a spike or this is abnormal." And then you can start drilling this down. And this comes back to overtime integration with whether it's APM or Logging Analytics, we can tie the dots, right? We can connect them, we can say, "Push this thing, then click on that link." We give you the information. So it's that integration with the entire cloud platform that's really happening now >> Integration, there's that theme again. I want to come back to migration and I think you did a good job of explaining how you sort of make that non-disruptive and you know, your customers, I think, you know, generally you're pushing you know, that experience which makes people more comfortable. But my question is, why do people want to migrate if it works and it's on prem, are they doing it just because they want to get out of the data center business? Or is it a better experience in the cloud? What can you tell us there? >> You know, it's a little bit of everything. You know, one is, of course the idea that data center maintenance costs are very high. The other one is that when you run your own data center, you know, we obviously have this problem but when you're a cloud vendor, you have these problems but we're in this business. But if you buy a server, then in three years that server basically is depreciated by new versions and they have to do migration stuff. And so one of the advantages with cloud is you push a button, you have a new version of the hardware, basically, right? So the refreshes happen on a regular basis. You don't have to go and recycle that yourself. Then the other part is the subscription model. It's a lot easier to pay for what you use rather than you have a data center whether it's used or not, you pay for it. So there's the cost advantages and predictability of what you need, you pay for, you can say, "Oh next year we need to get x more of EMs." And it's easier to scale that, right? We take care of dealing with capacity planning. You don't have to deal with capacity planning of hardware, we do that as the cloud vendor. So there's all these practical advantages you get from doing it remotely and that's really what the appeal is. >> Right. So, as it relates to Enterprise Manager, did you guys have to like tear down the code and rebuild it? Was it entire like redo? How did you achieve that? >> No, no, no. So, Enterprise Manager keeps evolving and you know, we changed the underlying technologies here and there, piecemeal, not sort of a wholesale replacement. And so in talking about five, there's a lot of new stuff but it's built on the existing EM core. And so we're just, you know, improving certain areas. One of the things is, stability is important for our customers, obviously. And so by picking things piecemeal, we replace one engine rather than the whole thing. It allows us to introduce change more slowly, right. And then it's well-tested as a unit and then when we go on to the next thing. And then the other one is I mentioned earlier, a lot of the automation and extensibility comes from REST APIs. And so instead of basically re-writing everything we just provide a REST endpoint and we make all the new features that we built automatically be REST enabled. So that makes it a lot easier for us to introduce new stuff. >> Got it. So if I want to poke around with this new version of Enterprise Manager, can I do that? Is there a place I can go, do I have to call a rep? How does that work? >> Yeah, so for information you can just go to oracle.com/enterprise manager. That's the website that has all the data. The other thing is if you're already playing with Oracle Cloud or you use Oracle Cloud, we have Enterprise Manager images in the marketplace. So if you have never used EM, you can go to Oracle Cloud, push a button in the marketplace and you get a full Enterprise Manager installation in a matter of minutes. And then you can just start using that as well. >> Awesome. Hey, I wanted to ask you about, you know, people forget that you guys are the stewards of MySQL and we've been looking at MySQL Database Cloud service with HeatWave Did you name that? And so I wonder if you could talk about what you're doing with regard to managing HeatWave environments? >> So, HeatWave is the MySQL option that helps with analytics, right? And it really accelerates MySQL usage by 100 x and in some cases more and it's transparent to the customer. So as a MySQL user, you connect with standard MySQL applications and APIs and SQL and everything. And the HeatWave part is all done within the MySQL server. The engine itself says, "Oh, this SQL query, we can offload to the backend HeatWave cluster," which then goes in memory operations and blazingly fast returns it to you. And so the nice thing is that it turns every single MySQL database into also a data warehouse without any change whatsoever in your application. So it's been widely popular and it's quite exciting. I didn't personally name it, HeatWave, that was not my decision, but it sounds very cool. >> That's very cool. >> Yeah, It's a very cool name. >> We love MySQL, we started our company on the lamp stack, so like many >> Oh? >> Yeah, yeah. >> Yeah, yeah. That's great. So, yeah. And so with HeatWave or MySQL in general we're basically doing the same thing as we have done for the Oracle Database. So we're going to add more functionality in our database management tools to also look at HeatWave. So whether it's doing things like performance hub or generic database management and monitoring tools, we'll expand that in, you know, in the near future, in the future. >> That's great. Well, Wim, it's always a pleasure. Thank you so much for coming back in "The Cube" and letting me ask all my Colombo questions. It was really a pleasure having you. (mumbling) >> It's good be here. Thank you so much. >> You're welcome. And thank you for watching, everybody, this is Dave Vellante. We'll see you next time. (bright music)

>> From theCUBE studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR, this is Breaking Analysis with Dave Vellante. >> In our 2020 predictions post, we said that organizations would begin to operationalize their digital transformation experiments and POCs. We also said that based on spending data that cybersecurity companies like CrowdStrike and Okta were poised to rise above the rest in 2020, and we even said the S&P 500 would surpass 3,700 this year. Little did we know that we'd have a pandemic that would make these predictions a virtual lock, and, of course, COVID did blow us out of the water in some other areas, like our prediction that IT spending would increase plus 4% in 2020, when in reality, we have a dropping by 4%. We made a number of other calls that did pretty well, but I'll let you review last year's predictions at your leisure to see how we did. Hello, everyone. This is Dave Vellante and welcome to this week's Wikibon CUBE Insights powered by ETR. Erik Bradley of ETR is joining me again for this Breaking Analysis, and we're going to lay out our top picks for 2021. Erik, great to see you. Welcome back. Happy to have you on theCUBE, my friend. >> Always great to see you too, Dave. I'm excited about these picks this year. >> Well, let's get right into it. Let's bring up the first prediction here. Tech spending will rebound in 2021. We expect a 4% midpoint increase next year in spending. Erik, there are a number of factors that really support this prediction, which of course is based on ETR's most recent survey work, and we've listed a number of them here in this slide. I wonder if we can talk about that a little bit, the pace of the vaccine rollout. I've called this a forced march to COVID, but I can see people doubling down on things that are working. Productivity improvements are going to go back into the business. People are going to come back to the headquarters and that maybe is going to spur infrastructure on some pent-up demand, and work from home, we're going to talk about that. What are your thoughts on this prediction? >> Well, first of all, you weren't wrong last year. You were just, (laughs) you were just delayed. Just delayed a little bit, that's all. No, very much so. Early on, just three months ago, we were not seeing this optimism. The most recent survey, however, is capturing 4%. I truly believe that still might be a little bit mild. I think it can go even higher, and that's going to be driven by some of the things you've said about. This is a year where a lot of spending was paused on machine learning, on automation, on some of these projects that had to be stopped because of what we all went through. Right now, that is not a nice to have, it's a must have, and that spending is going quickly. There's a rapid pace on that spending, so I do think that's going to push it and, of course, security. We're going to get to this later on so I don't want to bury the lede, but with what's happening right now, every CISO I speak to is not panicked, but they are concerned and there will definitely be increased security spending that might push this 4% even higher. >> Yeah, and as we've reported as well, the survey data shows that there's less freezing of IT, there are fewer layoffs, there's more hiring, we're accelerating IT deployments, so that, I think, 34% last survey, 34% of organizations are accelerating IT deployments over the next three months, so that's great news. >> And also your point too about hiring. I was remiss in not bringing that up because we had layoffs and we had freezes on hiring. Both of that is stopping. As you know, as more head count comes in, whether that be from home or whether that be in your headquarters, both of those require support and require spending. >> All right, let's bring up the next prediction. Remote worker trends are going to become fossilized, settling in at an average of 34% by year-end 2021. Now, I love this chart, you guys. It's been amazingly consistent to me, Erik. We're showing data here from ETR's latest COVID survey. So it shows that prior to the pandemic, about 15 to 16% of employees on average worked remotely. That jumped to where we are today and well into the 70s, and we're going to stay close to that, according to the ETR data, in the first half of 2021, but by the end of the year, it's going to settle in at around 34%. Erik, that's double the pre-pandemic numbers and that's been consistent in your surveys over the past six month, and even within the sub-samples. >> Yeah, super surprised by the consistency, Dave. You're right about that. We were expecting the most recent data to kind of come down, right? We see the vaccines being rolled out. We kind of thought that that number would shift, but it hasn't, it has been dead consistent, and that's just from the data perspective. What we're hearing from the interviews and the feedback is that's not going to change, it really isn't, and there's a main reason for that. Productivity is up, and we'll talk about that in a second, but if you have productivity up and you have employees happy, they're not commuting, they're working more, they're working effectively, there is no reason to rush. And now imagine if you're a company that's trying to hire the best talent and attract the best talent but you're also the only company telling them where they have to live. I mean, good luck with that, right? So even if a few of them decide to make this permanent, that's something where you're going to really have to follow suit to attract talent. >> Yeah, so let's talk about that. Productivity leads us to our next prediction. We can bring that up. Number three is productivity increases are going to lead organizations to double down on the successes of 2020 and productivity apps are going to benefit. Now, of course, I'm always careful to cautious to interpret when you ask somebody by how much did productivity increase. It's a very hard thing to estimate depending on how you measure it. Is it revenue per employee? Is it profit? But nonetheless, the vast majority of people that we talk to are seeing productivity is going up. The productivity apps are really the winners here. Who do you see, Erik, as really benefiting from this trend? This year we saw Zoom, Teams, even Webex benefit, but how do you see this playing out in 2021? >> Well, first of all, the real beneficiaries are the companies themselves because they are getting more productivity, and our data is not only showing more productivity, but that's continuing to increase over time, so that's number one. But you're 100% right that the reason that's happening is because of the support of the applications and what would have been put in place. Now, what we do expect to see here, early on it was a rising tide lifted all boats, even Citrix got pulled up, but over time you realize Citrix is really just about legacy applications. Maybe that's not really the virtualization platform we need or maybe we just don't want to go that route at all. So the ones that we think are going to win longer term are part of this paradigm shift. The easiest one to put out as example is DocuSign. Nobody is going to travel and sit in an office to sign a paper ever again. It's not happening. I don't care if you go back to the office or you go back to headquarters. This is a paradigm shift that is not temporary. It is permanent. Another one that we're seeing is Smartsheet. Early on it started in. I was a little concerned about it 'cause it was a shadow IT type of a company where it was just spreading and spreading and spreading. It's turned out that this, the data on Smartsheet is continuing to be strong. It's an effective tool for project management when you're remotely working, so that's another one I don't see changing anytime. The other one I would call out would be Twilio. Slightly different, yes. It's more about the customer experience, but when you look at how many brick and mortar or how many in-person transactions have moved online and will stay there, companies like Twilio that support that customer experience, I'll throw out a Qualtrics out there as well, not a name we hear about a lot, but that customer experience software is a name that needs to be watched going forward. >> What do you think's going to happen to Zoom and Teams? Certainly Zoom just escalated this year, a huge ascendancy, and Teams I look at a little differently 'cause it's not just video conferencing, and both have done really, really well. How do you interpret the data that you're seeing there? >> There's no way around it, our data is decelerating quickly, really quickly. We were kind of bullish when Zoom first came out on the IPO prospects. It did very well. Obviously what happened in this remote shift turned them into an absolute overnight huge success. I don't see that continuing going forward, and there's a reason. What we're seeing and hearing from our feedback interviews is that now that people recognize this isn't temporary and they're not scrambling and they need to set up for permanency, they're going to consolidate their spend. They don't need to have Teams and Zoom. It's not necessary. They will consolidate where they can. There's always going to be the players that are going to choose Slack and Zoom 'cause they don't want to be on Microsoft architecture. That's fine, but you and I both know that the majority of large enterprises have Microsoft already. It's bundled in in pricing. I just don't see it happening. There's going to be M&A out there, which we can talk about again soon, so maybe Zoom, just like Slack, gets to a point where somebody thinks it's worthwhile, but there's a lot of other video conferencing out there. They're trying to push their telephony. They're trying to push their mobile solutions. There's a lot of companies out there doing it, so we'll see, but the current market cap does not seem to make sense in a permanent remote work situation. >> I think I'm inferring Teams is a little different because it's Microsoft. They've got this huge software estate they can leverage. They can bundle. Now, it's going to be interesting to see how and if Zoom can then expand its TAM, use its recent largesse to really enter potentially new markets. >> It will be, but listen, just the other day there was another headline that one of Zoom's executives out in China was actually blocking content as per directed by the Chinese government. Those are the kind of headlines that just really just get a little bit difficult when you're running a true enterprise size. Zoom is wonderful in the consumer space, but what I do is I research enterprise technology, and it's going to be really, really difficult to make inroads there with Microsoft. >> Yep. I agree. Okay, let's bring up number four, prediction number four. Permanent shifts in CISO strategies lead to measurable share shifts in network security. So the remote work sort of hyper-pivot, we'll call it, it's definitely exposed us. We've seen recent breaches that underscore the need for change. They've been well-publicized. We've talked a lot about identity access management, cloud security, endpoint security, and so as a result, we've seen the upstarts, and just a couple that we called, CrowdStrike, Okta, Zscaler has really benefited and we expect them to continue to show consistent growth, some well over 50% revenue growth. Erik, you really follow this space closely. You've been focused on microsegmentation and other, some of the big players. What are your thoughts here? >> Yeah, first of all, security, number one in spending overall when we started looking and asking people what their priority is going to be. That's not changing, and that was before the SolarWinds breach. I just had a great interview today with a CISO of a global hospitality enterprise to really talk about the implications of this. It is real. Him and his peers are not panicking but pretty close, is the way he put it, so there is spend happening. So first of all, to your point, continued on Okta, continued on identity access. See no reason why that changes. CrowdStrike, continue. What this is going to do is bring in some new areas, like we just mentioned, in network segmentation. Illumio is a pure play in that name that doesn't have a lot of citations, but I have watched over the last week their net spending score go from about 30 to 60%, so I am watching in real time, as this data comes in in the later part of our survey, that it's really happening Forescout is another one that's in there. We're seeing some of the zero trust names really picking up in the last week. Now, to talk about some of the more established names, yeah, Cisco plays in this space and we can talk about Cisco and what they're doing in security forever. They're really reinventing themselves and doing a great job. Palo Alto was in this space as well, but I do believe that network and microsegmentation is going to be something that's going to continue. The other one I'm going to throw out that I'm hearing a lot about lately is user behavior analytics. People need to be able to watch the trends, compare them to past trends, and catch something sooner. Varonis is a name in that space that we're seeing get a lot of adoptions right now. It's early trend, but based on our data, Varonis is a name to watch in that area as well. >> Yeah, and you mentioned Cisco transitioning, reinventing themselves toward a SaaS player. Their subscription, Cisco's security business is a real bright spot for them. Palo Alto, every time I sit in on a VENN, which is ETR's proprietary roundtable, the CISOs, they love Palo Alto. They want to work, many of them, anyway, want to work with Palo Alto. They see them as a thought leader. They seem to be getting their cloud act together. Fortinet has been doing a pretty good job there and especially for mid-market. So we're going to see this equilibrium, best of breed versus the big portfolio companies, and I think 2021 sets up as a really interesting battle for those guys with momentum and those guys with big portfolios. >> I completely agree and you nailed it again. Palo Alto has this perception that they're really thought leaders in the space and people want to work with them, but let's not rule Cisco out. They have a much, much bigger market cap. They are really good