(soft electronic music) >> Okay, we're back with Tim Yocum who is the Director of Engineering at InfluxData. Tim, welcome, good to see you. >> Good to see you, thanks for having me. >> You're really welcome. Listen, we've been covering opensource software on theCUBE for more than a decade and we've kind of watched the innovation from the big data ecosystem, the cloud is being built out on opensource, mobile, social platforms, key databases, and of course, InfluxDB. And InfluxData has been a big consumer and crontributor of opensource software. So my question to you is where have you seen the biggest bang for the buck from opensource software? >> So yeah, you know, Influx really, we thrive at the intersection of commercial services and opensource software, so OSS keeps us on the cutting edge. We benefit from OSS in delivering our own service from our core storage engine technologies to web services, templating engines. Our team stays lean and focused because we build on proven tools. We really build on the shoulders of giants. And like you've mentioned, even better, we contribute a lot back to the projects that we use, as well as our own product InfluxDB. >> But I got to ask you, Tim, because one of the challenge that we've seen, in particular, you saw this in the heyday of Hadoop, the innovations come so fast and furious, and as a software company, you got to place bets, you got to commit people, and sometimes those bets can be risky and not pay off. So how have you managed this challenge? >> Oh, it moves fast, yeah. That's a benefit, though, because the community moves so quickly that today's hot technology can be tomorrow's dinosaur. And what we tend to do is we fail fast and fail often; we try a lot of things. You know, you look at Kubernetes, for example. That ecosystem is driven by thousands of intelligent developers, engineers, builders. They're adding value every day, so we have to really keep up with that. And as the stack changes, we try different technologies, we try different methods. And at the end of the day, we come up with a better platform as a result of just the constant change in the environment. It is a challenge for us, but it's something that we just do every day. >> So we have a survey partner down in New York City called Enterprise Technology Research, ETR, and they do these quarterly surveys of about 1500 CIOs, IT practitioners, and they really have a good pulse on what's happening with spending. And the data shows that containers generally, but specifically Kubernetes, is one of the areas that is kind of, it's been off the charts and seen the most significant adoption and velocity particularly along with cloud, but really, Kubernetes is just, you know, still up and to the right consistently, even with the macro headwinds and all of the other stuff that we're sick of talking about. So what do you do with Kubernetes in the platform? >> Yeah, it's really central to our ability to run the product. When we first started out, we were just on AWS and the way we were running was a little bit like containers junior. Now we're running Kubernetes everywhere at AWS, Azure, Google cloud. It allows us to have a consistent experience across three different cloud providers and we can manage that in code. So our developers can focus on delivering services not trying to learn the intricacies of Amazon, Azure, and Google, and figure out how to deliver services on those three clouds with all of their differences. >> Just a followup on that, is it now, so I presume it sounds like there's a PaaS layer there to allow you guys to have a consistent experience across clouds and out to the edge, wherever. Is that correct? >> Yeah, so we've basically built more or less platform engineering is this the new, hot phrase. Kubernetes has made a lot of things easy for us because we've built a platform that our developers can lean on and they only have to learn one way of deploying their application, managing their application. And so that just gets all of the underlying infrastructure out of the way and lets them focus on delivering Influx cloud. >> And I know I'm taking a little bit of a tangent, but is that, I'll call it a PaaS layer, if I can use that term, are there specific attributes to InfluxDB or is it kind of just generally off-the-shelf PaaS? Is there any purpose built capability there that is value-add or is it pretty much generic? >> So we really build, we look at things with a build versus buy, through a build versus buy lens. Some things we want to leverage, cloud provider services, for instance, POSTGRES databases for metadata, perhaps. Get that off of our plate, let someone else run that. We're going to deploy a platform that our engineers can deliver on, that has consistency, that is all generated from code. that we can, as an SRE group, as an OPS team, that we can manage with very few people, really, and we can stamp out clusters across multiple regions in no time. >> So sometimes you build, sometimes you buy it. How do you make those decisions and what does that mean for the platform and for customers? >> Yeah, so what we're doing is, it's like everybody else will do. We're looking for trade-offs that make sense. We really want to protect our customers' data, so we look for services that support our own software with the most up-time reliability and durability we can get. Some things are just going to be easier to have a cloud provider take care of on our behalf. We make that transparent for our own team and of course, for our customers; you don't even see that. But we don't want to try to reinvent the wheel, like I had mentioned with SQL datasource for metadata, perhaps. Let's build on top of what of these three large cloud providers have already perfected and we can then focus on our platform engineering and we can help our developers then focus on the InfluxData software, the Influx cloud software. >> So take it to the customer level. What does it mean for them, what's the value that they're going to get out of all these innovations that we've been talking about today, and what can they expect in the future? >> So first of all, people who use the OSS product are really going to be at home on our cloud platform. You can run it on your desktop machine, on a single server, what have you, but then you want to scale up. We have some 270 terabytes of data across over four billion series keys that people have stored, so there's a proven ability to scale. Now in terms of the opensource software and how we've developed the platform, you're getting highly available, high cardinality time-series platform. We manage it and really, as I had mentioned earlier, we can keep up with the state of the art. We keep reinventing, we keep deploying things in realtime. We deploy to our platform every day, repeatedly, all the time. And it's that continuous deployment that allow us to continue testing things in flight, rolling things out that change, new features, better ways of doing deployments, safer ways of doing deployments. All of that happens behind the scenes and like we had mentioned earllier, Kubernetes, I mean, that allows us to get that done. We couldn't do it without having that platform as a base layer for us to then put our software on. So we iterate quickly. When you're on the Influx cloud platform, you really are able to take advantage of new features immediately. We roll things out every day and as those things go into production, you have the ability to use them. And so in the then, we want you to focus on getting actual insights from your data instead of running infrastructure, you know, let us do that for you. >> That makes sense. Are the innovations that we're talking about in the evolution of InfluxDB, do you see that as sort of a natural evolution for existing customers? Is it, I'm sure the answer is both, but is it opening up new territory for customers? Can you add some color to that? >> Yeah, it really is. It's a little bit of both. Any engineer will say, "Well it depends." So cloud-native technologies are really the hot thing, IoT, industrial IoT especially. People want to just shove tons of data out there and be able to do queries immediately and they don't want to manage infrastructure. What we've started to see are people that use the cloud service as their datastore backbone and then they use edge computing with our OSS product to ingest data from say, multiple production lines, and down-sample that data, send the rest of that data off to Influx cloud where the heavy processing takes place. So really, us being in all the different clouds and iterating on that, and being in all sorts of different regions, allows for people to really get out of the business of trying to manage that big data, have us take care of that. And, of course, as we change the platform, endusers benefit from that immediately. >> And so obviously you've taken away a lot of the heavy lifting for the infrastructure. Would you say the same things about security, especially as you go out to IoT at the edge? How should we be thinking about the value that you bring from a security perspective? >> We take security super seriously. It's built into our DNA. We do a lot of work to ensure that our platform is secure, that the data that we store is kept private. It's, of course, always a concern, you see in the news all the time, companies being compromised. That's something that you can have an entire team working on which we do, to make sure that the data that you have, whether it's in transit, whether it's at rest is always kept secure, is only viewable by you. You look at things like software bill of materials, if you're running this yourself, you have to go vet all sorts of different pieces of software and we do that, you know, as we use new tools. That's something, that's just part of our jobs to make sure that the platform that we're running has fully vetted software. And you know, with opensource especially, that's a lot of work, and so it's definitely new territory. Supply chain attacks are definitely happening at a higher clip that they used to but that is really just part of a day in the life for folks like us that are building platforms. >> And that's key, especially when you start getting into the, you know, that we talk about IoT and the operations technologies, the engineers running that infrastrucutre. You know, historically, as you know, Tim, they would air gap everything; that's how they kept it safe. But that's not feasible anymore. Everything's-- >> Can't do that. >> connected now, right? And so you've got to have a partner that is, again, take away that heavy lifting to R&D so you can focus on some of the other activities. All right, give us the last word and the key takeaways from your perspective. >> Well, you know, from my perspective, I see it as a two-lane approach, with Influx, with any time-series data. You've got a lot of stuff that you're going to run on-prem. What you had mentioned, air gapping? Sure, there's plenty of need for that. But at the end of the day, people that don't want to run big datacenters, people that want to entrust their data to a company that's got a full platform set up for them that they can build on, send that data over to the cloud. The cloud is not going away. I think a more hybrid approach is where the future lives and that's what we're prepared for. >> Tim, really appreciate you coming to the program. Great stuff, good to see you. >> Thanks very much, appreciate it. >> Okay in a moment, I'll be back to wrap up today's session. You're watching theCUBE. (soft electronic music)

>>This past May, The Cube in collaboration with Influx data shared with you the latest innovations in Time series databases. We talked at length about why a purpose built time series database for many use cases, was a superior alternative to general purpose databases trying to do the same thing. Now, you may, you may remember the time series data is any data that's stamped in time, and if it's stamped, it can be analyzed historically. And when we introduced the concept to the community, we talked about how in theory, those time slices could be taken, you know, every hour, every minute, every second, you know, down to the millisecond and how the world was moving toward realtime or near realtime data analysis to support physical infrastructure like sensors and other devices and IOT equipment. A time series databases have had to evolve to efficiently support realtime data in emerging use cases in iot T and other use cases. >>And to do that, new architectural innovations have to be brought to bear. As is often the case, open source software is the linchpin to those innovations. Hello and welcome to Evolving Influx DB into the smart Data platform, made possible by influx data and produced by the Cube. My name is Dave Valante and I'll be your host today. Now in this program we're going to dig pretty deep into what's happening with Time series data generally, and specifically how Influx DB is evolving to support new workloads and demands and data, and specifically around data analytics use cases in real time. Now, first we're gonna hear from Brian Gilmore, who is the director of IOT and emerging technologies at Influx Data. And we're gonna talk about the continued evolution of Influx DB and the new capabilities enabled by open source generally and specific tools. And in this program you're gonna hear a lot about things like Rust, implementation of Apache Arrow, the use of par k and tooling such as data fusion, which powering a new engine for Influx db. >>Now, these innovations, they evolve the idea of time series analysis by dramatically increasing the granularity of time series data by compressing the historical time slices, if you will, from, for example, minutes down to milliseconds. And at the same time, enabling real time analytics with an architecture that can process data much faster and much more efficiently. Now, after Brian, we're gonna hear from Anna East Dos Georgio, who is a developer advocate at In Flux Data. And we're gonna get into the why of these open source capabilities and how they contribute to the evolution of the Influx DB platform. And then we're gonna close the program with Tim Yokum, he's the director of engineering at Influx Data, and he's gonna explain how the Influx DB community actually evolved the data engine in mid-flight and which decisions went into the innovations that are coming to the market. Thank you for being here. We hope you enjoy the program. Let's get started. Okay, we're kicking things off with Brian Gilmore. He's the director of i t and emerging Technology at Influx State of Bryan. Welcome to the program. Thanks for coming on. >>Thanks Dave. Great to be here. I appreciate the time. >>Hey, explain why Influx db, you know, needs a new engine. Was there something wrong with the current engine? What's going on there? >>No, no, not at all. I mean, I think it's, for us, it's been about staying ahead of the market. I think, you know, if we think about what our customers are coming to us sort of with now, you know, related to requests like sql, you know, query support, things like that, we have to figure out a way to, to execute those for them in a way that will scale long term. And then we also, we wanna make sure we're innovating, we're sort of staying ahead of the market as well and sort of anticipating those future needs. So, you know, this is really a, a transparent change for our customers. I mean, I think we'll be adding new capabilities over time that sort of leverage this new engine, but you know, initially the customers who are using us are gonna see just great improvements in performance, you know, especially those that are working at the top end of the, of the workload scale, you know, the massive data volumes and things like that. >>Yeah, and we're gonna get into that today and the architecture and the like, but what was the catalyst for the enhancements? I mean, when and how did this all come about? >>Well, I mean, like three years ago we were primarily on premises, right? I mean, I think we had our open source, we had an enterprise product, you know, and, and sort of shifting that technology, especially the open source code base to a service basis where we were hosting it through, you know, multiple cloud providers. That was, that was, that was a long journey I guess, you know, phase one was, you know, we wanted to host enterprise for our customers, so we sort of created a service that we just managed and ran our enterprise product for them. You know, phase two of this cloud effort was to, to optimize for like multi-tenant, multi-cloud, be able to, to host it in a truly like sass manner where we could use, you know, some type of customer activity or consumption as the, the pricing vector, you know, And, and that was sort of the birth of the, of the real first influx DB cloud, you know, which has been really successful. >>We've seen, I think like 60,000 people sign up and we've got tons and tons of, of both enterprises as well as like new companies, developers, and of course a lot of home hobbyists and enthusiasts who are using out on a, on a daily basis, you know, and having that sort of big pool of, of very diverse and very customers to chat with as they're using the product, as they're giving us feedback, et cetera, has has, you know, pointed us in a really good direction in terms of making sure we're continuously improving that and then also making these big leaps as we're doing with this, with this new engine. >>Right. So you've called it a transparent change for customers, so I'm presuming it's non-disruptive, but I really wanna understand how much of a pivot this is and what, what does it take to make that shift from, you know, time series, you know, specialist to real time analytics and being able to support both? >>Yeah, I mean, it's much more of an evolution, I think, than like a shift or a pivot. You know, time series data is always gonna be fundamental and sort of the basis of the solutions that we offer our customers, and then also the ones that they're building on the sort of raw APIs of our platform themselves. You know, the time series market is one that we've worked diligently to lead. I mean, I think when it comes to like metrics, especially like sensor data and app and infrastructure metrics, if we're being honest though, I think our, our user base is well aware that the way we were architected was much more towards those sort of like backwards looking historical type analytics, which are key for troubleshooting and making sure you don't, you know, run into the same problem twice. But, you know, we had to ask ourselves like, what can we do to like better handle those queries from a performance and a, and a, you know, a time to response on the queries, and can we get that to the point where the results sets are coming back so quickly from the time of query that we can like limit that window down to minutes and then seconds. >>And now with this new engine, we're really starting to talk about a query window that could be like returning results in, in, you know, milliseconds of time since it hit the, the, the ingest queue. And that's, that's really getting to the point where as your data is available, you can use it and you can query it, you can visualize it, and you can do all those sort of magical things with it, you know? And I think getting all of that to a place where we're saying like, yes to the customer on, you know, all of the, the real time queries, the, the multiple language query support, but, you know, it was hard, but we're now at a spot where we can start introducing that to, you know, a a limited number of customers, strategic customers and strategic availability zones to start. But you know, everybody over time. >>So you're basically going from what happened to in, you can still do that obviously, but to what's happening now in the moment? >>Yeah, yeah. I mean if you think about time, it's always sort of past, right? I mean, like in the moment right now, whether you're talking about like a millisecond ago or a minute ago, you know, that's, that's pretty much right now, I think for most people, especially in these use cases where you have other sort of components of latency induced by the, by the underlying data collection, the architecture, the infrastructure, the, you know, the, the devices and you know, the sort of highly distributed nature of all of this. So yeah, I mean, getting, getting a customer or a user to be able to use the data as soon as it is available is what we're after here. >>I always thought, you know, real, I always thought of real time as before you lose the customer, but now in this context, maybe it's before the machine blows up. >>Yeah, it's, it's, I mean it is operationally or operational real time is different, you know, and that's one of the things that really triggered us to know that we were, we were heading in the right direction, is just how many sort of operational customers we have. You know, everything from like aerospace and defense. We've got companies monitoring satellites, we've got tons of industrial users, users using us as a processes storing on the plant floor, you know, and, and if we can satisfy their sort of demands for like real time historical perspective, that's awesome. I think what we're gonna do here is we're gonna start to like edge into the real time that they're used to in terms of, you know, the millisecond response times that they expect of their control systems, certainly not their, their historians and databases. >>I, is this available, these innovations to influx DB cloud customers only who can access this capability? >>Yeah. I mean commercially and today, yes. You know, I think we want to emphasize that's a, for now our goal is to get our latest and greatest and our best to everybody over time. Of course. You know, one of the things we had to do here was like we double down on sort of our, our commitment to open source and availability. So like anybody today can take a look at the, the libraries in on our GitHub and, you know, can ex inspect it and even can try to, you know, implement or execute some of it themselves in their own infrastructure. You know, we are, we're committed to bringing our sort of latest and greatest to our cloud customers first for a couple of reasons. Number one, you know, there are big workloads and they have high expectations of us. I think number two, it also gives us the opportunity to monitor a little bit more closely how it's working, how they're using it, like how the system itself is performing. >>And so just, you know, being careful, maybe a little cautious in terms of, of, of how big we go with this right away, just sort of both limits, you know, the risk of, of, you know, any issues that can come with new software rollouts. We haven't seen anything so far, but also it does give us the opportunity to have like meaningful conversations with a small group of users who are using the products, but once we get through that and they give us two thumbs up on it, it'll be like, open the gates and let everybody in. It's gonna be exciting time for the whole ecosystem. >>Yeah, that makes a lot of sense. And you can do some experimentation and, you know, using the cloud resources. Let's dig into some of the architectural and technical innovations that are gonna help deliver on this vision. What, what should we know there? >>Well, I mean, I think foundationally we built the, the new core on Rust. You know, this is a new very sort of popular systems language, you know, it's extremely efficient, but it's also built for speed and memory safety, which goes back to that us being able to like deliver it in a way that is, you know, something we can inspect very closely, but then also rely on the fact that it's going to behave well. And if it does find error conditions, I mean we, we've