at acquisitions. In the past, they maybe didn't integrate them as well, but it seems like they're getting their act together on that. And they're pushing now what they call SecureX, which is sort of like their own full-on platform in the cloud, and they're starting to market that, I'm starting to hear more about it, and I do think Cisco is really changing people's perception of them. We shall see going forward because in the last year, you're 100% right, Palo Alto definitely got a little bit more of the sentiment, of positive sentiment. Now, let's also realize, and we'll talk about this again in a bit, there's a lot of players out there. There will probably be continued consolidation in the security space, that we'll see what happens, but it's an area where spending is increasing, there is a lot of vendors out there to play with, and I do believe we'll see consolidation in that space. >> Yes. No question. A highly fragmented business. A lack of skills is a real challenge. Automation is a big watch word and so I would expect, which brings us, Erik, to prediction number five. Can be hard to do prediction posts without talking about M&A. We see the trend toward increased tech spending driving more IPOs, SPACs and M&A. We've seen some pretty amazing liquidity events this year. Snowflake, obviously a big one. Airbnb, DoorDash, outside of our enterprise tech but still notable. Palantir, JFrog, number of others. UiPath just filed confidentially and their CEO said, "Over the next 12 to 18 months, I would think Automation Anywhere is going to follow suit at some point." Hashicorp was a company we called out in our 2020 predictions as one to watch along with Snowflake and some others, and, Erik, we've seen some real shifts in observability. The ELK Stack gaining prominence with Elastic, ChaosSearch just raised 40 million, and everybody's going after 5G. Lots of M&A opportunities. What are your thoughts? >> I think if we're going to make this a prediction show, I'm going to say that was a great year, but we're going to even have a better year next year. There is a lot of cash on the balance sheet. There are low interest rates. There is a lot of spending momentum in enterprise IT. The three of those set up for a perfect storm of more liquidity events, whether it be continued IPOs, whether it could be M&A, I do expect that to continue. You mentioned a lot of the names. I think you're 100% right. Another one I would throw out there in that observability space, is it's Grafana along with the ELK Stack is really making changes to some of the pure plays in that area. I've been pretty vocal about how I thought Splunk was having some problems. They've already made three acquisitions. They are trying really hard to get back up and keep that growth trajectory and be the great company they always have been, so I think the observability area is certainly one. We have a lot of names in that space that could be taken out. The other one that wasn't mentioned, however, that I'd like to mention is more in the CDN area. Akamai being the grandfather there, and we'll get into it a little bit too, but CloudFlare has a huge market cap, Fastly running a little bit behind that, and then there's Limelight, and there's a few startups in that space and the CDN is really changing. It's not about content delivery as much as it is about edge compute these days, and they would be a real easy takeout for one of these large market cap names that need to get into that spot. >> That's a great call. All right, let's bring up number six, and this is one that's near and dear to my heart. It's more of a longer-term prediction and that prediction is in the 2020s, 75% of large organizations are going to re-architect their big data platforms, and the premise here is we're seeing a rapid shift to cloud database and cross-cloud data sharing and automated governance. And the prediction is that because big data platforms are fundamentally flawed and are not going to be corrected by incremental improvements in data lakes and data warehouses and data hubs, we're going to see a shift toward a domain-centric ownership of the data pipeline where data teams are going to be organized around data product or data service builders and embedded into lines of business. And in this scenario, the technology details and complexity will become abstracted. You've got hyper-specialized data teams today. They serve multiple business owners. There's no domain context. Different data agendas. Those, we think, are going to be subsumed within the business lines, and in the future, the primary metric is going to shift from the cost and the quality of the big data platform outputs to the time it takes to go from idea to revenue generation, and this change is going to take four to five years to coalesce, but it's going to begin in earnest in 2021. Erik, anything you'd add to this? >> I'm going to let you kind of own that one 'cause I completely agree, and for all the listeners out there, that was Dave's original thought and I think it's fantastic and I want to get behind it. One of the things I will say to support that is big data analytics, which is what people are calling it because they got over the hype of machine learning, they're sick of vendors saying machine learning, and I'm hearing more and more people just talk about it as we need big data analytics, we need 'em at the edge, we need 'em faster, we need 'em in real time. That's happening, and what we're seeing more is this is happening with vendor-agnostic tools. This isn't just AWS-aligned. This isn't just GCP-aligned or Azure-aligned. The winners are the Snowflakes. The winners are the Databricks. The winners are the ones that are allowing this interoperability, the portability, which fully supports what you're saying. And then the only other comment I would make, which I really like about your prediction, is about the lines of business owning it 'cause I think this is even bigger. Right now, we track IT spending through the CIO, through the CTO, through IT in general. IT spending is actually becoming more diversified. IT spending is coming under the purview of marketing, it's coming under the purview of sales, so we're seeing more and more IT spending, but it's happening with the business user or the business lines and obviously data first, so I think you're 100% right. >> Yeah, and if you think about it, we've contextualized our operational systems, whether it's the CRM or the supply chain, the logistics, the business lines own their respective data. It's not true for the analytics systems, and we talked about Snowflake and Databricks. I actually see these two companies who were sort of birds of a feather in the early days together, applying Databricks machine learning on top of Snowflake, I actually see them going in diverging places. I see Databricks trying to improve on the data lake. I see Snowflake trying to reinvent the concept of data warehouse to this global mesh, and it's going to be really interesting to see how that shakes out. The data behind Snowflake, obviously very, very exciting. >> Yeah, it's just, real quickly to add on that if we have time, Dave. >> Yeah, sure. >> We all know the valuation of Snowflake, one of the most incredible IPOs I've seen in a long time. The data still supports it. It still supports that growth. Unfortunately for Databricks, their IPO has been a little bit more volatile. If you look at their stock chart every time they report, it's got a little bit of a roller coaster ride going on, and our most recent data for Databricks is actually decelerating, so again, I'm going to use the caveat that we only have about 950 survey responses in. We'll probably get that up to 1,300 or so, so it's not done yet, but right now we are putting Databricks into a category where we're seeing it decelerate a little bit, which is surprising for a company that's just right out of the gate. >> Well, it's interesting because I do see Databricks as more incremental on data lakes and I see Snowflake as more transformative, so at least from a vision standpoint, we'll see if they can execute on that. All right, number seven, let's bring up number seven. This is talking about the cloud, hybrid cloud, multi-cloud. The battle to define hybrid and multi-cloud is going to escalate in 2021. It's already started and it's going to create bifurcated CIO strategies. And, Erik, spending data clearly shows that cloud is continuing its steady margin share gains relative to on-prem, but the definitions of the cloud, they're shifting. Just a couple of years ago, AWS, they never talk about hybrid, just like they don't talk about multi-cloud today, yet AWS continues now to push into on-prem. They treat on-prem as just another node at the edge and they continue to win in the marketplace despite their slower growth rates. Still, they're so large now. 45 billion or so this year. The data is mixed. This ETR data shows that just under 50% of buyers are consolidating workloads, and then a similar, in the cloud workloads, and a similar percentage of customers are spreading evenly across clouds, so really interesting dynamic there. Erik, how do you see it shaking out? >> Yeah, the data is interesting here, and I would actually state that overall spend on the cloud is actually flat from last year, so we're not seeing a huge increase in spend, and coupled with that, we're seeing that the overall market share, which means the amount of responses within our survey, is increasing, certainly increasing. So cloud usage is increasing, but it's happening over an even spectrum. There's no clear winner of that market share increase. So they really, according to our data, the multi-cloud approach is happening and not one particular winner over another. That's just from the data perspective that various do point on AWS. Let's be honest, when they first started, they wanted all the data. They just want to take it from on-prem, put it in their data center. They wanted all of it. They never were interested in actually having interoperability. Then you look at an approach like Google. Google was always about the technology, but not necessarily about the enterprise customer. They come out with Anthos which is allowing you to have interoperability in more cloud. They're not nearly as big, but their growth rate is much higher. Law of numbers, of course. But it really is interesting to see how these cloud players are going to approach this because multi-cloud is happening whether they like it or not. >> Well, I'm glad you brought up multi-cloud in a context of what the data's showing 'cause I would agree we're, and particularly two areas that I would call out in ETR data, VMware Cloud on AWS as well as VM Cloud Foundation are showing real momentum and also OpenStack from Red Hat is showing real progress here and they're making moves. They're putting great solutions inside of AWS, doing some stuff on bare metal, and it's interesting to see. VMware, basically it's the VMware stack. They want to put that everywhere. Whereas Red Hat, similarly, but Red Hat has the developer angle. They're trying to infuse Red Hat in throughout everybody's stack, and so I think Red Hat is going to be really interesting to, especially to the extent that IBM keeps them, sort of lets them do their own thing and doesn't kind of pollute them. So, so far so good there. >> Yeah, I agree with that. I think you brought up the good point about it being developer-friendly. It's a real option as people start kicking a little bit more of new, different developer ways and containers are growing, growing more. They're not testing anymore, but they're real workloads. It is a stack that you could really use. Now, what I would say to caveat that though is I'm not seeing any net new business go to IBM Red Hat. If you were already aligned with that, then yes, you got to love these new tools they're giving you to play with, but I don't see anyone moving to them that wasn't already net new there and I would say the same thing with VMware. Listen, they have a great entrenched base. The longer they can kick that can down the road, that's fantastic, but I don't see net new customers coming onto VMware because of their alignment with AWS. >> Great, thank you for that. That's a good nuance. Number eight, cloud, containers, AI and ML and automation are going to lead 2021 spending velocity, so really is those are the kind of the big four, cloud, containers, AI, automation, And, Erik, this next one's a bit nuanced and it supports our first prediction of a rebound in tech spending next year. We're seeing cloud, containers, AI and automation, in the form of RPA especially, as the areas with the highest net scores or spending momentum, but we put an asterisk around the cloud because you can see in this inserted graphic, which again is preliminary 'cause the survey's still out in the field and it's just a little tidbit here, but cloud is not only above that 40% line of net score, but it has one of the higher sector market shares. Now, as you said, earlier you made a comment that you're not necessarily seeing the kind of growth that you saw before, but it's from a very, very large base. Virtually every sector in the ETR dataset with the exception of outsourcing and IT consulting is seeing meaningful upward spending momentum, and even those two, we're seeing some positive signs. So again, with what we talked about before, with the freezing of the IT projects starting to thaw, things are looking much, much better for 2021. >> I'd agree with that. I'm going to make two quick comments on that, one on the machine learning automation. Without a doubt, that's where we're seeing a lot of the increase right now, and I've had a multiple number of people reach out or in my interviews say to me, "This is very simple. These projects were slated to happen in 2020 and they got paused. It's as simple as that. The business needs to have more machine learning, big data analytics, and it needs to have more automation. This has just been paused and now it's coming back and it's coming back rapidly." Another comment, I'm actually going to post an article on LinkedIn as soon as we're done here. I did an interview with the lead technology director, automation director from Disney, and this guy obviously has a big budget and he was basically saying UiPath and Automation Anywhere dominate RPA, and that on top of it, the COVID crisis greatly accelerated automation, greatly accelerated it because it had to happen, we needed to find a way to get rid of these mundane tasks, we had to put them into real workloads. And another aspect you don't think about, a lot of times with automation, there's people, employees that really have friction. They don't want to adopt it. That went away. So COVID really pushed automation, so we're going to see that happening in machine learning and automation without a doubt. And now for a fun prediction real quick. You brought up the IT outsourcing and consulting. This might be a little bit more out there, the dark horse, but based on our data and what we're seeing and the COVID information about, you said about new projects being unwrapped, new hiring happening, we really do believe that this might be the bottom on IT outsourcing and consulting. >> Great, thank you for that, and then that brings us to number nine here. The automation mandate is accelerating and it will continue to accelerate in 2021. Now, you may say, "Okay, well, this is a lay-up," but not necessarily. UiPath and Automation Anywhere go public and Microsoft remains a threat. Look, UiPath, I've said UiPath and Automation Anywhere, if they were ready to go public, they probably would have already this year, so I think they're still trying to get their proverbial act together, so this is not necessarily a lay-up for them from an operational standpoint. They probably got some things to still clean up, but I think they're going to really try to go for it. If the markets stay positive and tech spending continues to go forward, I think we can see that. And I would say this, automation is going mainstream. The benefits of taking simple RPA tools to automate mundane tasks with software bots, it's both awakened organizations to the possibilities of automation, and combined with COVID, it's caused them to get serious about automation. And we think 2021, we're going to see organizations go beyond implementing point tools, they're going to use the pandemic to restructure their entire business. Erik, how do you see it, and what are the big players like Microsoft that have entered the market? What kind of impact do you see them having? >> Yeah, completely agree with you. This is a year where we go from small workloads into real deployment, and those two are the leader. In our data, UiPath by far the clear leader. We are seeing a lot of adoptions on Automation Anywhere, so they're getting some market sentiment. People are realizing, starting to actually adopt them. And by far, the number one is Microsoft Power Automate. Now, again, we have to be careful because we know Microsoft is entrenched everywhere. We know that they are good at bundling, so if I'm in charge of automation for my enterprise and I'm already a Microsoft customer, I'm going to use it. That doesn't mean it's the best tool to use for the right job. From what I've heard from people, each of these have a certain area where they are better. Some can get more in depth and do heavier lifting. Some are better at doing a lot of projects at once but not in depth, so we're going to see this play out. Right now, according to our data, UiPath is still number one, Automation Anywhere is number two, and Microsoft just by default of being entrenched in all of these enterprises has a lot of market share or mind share. >> And I also want to do a shout out to, or a call out, not really a shout out, but a call out to Pegasystems. We put them in the RPA category. They're covered in the ETR taxonomy. I don't consider them an RPA vendor. They're a business process vendor. They've been around for a long, long time. They've had a great year, done very, very well. The stock has done well. Their spending momentum, the early signs in the latest survey are just becoming, starting to moderate a little bit, but I like what they've done. They're not trying to take UiPath and Automation Anywhere head-on, and so I think there's some possibilities there. You've also got IBM who went to the market, SAP, Infor, and everybody's going to hop on the bandwagon here who's a software player. >> I completely agree, but I do think there's a very strong line in the sand between RPA and business process. I don't know if they're going to be able to make that transition. Now, business process also tends to be extremely costly. RPA came into this with trying to be, prove their ROI, trying to say, "Yeah, we're going to cost a little bit of money, but we're going to make it back." Business process has always been, at least the legacies, the ones you're mentioning, the Pega, the IBMs, really expensive. So again, I'm going to allude to that article I'm about to post. This particular person who's a lead tech automation for a very large company said, "Not only are UiPath and AA dominating RPA, but they're likely going to evolve to take over the business process space as well." So if they are proving what they can do, he's saying there's no real reason they can't turn around and take what Appian's doing, what IBM's doing and what Pega's doing. That's just one man's opinion. Our data is not actually tracking it in that space, so we can't back that, but I did think it was an interesting comment for and an interesting opportunity for UiPath and Automation Anywhere. >> Yeah, it's always great to hear directly from the mouths of the practitioners. All right, brings us to number 10 here. 5G rollouts are going to push new edge IoT workloads and necessitate new system architectures. AI and real-time inferencing, we think, require new thinking, particularly around processor and system design, and the focus is increasingly going to be on efficiency and at much, much lower costs versus what we've known for decades as general purpose workloads accommodating a lot of different use cases. You're seeing alternative processors like Nvidia, certainly the ARM acquisition. You've got companies hitting the market like Fungible with DPAs, and they're dominating these new workloads in the coming decade, we think, and they continue to demonstrate superior price performance metrics. And over the next five years they're going to find their way, we think, into mainstream enterprise workloads and put continued pressure on Intel general purpose microprocessors. Erik, look, we've seen cloud players. They're diversifying their processor suppliers. They're developing their own in-house silicon. This is a multi-year trend that's going to show meaningful progress next year, certainly if you measure it in terms of innovations, announcements and new use cases and funding and M&A activity. Your thoughts? >> Yeah, there's a lot there and I think you're right. It's a big trend that's going to have a wide implication, but right now, it's there's no doubt that the supply and demand is out of whack. You and I might be the only people around who still remember the great chip famine in 1999, but it seems to be happening again and some of that is due to just overwhelming demand, like you mentioned. Things like IoT. Things like 5G. Just the increased power of handheld devices. The remote from work home. All of this is creating a perfect storm, but it also has to do with some of the chip makers themselves kind of misfired, and you probably know the space better than me, so I'll leave you for that on that one. But I also want to talk a little bit, just another aspect of this 5G rollout, in my opinion, is we have to get closer to the edge, we have to get closer to the end consumer, and I do believe the CDN players have an area to play in this. And maybe we can leave that as there and we could do this some other time, but I do believe the CDN players are no longer about content delivery and they're really about edge compute. So as we see IoT and 5G roll out, it's going to have huge implications on the chip supply. No doubt. It's also could have really huge implications for the CDN network. >> All right, there you have it, folks. Erik, it's great working with you. It's been awesome this year. I hope we can do more in 2021. Really been a pleasure. >> Always. Have a great holiday, everybody. Stay safe. >> Yeah, you too. Okay, so look, that's our prediction for 2021 and the coming decade. Remember, all these episodes are available as podcasts. All you got to do is search Breaking Analysis podcast. You'll find it. We publish each week on wikibon.com and siliconangle.com, and you got to check out etr.plus. It's where all the survey action is. Definitely subscribe to their services if you haven't already. You can DM me @dvellante or email me at david.vellante@siliconangle.com. This is Dave Vellante for Erik Bradley for theCUBE Insights powered by ETR. Thanks for watching, everyone. Be well and we'll see you next time. (relaxing music)