loved working with Go and, you know, a lot of our libraries will continue to, to be sort of implemented in Go, but you know, when it came to this particular new engine, you know, that power performance and stability rust was critical. On top of that, like, we've also integrated Apache Arrow and Apache Parque for persistence. I think for anybody who's really familiar with the nuts and bolts of our backend and our TSI and our, our time series merged Trees, this is a big break from that, you know, arrow on the sort of in MI side and then Par K in the on disk side. >>It, it allows us to, to present, you know, a unified set of APIs for those really fast real time inquiries that we talked about, as well as for very large, you know, historical sort of bulk data archives in that PARQUE format, which is also cool because there's an entire ecosystem sort of popping up around Parque in terms of the machine learning community, you know, and getting that all to work, we had to glue it together with aero flight. That's sort of what we're using as our, our RPC component. You know, it handles the orchestration and the, the transportation of the Coer data. Now we're moving to like a true Coer database model for this, this version of the engine, you know, and it removes a lot of overhead for us in terms of having to manage all that serialization, the deserialization, and, you know, to that again, like blurring that line between real time and historical data. It's, you know, it's, it's highly optimized for both streaming micro batch and then batches, but true streaming as well. >>Yeah. Again, I mean, it's funny you mentioned Rust. It is, it's been around for a long time, but it's popularity is, is you know, really starting to hit that steep part of the S-curve. And, and we're gonna dig into to more of that, but give us any, is there anything else that we should know about Bryan? Give us the last word? >>Well, I mean, I think first I'd like everybody sort of watching just to like take a look at what we're offering in terms of early access in beta programs. I mean, if, if, if you wanna participate or if you wanna work sort of in terms of early access with the, with the new engine, please reach out to the team. I'm sure you know, there's a lot of communications going out and you know, it'll be highly featured on our, our website, you know, but reach out to the team, believe it or not, like we have a lot more going on than just the new engine. And so there are also other programs, things we're, we're offering to customers in terms of the user interface, data collection and things like that. And, you know, if you're a customer of ours and you have a sales team, a commercial team that you work with, you can reach out to them and see what you can get access to because we can flip a lot of stuff on, especially in cloud through feature flags. >>But if there's something new that you wanna try out, we'd just love to hear from you. And then, you know, our goal would be that as we give you access to all of these new cool features that, you know, you would give us continuous feedback on these products and services, not only like what you need today, but then what you'll need tomorrow to, to sort of build the next versions of your business. Because you know, the whole database, the ecosystem as it expands out into to, you know, this vertically oriented stack of cloud services and enterprise databases and edge databases, you know, it's gonna be what we all make it together, not just, you know, those of us who were employed by Influx db. And then finally I would just say please, like watch in ICE in Tim's sessions, like these are two of our best and brightest, They're totally brilliant, completely pragmatic, and they are most of all customer obsessed, which is amazing. And there's no better takes, like honestly on the, the sort of technical details of this, then there's, especially when it comes to like the value that these investments will, will bring to our customers and our communities. So encourage you to, to, you know, pay more attention to them than you did to me, for sure. >>Brian Gilmore, great stuff. Really appreciate your time. Thank you. >>Yeah, thanks Dave. It was awesome. Look forward to it. >>Yeah, me too. Looking forward to see how the, the community actually applies these new innovations and goes, goes beyond just the historical into the real time really hot area. As Brian said in a moment, I'll be right back with Anna East dos Georgio to dig into the critical aspects of key open source components of the Influx DB engine, including Rust, Arrow, Parque, data fusion. Keep it right there. You don't wanna miss this >>Time series Data is everywhere. The number of sensors, systems and applications generating time series data increases every day. All these data sources producing so much data can cause analysis paralysis. Influx DB is an entire platform designed with everything you need to quickly build applications that generate value from time series data influx. DB Cloud is a serverless solution, which means you don't need to buy or manage your own servers. There's no need to worry about provisioning because you only pay for what you use. Influx DB Cloud is fully managed so you get the newest features and enhancements as they're added to the platform's code base. It also means you can spend time building solutions and delivering value to your users instead of wasting time and effort managing something else. Influx TVB Cloud offers a range of security features to protect your data, multiple layers of redundancy ensure you don't lose any data access controls ensure that only the people who should see your data can see it. >>And encryption protects your data at rest and in transit between any of our regions or cloud providers. InfluxDB uses a single API across the entire platform suite so you can build on open source, deploy to the cloud and then then easily query data in the cloud at the edge or on prem using the same scripts. And InfluxDB is schemaless automatically adjusting to changes in the shape of your data without requiring changes in your application. Logic. InfluxDB Cloud is production ready from day one. All it needs is your data and your imagination. Get started today@influxdata.com slash cloud. >>Okay, we're back. I'm Dave Valante with a Cube and you're watching evolving Influx DB into the smart data platform made possible by influx data. Anna ETOs Georgio is here, she's a developer advocate for influx data and we're gonna dig into the rationale and value contribution behind several open source technologies that Influx DB is leveraging to increase the granularity of time series analysis analysis and bring the world of data into real-time analytics and is welcome to the program. Thanks for coming on. >>Hi, thank you so much. It's a pleasure to be here. >>Oh, you're very welcome. Okay, so IX is being touted as this next gen open source core for Influx db. And my understanding is that it leverages in memory of course for speed. It's a kilo store, so it gives you a compression efficiency, it's gonna give you faster query speeds, you store files and object storage, so you got very cost effective approach. Are these the salient points on the platform? I know there are probably dozens of other features, but what are the high level value points that people should understand? >>Sure, that's a great question. So some of the main requirements that IOx is trying to achieve and some of the most impressive ones to me, the first one is that it aims to have no limits on cardinality and also allow you to write any kind of event data that you want, whether that's live tag or a field. It also wants to deliver the best in class performance on analytics queries. In addition to our already well served metrics queries, we also wanna have operator control over memory usage. So you should be able to define how much memory is used for buffering caching and query processing. Some other really important parts is the ability to have bulk data export and import super useful. Also broader ecosystem compatibility where possible we aim to use and embrace emerging standards in the data analytics ecosystem and have compatibility with things like sql, Python, and maybe even pandas in the future. >>Okay, so lot there. Now we talked to Brian about how you're using Rust and which is not a new programming language and of course we had some drama around Rust during the pandemic with the Mozilla layoffs, but the formation of the Rust Foundation really addressed any of those concerns. You got big guns like Amazon and Google and Microsoft throwing their collective weights behind it. It's really, the adoption is really starting to get steep on the S-curve. So lots of platforms, lots of adoption with rust, but why rust as an alternative to say c plus plus for example? >>Sure, that's a great question. So Russ was chosen because of his exceptional performance and reliability. So while Russ is synt tactically similar to c plus plus and it has similar performance, it also compiles to a native code like c plus plus. But unlike c plus plus, it also has much better memory safety. So memory safety is protection against bugs or security vulnerabilities that lead to excessive memory usage or memory leaks. And rust achieves this memory safety due to its like innovative type system. Additionally, it doesn't allow for dangling pointers. And dangling pointers are the main classes of errors that lead to exploitable security vulnerabilities in languages like c plus plus. So Russ like helps meet that requirement of having no limits on ality, for example, because it's, we're also using the Russ implementation of Apache Arrow and this control over memory and also Russ Russ's packaging system called crates IO offers everything that you need out of the box to have features like AY and a weight to fix race conditions, to protection against buffering overflows and to ensure thread safe async cashing structures as well. So essentially it's just like has all the control, all the fine grain control, you need to take advantage of memory and all your resources as well as possible so that you can handle those really, really high ity use cases. >>Yeah, and the more I learn about the, the new engine and, and the platform IOCs et cetera, you know, you, you see things like, you know, the old days not even to even today you do a lot of garbage collection in these, in these systems and there's an inverse, you know, impact relative to performance. So it looks like you really, you know, the community is modernizing the platform, but I wanna talk about Apache Arrow for a moment. It it's designed to address the constraints that are associated with analyzing large data sets. We, we know that, but please explain why, what, what is Arrow and and what does it bring to Influx db? >>Sure, yeah. So Arrow is a, a framework for defining in memory calmer data. And so much of the efficiency and performance of IOx comes from taking advantage of calmer data structures. And I will, if you don't mind, take a moment to kind of of illustrate why column or data structures are so valuable. Let's pretend that we are gathering field data about the temperature in our room and also maybe the temperature of our stove. And in our table we have those two temperature values as well as maybe a measurement value, timestamp value, maybe some other tag values that describe what room and what house, et cetera we're getting this data from. And so you can picture this table where we have like two rows with the two temperature values for both our room and the stove. Well usually our room temperature is regulated so those values don't change very often. >>So when you have calm oriented st calm oriented storage, essentially you take each row, each column and group it together. And so if that's the case and you're just taking temperature values from the room and a lot of those temperature values are the