>> Narrator: From around the globe it's theCUBE, with digital coverage of AWS re:Invent 2020. Special coverage sponsored by AWS Global Partner Network. >> Hello and welcome to theCUBE Virtual and our coverage of AWS re:Invent 2020 with special coverage of APN partner experience. We are theCUBE Virtual and I'm your host, Justin Warren. And today I'm joined by Ed Walsh, CEO of ChaosSearch. Ed, welcome to theCUBE. >> Well thank you for having me, I really appreciate it. >> Now, this is not your first time here on theCUBE. You're a regular here and I've loved it to have you back. >> I love the platform you guys are great. >> So let's start off by just reminding people about what ChaosSearch is and what do you do there? >> Sure, the best way to say is so ChaosSearch helps our clients know better. We don't do that by a special wizard or a widget that you give to your, you know, SecOp teams. What we do is a hard work to give you a data platform to get insights at scale. And we do that also by achieving the promise of data lakes. So what we have is a Chaos data platform, connects and indexes data in a customer's S3 or glacier accounts. So inside your data lake, not our data lake but renders that data fully searchable and available for analysis using your existing tools today 'cause what we do is index it and publish open API, it's like API like Elasticsearch API, and soon SQL. So give you an example. So based upon those capabilities were an ideal replacement for a commonly deployed, either Elasticsearch or ELK Stack deployments, if you're hitting scale issues. So we talk about scalable log analytics, and more and more people are hitting these scale issues. So let's say if you're using Elasticsearch ELK or Amazon Elasticsearch, and you're hitting scale issues, what I mean by that is like, you can't keep enough retention. You want longer retention, or it's getting very expensive to keep that retention, or because the scale you hit where you have availability, where the cluster is hard to keep up running or is crashing. That's what we mean by the issues at scale. And what we do is simply we allow you, because we're publishing the open API of Elasticsearch use all your tools, but we save you about 80% off your monthly bill. We also give you an, and it's an and statement and give you unlimited retention. And as much as you want to keep on S3 or into Glacier but we also take care of all the hassles and management and the time to manage these clusters, which ends up being on a database server called leucine. And we take care of that as a managed service. And probably the biggest thing is all of this without changing anything your end users are using. So we include Kibana, but imagine it's an Elastic API. So if you're using API or Kibana, it's just easy to use the exact same tools used today, but you get the benefits of a true data lake. In fact, we're running now Elasticsearch on top of S3 natively. If that makes it sense. >> Right and natively is pretty cool. And look, 80% savings, is a dramatic number, particularly this year. I think there's a lot of people who are looking to save a few quid. So it'd be very nice to be able to save up to 80%. I am curious as to how you're able to achieve that kind of saving though. >> Yeah, you won't be the first person to ask me that. So listen, Elastic came around, it was, you know we had Splunk and we also have a lot of Splunk clients, but Elastic was a more cost effective solution open source to go after it. But what happens is, especially at scale, if it's fall it's actually very cost-effective. But underneath last six tech ELK Stack is a leucine database, it's a database technology. And that sits on our servers that are heavy memory count CPU count in and SSDs. So you can do on-prem or even in the clouds, so if you do an Amazon, basically you're spinning up a server and it stays up, it doesn't spin up, spin down. So those clusters are not one server, it's a cluster of those servers. And typically if you have any scale you're actually having multiple clusters because you don't dare put it on one, for different use cases. So our savings are actually you no longer need those servers to spin up and you don't need to pay for those seen underneath. You can still use Kibana under API but literally it's $80 off your bill that you're paying for your service now, and it's hard dollars. So it's not... And we typically see clients between 70 and 80%. It's up to 80, but it's literally right within a 10% margin that you're saving a lot of money, but more importantly, saving money is a great thing. But now you have one unified data lake that you can have. You used to go across some of the data or all the data through the role-based access. You can give different people. Like we've seen people who say, hey give that, help that person 40 days of this data. But the SecOp up team gets to see across all the different law. You know, all the machine generated data they have. And we can give you a couple of examples of that and walk you through how people deploy if you want. >> I'm always keen to hear specific examples of how customers are doing things. And it's nice that you've thought of drawn that comparison there around what what cloud is good for and what it isn't is. I'll often like to say that AWS is cheap to fail in, but expensive to succeed. So when people are actually succeeding with this and using this, this broad amount of data so what you're saying there with that savings I've actually got access to a lot more data that I can do things with. So yeah, if you could walk through a couple of examples of what people are doing with this increased amount of data that they have access to in EKL Search, what are some of the things that people are now able to unlock with that data? >> Well, literally it's always good for a customer size so we can go through and we go through it however it might want, Kleiner, Blackboard, Alert Logic, Armor Security, HubSpot. Maybe I'll start with HubSpot. One of our good clients, they were doing some Cloud Flare data that was one of their clusters they were using a lot to search for. But they were looking at to look at a denial service. And they were, we find everyone kind of at scale, they get limited. So they were down to five days retention. Why? Well, it's not that they meant to but basically they couldn't cost-effectively handle that in the scale. And also they're having scale issues with the environment, how they set the cluster and sharding. And when they also denial service tech, what happened that's when the influx of data that is one thing about scale is how fast it comes out, yet another one is how much data you have. But this is as the data was coming after them at denial service, that's when the cluster would actually go down believe it or not, you know right. When you need your log analysis tools. So what we did is because they're just using Kibana, it was easy swap. They ran in parallel because we published the open API but we took them from five days to nine days. They could keep as much as they want but nine days for denial services is what they wanted. And then we did save them in over $4 million a year in hard dollars, What they're paying in their environment from really is the savings on the server farm and a little bit on the Elasticsearch Stack. But more importantly, they had no outages since. Now here's the thing. Are you talking about the use case? They also had other clusters and you find everyone does it. They don't dare put it on one cluster, even though these are not one server, they're multiple servers. So the next use case for CloudFlare was one, the next QS and it was a 10 terabyte a day influx kept it for 90 days. So it's about a petabyte. They brought another use case on which was NetMon, again, Network Monitoring. And again, I'm having the same scale issue, retention area. And what they're able to do is easily roll that on. So that's one data platform. Now they're adding the next one. They have about four different use cases and it's just different clusters able to bring together. But now what they're able to do give you use cases either they getting more cost effective, more stability and freedom. We say saves you a lot of time, cost and complexity. Just the time they manage that get the data in the complexities around it. And then the cost is easy to kind of quantify but they've got better but more importantly now for particular teams they only need their access to one data but the SecOP team wants to see across all the data. And it's very easy for them to see across all the data where before it was impossible to do. So now they have multiple large use cases streaming at them. And what I love about that particular case is at one point they were just trying to test our scale. So they started tossing more things at it, right. To see if they could kind of break us. So they spiked us up to 30 terabytes a day which is for Elastic would even 10 terabytes a day makes things fall over. Now, if you think of what they just did, what were doing is literally three steps, put your data in S3 and as fast as you can, don't modify, just put it there. Once it's there three steps connect to us, you give us readability access to those buckets and a place to write the indexy. All of that stuff is in your S3, it never comes out. And then basically you set up, do you want to do live or do you want to do real time analysis? Or do you want to go after old data? We do the rest, we ingest, we normalize the schema. And basically we give you our back and the refinery to give the right people access. So what they did is they basically throw a whole bunch of stuff at it. They were trying to outrun S3. So, you know, we're on shoulders of giants. You know, if you think about our platform for clients what's a better dental like than S3. You're not going to get a better cross curve, right? You're not going to get a better parallelism. And so, or security it's in your, you know a virtual environment. But if you... And also you can keep data in the right location. So Blackboard's a good example. They need to keep that in all the different regions and because it's personal data, they, you know, GDPR they got to keep data in that location. It's easy, we just put compute in each one of the different areas they are. But the net net is if you think that architecture is shoulders of giants if you think you can outrun by just sheer volume or you can put in more cost-effective place to keep long-term or you think you can out store you have so much data that S3 and glacier can't possibly do it. Then you got me at your bigger scale at me but that's the scale we'r&e talking about. So if you think about the spiked our throughput what they really did is they try to outrun S3. And we didn't pick up. Now, the next thing is they tossed a bunch of users at us which were just spinning up in our data fabric different ways to do the indexing, to keep up with it. And new use cases in case they're going after everyone gets their own worker nodes which are all expected to fail in place. So again, they did some of that but really they're like you guys handled all the influx. And if you think about it, it's the shoulders of giants being on top of an Amazon platform, which is amazing. You're not going to get a more cost effective data lake in the world, and it's continuing to fall in price. And it's a cost curve, like no other, but also all that resiliency, all that security and the parallelism you can get, out of an S3 Glacier is just a bar none is the most scalable environment, you can build an environment. And what we do is a thin layer. It's a data platform that allows you to have your data now fully searchable and queryable using your tools >> Right and you, you mentioned there that, I mean you're running in AWS, which has broad experience in doing these sorts of things at scale but on that operational management side of things. As you mentioned, you actually take that off, off the hands of customers so that you run it on their behalf. What are some of the areas that you see people making in trying to do this themselves, when you've gone into customers, and brought it into the EKL Search platform? >> Yeah, so either people are just trying their best to build out clusters of Elasticsearch or they're going to services like Logz.io, Sumo Logic or Amazon Elasticsearch services. And those are all basically on the same ELK Stack. So they have the exact same limits as the same bits. Then we see people trying to say, well I really want to go to a data lake. I want to get away from these database servers and which have their limits. I want to use a data Lake. And then we see a lot of people putting data into environments before they, instead of using Elasticsearch, they want to use SQL type tools. And what they do is they put it into a Parquet or Presto form. It's a Presto dialect, but it into Parquet and structure it. And they go a lot of other way to, Hey it's in the data lake, but they end up building these little islands inside their data lake. And it's a lot of time to transform the data, to get it in a format that you can go after our tools. And then what we do is we don't make you do that. Just literally put the data there. And then what we do is we do the index and a polish API. So right now it's Elasticsearch in a very short time we'll publish Presto or the SQL dialect. You can use the same tool. So we do see people, either brute forcing and trying their best with a bunch of physical servers. We do see another group that says, you know, I want to go use an Athena use cases, or I want to use a there's a whole bunch of different startups saying, I do data lake or data lake houses. But they are, what they really do is force you to put things in the structure before you get insight. True data lake economics is literally just put it there, and use your tools natively to go after it. And that's where we're unique compared to what we see from our competition. >> Hmm, so with people who have moved into ChaosSearch, what's, let's say pick one, if you can, the most interesting example of what people have started to do with, with their data. What's new? >> That's good. Well, I'll give you another one. And so Armor Security is a good one. So Armor Security is a security service company. You know, thousands of clients doing great I mean a beautiful platform, beautiful business. And they won Rackspace as a partner. So now imagine thousand clients, but now, you know massive scale that to keep up with. So that would be an example but another example where we were able to come in and they were facing a major upgrade of their environment just to keep up, and they expose actually to their customers is how their customers do logging analytics. What we're able to do is literally simply because they didn't go below the API they use the exact same tools that are on top and in 30 days replaced that use case, save them tremendous amount of dollars. But now they're able to go back and have unlimited retention. They used to restrict their clients to 14 days. Now they have an opportunity to do a bunch of different things, and possible revenue opportunities and other. But allow them to look at their business differently and free up their team to do other things. And now they're, they're putting billing and other things into the same environment with us because one is easy it's scale but also freed up their team. No one has enough team to do things. And then the biggest thing is what people do interesting with our product is actually in their own tools. So, you know, we talk about Kibana when we do SQL again we talk about Looker and Tableau and Power BI, you know, the really interesting thing, and we think we did the hard work on the data layer which you can say is, you know I can about all the ways you consolidate the performance. Now, what becomes really interesting is what they're doing at the visibility level, either Kibana or the API or Tableau or Looker. And the key thing for us is we just say, just use the tools you're used to. Now that might be a boring statement, but to me, a great value proposition is not changing what your end users have to use. And they're doing amazing things. They're doing the exact same things they did before. They're just doing it with more data at bigger scale. And also they're able to see across their different machine learning data compared to being limited going at one thing at a time. And that getting the correlation from a unified data lake is really what we, you know we get very excited about. What's most exciting to our clients is they don't have to tell the users they have to use a different tool, which, you know, we'll decide if that's really interesting in this conversation. But again, I always say we didn't build a new algorithm that you going to give the SecOp team or a new pipeline cool widget that going to help the machine learning team which is another API we'll publish. But basically what we do is a hard work of making the data platform scalable, but more importantly give you the APIs that you're used to. So it's the platform that you don't have to change what your end users are doing, which is a... So we're kind of invisible behind the scenes. >> Well, that's certainly a pretty strong proposition there and I'm sure that there's plenty of scope for customers to come and and talk to you because no one's creating any less data. So Ed, thanks for coming out of theCUBE. It's always great to see you here. >> Know, thank you. >> You've been watching theCUBE Virtual and our coverage of AWS re:Invent 2020 with special coverage of APN partner experience. Make sure you check out all our coverage online, either on your desktop, mobile on your phone, wherever you are. I've been your host, Justin Warren. And I look forward to seeing you again soon. (soft music)