same, then you'll, you might be able to imagine how equal values will then enable each other and when they neighbor each other in the storage format, this provides a really perfect opportunity for cheap compression. And then this cheap compression enables high cardinality use cases. It also enables for faster scan rates. So if you wanna define like the men and max value of the temperature in the room across a thousand different points, you only have to get those a thousand different points in order to answer that question and you have those immediately available to you. But let's contrast this with a row oriented storage solution instead so that we can understand better the benefits of calmer oriented storage. >>So if you had a row oriented storage, you'd first have to look at every field like the temperature in, in the room and the temperature of the stove. You'd have to go across every tag value that maybe describes where the room is located or what model the stove is. And every timestamp you'd then have to pluck out that one temperature value that you want at that one time stamp and do that for every single row. So you're scanning across a ton more data and that's why Rowe Oriented doesn't provide the same efficiency as calmer and Apache Arrow is in memory calmer data, commoner data fit framework. So that's where a lot of the advantages come >>From. Okay. So you basically described like a traditional database, a row approach, but I've seen like a lot of traditional database say, okay, now we've got, we can handle colo format versus what you're talking about is really, you know, kind of native i, is it not as effective? Is the, is the foreman not as effective because it's largely a, a bolt on? Can you, can you like elucidate on that front? >>Yeah, it's, it's not as effective because you have more expensive compression and because you can't scan across the values as quickly. And so those are, that's pretty much the main reasons why, why RO row oriented storage isn't as efficient as calm, calmer oriented storage. Yeah. >>Got it. So let's talk about Arrow Data Fusion. What is data fusion? I know it's written in Rust, but what does it bring to the table here? >>Sure. So it's an extensible query execution framework and it uses Arrow as it's in memory format. So the way that it helps in influx DB IOCs is that okay, it's great if you can write unlimited amount of cardinality into influx Cbis, but if you don't have a query engine that can successfully query that data, then I don't know how much value it is for you. So Data fusion helps enable the, the query process and transformation of that data. It also has a PANDAS API so that you could take advantage of PANDAS data frames as well and all of the machine learning tools associated with Pandas. >>Okay. You're also leveraging Par K in the platform cause we heard a lot about Par K in the middle of the last decade cuz as a storage format to improve on Hadoop column stores. What are you doing with Parque and why is it important? >>Sure. So parque is the column oriented durable file format. So it's important because it'll enable bulk import, bulk export, it has compatibility with Python and Pandas, so it supports a broader ecosystem. Par K files also take very little disc disc space and they're faster to scan because again, they're column oriented in particular, I think PAR K files are like 16 times cheaper than CSV files, just as kind of a point of reference. And so that's essentially a lot of the, the benefits of par k. >>Got it. Very popular. So and he's, what exactly is influx data focusing on as a committer to these projects? What is your focus? What's the value that you're bringing to the community? >>Sure. So Influx DB first has contributed a lot of different, different things to the Apache ecosystem. For example, they contribute an implementation of Apache Arrow and go and that will support clearing with flux. Also, there has been a quite a few contributions to data fusion for things like memory optimization and supportive additional SQL features like support for timestamp, arithmetic and support for exist clauses and support for memory control. So yeah, Influx has contributed a a lot to the Apache ecosystem and continues to do so. And I think kind of the idea here is that if you can improve these upstream projects and then the long term strategy here is that the more you contribute and build those up, then the more you will perpetuate that cycle of improvement and the more we will invest in our own project as well. So it's just that kind of symbiotic relationship and appreciation of the open source community. >>Yeah. Got it. You got that virtuous cycle going, the people call the flywheel. Give us your last thoughts and kind of summarize, you know, where what, what the big takeaways are from your perspective. >>So I think the big takeaway is that influx data is doing a lot of really exciting things with Influx DB IOx and I really encourage, if you are interested in learning more about the technologies that Influx is leveraging to produce IOCs, the challenges associated with it and all of the hard work questions and you just wanna learn more, then I would encourage you to go to the monthly Tech talks and community office hours and they are on every second Wednesday of the month at 8:30 AM Pacific time. There's also a community forums and a community Slack channel look for the influx DDB unders IAC channel specifically to learn more about how to join those office hours and those monthly tech tech talks as well as ask any questions they have about iacs, what to expect and what you'd like to learn more about. I as a developer advocate, I wanna answer your questions. So if there's a particular technology or stack that you wanna dive deeper into and want more explanation about how INFLUX DB leverages it to build IOCs, I will be really excited to produce content on that topic for you. >>Yeah, that's awesome. You guys have a really rich community, collaborate with your peers, solve problems, and, and you guys super responsive, so really appreciate that. All right, thank you so much Anise for explaining all this open source stuff to the audience and why it's important to the future of data. >>Thank you. I really appreciate it. >>All right, you're very welcome. Okay, stay right there and in a moment I'll be back with Tim Yoakum, he's the director of engineering for Influx Data and we're gonna talk about how you update a SAS engine while the plane is flying at 30,000 feet. You don't wanna miss this. >>I'm really glad that we went with InfluxDB Cloud for our hosting because it has saved us a ton of time. It's helped us move faster, it's saved us money. And also InfluxDB has good support. My name's Alex Nada. I am CTO at Noble nine. Noble Nine is a platform to measure and manage service level objectives, which is a great way of measuring the reliability of your systems. You can essentially think of an slo, the product we're providing to our customers as a bunch of time series. So we need a way to store that data and the corresponding time series that are related to those. The main reason that we settled on InfluxDB as we were shopping around is that InfluxDB has a very flexible query language and as a general purpose time series database, it basically had the set of features we were looking for. >>As our platform has grown, we found InfluxDB Cloud to be a really scalable solution. We can quickly iterate on new features and functionality because Influx Cloud is entirely managed, it probably saved us at least a full additional person on our team. We also have the option of running InfluxDB Enterprise, which gives us the ability to even host off the cloud or in a private cloud if that's preferred by a customer. Influx data has been really flexible in adapting to the hosting requirements that we have. They listened to the challenges we were facing and they helped us solve it. As we've continued to grow, I'm really happy we have influx data by our side. >>Okay, we're back with Tim Yokum, who is the director of engineering at Influx Data. Tim, welcome. Good to see you. >>Good to see you. Thanks for having me. >>You're really welcome. Listen, we've been covering open source software in the cube for more than a decade, and we've kind of watched the innovation from the big data ecosystem. The cloud has been being built out on open source, mobile, social platforms, key databases, and of course influx DB and influx data has been a big consumer and contributor of open source software. So my question to you is, where have you seen the biggest bang for the buck from open source software? >>So yeah, you know, influx really, we thrive at the intersection of commercial services and open, so open source software. So OSS keeps us on the cutting edge. We benefit from OSS in delivering our own service from our core storage engine technologies to web services temping engines. Our, our team stays lean and focused because we build on proven tools. We really build on the shoulders of giants and like you've mentioned, even better, we contribute a lot back to the projects that we use as well as our own product influx db. >>You know, but I gotta ask you, Tim, because one of the challenge that that we've seen in particular, you saw this in the heyday of Hadoop, the, the innovations come so fast and furious and as a software company you gotta place bets, you gotta, you know, commit people and sometimes those bets can be risky and not pay off well, how have you managed this challenge? >>Oh, it moves fast. Yeah, that, that's a benefit though because it, the community moves so quickly that today's hot technology can be tomorrow's dinosaur. And what we, what we tend to do is, is we fail fast and fail often. We try a lot of things. You know, you look at Kubernetes for example, that ecosystem is driven by thousands of intelligent developers, engineers, builders, they're adding value every day. So we have to really keep up with that. And as the stack changes, we, we try different technologies, we try different methods, and at the end of the day, we come up with a better platform as a result of just the constant change in the environment. It is a challenge for us, but it's, it's something that we just do every day. >>So we have a survey partner down in New York City called Enterprise Technology Research etr, and they do these quarterly surveys of about 1500 CIOs, IT practitioners, and they really have a good pulse on what's happening with spending. And the data shows that containers generally, but specifically Kubernetes is one of the areas that has kind of, it's been off the charts and seen the most significant adoption and velocity particularly, you know, along with cloud. But, but really Kubernetes is just, you know, still up until the right consistently even with, you know, the macro headwinds and all, all of the stuff that we're sick of talking about. But, so what are you doing with Kubernetes in the platform? >>Yeah, it, it's really central to our ability to run the product. When we first started out, we were just on AWS and, and the way we were running was, was a little bit like containers junior. Now we're running Kubernetes everywhere at aws, Azure, Google Cloud. It allows us to have a consistent experience across three different cloud providers and we can manage that in code so our developers can focus on delivering services, not trying to learn the intricacies of Amazon, Azure, and Google and figure out how to deliver services on those three clouds with all of their differences. >>Just to follow up on that, is it, no. So I presume it's sounds like there's a PAs layer there to allow you guys to have a consistent experience across clouds and out to the edge, you know, wherever is that, is that correct? >>Yeah, so we've basically built more or less platform engineering, This is the new hot phrase, you know, it, it's, Kubernetes has made a lot of things easy for us because we've built a platform that our developers can lean on and they only have to learn one way of deploying their application, managing their application. And so that, that just gets all of the underlying infrastructure out of the way and, and lets them focus on delivering influx cloud. >>Yeah, and I know I'm taking a little bit of a tangent, but is that, that, I'll call it a PAs layer if I can use that term. Is that, are there specific attributes to Influx db or is it kind of just generally off the shelf paths? You know, are there, is, is there any purpose built capability there that, that is, is value add or is it pretty much generic? >>So we really build, we, we look at things through, with a build versus buy through a, a build versus by lens. Some things we want to leverage cloud provider services, for instance, Postgres databases for metadata, perhaps we'll get that off of our plate, let someone else run that. We're going to deploy a platform that our engineers can, can deliver on that has consistency that is, is all generated from code that we can as a, as an SRE group, as an ops team, that we can manage with very few people really, and we can stamp out clusters across multiple regions and in no time. >>So how, so sometimes you build, sometimes you buy it. How do you make those decisions and and what does that mean for the, for the platform and for customers? >>Yeah, so what we're doing is, it's like everybody else will do, we're we're looking for trade offs that make sense. You know, we really want to protect our customers data. So we look for services that support our own software with the most uptime, reliability, and durability we can get. Some things are just going to be easier to have a cloud provider take care of on our behalf. We make that transparent for our own team. And of course for customers you don't even see that, but we don't want to try to reinvent the wheel, like I had mentioned with SQL data stores for metadata, perhaps let's build on top of what of these three large cloud providers have already perfected. And we can then focus on our platform engineering and we can have our developers then focus on the influx data, software, influx, cloud software. >>So take it to the customer level, what does it mean for them? What's the value that they're gonna get out of all these innovations that we've been been talking about today and what can they expect in the future? >>So first of all, people who use the OSS product are really gonna be at home on our cloud platform. You can run it on your desktop machine, on a single server, what have you, but then you want to scale up. We have some 270 terabytes of data across, over 4 billion series keys that people have stored. So there's a proven ability to scale now in terms of the open source, open source software and how we've developed the platform. You're getting highly available high cardinality time series platform. We manage it and, and really as, as I mentioned earlier, we can keep up with the state of the art. We keep reinventing, we keep deploying things in real time. We deploy to our platform every day repeatedly all the time. And it's that continuous deployment that allows us to continue testing things in flight, rolling things out that change new features, better ways of doing deployments, safer ways of doing deployments. >>All of that happens behind the scenes. And like we had mentioned earlier, Kubernetes, I mean that, that allows us to get that done. We couldn't do it without having that platform as a, as a base layer for us to then put our software on. So we, we iterate quickly. When you're on the, the Influx cloud platform, you really are able to, to take advantage of new features immediately. We roll things out every day and as those things go into production, you have, you have the ability to, to use them. And so in the end we want you to focus on getting actual insights from your data instead of running infrastructure, you know, let, let us do that for you. So, >>And that makes sense, but so is the, is the, are the innovations that we're talking about in the evolution of Influx db, do, do you see that as sort of a natural evolution for existing customers? I, is it, I'm sure the answer is both, but is it opening up new territory for customers? Can you add some color to that? >>Yeah, it really is it, it's a little bit of both. Any engineer will say, well, it depends. So cloud native technologies are, are really the hot thing. Iot, industrial iot especially, people want to just shove tons of data out there and be able to do queries immediately and they don't wanna manage infrastructure. What we've started to see are people that use the cloud service as their, their data store backbone and then they use edge computing with R OSS product to ingest data from say, multiple production lines and downsample that data, send the rest of that data off influx cloud where the heavy processing takes place. So really us being in all the different clouds and iterating on that and being in all sorts of different regions allows for people to really get out of the, the business of man trying to manage that big data, have us take care of that. And of course as we change the platform end users benefit from that immediately. And, >>And so obviously taking away a lot of the heavy lifting for the infrastructure, would you say the same thing about security, especially as you go out to IOT and the Edge? How should we be thinking about the value that you bring from a security perspective? >>Yeah, we take, we take security super seriously. It, it's built into our dna. We do a lot of work to ensure that our platform is secure, that the data we store is, is kept private. It's of course always a concern. You see in the news all the time, companies being compromised, you know, that's something that you can have an entire team working on, which we do to make sure that the data that you have, whether it's in transit, whether it's at rest, is always kept secure, is only viewable by you. You know, you look at things like software, bill of materials, if you're running this yourself, you have to go vet all sorts of different pieces of software. And we do that, you know, as we use new tools. That's something that, that's just part of our jobs to make sure that the platform that we're running it has, has fully vetted software and, and with open source especially, that's a lot of work. And so it's, it's definitely new territory. Supply chain attacks are, are definitely happening at a higher clip than they used to, but that is, that is really just part of a day in the, the life for folks like us that are, are building platforms. >>Yeah, and that's key. I mean especially when you start getting into the, the, you know, we talk about IOT and the operations technologies, the engineers running the, that infrastructure, you know, historically, as you know, Tim, they, they would air gap everything. That's how they kept it safe. But that's not feasible anymore. Everything's >>That >>Connected now, right? And so you've gotta have a partner that is again, take away that heavy lifting to r and d so you can focus on some of the other activities. Right. Give us the, the last word and the, the key takeaways from your perspective. >>Well, you know, from my perspective I see it as, as a a two lane approach with, with influx, with Anytime series data, you know, you've got a lot of stuff that you're gonna run on-prem, what you had mentioned, air gaping. Sure there's plenty of need for that, but at the end of the day, people that don't want to run big data centers, people that want torus their data to, to a company that's, that's got a full platform set up for them that they can build on, send that data over to the cloud, the cloud is not going away. I think more hybrid approach is, is where the future lives and that's what we're prepared for. >>Tim, really appreciate you coming to the program. Great stuff. Good to see you. >>Thanks very much. Appreciate it. >>Okay, in a moment I'll be back to wrap up. Today's session, you're watching The Cube. >>Are you looking for some help getting started with InfluxDB Telegraph or Flux Check >>Out Influx DB University >>Where you can find our entire catalog of free training that will help you make the most of your time series data >>Get >>Started for free@influxdbu.com. >>We'll see you in class. >>Okay, so we heard today from three experts on time series and data, how the Influx DB platform is evolving to support new ways of analyzing large data sets very efficiently and effectively in real time. And we learned that key open source components like Apache Arrow and the Rust Programming environment Data fusion par K are being leveraged to support realtime data analytics at scale. We also learned about the contributions in importance of open source software and how the Influx DB community is evolving the platform with minimal disruption to support new workloads, new use cases, and the future of realtime data analytics. Now remember these sessions, they're all available on demand. You can go to the cube.net to find those. Don't forget to check out silicon angle.com for all the news related to things enterprise and emerging tech. And you should also check out influx data.com. There you can learn about the company's products. You'll find developer resources like free courses. You could join the developer community and work with your peers to learn and solve problems. And there are plenty of other resources around use cases and customer stories on the website. This is Dave Valante. Thank you for watching Evolving Influx DB into the smart data platform, made possible by influx data and brought to you by the Cube, your leader in enterprise and emerging tech coverage.

>>This past May, The Cube in collaboration with Influx data shared with you the latest innovations in Time series databases. We talked at length about why a purpose built time series database for many use cases, was a superior alternative to general purpose databases trying to do the same thing. Now, you may, you may remember the time series data is any data that's stamped in time, and if it's stamped, it can be analyzed historically. And when we introduced the concept to the community, we talked about how in theory, those time slices could be taken, you know, every hour, every minute, every second, you know, down to the millisecond and how the world was moving toward realtime or near realtime data analysis to support physical infrastructure like sensors and other devices and IOT equipment. A time series databases have had to evolve to efficiently support realtime data in emerging use cases in iot T and other use cases. >>And to do that, new architectural innovations have to be brought to bear. As is often the case, open source software is the linchpin to those innovations. Hello and welcome to Evolving Influx DB into the smart Data platform, made possible by influx data and produced by the Cube. My name is Dave Valante and I'll be your host today. Now in this program we're going to dig pretty deep into what's happening with Time series data generally, and specifically how Influx DB is evolving to support new workloads and demands and data, and specifically around data analytics use cases in real time. Now, first we're gonna hear from Brian Gilmore, who is the director of IOT and emerging technologies at Influx Data. And we're gonna talk about the continued evolution of Influx DB and the new capabilities enabled by open source generally and specific tools. And in this program you're gonna hear a lot about things like Rust, implementation of Apache Arrow, the use of par k and tooling such as data fusion, which powering a new engine for Influx db. >>Now, these innovations, they evolve the idea of time series analysis by dramatically increasing the granularity of time series data by compressing the historical time slices, if you will, from, for example, minutes down