>> Narrator: From around the globe it's theCUBE, with digital coverage of AWS reinvent 2020 special coverage sponsored by AWS global partner network. >> Hello, and welcome to theCUBE virtual with our special coverage of AWS reinvent 2020 with additional special coverage of APN partner experience. We are theCUBE virtual and I'm your host, Justin Warren. And today I'm joined by Angelos Kottas who is vice president of product marketing at elastic and he comes to us from San Francisco. Angelos , welcome to theCUBE. >> Thank you, Justin. A pleasure to join you. >> Great to have you here. Now. I've been a big fan of elastic for a while have used your products in a variety of circumstances? You're big partners of AWS and have seen quite a bit of change over the last couple of years. We were talking just before we came on air. Maybe you could talk us through what elastic is doing with AWS and a little bit about those changes that you've seen over the last >> Absolutely one period. >> Sounds good Justin. So first of all many people know elastic as the makers of elastic search. One of the most popular open source of search engines and along with elastic search we have Kibana and beats and Logstash and many people know us as the Elk Stack, right? And so clearly we have roots in the open source community and people have used us for custom applications for years and years. One of the key changes over the last few years is that we've realized that many customers were doing some of the same things with elastic. So we said, what if we really focus on end to end experiences for our three core use cases? And so we chose three use cases and built solutions around them. What is enterprise search, right? Which is how do you find information on your website in your application or in your workspace? The second is observability. So think about software development software in every industry. What about dev ops? What about performance? What about consistency and last but not least, especially you know, with some of the current transitions in digital transformation, think about security. Think about your network security, your endpoint security and how you have visibility across your entire IT ecosystem. So we've chosen those three solution areas and put significant engineering into building out that experience. How quickly can we deliver value, how pre-built can the configuration be the integrations be, the workflow, the reporting and the dashboards around those use cases. The last piece, which is very relevant for reinvent is the transition to cloud, right? So we still offer a downloadable software and many of our customers and users download the elastic stack and deploy it on-prem and hybrid cloud environments. But one of the fastest growing deployment models is in the public cloud. And of course, elastic cloud on AWS is one of our major routes to market, happy to meet many of our customers where they are, which is on AWS. >> Oh it's great to be able to have that choice I think that people can download the software try and get it, get comfortable with it but then people often find that actually running software yourself, there's quite a lot of work involved in doing that. I know that I, I've experienced that myself. Just little things like maintenance and so on. So it sounds like you're actually taking care of a lot of that for customers if they move to the cloud service. But is there anything else special about the cloud service that customers might not be that aware of? >> Well, I mean, choice is a big part of it and so it's not just do I choose cloud it's wearing cloud. So we've actually, we now run elastic cloud in over 40 regions around the world. So we can be close to you in terms of latency, and in terms of performance, in terms of data sovereignty we can be local to your environment. The other aspect it's not just how we simplify deploying elastic. You know, clearly we architect it we install it, deploy and upgraded for you. But also we have focused quite a bit on integrating cloud data sources. So with AWS, as an example, we look at all of the applications and data sources that you host on AWS. And we think about how do we get those data streams how do we get that data directly integrated into elastic. One final piece, actually which I forget sometimes it's not the technical side. It's the business side is the commercial integration, right? So we are, you know, very happy to to be listed on the AWS marketplace. We've made it easy for you to find, deploy and actually build through your AWS commercial agreements via the marketplace integration. >> Right, so easy to get started and to start using it and search is certainly something that elastic is famous for. But you mentioned observability there, a bit of a question I have around observability is, is it that just a fancy way of saying monitoring? There seems to be this, this buzzword around the place. So what do you mean when you say observability? >> So one of the key foundational principles of the elastic observability solution is that, you know you want a unified data database a unified place to store all that data. So it is stretching across logs metrics, application traces it's bringing together a common platform that lets you look at different aspects of observability. So whether you're doing end to end application traces or whether you're just collecting infrastructure logs and looking at performance metrics it's kind of across the board, even looking at things in our most recent release that just came out last week, you know expanding on user experience, monitoring and synthetics. So you can optimize web interactions and web experiences, for example. >> Right. Okay. So there's a bunch of different types of data that are involved there. I know traditionally people would silo those off into a specific customized thing just for that particular type of workload. What is it about elastic that means that you can put all of these in one place? >> Yeah. You know, one of early catchphrases for what does elastic do? What do we focus on? The value we deliver is speed, scale and relevance. And so one of the things that is famous about the elastic way of doing things is the way in which we index data on ingest and so that you can get search queries that return within milliseconds and so that performance characteristics. A second one is scale. And this is actually really key, not just for observability but right next to observability, you get security as well. We like to say, if you're going to observe you might as well protect as well. So when you expand to that universe you have not just hundreds of devices you might have thousands or tens of thousands of devices that you are ingesting information whether it's operational data, whether it's security data. So scale becomes extremely significant. How can you scale horizontally and vertically and maintain that performance even when you are in a fortune 500 scale infrastructure The last piece is relevance. And so, you know that data it's not just about knowing what to look for. It's about using things like machine learning and anomaly detection to uncover unusual patterns of behavior and proactively alerting and making that visible through notifications and through alerts that can actually integrate not just with your elastic operations but actually with third party software. Maybe you want to trigger a service now ticket or a, you know, a Slack integration and all of that is part of the elastic platform as well. >> Right? Okay. So by putting everything kind of in one place that is around what you're talking about. So we have enterprise search and then to be able to find things we're collecting all of the data that we need to find things. And then you touched on security at the beginning and we're starting to talk around security there. So I'm keen to move on to that >> (chuckles) >> By looking at all of these, these different, these signals we can hopefully then manage some of security which I know is very much front of mind for everyone over the last year. Cyber security has very much come to the forefront of everyone's thinking. >> Absolutely. And you know, we've been on the network side of security for some time. So we've had our SIM solution, you know security information event monitoring, but we made a very strategic acquisition a little over a year ago. We saw that a critical piece of visibility is also the end point. And so we partnered with end game and eventually we acquired end game to create end to end visibility on that security. So it is being able to connect, you know the path of data from your servers and network devices all the way to the end points. And an example of the power of this unified architecture is the new elastication that we introduced in beta a couple of months ago. We said, what if we had a single deployment that both does endpoint protection and does malware scanning of your endpoint devices while also ingesting data into your observability systems. And so that's kind of the power of the platform the ability to use common infrastructure common integrations, so that every use case you adopt on top of elastic, it sort of multiplies the value you're getting from using elastic as an infrastructure player. >> Alright that's a good combining a couple of different things into the one tool that you can use. I know sys who I'd spoken to are quite concerned about the proliferation of tools that they have in their environment, it seems that they've bought lots of different things but a lot of them are kind of sitting in a drawer, not really being used. And partly, it's just, we we have so many different ways of dealing with these issues. None of it's really flushed out or sorry has been fully fleshed out that we definitely know this is the one true way to solve this. So what are you hearing from customers as they start to use these security functions? What are they telling you about the way that they're managing security in their environments? >> Well, you know, we think about a few different personas in the security market, right? We think about threat hunters, for example who are looking to identify threats, we're looking at the operations team that do the cleanup that do the you know, the resolution of security threats. And we also, so there's a, you know, there's two competing terms in the security market. We have security operations in the observability world. We have dev ops, right? And, and developer, you know, the continue of developer and deployment into a dev ops role. And so we're starting to see this concept of DevSecOps, right? What if there is a unified set it's not all things to all people and that's an important thing, right? We're not trying to be, your single security vendor for all IT security needs, but instead we're saying, what if you had a security operations analyst, a thrent Hunter an executive, a CSO who's looking for, you know an overall level of threat or compliance to policy and you can bring those experiences together through the elastic security solution. >> Right? So it sounds like you you're trying to allow people to work in the way that they need to providing them the tools that suit their particular circumstance. >> That's right. That's right. I mean, in terms of how do you define success? You look at metrics like meantime to resolution, you know can we reduce the meantime to resolution or you look at law collection and how much more efficiently can you collect logs? You look at asset monitoring and what percentage of your IT infrastructure you actually have unified visibility into, you know we have one great cloud customer OALEKS group. They are a popular online marketplace, you know and they quoted to us that they had a 1900% increase in law collection, right. In terms of scope of what they are collecting logs on they reduce that MTTR by 30% for security incidents so dramatically streamlined and shortened the exposure. And then they increased asset monitoring by 35% across cloud, as well as on-prem. And I think that's the other piece is that, you know whether you deploy your security in the cloud or on-prem you are looking to secure your hybrid environment. And so being able to take data feeds from your SAS partners from your infrastructure running on AWS as well as from those endpoint devices. >> Well, it sounds like there's plenty of scope of interesting things for people to come and have a look at it, at elastic. So, Angelos, thank you so much for joining us here, please. Thank you to my guests Angelos Kottas, vice president of product marketing at elastic. You've been watching theCUBE virtual and our coverage of AWS reinvent 2020 with special coverage of APN partner experience. Make sure you check out all our coverage on your desktop laptop or on your phone, wherever you are. I've been your host, Justin Warren. And I look forward to seeing you again soon. (upbeat music)

>> Narrator: From around the globe, it's the CUBE, with digital coverage of Dell Technologies world. Digital experience brought to you by Dell Technologies. >> Welcome to the CUBE'S coverage of Dell Technologies World 2020, The Digital Experience. I'm Lisa Martin joined by a couple of guys from Dell Technology. Please welcome Martin Glynn, the senior director for product management for PowerMax Martin good morning. >> Good morning. >> Nice to see you. And joining Martin is Matthew Paul, the senior director of product management for PowerFlex at Dell Technologies. Matthew, nice to see you. >> Nice to see you thanks for having us Lisa. >> So our virtual cube this year can't be with you guys in person or the 14,000 other folks that usually attend at Dell Technologies World but a lot of opportunities to engage customers and partners and present analysts digitally, which is great. So Matthew, let's go ahead and start with you. Talk to us about what's new with PowerFlex, this was the kind of the end of the rebrand under the power portfolio that Dell Technologies undertook the last couple of years formerly the VXFlex excuse me, from Scale IO, what's new with PowerFlex? >> Yeah, that's a spot on. So really the idea of us aligning the full power portfolio is kind of a big deal, right? Part of the winning roadmap to at IO, kind of assigned to our customers and our field and everyone that software defined storage is a critical part of the Dell Technologies strategy. If you think about PowerFlex, just to kind of level set, it's really a software defined infrastructure kind of system that brings you the best of traditional three tier infrastructure and the best of HCI infrastructure while being able to make that experience really simple in the enterprise while still delivering exemplary really great performance and scale. In terms of new things, well, just real quick, in terms of kind of new things, we brought interesting topics like native Async replication, secure snapshots, some end to end lifecycle management pieces. So a lot of great innovation in the last year. >> And that was some of the recent announcements. Tell me Matthew, from a customer perspective since you've announced Asynchronous replication snapshots, what's the customer adoption, customer feedback been like? >> Yeah, it's been fantastic. We continue to grow this market really strong, you know, we're focusing on high end large enterprise customers working towards, bringing down also into kind of enterprise and commercial customers, so it'll make things easier to use. But very strong adoption and great investments here at Dell with this product. >> All right, so PowerFlex, Martin, let's go to you PowerMax, talk to us about PowerMax. And then also how it kind of fits into the whole power portfolio. >> Sure, yeah, so thanks Lisa. The PowerMax products, I think was the first product other than of course, the server products to be powered up in the storage portfolio, PowerMax is the sort of flagship sort of derived product that we've had now for, you know, a few decades really been a leader in mission critical data centers. But I think that pace of innovation over the last year just like Matt describing the PowerFlex side has been a really phenomenal. Just about a year ago he came out with a storage class memory, we did fiber channel Endymion over fiber channel, and more recently brought in a few really interesting new technologies, like support for replication, with VVols, cloud mobility, and now, efficient encryption. So the set of things we're enabling our customers to do with their you know, sort of traditional three tier SAN infrastructure is really just unmatched. >> So Matt talk to me about the last six seven months, where are these enterprise customers in terms of leveraging PowerMax for example, when everything just changed dramatically almost overnight. Enterprises in every industry had to suddenly remote workforce. How did PowerMax help your customers pivot and ensure that their digital transformation could support this business surviving? >> Yeah, well, like everybody we were a little worried at the outset, you know lot of uncertainty about how things would play out and the response from our customers has been amazing. You know, they've all sort of really doubled down on using our technology to support their businesses through this new model. So, you know, the business has been really amazing really incredible, and it's been great to partner with our customers that help them continue to deliver the services that they need you know, in this new model. So that part's been, been really wonderful, and as we work really closely with them, some of the things we just came out with, you know, they've helped us to design and deliver in a way that they can best take advantage of so, you know, for example the new cloud mobility functionality that's letting them take information directly off of their mission, critical sort of bedrock sand infrastructure and push it up to an object store. And that could be a local private object store, it could be a public object store like AWS. And so that's you know, it's enabling them to take advantage of some new models and a new approach to doing things. And I think ultimately that's going to help them work through this you know, new normal, we're all participating in. >> Yeah, we want to help those businesses not just survive this time, but be able to thrive, especially as we don't know how much of this remote scattered workforce is going to remain. We're hearing estimates from some of the big technology leaders at all. 50% percent of the workforce is going to remain at home so really helping organizations to maneuver and navigate these challenging landscapes is a big priority I know for Dell Technologies we talked about that with some other guests. Matthew, over to you talk to me about PowerFlex from a workloads perspective, so we can get a good idea for the workloads that it's really ideally best suited for. >> Yeah, I think wanted to just take a quick second on the COVID piece, because we have a couple of really big customers that we had to enable really quickly for curbside checkout and, you know, they were trying to run things, they were putting it on their existing infrastructure, their existing systems, and it just wasn't fast enough, it wasn't keeping up. And by working closely with the customer and designing a system with PowerFlex as the core, allowed us to enable them really quickly to turn from a customer who didn't have this idea of curbside checkout to enabling curbside checkout. So I think working and partnering closely with our customers is a critical part of how Dell Tech is successful and enabling