to milliseconds. And at the same time, enabling real time analytics with an architecture that can process data much faster and much more efficiently. Now, after Brian, we're gonna hear from Anna East Dos Georgio, who is a developer advocate at In Flux Data. And we're gonna get into the why of these open source capabilities and how they contribute to the evolution of the Influx DB platform. And then we're gonna close the program with Tim Yokum, he's the director of engineering at Influx Data, and he's gonna explain how the Influx DB community actually evolved the data engine in mid-flight and which decisions went into the innovations that are coming to the market. Thank you for being here. We hope you enjoy the program. Let's get started. Okay, we're kicking things off with Brian Gilmore. He's the director of i t and emerging Technology at Influx State of Bryan. Welcome to the program. Thanks for coming on. >>Thanks Dave. Great to be here. I appreciate the time. >>Hey, explain why Influx db, you know, needs a new engine. Was there something wrong with the current engine? What's going on there? >>No, no, not at all. I mean, I think it's, for us, it's been about staying ahead of the market. I think, you know, if we think about what our customers are coming to us sort of with now, you know, related to requests like sql, you know, query support, things like that, we have to figure out a way to, to execute those for them in a way that will scale long term. And then we also, we wanna make sure we're innovating, we're sort of staying ahead of the market as well and sort of anticipating those future needs. So, you know, this is really a, a transparent change for our customers. I mean, I think we'll be adding new capabilities over time that sort of leverage this new engine, but you know, initially the customers who are using us are gonna see just great improvements in performance, you know, especially those that are working at the top end of the, of the workload scale, you know, the massive data volumes and things like that. >>Yeah, and we're gonna get into that today and the architecture and the like, but what was the catalyst for the enhancements? I mean, when and how did this all come about? >>Well, I mean, like three years ago we were primarily on premises, right? I mean, I think we had our open source, we had an enterprise product, you know, and, and sort of shifting that technology, especially the open source code base to a service basis where we were hosting it through, you know, multiple cloud providers. That was, that was, that was a long journey I guess, you know, phase one was, you know, we wanted to host enterprise for our customers, so we sort of created a service that we just managed and ran our enterprise product for them. You know, phase two of this cloud effort was to, to optimize for like multi-tenant, multi-cloud, be able to, to host it in a truly like sass manner where we could use, you know, some type of customer activity or consumption as the, the pricing vector, you know, And, and that was sort of the birth of the, of the real first influx DB cloud, you know, which has been really successful. >>We've seen, I think like 60,000 people sign up and we've got tons and tons of, of both enterprises as well as like new companies, developers, and of course a lot of home hobbyists and enthusiasts who are using out on a, on a daily basis, you know, and having that sort of big pool of, of very diverse and very customers to chat with as they're using the product, as they're giving us feedback, et cetera, has has, you know, pointed us in a really good direction in terms of making sure we're continuously improving that and then also making these big leaps as we're doing with this, with this new engine. >>Right. So you've called it a transparent change for customers, so I'm presuming it's non-disruptive, but I really wanna understand how much of a pivot this is and what, what does it take to make that shift from, you know, time series, you know, specialist to real time analytics and being able to support both? >>Yeah, I mean, it's much more of an evolution, I think, than like a shift or a pivot. You know, time series data is always gonna be fundamental and sort of the basis of the solutions that we offer our customers, and then also the ones that they're building on the sort of raw APIs of our platform themselves. You know, the time series market is one that we've worked diligently to lead. I mean, I think when it comes to like metrics, especially like sensor data and app and infrastructure metrics, if we're being honest though, I think our, our user base is well aware that the way we were architected was much more towards those sort of like backwards looking historical type analytics, which are key for troubleshooting and making sure you don't, you know, run into the same problem twice. But, you know, we had to ask ourselves like, what can we do to like better handle those queries from a performance and a, and a, you know, a time to response on the queries, and can we get that to the point where the results sets are coming back so quickly from the time of query that we can like limit that window down to minutes and then seconds. >>And now with this new engine, we're really starting to talk about a query window that could be like returning results in, in, you know, milliseconds of time since it hit the, the, the ingest queue. And that's, that's really getting to the point where as your data is available, you can use it and you can query it, you can visualize it, and you can do all those sort of magical things with it, you know? And I think getting all of that to a place where we're saying like, yes to the customer on, you know, all of the, the real time queries, the, the multiple language query support, but, you know, it was hard, but we're now at a spot where we can start introducing that to, you know, a a limited number of customers, strategic customers and strategic availability zones to start. But you know, everybody over time. >>So you're basically going from what happened to in, you can still do that obviously, but to what's happening now in the moment? >>Yeah, yeah. I mean if you think about time, it's always sort of past, right? I mean, like in the moment right now, whether you're talking about like a millisecond ago or a minute ago, you know, that's, that's pretty much right now, I think for most people, especially in these use cases where you have other sort of components of latency induced by the, by the underlying data collection, the architecture, the infrastructure, the, you know, the, the devices and you know, the sort of highly distributed nature of all of this. So yeah, I mean, getting, getting a customer or a user to be able to use the data as soon as it is available is what we're after here. >>I always thought, you know, real, I always thought of real time as before you lose the customer, but now in this context, maybe it's before the machine blows up. >>Yeah, it's, it's, I mean it is operationally or operational real time is different, you know, and that's one of the things that really triggered us to know that we were, we were heading in the right direction, is just how many sort of operational customers we have. You know, everything from like aerospace and defense. We've got companies monitoring satellites, we've got tons of industrial users, users using us as a processes storing on the plant floor, you know, and, and if we can satisfy their sort of demands for like real time historical perspective, that's awesome. I think what we're gonna do here is we're gonna start to like edge into the real time that they're used to in terms of, you know, the millisecond response times that they expect of their control systems, certainly not their, their historians and databases. >>I, is this available, these innovations to influx DB cloud customers only who can access this capability? >>Yeah. I mean commercially and today, yes. You know, I think we want to emphasize that's a, for now our goal is to get our latest and greatest and our best to everybody over time. Of course. You know, one of the things we had to do here was like we double down on sort of our, our commitment to open source and availability. So like anybody today can take a look at the, the libraries in on our GitHub and, you know, can ex inspect it and even can try to, you know, implement or execute some of it themselves in their own infrastructure. You know, we are, we're committed to bringing our sort of latest and greatest to our cloud customers first for a couple of reasons. Number one, you know, there are big workloads and they have high expectations of us. I think number two, it also gives us the opportunity to monitor a little bit more closely how it's working, how they're using it, like how the system itself is performing. >>And so just, you know, being careful, maybe a little cautious in terms of, of, of how big we go with this right away, just sort of both limits, you know, the risk of, of, you know, any issues that can come with new software rollouts. We haven't seen anything so far, but also it does give us the opportunity to have like meaningful conversations with a small group of users who are using the products, but once we get through that and they give us two thumbs up on it, it'll be like, open the gates and let everybody in. It's gonna be exciting time for the whole ecosystem. >>Yeah, that makes a lot of sense. And you can do some experimentation and, you know, using the cloud resources. Let's dig into some of the architectural and technical innovations that are gonna help deliver on this vision. What, what should we know there? >>Well, I mean, I think foundationally we built the, the new core on Rust. You know, this is a new very sort of popular systems language, you know, it's extremely efficient, but it's also built for speed and memory safety, which goes back to that us being able to like deliver it in a way that is, you know, something we can inspect very closely, but then also rely on the fact that it's going to behave well. And if it does find error conditions, I mean we, we've loved working with Go and, you know, a lot of our libraries will continue to, to be sort of implemented in Go, but you know, when it came to this particular new engine, you know, that power performance and stability rust was critical. On top of that, like, we've also integrated Apache Arrow and Apache Parque for persistence. I think for anybody who's really familiar with the nuts and bolts of our backend and our TSI and our, our time series merged Trees, this is a big break from that, you know, arrow on the sort of in MI side and then Par K in the on disk side. >>It, it allows us to, to present, you know, a unified set of APIs for those really fast real time inquiries that we talked about, as well as for very large, you know, historical sort of bulk data archives in that PARQUE format, which is also cool because there's an entire ecosystem sort of popping up around Parque in terms of the machine learning community, you know, and getting that all to work, we had to glue it together with aero flight. That's sort of what we're using as our, our RPC component. You know, it handles the orchestration and the, the transportation of the Coer data. Now we're moving to like a true Coer database model for this, this version of the engine, you know, and it removes a lot of overhead for us in terms of having to manage all that serialization, the deserialization, and, you know, to that again, like blurring that line between real time and historical data. It's, you know, it's, it's highly optimized for both streaming micro batch and then batches, but true streaming as well. >>Yeah. Again, I mean, it's funny you mentioned Rust. It is, it's been around for a long time, but it's popularity is, is you know, really starting to hit that steep part of the S-curve. And, and we're gonna dig into to more of that, but give us