them to kind of work through these tough times. With workloads, Yeah, oh, go ahead sorry. >> That's okay go ahead. >> I was going to say with workloads in general, the way that we have to think about them with enterprise quality or enterprise requirements is really in kind of a scheme of looking at performance, understanding scalability, ensuring we have enterprise class availability, and then last but definitely not least is like how we manage that and how we make it easier for customers to work through those. And when I think about Flex there's two or three key areas that we try to go after, if you, one of the key differentiation pieces around Flex is the fact that we can deploy it in multiple manners. So you can deploy it in an HCI mode, where you have the compute and networking together, or you can go deploy it in a dis-aggregated mode where you have compute and networking, I mean, compute and storage separate. And if those are separate that allows you to scale those independently work really, really well for key database workloads, key workloads like, let's say even like Honda, where you maybe have really high compute but little less storage requirements. So that really allows customers to dial up and down what makes the most sense for them right? The other angle that we're seeing pretty big adoption is around this idea of re-platform or realigning the data center with transformation with software defined scale all block storage. So think about deploying Powerflex in an environment and then being able to use that in a virtual environment in a physical environment, in a container environment being able to have your traditional applications like SQL or Oracle, right along really cool new applications like the ELK Stack or Mongo DB or other things, because of the way that we design our layout, it's really aligned towards being able to re-platform and align in a software defined infrastructure. So customers are using to kind of align those pieces meaning platforms, re-platforming and then also aligning specific applications that require high performance. >> I heard a lot in that and one word that pops up is no, that's good. >> No, I can tell you're passionate about it. >> I love it, yeah. >> And also the customer influence is absolutely critical. I think this is a time you mentioned the curbs I check in, and then I was reading a few months ago about some of the huge brands that were filing for chapter 11 and companies like big retailers that simply couldn't pivot, couldn't digitally transform to even offer curbside check in so that factor alone since us consumers are so demanding was table stakes a few months ago. It still is, but getting an organization able to pivot so quickly is key. Martin let's go over to you, PowerMax, workloads. Talk to me about some differentiators as well. >> Yeah Aatually, if I could I'll start with sort of some similar examples that Matt laid out there, you know, just like we have customers who chose PowerFlex you know, were in environments that made sense for them. We had customers who chose PowerMax to meet similar new demands with the whole, you know pandemic. So we had some really big customers just so okay, now we have sort of line of sight and, you know, across both products, I think the thing that our customers value most is you know, the quality of the experience, the performance of the experience, some of the things Matt mentioned already. But they really pull forward, you know, huge numbers of systems and business, and be able to support you know, where they saw things going. So that was really great to partner with them on that and be ready to help support them and provide a product that they felt really good about making such huge investments in, you know, it was great to see their trust in us and be able to deliver for them. So, that was, I think a big part of the first half of the year, that sort of new, you know, new workloads and new use cases for us on the PowerMax side really revolve around giving our customers new capabilities that can deliver new services for their end users. So one of those is our new support for VVols remote replication. And this really lets us tie together the way that the infrastructure is managed at the VMware level, much more closely to the way that the storage infrastructure is managed. And the result is that our, our customers can do more granular operations for their end users, they can simplify the whole process, and now they can do it on top of our remote replication solution, which, you know going on 20 plus years now, it's really been sort of the gold standard in which they've come to rely on so much. So that's really exciting to be able to offer that to them now, to have it be part of the whole VMware stack that they're deploying and let them use you know, new things like, you know the way VVols works with our cyber site recovery manager, to let them automate you know, the testing, I feel always in the actual fail over. There's an interesting example of how I think our customers are going to take advantage of some of these new technologies as we go forward. >> You mentioned giving customers the ability with the right infrastructure to offer new services. And that's another critical component as we've seen in 2020 is businesses needing to pivot continuously and come up with new creative ideas, products, and services and new ways of delivering those to their existing customers holding onto them and hopefully growing their customer base. And that ability to leverage technology, to deliver new services is also one of the key kind of foundations that will allow businesses to be the winners of tomorrow. Matthew, to you talk to me when you're in customer situations, customers have choice, we know this, ding into me, give me the top three differentiators when you're talking to customers, why PowerFlex is the ideal solution for them? >> That's a great question. I'm glad you asked. (laughs) So I think, you know, as part of being a product guy it's really cool when the intellectual property within your product is software that your company owns and hardware, your company owns. So we're able to do some really cool stuff together to deliver innovative solutions for our customers. But, you know, when I think about my product I think first and foremost, around performance and scale right? You know, several million, IO'S a sub-millisecond response time and anytime someone wants more performance they just add another server, right? So this idea that we scale literally is a key differentiator for the product. A second key differentiator is this idea that I talked a little bit about before that we, you can kind of multi-platform this. So when you roll this out, you can deploy to use it with virtual environments, whether it's VMware or Hyper-V or other virtual environments. You can have bare metal deployment. So if you want to run this with Linux and use software defined storage in the bare metal, we can support that. Or we can go directly to containers. So you can use containers, bare metal or virtual. And so this idea of choice is a huge differentiator. And then the last one is anchored around this idea that when you scale and you get the benefit of management, you don't have to scale everything at the same time. So in traditional software defined infrastructure on the HCI side you have to scale compute and storage together. So every time you add a node you add compute power and storage power. With power flex, we've been able to effectively split those two pieces off, so a customer could actually only scale what they need. And in fact, if they only want to buy storage side of the solution, you can just buy storage side solution and then you can have existing infrastructure connect to that and it behaves just like a traditional three tier model. So those are, I think are the key things that I think differentiate the product and kind of make it special here at Dell and for our customers. >> Matthew, sticking with you, are there any, I think of things like compliance and healthcare and financial services, especially right now, what are some of the key benefits that PowerFlex delivers, say for some of those essential industries right now? >> Yeah, I think, you know it's interesting 'cause those are two of our largest space and financial is probably our largest space. And really for them, it comes down to, you talked about compliance, you talk about scale and then you talk about management. So we said some really interesting requirements because of scale so large, for example, in our last release we're able to start to do rack level firmware and software updates. So when you look at other solutions they might be doing system at a time, doing updates taking them offline and then running those around. But in our scenario, since we kind of own the SDS layer and the compute side, we can actually do update these for an entire rack in one shot. Dramatically reducing the complexity, dramatically reducing the amount of time it takes to do updates. So that's a real big deal in financial space. And then in terms of healthcare, for example we're the only software defined solution product that can run all of Epic healthcare, all pieces of Epic within our product. All other products run out of bandwidth, run out of performance. So they end up not being able to run all sides of the requirement, whether it's the database back end, or the VDI front end, we're the only one on the market that can do all of that. >> It seems to really be a big differentiator in healthcare as a lot of organizations run on Epic or try to, to help with patient care and care delivery. Martin, last question for you. Give me a snapshot of the partner's perspective over the last couple of years with the rebrand under Dell Technologies, with the power portfolio, how have your partners embraced the simplification? >> So, you know, I think that the overall, this gave them clearer understanding of where and what to sell and what made sense for power max in particular, you know, I think it let them anchor on, you know the flagship product of the legendary performance and reliability of that platform and, you know, gave them an easy way to think about where to position that with, you know, our end customers and, you know, in what ways that the products would benefit their customers the most. So, you know, as Matt described on the PowerFlex side, it starts with our performance and reliability and then ultimately, you know enabling them to do whatever they need to do, so across all the different data services and we got to talk ready about some of the new ones you know, but we also have a lot that we've you know, refined over the years and, you know making it sort of official and sort of the PowerMax envelope what everyone really just sort of simplify how they would consume it all. So, you know, I think, you know maybe one of the thing, you know, worth mentioning in all these new use cases and environments and, you know, all the different applications that our customers are trying to operate and deliver on is, you know, security, you know, so we developed a new capability that we call end-to-end efficient encryption. And this really lets customers do encryption all the way from the host through to the storage. And, you know I think ultimately that's going to help them sleep better at night and also, you know help them avoid some of the things that you've seen crop up now. Now that the world is so digital and all the different threats that our customers face. So we're keeping our finger on the pulse of a lot of different needs you know, whether it's flexibility, performance reliability, but all these new new technologies as well to make sure that we set our customers up to be successful as possible. >> That's exactly what they want to be, successful. Martin, Matthew, thank you so much for joining me on the Cube, sharing the updates for PowerMax, PowerFlex, the differentiators. We appreciate your time. >> Thank you, Lisa. >> Yeah, thank you Lisa this was fun. Alright from my guests, I'm Lisa Martin. You've been watching the cubes coverage, Dell Technologies World at 2020, the digital experience. (gentle music)

(lively music) >> Hello, and welcome to this special CUBE conversation. I'm John Furrier, founder of SiliconANGLE Media, co-host of theCUBE. We are here in our Palo Alto Studio to have a conversation around cloud computing, multi-cloud, hybrid cloud, the changes going on in the IT industry and for businesses across the globe as impacted by cloud computing, data, AI. All that's coming together, and a lot of people are trying to figure out how to architect their solution to scale globally but also take care of their businesses, not just cutting costs for information technologies, but delivering services that scale and benefit the businesses and ultimately their customers, the end users. I'm here with a very special guest, Donnie Berkholz, who's the VP of IT services delivery at CWT, Carlson Wagonlit Travel. Also the program chair of the Open Source summit, part of the Linux Foundation, formerly an analyst, a great friend of theCUBE. Donnie, great to see you. Thanks for joining us today. >> Well, thanks for having me on the show. I really appreciate it. >> So we've been having a lot of conversations around, obviously, cloud. We've been there, watching it, from day one. I know you have been covering it as an analyst. Part of that cloud ought to go back to 2007, '08 time frame roughly speaking, you know, even before that with Amazon. Just the massive growth certainly got everyone's attention. IBM once called Amazon irrelevant. Now going full cloud with buying Red Hat for billions and billions of dollars at a 63% premium. Open Source has grown significantly, and now cloud absolutely is the architectural linchpin for companies trying to change how they do business, gather more efficiencies, all built on the ethos of DevOps. That is now kind of going mainstream. So I want to get your thoughts and talk about this across a variety of touchpoints. One is what people are doing in your delivering services, IT services for CWT, and also trying to get positioned for the future. And then Open Source. You're on the Open Source program chair. Open Source driving all these benefits, now with IBM buying Red Hat, you've seen the commercialization of Open Source at a whole nother level which is causing a lot of conversation. So tell us what you're doing and what CWT is about and your role at the company. >> Absolutely, thank you. So CWT, we're in the middle of this journey we call CWT 3.0, which is really one about how do we take the old school green screens that you've seen when you've got travel agents or airline agents booking travel and bring people into the picture and blend together people with technology. So I joined about a year and a half ago to really help push things forward from the perspective of DevOps, because what we came to realize here was we can't deliver quickly and iterate quickly without the underlying platforms that give us the kind of agility that we need without the connections across a lot of our different product groups that led us, again, to iterate on the right things from the perspective of our customers. So I joined a year and a half ago. We've made a lot of strides since then in modernizing many of our technology platforms. The way I think about it here, it's a large enterprise. We've got hundreds of different applications. We've got many, many different product teams, and everything is on a spectrum. We've got some teams that are on the bleeding edge. Not even the leading edge, but I'd say the bleeding edge, trying out the very latest things that come out, experimenting with brand new Open Source tools, with brand new cloud offerings to see, can we incorporate that as quickly as possible so we can innovate faster than our competitors? Whether those are the traditional competitors or some of the new software companies coming into things from that angle. And then on the other end of the spectrum, we've got teams who are taking a much more conservative approach, and saying, "Let's wait and see what sticks "before we pick it up." And the fortunate thing, I think, about a company at the scale we are, is that we can have some of those groups really innovating and pushing the needle, and then other groups who can wait and see which parts stick before we start adopting those at scale. >> And so you've got to manage the production kind of stability versus kind of kicking the tires for the new functionality. So I've got to ask you first. Set up the architecture there. Are you guys on premise with cloud hybrid? Are you in the cloud-native? Do you have multiple clouds? Could you just give a sense of how you're deploying specifically with cloud? >> Yeah, absolutely. I think just like anything else, it's a spectrum of all we see here. There's a lot of different products. Some of them have been built cloud-native. They're using those serverless functions as service technologies from scratch. Brought in some leaders from Amazon to lead some of that drive here. They brought in a lot of good thinking, a lot of good culture, a lot of new perspective to the technologies we're adopting as a company that's not traditionally been a software company. But that is more and more so every day. So we've got some of that going on as completely cloud-native. We've got some going on that's more, I would say, hybrid cloud, where we're spanning between a public cloud environment back to our data centers, and then we've got some that are different applications across multiple different public clouds, because we're not in any one place right now. We're putting things in the best place to do the job. So that's very much the approach that we take, and it's one that, you know, back when I was in my analyst's world, as one of my colleagues called it, the best execution venue. What's the best place? What's the right place to do the right kind of task? We incorporate what are the best technologies we can adopt to help us differentiate more quickly, and where does the data live? What's the data gravity look like? Because we can't be shipping data back and forth. We can't have tons of transactions going back and forth all the time between different public clouds or between a public cloud and one of our data centers. So how do we best account for that when we're architecting what our applications should look like, whether they're brand new ones or whether they're ones we're in the middle of modernizing. >> Great, thanks for sharing, that's great, so yeah, I totally see that same thing. People put, you know, where the best cloud for the app, and if you're Microsoft Shop, you use Azure. If you want to kick the tires on Amazon, there's good roles for that, so we're seeing a lot of those multiple clouds. But while I've got you on the line here, I know you've been an analyst. I want you to just help me define something real quick because there's always kind of confusion between hybrid cloud and multi-cloud. Certainly the multi-cloud, we're getting a lot of hype on that. We're seeing with Kubernetes, with stateful applications versus stateless. You're seeing some conversations there. Certainly on Open Source, that's top of the agenda. Donnie, explain for folks watching the difference between hybrid cloud and multi-cloud, because there's some nuances there, and some people have different definitions. How do you guys look at that? Cause you have multiple clouds, but some aren't necessarily running a workload across clouds yet because of latency issues, so define what hybrid means to you guys and what multi-cloud means to you. >> All right, yeah, I think for us, hybrid cloud would be something where it's about integrating an on-prem workload off a more traditional workload with something in a public cloud environment. It's really, hybrid cloud to me is not two different public clouds working together or even the same application in two different public clouds. That's something a little bit different, and that's where you start to get, I think, into a lot of the questions of what is multi-cloud? We've seen that go through a lot of different transitions over the past decade or so. We've seen a lot of different, you know, vendors, going out there thinking they could sell multi-cloud management that, you know, panned out at different levels of success. I think for at least a decade, we've been talking about ideas like can we do cloud bursting? Has that ever really worked in practice? And I think it's almost as rare as a unicorn. You know, on-prem for the cost efficiencies and then we burst the cloud for the workload. Well, you know, to this day, I've never seen anything that gives you 100% functionality and 100% performance comparability between an on-prem workload and public cloud workload. There always seems to be some kind of difference, and this is a conversation that, I think, Randy Bias has actually been a great proponent of it's not just about the API compatibility. It's not just, you know, can I run Azure in their data centers or in mine? It's about what is the performance difference look like? What does the availability difference look like? Can I support that software in my data center as well as the engineers at Microsoft or at Amazon or at Google or wherever else they're supporting it today? Can I keep it up and running as well? Can I keep it performing as well? Can I find problems as quickly? And that's where it comes to the question of how do we focus on our differentiators and let the experts focus on theirs. >> That's a great point about Randy Bias. Love that great API debate. I was looking at some of that footage we had years ago. But this brings up a good point that I want to get your reaction to, because, you know, a lot of vendors going out there, saying, "Oh, our cloud's this. "We've got all this stuff going on," and there's a lot of hype and a lot of posturing and positioning. The great thing about cloud is that you really can't fake it until you make it. It's got to be working, right? So when you get into the kind of buying into the cloud. You say, "Okay, great, we're going to do some cloud," and maybe you get some cloud architects together. They say, "Okay, here's what it means to us. "In each environment, we'll have to, you know, "understand what that means and then go do it." The reality kind of kicks in, and this is what I'd like to get your reaction to. What is the realities when you say, "Okay, "I want to go to cloud," either for pushing the envelope and/or moving solid workloads that are in production into the cloud. What is the impact on the network, network security, and application performance? Because at the end of the day, those are going to be impacted. Those three areas come up a lot in conversations when all of the glam and all the bloom is off the rose, those are the things that are impacted. What's your thoughts on how practitioners should prepare for those three areas? The network impact, network security impact, and application performance? >> Yeah, I think preparation is exactly the right word there of how do we get the people we have up to speed? And how do we get more and more out of that kind of project mindset and into much more of the product mindset and whether that product is customer-facing or whether that product is some kind of infrastructure or platform product? That's the kind of thinking we're trying to have going into it of how do we get our people, who, you know, may run a Ci Cd pipeline, may run an on-prem container platform, may even be responsible for virtualization, may be responsible for on-prem networks or firewalls or security. How do we get them up to speed and turn them into real software engineers? That's a multi-year journey. That's not something that happens overnight. You can't bring in a team of consultants to fix that problem for you and say, "Oh, well, we came in and implemented it, "and now it's yours, and we walk out the door." It's no longer that, you know, build and operate mindset that you could take a little bit more with on-prem. Because everything is defined as code. And if you don't know how to deal with code, you're going to be in a real rough spot the next time you have to make a change to that stuff that that team of consultants came in and implemented for you. So I think it's turned into a much more long-term approach, which is very, very healthy for technology and for technology companies as a whole of how do we think about this long-term and in a sustainable way, think about scaling up our people. What do those training paths look like? What do those career paths look like? So we can decide, you know, how many people do we want certified? What kind of certifications should they have or equivalent skill sets? I remember hearing not too long ago that I think it was Capital One had over 10,000 people who were AWS certified, which is an enormously large number to think about, but that's the kind of transitions that we've been making as we become more and more cloud-native and cloud by default, is getting the right people. The people we have today trained up in these new kinds of skill sets instead of assuming that's something we can have some team fly in from magic land and implement and then fly away again afterwards. >> That's great, Don, thanks for sharing that insight. I also want to get your thoughts on the Open Source summit, but before we get there, I've got to ask you a question around some of the trends we've been seeing. Early on at DevOps we saw this together of the folks doing the hard work in the early pioneering days, where you saw the developers really getting closer to the front lines. They were becoming part of the business conversation. In the old world of IT, "Okay, here's our strategy. "Consolidate this, load some virtual machines," you know, "Get all this stuff up and running." The business decisions would then trickle down to the tech folks, then with the DevOps revolution, that's now cloud computing and all things, you know, IoT and everything else happening where the developers and the engineering side of it and the applications are on the front lines. They're in more of the business conversations, so I have to ask you. When you're at CWT, what are some of the business drivers and conversations that you guys are having with executive management around choices? Are they business drivers? Do you see an order of preference around agility? The transformation value for either customers or employees, compliance and security, are the top ones that people talk about generally. Of those business drivers, which ones do you guys see the most that are part of iterating through the architecture and ultimately the environment that you deploy? >> Yeah, I think as part of what I mentioned earlier, that we're on this journey we call CWT 3.0, and what's really new about that is bringing in speed and agility into the conversation of if we have something that we imagine as a five year transformation, how do we get to market quickly with new products so that we can start really executing and seeing the outcomes of it? So we've always had the expectations around availability, around security, around all these other factors. Those aren't going away. Instead, we're adding a new one, so we've got new conversations and a new balance to reach at an executive level of we now need a degree of speed that was not the expectation, let's say, a decade ago. It may not even have been the expectation in our industry five years ago, but is today. And so we're now incorporating speed into that balance of maybe we'll decide to very intentionally say, "We're not going to go over quite as many nine's today "so that we can be iterating more quickly on our software." Or, "We're going to invest more "in better release management approaches and tools," right? Like Canary releases, like, you know, Green-Blue releases, all these sorts of new techniques, feature flags, that sort of thing so that we can better deal with speed and better account for the risk and spread it to the smallest surface area possible. >> And you were probably doing those things also to understand the impact and look at kind of what's that's coming in that you're instrumenting in infrastructure because you don't want to have to put it out there and pray and hope that it works. Right, I mean? The old way. >> The product teams that are building it are really great and really quick at understanding about what the user experience looks like. And whether that's their Real User monitoring tools or through, you know, other tools and tricks that we may incorporate to understand what our users are doing on our tools in real time, that's the important part of this, is to shorten the iteration cycle and to understand what things look like in production. You've got to expose that back to the software engineers, to the business analysts, to the product managers who are building it or deciding what should be built in the first place. >> All right, so now that you're on the buyer's side, you've actually got people knocking on your door. "Hey, Donnie, buy my cloud. "Do this, you know, I've got all these solutions. "I've got all these tools. "I've got a toolshed full of," you know, the fool with the tool, as they say. You don't want to be that person, right? So ultimately you've got to pick an environment that's going to scale. When you look at the cloud, how do you evaluate the different clouds? You mentioned gravity or data gravity earlier. All kinds of new criteria is up there now in terms of cloud selection. You mentioned best cloud for the job. I get that. Is there certain things that you look for? Is there a list? Is there criteria on cloud selection that goes through your desk? >> Yeah, I think something that's been really healthy for me coming into the enterprise side from the analyst perspective is you get a couple of new criteria that start to rise up real quickly. You start thinking about things like what's that vendor relationship going to look like? How is the sales force? Are they willing to work with you? Are they willing to adapt to your needs? And then you can adapt back with them so you can build a really strong, healthy relationship with some of your strategic vendors, and to me, a public cloud vendor is absolutely a strategic vendor. That's one where you have to really care a lot and invest in that relationship and make sure things go well when you're sailing together, going in the same direction. And so to me, that's a little bit of a newer factor because it was easy to sit back and come in as the strategic advisor role and say, "Oh, you should go with this cloud. "You should go with that cloud "because of reasons X, Y, or Z," but that doesn't really account for a lot of things that happen behind the scenes, right? What's your sourcing and human department doing? How do they like to work with around contract, right? Will you negotiate a good MSA? All these sorts of things where you don't think about that when you're only thinking about technology and business value. You also have to think about the other, just the day to day, what does it look like? What's the blocking and tackling working with some of those strategic vendors? So you've got that to incorporate in addition to the other criteria around do they have great managed services? You know, self-service managed services that will work for your needs? For example, what do they have around data bases? What do they have around stream processing? What do they have around serverless platforms, right? Whatever it might be that suits the kinds of needs you have. Like for example, you might think about what does our business look like, and it's a graph, right? It's travelers, it's airports, it's planes, it's hotels. It's a bunch of different graphs all intersecting, and so we might imagine looking for a cloud provider that's really well-suited to processing those sorts of workloads. >> In the old days, the networking guys used to run the keys to the kingdom. Hey, you know, I'm going to rack and stack servers. I'm going to do all this stuff, but I've got to go talk to the networking guys, make sure all the routes are provisional and all that's locked down, mainly because that was a perimeter environment then. With cloud now, what's the impact of the networking? What's the role of the network? As we see DevOps notion of infrastructure as code, you've got to compute networking stores as three main pillars of all environments. Compute, check. Stores getting better. Networking, can you imagine Randy Bias? This was a big pet peeve for him. What's the role that cloud does? What's the role of the network with your cloud strategy? >> Yeah, I think something that I've seen following DevOps for the past decade or so has been that, you know, it really started as the ops doing development moved more into the developers and the ops working together and in many cases sharing roles in different ways, then incorporated, you know, QA, and incorporated product, to some extent. Most recently it's really been focused on security and how do we have that whole DevSecOps, SecDevOps thing going on. Something that's been trailing behind a little bit was network, absolutely. I had some very close friends about 10 years ago, maybe, who were getting into that, and they were the only people they knew and they only people they'd ever even heard of thinking beyond the level of using some kind of an expect script to automate your network interaction. But now I think networking as code is really starting to pick up. I mean, you look at what people are doing in public cloud environments. You look at what Open Source projects like Ansible are doing or on the new focus on network functionality. They're not alone in that. Many others are investing in that same kind of area. It's finally really starting to get up. Like for example, we have an internal DevOps Day that we run twice a year, and at the most recent one, guess who one of our speakers was? It was a network engineer talking about the kinds of automation they'd been starting to build against our network environments, not just in public cloud, but also on-premise. And so we're really investing in bringing them into our broader DevOps community, even though Net may not be in the name today. I don't think the name can ever extend to include all possible roles. But it is absolutely a big transition that more and more companies, I think, are going to see rolling along, and one that we've seen happening in public cloud externally for many, many years now. It's been inevitable that the network's going to get engaged in that automation piece. And the network teams are going to be more and more thinking about how do we focus our time in automation and on defining policy, and how do we enable the product teams to work in a self-service way, right? We set up the governance, but governance now means they can move at speed. It doesn't mean wait seven to 30 days for us to verify all of the port openings, match our requirements, and so on and so forth. That's defined up front. >> Yeah, and that's awesome, and I think that's the last leg of the stool in my opinion, and I think you nailed it. Making it operationally automation enabled, and then actually automating it. So, okay, before we get to the Open Source, one final question for you. You know, as you look at plan for the technologies around containers and microservices, what sounds a lot like networking constructs, provisioning, services. The role of stateless applications become a big part of that. As you look at those technologies, what are some of the things you're looking for and evaluating containers and microservices? And what role will that play in your environment and your job? >> I think something that we spend a lot of time focusing on is what is the day two experience going to look like? What is it going to be like? Not just to roll it out initially, but to, you know, operate on an ongoing basis, to make upgrades, to monitor it, to understand what's happening when things are going wrong, to understand, you know, the security stance we're at, right? How well are we locked down? Is everything up-to-date? How do we know that and verify it on a continuous basis instead of the, you know, older school approach of hey, we kind of do a ECI survey or an audit, you know, once a year, and that's the day we're in compliance, and then after that, we're not. Which I was just reading some stories the other day about companies saying, "Hey, there's a large percentage "of the time that you're out of compliance, "but you make sure to fix it just in time "for your quarterly surveys or scans or what have you." And so that's what we spend a lot of our time focusing on is not just the ease of installation, but the ease of ongoing operability and getting really good visibility into the security, into the health, of the underlying platforms that we're running. And in some cases, that may push us to, let's say, a cloud managed service. In some cases, we may say, "Well, that doesn't quite suit our needs." We might have some unique requirements, although I spend a lot of my time personally saying, "In most cases, we are not a snowflake, right?" We should be a snowflake where we differentiate as a company. We should not be a snowflake at the level of our monitoring tools. There's nothing unique we should really be doing in that area. So how can we make sure that we use, whether it's trusted vendors, trusted cloud providers, or trusted Open Source projects with a large and healthy community behind them to run that stuff instead of build it ourselves, 'cause that's not our forte. >> I love that. That's a great conversation I'd love to have with you another time around competitive advantage around IT which is coming back in vogue again. It hasn't been that way in awhile because of all the consolidation and outsourcing. You're seeing people really, really ramp up and say, "Wait a minute, we outsourced our core competency and IT," and now with cloud, there's a competitive advantage, so how do you balance the intellectual property that you need to build for the business and then also use the scale and agility with Open Source? So I want to move to that Open Source conversation. I think this is a good transition. Developers at the end of the day still have to build the apps and services they're going to run on these environments to add value. So Open Source has become, I won't say a professional circuit for developers. It really is become the place for developers because that's where now corporations and projects have been successful, and it's going to a whole nother level. Talk about how Open Source is changing, and specifically around it becoming a common vehicle for one, employees of companies to participate in as part of their job, and two, how it's going to a whole nother level with all this code that's flying around. You can't, you know, go dig without finding out that, you know, new TensorFlow library's been donated for Google, big code bases are being rolled in there, and still the same old success formula for Open Source is continuing to work. You're on the program chair for Open Source summit, which is part of the Linux foundation, which has been very, very successful in this modern era. How has that changed? What's going on in Open Source? And how does that help people who are trying to stand up architecture and build businesses? >> I think Open Source has gone through a lot of transitions over the past decade or so. All right, so it started, and in many ways it was driven by the end users. And now it's come back full circle so that it's again driven more and more by the end users in a way that there was a middle term there where Open Source was really heavily dominated by vendors, and it's started to come back around, and you see a lot of the web companies in particular, right? You're sort of Googles and Amazons and LinkedIns and Facebooks and Twitters, they're open sourcing tools on an almost daily basis, it feels like. I just saw another announcement yesterday, maybe the day before, about a whole set of kernel tools that I think it was Facebook had open sourced. And so you're seeing that pace just going so quickly, and you think back to the days of, for example, the Apache web server, right? Where did that come about