any, is there anything else that we should know about Bryan? Give us the last word? >>Well, I mean, I think first I'd like everybody sort of watching just to like take a look at what we're offering in terms of early access in beta programs. I mean, if, if, if you wanna participate or if you wanna work sort of in terms of early access with the, with the new engine, please reach out to the team. I'm sure you know, there's a lot of communications going out and you know, it'll be highly featured on our, our website, you know, but reach out to the team, believe it or not, like we have a lot more going on than just the new engine. And so there are also other programs, things we're, we're offering to customers in terms of the user interface, data collection and things like that. And, you know, if you're a customer of ours and you have a sales team, a commercial team that you work with, you can reach out to them and see what you can get access to because we can flip a lot of stuff on, especially in cloud through feature flags. >>But if there's something new that you wanna try out, we'd just love to hear from you. And then, you know, our goal would be that as we give you access to all of these new cool features that, you know, you would give us continuous feedback on these products and services, not only like what you need today, but then what you'll need tomorrow to, to sort of build the next versions of your business. Because you know, the whole database, the ecosystem as it expands out into to, you know, this vertically oriented stack of cloud services and enterprise databases and edge databases, you know, it's gonna be what we all make it together, not just, you know, those of us who were employed by Influx db. And then finally I would just say please, like watch in ICE in Tim's sessions, like these are two of our best and brightest, They're totally brilliant, completely pragmatic, and they are most of all customer obsessed, which is amazing. And there's no better takes, like honestly on the, the sort of technical details of this, then there's, especially when it comes to like the value that these investments will, will bring to our customers and our communities. So encourage you to, to, you know, pay more attention to them than you did to me, for sure. >>Brian Gilmore, great stuff. Really appreciate your time. Thank you. >>Yeah, thanks Dave. It was awesome. Look forward to it. >>Yeah, me too. Looking forward to see how the, the community actually applies these new innovations and goes, goes beyond just the historical into the real time really hot area. As Brian said in a moment, I'll be right back with Anna East dos Georgio to dig into the critical aspects of key open source components of the Influx DB engine, including Rust, Arrow, Parque, data fusion. Keep it right there. You don't wanna miss this >>Time series Data is everywhere. The number of sensors, systems and applications generating time series data increases every day. All these data sources producing so much data can cause analysis paralysis. Influx DB is an entire platform designed with everything you need to quickly build applications that generate value from time series data influx. DB Cloud is a serverless solution, which means you don't need to buy or manage your own servers. There's no need to worry about provisioning because you only pay for what you use. Influx DB Cloud is fully managed so you get the newest features and enhancements as they're added to the platform's code base. It also means you can spend time building solutions and delivering value to your users instead of wasting time and effort managing something else. Influx TVB Cloud offers a range of security features to protect your data, multiple layers of redundancy ensure you don't lose any data access controls ensure that only the people who should see your data can see it. >>And encryption protects your data at rest and in transit between any of our regions or cloud providers. InfluxDB uses a single API across the entire platform suite so you can build on open source, deploy to the cloud and then then easily query data in the cloud at the edge or on prem using the same scripts. And InfluxDB is schemaless automatically adjusting to changes in the shape of your data without requiring changes in your application. Logic. InfluxDB Cloud is production ready from day one. All it needs is your data and your imagination. Get started today@influxdata.com slash cloud. >>Okay, we're back. I'm Dave Valante with a Cube and you're watching evolving Influx DB into the smart data platform made possible by influx data. Anna ETOs Georgio is here, she's a developer advocate for influx data and we're gonna dig into the rationale and value contribution behind several open source technologies that Influx DB is leveraging to increase the granularity of time series analysis analysis and bring the world of data into real-time analytics and is welcome to the program. Thanks for coming on. >>Hi, thank you so much. It's a pleasure to be here. >>Oh, you're very welcome. Okay, so IX is being touted as this next gen open source core for Influx db. And my understanding is that it leverages in memory of course for speed. It's a kilo store, so it gives you a compression efficiency, it's gonna give you faster query speeds, you store files and object storage, so you got very cost effective approach. Are these the salient points on the platform? I know there are probably dozens of other features, but what are the high level value points that people should understand? >>Sure, that's a great question. So some of the main requirements that IOx is trying to achieve and some of the most impressive ones to me, the first one is that it aims to have no limits on cardinality and also allow you to write any kind of event data that you want, whether that's live tag or a field. It also wants to deliver the best in class performance on analytics queries. In addition to our already well served metrics queries, we also wanna have operator control over memory usage. So you should be able to define how much memory is used for buffering caching and query processing. Some other really important parts is the ability to have bulk data export and import super useful. Also broader ecosystem compatibility where possible we aim to use and embrace emerging standards in the data analytics ecosystem and have compatibility with things like sql, Python, and maybe even pandas in the future. >>Okay, so lot there. Now we talked to Brian about how you're using Rust and which is not a new programming language and of course we had some drama around Rust during the pandemic with the Mozilla layoffs, but the formation of the Rust Foundation really addressed any of those concerns. You got big guns like Amazon and Google and Microsoft throwing their collective weights behind it. It's really, the adoption is really starting to get steep on the S-curve. So lots of platforms, lots of adoption with rust, but why rust as an alternative to say c plus plus for example? >>Sure, that's a great question. So Russ was chosen because of his exceptional performance and reliability. So while Russ is synt tactically similar to c plus plus and it has similar performance, it also compiles to a native code like c plus plus. But unlike c plus plus, it also has much better memory safety. So memory safety is protection against bugs or security vulnerabilities that lead to excessive memory usage or memory leaks. And rust achieves this memory safety due to its like innovative type system. Additionally, it doesn't allow for dangling pointers. And dangling pointers are the main classes of errors that lead to exploitable security vulnerabilities in languages like c plus plus. So Russ like helps meet that requirement of having no limits on ality, for example, because it's, we're also using the Russ implementation of Apache Arrow and this control over memory and also Russ Russ's packaging system called crates IO offers everything that you need out of the box to have features like AY and a weight to fix race conditions, to protection against buffering overflows and to ensure thread safe async cashing structures as well. So essentially it's just like has all the control, all the fine grain control, you need to take advantage of memory and all your resources as well as possible so that you can handle those really, really high ity use cases. >>Yeah, and the more I learn about the, the new engine and, and the platform IOCs et cetera, you know, you, you see things like, you know, the old days not even to even today you do a lot of garbage collection in these, in these systems and there's an inverse, you know, impact relative to performance. So it looks like you really, you know, the community is modernizing the platform, but I wanna talk about Apache Arrow for a moment. It it's designed to address the constraints that are associated with analyzing large data sets. We, we know that, but please explain why, what, what is Arrow and and what does it bring to Influx db? >>Sure, yeah. So Arrow is a, a framework for defining in memory calmer data. And so much of the efficiency and performance of IOx comes from taking advantage of calmer data structures. And I will, if you don't mind, take a moment to kind of of illustrate why column or data structures are so valuable. Let's pretend that we are gathering field data about the temperature in our room and also maybe the temperature of our stove. And in our table we have those two temperature values as well as maybe a measurement value, timestamp value, maybe some other tag values that describe what room and what house, et cetera we're getting this data from. And so you can picture this table where we have like two rows with the two temperature values for both our room and the stove. Well usually our room temperature is regulated so those values don't change very often. >>So when you have calm oriented st calm oriented storage, essentially you take each row, each column and group it together. And so if that's the case and you're just taking temperature values from the room and a lot of those temperature values are the same, then you'll, you might be able to imagine how equal values will then enable each other and when they neighbor each other in the storage format, this provides a really perfect opportunity for cheap compression. And then this cheap compression enables high cardinality use cases. It also enables for faster scan rates. So if you wanna define like the men and max value of the temperature in the room across a thousand different points, you only have to get those a thousand different points in order to answer that question and you have those immediately available to you. But let's contrast this with a row oriented storage solution instead so that we can understand better the benefits of calmer oriented storage. >>So if you had a row oriented storage, you'd first have to look at every field like the temperature in, in the room and the temperature of the stove. You'd have to go across every tag value that maybe describes where the room is located or what model the stove is. And every timestamp you'd then have to pluck out that one temperature value that you want at that one time stamp and do that for every single row. So you're scanning across a ton more data and that's why Rowe Oriented doesn't provide the same efficiency as calmer and Apache Arrow is in memory calmer data, commoner data fit framework. So that's where a lot of the advantages come >>From. Okay. So you basically described like a traditional database, a row approach, but I've seen like a lot of traditional database say, okay, now we've got, we can handle colo format versus what you're talking about is really, you know, kind of native i, is it not as effective? Is the, is the foreman not as effective because it's largely a, a bolt on? Can you, can you like elucidate on that front? >>Yeah, it's, it's not as effective because you have more