from? It didn't come from a software vendor. It came from a coalition of end users all working together to develop the software that they needed because they felt like there's a big gap there and there's an opportunity to cooperate. So it's been really pleasing for me to see that kind of come back around full circle of now, you can hardly turn around and see a company that doesn't have some sort of Open Source program office or something along those lines where they start to develop a much more healthy approach to it. All right, the early 2000's, it was really heavy on that fear and uncertainty and doubt around Open Source. In particular by some vendors, but also a lot of uncertainty because it wasn't that common, or maybe it wasn't that visible inside of these Fortune 500 global 2000 companies. It may have been common, right? What we used to say back when I worked at RedMonk was you turned around, and you asked the database admins, you know, "Are you running MySQL? "Or are you running Postgres?" You asked the infrastructure engineers, "Are you running Linux here?" and you'll get a yes, nine times out of ten, but the CIO was the last to know. Well now, it's started to flip back around because the CIO's are seeing the business value and adopting Open Source and having a really healthy approach to it, and they're trying to kind of normalize the approach to it as a consequence to that, saying, "Look, it's awesome "that we're adopting Open Source. "We have to use this "so that we can get a competitive advantage "because every thousand lines of code we can adopt "is a thousand lines of code we don't have to write, "and we can focus on our own products instead." And then starting to balance that new model of it used to be, you know, is it buy versus built? And then Sass came around, and it's buy versus build versus rent. And now there's Open Source, and it's buy versus build versus rent versus adopt. So every one of these just shifts conversation a little bit of how do you make the right choice at the right time at the right level of the stack? >> Yeah, that's a great observation, and it's awesome insight. It feels like dumping a little bit, a lot of dumping going on in Open Source, and you worry that the flood of vendor-contributed code is the new tactic, but if you look at all the major inflection points from the web, you know, through bitcoin, which is now 10 years old this year, it all started out as organic community projects or conversations on a message board. So there's still a revolution, and I think you're right. Their script is flipping around. I love that comment about the CIO's were last to know about Open Source. I think now that might be flipping around to the CIO's will be last to know about some proprietary advantage that might come out. So it's interesting to see the trend where you're starting to see smart people look at using Open Source but really identifying how they can use their engineering and their intellectual capital to build something proprietary within Open Source for IT advantage. Are you seeing that same trend? Is that on the radar at all? Is that just more of a fantasy on my part? >> I think it's always on the radar, and I think especially with Open Source projects that might be just a little bit below the surface of where a company's line of business is, that's where it will happen the most often. And so, you know, if you were building an analytics product, and you decided to build it on top of, you know, maybe there's the ELK Stack or the Elastic Stack, or maybe there's Graylog. There's a bunch of tools in that space, right? Maybe, you know, Solar, that sort of thing. And you're building an analytics tool or some kind of graph tool or whatever it might be, yeah, you might be inclined to say, "Well, the functionality's not quite there. "Maybe we need to build a new plugin. "Maybe we need to enhance a little bit." And I think this is the same conversation that a lot of the Linux kernel embedded group went through some number of years ago, which is, it's long term a higher burden to maintain a lot of those forks in-house and keep updating them forever than it is to bring some of that functionality back upstream. That's a good, healthy dialogue that hopefully will be happening more and more inside a lot of these companies that are taking Open Source and enhancing it for their own purposes, is taking the right level of those enhancements, deciding what that right level is, and contributing those back upstream and building a really healthy upstream participation regardless of whether you're a software vendor or an adopter of that software that uses it as a really critical part of their product stack. >> Awesome, Donnie, thanks for spending the time chatting with me today. Great to see you, great to connect over our remote here in our studio in Palo Alto. A final question for you. Are you having fun, these days? And what are you most excited about because, again, you've seen. You've been on multiple sides of the table. You've seen what the vendors have. You actually had the realities of doing your job to build value for Carlson Wagonlit Travel, CWT. What are you excited about right now? What's hot for you? What's jazzing you these days? >> Yeah, I think what's hot for me is, you know, to me there's nothing or very little that's revolutionary in technology. A lot of it is evolutionary, right? So you can't say nothing's new. There's always something a little bit different. And so the serverless is another example of something that it's a little bit different. It's a little bit new. It's similar to some previous takes, but you got new angles, specifically around the financials and around, you know, how do you pay? How is it priced? How do you get really almost closer to the metal, right? Get the things you need to happen closer to the way you're paying for them or the way they're running. That's remains a really exciting area for me. I've been going to Serverlessconf for probably since the first or second one now. I haven't been to the most recent one, but you know, there's so much value left in there to be tapped that I'm not yet really on to say, "What's next? What's next?" I've helped myself move out of that analyst world of getting excited about what's next, and for me it's now, "What's ready now?" Where can I leverage some value today or tomorrow or next week? And not think about what's coming down the pipe. So for me, that's, "Well, what went GA?" Right? What can I pick up? What can I scale inside our company so that we can drive the kinds of change we're looking for? So, you know, you asked me what am I the most excited about right now, and it's being here a year and a half and seeing the culture change that I've been driving since day one start to come back. Seeing teams that have never built automation in their lives independently go and learn it and build some automation and save themselves 80 hours a month. That's one example that just came out of our group a couple months back. That's what's valuable for me. That's what I love to see happen. >> Automation's addicting. It's almost an addictive flywheel. We automate something. Oh, that's awesome. I can move on to something else, something better. That was grunt work. Why do I want to do that again? Donnie, thanks so much, and again, thanks for the insight. I appreciate you taking the time and sharing with theCUBE here in our studio. Donnie Berkholz is the VP of IT source of CWT, a great guest. I'm John Furrier here inside theCUBE studio in Palo Alto. Thanks for watching. (lively music)

>> Announcer: Live, from Washington DC, it's theCube. Covering .conf2017 Brought to you by splunk. >> Welcome back inside the Walter Washington Convention Center. We're at .conf2017 in Washington DC, the nations capital, it is alive and well and thriving. A little warm out there, almost 90 degrees. But hot topic inside here, Dave. >> There's a lot of heat in this city. (laughter) >> A lot of hot air. >> Yeah, absolutely. >> We'll just leave it at that. Politics aside, of course. Joining us is Ben Miller, who is Director of High Thoughput Screening at Recursion Pharmaceuticals. Ben, thanks for being with us here on theCube. We appreciate the time. First off, I have many questions. First off let's talk about the company, what you do, and then what high throughput screening means, and how that operation comes into play when you have this great nexus of biology and engineering that you've brought together. >> Recursion Pharmaceuticals is treating drug discovery as a facial recognition problem. We're applying machine-learning concepts to biological images to help detect what types of drugs can rescue what types of diseases. We're one of the few companies that is both generating and analyzing our own data. As the director of the high throughput screening group, what I do is generate images for our data science teams to analyze, and that means growing human cells up in massive quantities, perturbing them with different types of disease reagents that cause their morphology to change, and then photographing them in the presence of compounds and in the absence of compounds. So we can see which compounds cause these disease states to revert more to a normal state for the cell. >> Okay, HTS then ... Walk us through that if you would. >> HTS is a general term that's used in the pharmaceutical industry to denote a assay that is executed in very large scale and in parallel. We tend to work on the order of multiples of 384 experiments per plate. We're looking at hundreds of thousands of images per plate, and we're looking at hundreds of plates per week. So when we say high throughput, we mean 6-10 terabytes of data per day. >> Just extraordinary amounts of data. And the mission, as we understand it, you're looking at very rare genetic diseases, your goal is to find cures for these over the next 15-20 years. Up to 100 of them, so that's why you're going through this multiple examinations of vast amounts of data. Human data. >> Yeah, there's been a trend in the pharmaceutical industry over the last years, where the number of dollars spent per drug developed is increasing. And it now takes over one billion dollars to bring a drug to market. And every year it costs more to bring a drug to market. We believe we can change that by operating at a massively parallel scale and also analyzing image data at a truly deep level. Looking at thousands of different features per image, instead of just a single feature in the image. >> That business is just like this vicious cycle going on, and you guys are trying to break it. >> Yes, exactly. >> So what's the state of facial recognition been? I've had mixed reviews about it. Because I rave about it, I go, "Oh my God, "Facebook tagged me again, it must be really good." And then other's have told me, "Well it's not really "as reliable as you might think." What is your experience been? >> The only experience I've had with facial recognition has been like yours, on Facebook and things like that. What we're doing is looking more at cellular recognition. Being able to see differences in these cellular morphologies. I think there are some unique challenges when you're looking at images of thousands of cells, versus images of a single person's face. >> Okay, so you've taken that concept down to the cell level and it's highly accurate, presumably. >> It's highly reproducible is what I would say, yeah. >> So it takes some work to be accurate, and once you get it there you can reproduce that, is that right? How does the sequence work? >> Yes, so there are two parts to the coin. One is how consistently we can produce these images and then how consistently those images represent the disease state. My focus is on making the images as consistent as they can be, while realizing that the disease states are all unique. So from our perspective, we're looking at thousands of different features in each image, and figuring out how consistent those features are from image to image. >> So paint a picture of your data stack, if you will. Infrastructure on up to the apps, and where splunk fits in. >> Sure. So I guess you could say that our data stack actually begins at hospitals around the world where human cells are collected from various medical waste samples. We culture those up, perturb them with different reagents, add different potential drugs back to them, and then photograph them. So at the beginning of our stack we've got biological agents that are mixed together and then photographs are generated. Those photographs are actually .tif files, and we have thousands and thousands of them. They're all uploaded in to Amazon Web Services, their S3 system. We spin up a near infinite number of virtual computers to process all of that image data within a couple of hours. And then produce a result. This drug makes this disease model look more like healthy and doesn't have other side effects. We're really reducing those thousands of dimensions in our image down to two. How much does it look like a healthy cell, and how much does it just look different then it should. >> And where does splunk fit into that stack? >> All of those instruments that are generating that data are equipped with splunk forwarders. So splunk is pulling all of our operational data from the laboratory together, and marrying it up with the image analysis that comes from our proprietary data analysis system. So by looking at the data that we're generating, how many cells we're counting, how bright the intensity of the image is, comparing that back to which dispenser we used, how long the plates sat at room temperature, et cetera. We can figure out how to optimize our production process so that we get reliable data. >> It's essentially storing machine data in the splunk data store. And then do you have an image database for ...? >> Yeah. And the image database is incredibly large. I wouldn't even guess at the current size. >> Dave: And what is it? Is it something on Amazon, an Amazon service? >> Yeah. So right now all of our image data is stored on AWS. >> This is one of those interviews Dave that the subject matter kind of trumps the technology because I want to know how it works. But you need the technology obviously to drive it. So I'm trying to figure out, "Alright, so you're taking "human cells and you're taking snapshots in time, "and then looking at how they react "to certain perturbed actions." But how does that picture of maybe one person's cell reacting to a reagent to another person's ... How does your data analysis provide you with some insight because Dave's DNA is different from my DNA, different from everybody in this building, so ultimately how are you combing through all of that data to make sense of it. >> That's true. Everybody has a unique genetic fingerprint, but everybody is susceptible to the same sets of major diseases. By looking at these images, and really that's the billion dollar question, is how representative are these individual cellular images, how representative are they of the general human population? And the effects that we see at a cellular level, will they translate in to human populations? We're very close to clinical trials on several compounds, but that's when we will really find out how much proof there is in this concept. >> Okay. You can't really predict ... Do you have a timeframe or is just sort of, "Keep going, keep getting funding until you reach the answer?" Is it like survive until you thrive? >> I personally don't maintain that kind of timeline. My role is within the laboratory producing the data as quickly as we can. We do have a goal of treating 100 different diseases in the next 10 years. And it's really early days, we're about 2 1/2 years in to that goal. It seems like we're on track, but there's still a lot of work to be done between now and then. >> So it's all cloud, right? And then splunk is throughout that stack, as we talked about. How do you envision, or do you envision, using it differently? Are you trying to get more out of the splunk platform? What do you want to see from splunk? >> That's a good question. I think right now we're using really the rudimentary basic features of splunk. Their database-connect app and their Machine Learning Toolkit are both pretty foundational to the work that we do. But right now a lot of our data models are one time use. We do a particular analysis to find the root cause of a particular problem, we learn that, and that's the last time we use that model. Continuous implementation of data models is something that is high on my list to do. As well as just ingesting more and more data. We're still fairly siloed. Our temperature and humidity data is separate from our machine data, and bringing that all into splunk is on the list. >> Why are your models disposable? It sounds like it's not done on purpose, it's more of some kind of infrastructure barrier? >> We're really at the cutting edge of technology right now, and we're learning a lot of things that people haven't learned, that in retrospect are obvious. To figure out the true cause of a particular situation, a data model or a machine-learning model is really valuable, but once you know that key salient fact, you don't need to keep track of it over time. You don't need to know that when your tire pressure is low your car gets less miles to the gallon. >> David: You have the answer. >> Right. But there are a lot of problems like that in our field that have not been discovered yet. >> I inferred from your answer you do see the potential to have some kind of ongoing model evolution. For new use cases? >> In the extreme situation we have a set of hundreds of operational parameters that are going into producing this image of cells. And then we have thousands of cellular features that are extracted from that image. There's a machine-learning problem there. What are the optimal parameters to extract the optimal information? And that whole process could be automated to the point where we're using machine-learning to optimize our assay. To me that's the future of what we want to do. >> Were you with Recursion when they brought in splunk? >> Yeah. >> You were. Did you look at alternatives? Did you look at maybe rolling your own with open source? Is that even feasible? Wonder if you could talk about that. >> I had already been introduced to splunk at my previous job, and at that previous company, before I heard of splunk, I was starting to roll my own. I was writing a ton of Perl scripts, and all of these regular expressions, and searching network drives to pull log files together. And I thought that maybe there would be a good business model behind that. >> You were building splunk. (laughter) >> And then I found splunk, and those guys were so far ahead of things I was trying to do on my own in a lab. So for me it was a no-brainer. But for our software engineering team, they are really dedicated to open source platforms whenever possible. They evaluated the ELK Stack. Some of us had used Sumo Logic and things like that. But for me, splunk had the right license model and I could get off the ground really really rapidly with it. >> What about the license model was attractive to you? >> Unlimited users, and only paying for the data that we ingest. The ability to democratize that data, so that everybody in the lab can go in and view it and I don't have to worry about how many accounts I'm creating. That was really powerful. >> Dave: So you like the pricing model. >> Yeah. >> Some users have chirped about the pricing, I saw some Wall Street concerns about the pricing. The guys that we've talked to on theCube today have said, "They like the pricing model, that there's value there." And you're sort of confirming that. >> Ben: Yeah. >> You're not concerned about the exponential growth of you data causing your license fees to go through the roof >> In the laboratory, the image data that we're generating is exponentially growing, but the operational parameter data is more linearly growing. >> Dave: So it's under control basically. >> Yeah, for our needs it is. >> Dave: You're not paying for the images, you're paying for the meta data around that. >> Yeah. >> Well it's a fascinating proposition, it really is. Very eager to keep up with this, keep track, and see the progress. Good luck with that. Look for having you back on theCube to monitor that progress, alright Ben? >> Great. Very good, thank you so much. Ben Miller joining us from Salt Lake City, good to have you here. Back with more on theCube in just a bit. You're watching our live coverage of .conf2017. (upbeat innovative music)

>> ANNOUNCER: Live from Las Vegas, it's theCUBE. Covering VM World 2017. Brought to you by Vmware and its ecosystem partner. >> Hi, I'm Stu Miniman here with John Troyer and excited to welcome back to the program Chris Wahl, who's the Chief Technologist at Rubrik. Chris, thanks for joining us. >> Oh, my pleasure. It's my first VMworld CUBE appearance so I'm super stoked. >> Yeah, we're pretty excited that you hang out with, you know, just a couple of geeks as opposed to, what's it Kevin Durant and Ice Cube. Is this a technology conference or Did you and Bipple work for some Hollywood big time company? >> It's funny you say that, they'll be more tomorrow. So I'll allude to that. But ideally, why not hang out with some cool folks. I mean I live in Oakland. Hip Hop needs to be represented and the Golden State Warriors. >> It's pretty cool. I'm looking forward to the party. I know there will be huge lines. When Katie comes to throw down with a bunch of people. So looking forward to those videos. So we've been looking at Rubrik since, you know, came out of stealth. I got to interview Bipple, you know, really early on, so we've been watching. What you're on like the 4.0 release now right? How long has that taken and you know why don't you bring us up to speed with what's going on with Rubrik. >> Yeah, it's our ninth, our ninth major release over basically eight quarters. And along with that, we've announced we've hit like a 150 million dollar run rate that we've included when we started it was all about VMWare, doing back-ups providing those back-ups a place to land, meaning object store or AWS S3. And now it's, we protect Hyper-V, Acropolis from Nutanix, obviously the VMWare Suite, we can do archive to Azure, we can do, there's like 30 some-odd integration points. With various storage vendors, archive vendors, public cloud, etcetera. And the ulta release which is 4.0, just really extends that because now, not only can we provide backups and recovery and archive, which is kind of our bread and butter. But you can archive that to public cloud and now you can start running those workloads. Right, so what we call a cloud on, I can take either on demand or archive data that's been sent to S3, and I can start building virtual machines, like I said on demand. I can take the AMI, put it in EC2 and start running it right now. And I start taking advantage of the services and it's a backup product. Like, that's what always kind of blows my mind. This isn't, that's not the use case, it's one thing that we unlock from backup to archive data >> One of the challenges I usually see out there, is that people are like, oh Rubrik, you know they do backups for VMWare, how do you, you know, you're very much involved in educating and getting out there and telling people about it, how do you get over the, oh wait you heard what we were doing six months ago or six weeks ago, and now we're doing so much more. So how do you stay up with that? >> It's tough to keep up obviously, because every quarter we basically have either some kind of major or a dot release that comes out. I mean realistically, I set the table a little bit differently, I say, what are you looking to do? What are the outcomes that you're trying to drive? Simplicity's a huge one because everyone's dealing with I have a backup storage vendor and I have a storage vendor, and I have tape vendor, and all this other hodge podge things that they're dealing with. They're looking to save money, but ultimately they're trying to automate, start leveraging the cloud. Start really like, taking the headache out of providing something that's very necessary. And when I start talking about the services they can add, beyond that, because it's not just about taking a backup, leaving it in some rotting archive for 10 years, or whatever, it's really what can I do with the data once I have this duplicated and compressed, kind of pool, that I can start drawing from. And that's where people start to, their mind gets blown a little bit. Now that the individual features and check boxes sets, it is what it is, you know, like if you happen to need Hyper-V or Acropolis or whatever, it's really just where you are on that journey to start taking advantage of this data. And I think that's where people start to get really excited and we start white boarding and nerding out a little bit. >> Well Chris, so don't keep us in suspense, what kinds of things can you do once you have a copy of this data? It's still, it's all live, it's either on solid state or spinning disk or in the cloud somewhere. That's very different than just putting it on tape, so what do I do now, that I have all this data pool? >> So probably the most common use case is, I have VBC and a security group in Amazon. That exists today. I'm archiving to S3 in some way, shape, or form. Either IA or whatever flavor vessel you want. And then you're thinking, well I have these applications, what else can I do with them? What if I put it to a query service or a relational data base service, or what if I sped up 10 different copies because I need to for lode testing or some type of testing. I mean it all falls under the funnel of dev test, but I hate just capping it that way, because I think it's unimaginative. Realistically, we're saying here you have this giant pile of compute, that you're already leveraging the storage part of it, you the object store that is S3. What if you could unlock all the other services with no heavy lift? And the workload is actually built as an AMI. Right, so an ami, it's actually running an EC2, so there's no, you don't necessarily have to extend the Hyper Visor layer or anything like that. And it's essentially S3 questions, from the product perspective. It's you know, what security group, BCP, and shape of the format you want it to be. Like large, small, Xlarge, et cetera. That's it. So think about unlocking cloud potentials for less technical people or people that are dipping their toe in a public cloud. It really unlocks that ability and we control the data plane across it. >> Just one thing on that, because it's interesting, dev tests a lot of times, used to get shoved to the back. And it was like, oh you can run on that old gear, you know you don't have any money for it. We've actually found that it can increase, kind of the companies agility and development is a big part of creating big cool things out of a company, so you don't under sell what improving dev tests can do. So did you have some customer stories or great things that customers have done with what this capability has. >> Yeah, but to be fair, at first when I saw that we were going to start, basically taking VMWare backups and pushing that in archive and then turning those into EC2 instances of any shape or quantity. I was like, that's kind of crazy, who has really wanted that Then I started talking to customers and it was a huge request. And a lot of times, my architectural background would think, lift and shift, oh no, don't necessarily do that. I'm not a huge fan of that process. But while that is certainly something you can do, what they're really looking to do is, well, I have this binary package or application suite that's running on Elk Stack or some Linux distro, or whatever, and I can't do anything with that because it's in production and it's making me money, but I'd really like to see what could be done with that? Or potentially can I just eliminate it completely and turn it into a service. And so I've got some customers that completely what they're doing, they're archiving already and what they have the product doing is every time a new snapshot is taken and is sent to the cloud, it builds automatically that EC2 instance, and it starts running it. So they have a collection of various state points that they can start playing with. The actual backup is immutable, but then they're saying, alright, what if exactly what I kind of alluded to a little, what if I start using a native service in the cloud. Or potentially just discard that workload completely. And start turning it into a service, or refactor it, re platform it et cetera. And they're not having to provision, usually you have to buy infrastructure to do that. Like you're talking about the waterfall of Chinese stuff, that turns into dev stuff three years later. They don't have to do that, they can literally start taking advantage of this cloud resource. Run it for an hour or so, because devs are great at CDIC pipelines, let's just automate the whole stack, let's answer our question by running queries through jenkins or something like that. And then throw it away and it cost a couple of bucks. I think that's pretty huge. >> Well Chris, can you also use this capability for DR, for disaster recovery? Can you re hydrate your AMI's up there if everything goes South in your data center? >> Absolutely. I mean it's a journey and this is for dot zero. So I'm not going to wave my hands and say that it's an amazing DR solution. But the third kind of use case that we highlight with our product is that absolutely. You can take the work loads either as a planned event, and say I'm actually putting it here and this is a permanent thing. Or an unplanned event, which is what we all are trying to avoid. Where you're running the work loads in the cloud, for some deterministic period of time, and either the application layer or the file system layer, or even, like a data base layer, you're then protecting it, using our cloud cluster technology, which is Rubrik running in the cloud. Right there, it has access to S3 and EC2, you know, adjacently, there is not net fee and then you start protecting that and sending the data the other way. Because Rubriks software can talk to any other Rubrik's software. We don't care what format or package it's in. In the future we'd like to add more to that. I don't want to over sell it, but certainly that's the journey. >> Chris tell us about how your customers are feeling about the cloud in general. You know you've lived with the VM community for a lot of years, like many of us, and that journey to cloud and you know, what is Hybrid and multi-cloud mean to them, and you know, what you've been seeing at Rubrik over the last year. >> Yeah it's ahh, everybody has a different definition between hybrid, public, private-- >> Stu: Every customer I ever talked to will have a different answer to that. >> I just say multi cloud, because it feels the most safe And the technically correct version of that definition. It's certainly something that, everyone's looking to do. I think kind of the I want to build a private cloud phase of the journey is somewhat expired in some cases. >> Stu: Did you see Pat's keynote this morning? >> Yeah, the I want to build a private cloud using open stack and you know, build all my widgets. I feel that era of marketing or whatnot, that was kind of like 2008 or 2010. So that kind of era of marketing message has died a little bit. It's really just more I have on prem stuff, I'm trying to modernize it, using hyper-converge, or using software to find X, you know, networking et cetera But ultimately I have to start leveraging the places where my paths, my iya's and my sas are going to start running. How do I then cobble all that together. I mean at the sea level, I need visibility, I need control, I need to make executable decisions. That are financially impactful. And so having something they can look across to those different ecosystems, and give you actionable data, like here's where it's running, here's where it could run, you know, it's all still just a business decision, based on SLA. It's powerful. But then as you go kind of down message for maybe a director or someone's who's managing IT, that's really, someone's breathing down their neck, saying, we've got to have a strategy. But they're technically savvy, they don't want to just put stuff in the cloud and get that huge bill. Then they have to like explain that as well. So it kind of sits in a nice place where we can protect the modern apps, or kind of, I guess you can call them, modern slash legacy in the data center. But also start providing protection at a landing pad for the cloud native to use as an over watch term The stuff that's built for cloud that runs there, that's distributed and very sensitive to the fact that it charges per iota of use at the same time. >> Well Chris, originally Rubrik was deploying to customers as an appliance, right? So can you talk a little bit about that, right, you have many different options now, the customer, right? You can get open source, you can get commercial software, or you can get appliances, you can get SAS, and now it sounds like you're, there's also a piece that can run in the cloud, right? That it's not just a box that sits in a did center somewhere So can you talk about, again, what do customers want? What's the advantage of some of those different deployment mechanisms, what do you see? >> I'm not saying this as a stalling tactic, but I love that question. Because yes, when we started it made sense, build a turnkey appliance, make sure that it's simple. Like in deployment, we used to say it can deploy in an hour and that includes the time to take it out of the box and that only goes so far because that's one use case. So certainly, for the first year or so, the product that was where we were driving it, as a scale out node based solution then we added Rubrik edge as a virtual appliance. And really it was meant to, I have a data center and I'm covering those remote offices, type use cases. And we required that folks kind of tether the two, because it's a single node that's really just a suggesting data and bringing it back using policy. Then we introduced cloud cluster in 3.2 which is a couple of releases ago. And that allows you to literally build a four plus node cluster as your AWS, basically you give us your account info and we share the EMI with you or the VM in case of Azure and then you can just build it, right? And that's totally independent, like you can just be a customer. We have a couple of customers that are public, that's all they do, they deploy cloud cluster they backup things in that environment. And then they replicate or archive to various clouds or various regions within clouds. And there's no requirement to buy the appliance because that would be kind of no bueno to do that. >> Sure. >> So right, there's various packages or we have the idea now where you can bring your own hardware to the table. And we'll sell you the software, so like Lenovo and Cisco and things like that. It can be your choice based on the relationships you have. >> Wow Chris your teams are gone a lot, not just your personal team but the Rubrik team I walked by the booth and wait, I saw five more people that I know from various companies. Talk about the growth of like, you know Rubrik. You joined a year ago and it felt like a small company then. Now you guys are there, I get the report from this financial analyst firms and like, have you seen the latest unicorn, Rubrik and I'm like, Rubrik, I know those guys. And gals. So yeah absolutely, talk about the growth of the company. What's the company hiring for? Tell us a little bit about the culture inside. >> Sure, I mean, it's actually been a little over two years now that I've been there, it's kind of flying. I was in the first 50 hires for the company. So at the time I felt like the FNG, but I guess now, I'm kind like the old, old man. I think we're approaching or have crossed the 500 employee threshold and we're talking eight quarters essentially. A lot of investment, across the world, right, so we decided very early on to invest in Europe as a market. We had offices in Utruck in the Netherlands. And in London, the UK, we've got a bunch of engineering folks in India. So we've got two different engineering teams. As well as, we have an excellent, center of excellence, I think in Kansas City. So there's a whole bunch of different roots that we're planting as a company. As well as a global kind of effort to make sales, support, product, engineering, marketing obviously, something that scales everywhere. It's not like all the engineers are in Palo Alto and Silicone Valley and everyone else is just in sales. But we're kind of driving across everywhere. My team went from one to six. Over the last eight or nine months. So everything is growing. Which I guess is good. >> As part of that you also moved to Silicone Valley and so how does it compare to the TV show. >> Chris: It's in Oakland. >> Well it's close enough to Silicone Valley. >> It's Silicone Valley adjacent. I will say I used to visit all the time, you know. For various events and things like that. Or for VM World or whatnot. I always got the impression that I liked being there for about a week and then I wanted to leave before I really started drinking the kool aid a little heavily so it's nice being just slightly on the east bay area. At the same time, I go to events and things now. More as a local and it's kind of awesome to hear oh I invented whatever technology, I invented bootstrap or MPM or something like that. And they're just available to chat with. I tried it at that the, the sunscreen song, where he says, you know, move to california, but leave before you turn soft. So at some point I might have to go back to Texas or something to just to keep the scaley rigidity to my persona intact. >> Yeah, so you missed the barbecue? >> Well I don't know if you saw Franklin's barbecue actually burned down during the hurricane, so. >> No >> Yeah, if you're a, a huge barbecue fan in Austin, weep a tear, it might be a bad mojo for a little bit. >> Wow. Alright, we were alluding at the very beginning of the interview, you've got some VIP guests, we don't talk too much about, like, oh we're doing this tomorrow and everything, but you got some cool activities, the all stars, you know some of the things. Give us a little viewpoint, what's the goal coming into VM World this year and what are some of the cool things that you're team and the extended team are doing. >> Yeah, so kind of more on the nerdy fun side, we've actually built up, one of my team, Rebecca Fitzhughes build out this V all stars card deck so we picked a bunch of infuencers, and people that, you know friends and family kind of thing built them some trading cards and based on what you turn in you can win prizes and things like that. It was just a lot of other vendors have done things that I really respect. Like Solid Fire has the socks and the cards against humanity as an example. I wanted to do something similar and Rebecca had a great idea. She executed on that. Beyond that though, we obviously have Ice Cube coming in. He's going to be partying at the Marquis on Tuesday evening so he'll be, he'll be hanging around, you know the king of hip hop there. And on a more like fun, charitable note, we actually have Kevin Durant coming in tomorrow. We are shooting hoops for his charity fund. So everybody that sinks a goal, or ahh, I'm obviously not a basket ball person, but whoever sinks the ball into the hoop gets two dollars donated to his charity fund and you build it to win a jersey and things like that. So kind of spreading it across sports, music, and various digital transformation type things. To make sure that everyone who comes in, has a good time. VMWare's our roots, right? 1.0, the product was focused on that environment. It's been my roots for a long time. And we want to pay that back to the community. You can't forget where you came from, right? >> Alright, Chris Wahl, great to catch up with you. Thanks for joining us sporting your Alta t-shirt your Rubrik... >> I'm very branded. >> John Troyer and I will be back with lots more coverage here at VM World 2017, you're watching theCUBE.