expensive compression and because you can't scan across the values as quickly. And so those are, that's pretty much the main reasons why, why RO row oriented storage isn't as efficient as calm, calmer oriented storage. Yeah. >>Got it. So let's talk about Arrow Data Fusion. What is data fusion? I know it's written in Rust, but what does it bring to the table here? >>Sure. So it's an extensible query execution framework and it uses Arrow as it's in memory format. So the way that it helps in influx DB IOCs is that okay, it's great if you can write unlimited amount of cardinality into influx Cbis, but if you don't have a query engine that can successfully query that data, then I don't know how much value it is for you. So Data fusion helps enable the, the query process and transformation of that data. It also has a PANDAS API so that you could take advantage of PANDAS data frames as well and all of the machine learning tools associated with Pandas. >>Okay. You're also leveraging Par K in the platform cause we heard a lot about Par K in the middle of the last decade cuz as a storage format to improve on Hadoop column stores. What are you doing with Parque and why is it important? >>Sure. So parque is the column oriented durable file format. So it's important because it'll enable bulk import, bulk export, it has compatibility with Python and Pandas, so it supports a broader ecosystem. Par K files also take very little disc disc space and they're faster to scan because again, they're column oriented in particular, I think PAR K files are like 16 times cheaper than CSV files, just as kind of a point of reference. And so that's essentially a lot of the, the benefits of par k. >>Got it. Very popular. So and he's, what exactly is influx data focusing on as a committer to these projects? What is your focus? What's the value that you're bringing to the community? >>Sure. So Influx DB first has contributed a lot of different, different things to the Apache ecosystem. For example, they contribute an implementation of Apache Arrow and go and that will support clearing with flux. Also, there has been a quite a few contributions to data fusion for things like memory optimization and supportive additional SQL features like support for timestamp, arithmetic and support for exist clauses and support for memory control. So yeah, Influx has contributed a a lot to the Apache ecosystem and continues to do so. And I think kind of the idea here is that if you can improve these upstream projects and then the long term strategy here is that the more you contribute and build those up, then the more you will perpetuate that cycle of improvement and the more we will invest in our own project as well. So it's just that kind of symbiotic relationship and appreciation of the open source community. >>Yeah. Got it. You got that virtuous cycle going, the people call the flywheel. Give us your last thoughts and kind of summarize, you know, where what, what the big takeaways are from your perspective. >>So I think the big takeaway is that influx data is doing a lot of really exciting things with Influx DB IOx and I really encourage, if you are interested in learning more about the technologies that Influx is leveraging to produce IOCs, the challenges associated with it and all of the hard work questions and you just wanna learn more, then I would encourage you to go to the monthly Tech talks and community office hours and they are on every second Wednesday of the month at 8:30 AM Pacific time. There's also a community forums and a community Slack channel look for the influx DDB unders IAC channel specifically to learn more about how to join those office hours and those monthly tech tech talks as well as ask any questions they have about iacs, what to expect and what you'd like to learn more about. I as a developer advocate, I wanna answer your questions. So if there's a particular technology or stack that you wanna dive deeper into and want more explanation about how INFLUX DB leverages it to build IOCs, I will be really excited to produce content on that topic for you. >>Yeah, that's awesome. You guys have a really rich community, collaborate with your peers, solve problems, and, and you guys super responsive, so really appreciate that. All right, thank you so much Anise for explaining all this open source stuff to the audience and why it's important to the future of data. >>Thank you. I really appreciate it. >>All right, you're very welcome. Okay, stay right there and in a moment I'll be back with Tim Yoakum, he's the director of engineering for Influx Data and we're gonna talk about how you update a SAS engine while the plane is flying at 30,000 feet. You don't wanna miss this. >>I'm really glad that we went with InfluxDB Cloud for our hosting because it has saved us a ton of time. It's helped us move faster, it's saved us money. And also InfluxDB has good support. My name's Alex Nada. I am CTO at Noble nine. Noble Nine is a platform to measure and manage service level objectives, which is a great way of measuring the reliability of your systems. You can essentially think of an slo, the product we're providing to our customers as a bunch of time series. So we need a way to store that data and the corresponding time series that are related to those. The main reason that we settled on InfluxDB as we were shopping around is that InfluxDB has a very flexible query language and as a general purpose time series database, it basically had the set of features we were looking for. >>As our platform has grown, we found InfluxDB Cloud to be a really scalable solution. We can quickly iterate on new features and functionality because Influx Cloud is entirely managed, it probably saved us at least a full additional person on our team. We also have the option of running InfluxDB Enterprise, which gives us the ability to even host off the cloud or in a private cloud if that's preferred by a customer. Influx data has been really flexible in adapting to the hosting requirements that we have. They listened to the challenges we were facing and they helped us solve it. As we've continued to grow, I'm really happy we have influx data by our side. >>Okay, we're back with Tim Yokum, who is the director of engineering at Influx Data. Tim, welcome. Good to see you. >>Good to see you. Thanks for having me. >>You're really welcome. Listen, we've been covering open source software in the cube for more than a decade, and we've kind of watched the innovation from the big data ecosystem. The cloud has been being built out on open source, mobile, social platforms, key databases, and of course influx DB and influx data has been a big consumer and contributor of open source software. So my question to you is, where have you seen the biggest bang for the buck from open source software? >>So yeah, you know, influx really, we thrive at the intersection of commercial services and open, so open source software. So OSS keeps us on the cutting edge. We benefit from OSS in delivering our own service from our core storage engine technologies to web services temping engines. Our, our team stays lean and focused because we build on proven tools. We really build on the shoulders of giants and like you've mentioned, even better, we contribute a lot back to the projects that we use as well as our own product influx db. >>You know, but I gotta ask you, Tim, because one of the challenge that that we've seen in particular, you saw this in the heyday of Hadoop, the, the innovations come so fast and furious and as a software company you gotta place bets, you gotta, you know, commit people and sometimes those bets can be risky and not pay off well, how have you managed this challenge? >>Oh, it moves fast. Yeah, that, that's a benefit though because it, the community moves so quickly that today's hot technology can be tomorrow's dinosaur. And what we, what we tend to do is, is we fail fast and fail often. We try a lot of things. You know, you look at Kubernetes for example, that ecosystem is driven by thousands of intelligent developers, engineers, builders, they're adding value every day. So we have to really keep up with that. And as the stack changes, we, we try different technologies, we try different methods, and at the end of the day, we come up with a better platform as a result of just the constant change in the environment. It is a challenge for us, but it's, it's something that we just do every day. >>So we have a survey partner down in New York City called Enterprise Technology Research etr, and they do these quarterly surveys of about 1500 CIOs, IT practitioners, and they really have a good pulse on what's happening with spending. And the data shows that containers generally, but specifically Kubernetes is one of the areas that has kind of, it's been off the charts and seen the most significant adoption and velocity particularly, you know, along with cloud. But, but really Kubernetes is just, you know, still up until the right consistently even with, you know, the macro headwinds and all, all of the stuff that we're sick of talking about. But, so what are you doing with Kubernetes in the platform? >>Yeah, it, it's really central to our ability to run the product. When we first started out, we were just on AWS and, and the way we were running was, was a little bit like containers junior. Now we're running Kubernetes everywhere at aws, Azure, Google Cloud. It allows us to have a consistent experience across three different cloud providers and we can manage that in code so our developers can focus on delivering services, not trying to learn the intricacies of Amazon, Azure, and Google and figure out how to deliver services on those three clouds with all of their differences. >>Just to follow up on that, is it, no. So I presume it's sounds like there's a PAs layer there to allow you guys to have a consistent experience across clouds and out to the edge, you know, wherever is that, is that correct? >>Yeah, so we've basically built more or less platform engineering, This is the new hot phrase, you know, it, it's, Kubernetes has made a lot of things easy for us because we've built a platform that our developers can lean on and they only have to learn one way of deploying their application, managing their application. And so that, that just gets all of the underlying infrastructure out of the way and, and lets them focus on delivering influx cloud. >>Yeah, and I know I'm taking a little bit of a tangent, but is that, that, I'll call it a PAs layer if I can use that term. Is that, are there specific attributes to Influx db or is it kind of just generally off the shelf paths? You know, are there, is, is there any purpose built capability there that, that is, is value add or is it pretty much generic? >>So we really build, we, we look at things through, with a build versus buy through a, a build versus by lens. Some things we want to leverage cloud provider services, for instance, Postgres databases for metadata, perhaps we'll get that off of our plate, let someone else run that. We're going to deploy a platform that our engineers can, can deliver on that has consistency that is, is all generated from code that we can as a, as an SRE group, as an ops team, that we can manage with very few people really, and we can stamp out clusters across multiple regions and in no time. >>So how, so sometimes you build, sometimes you buy it. How do you make those decisions and and what does that mean for the, for the platform and for customers? >>Yeah, so what we're doing is, it's like everybody else will do, we're we're looking for trade offs that make sense. You know, we really want to protect our customers data. So we look for services that support our own software with the most uptime, reliability, and durability we can get. Some things are just going to be easier to have a cloud provider take care of on our behalf. We make that transparent for our own team. And of course for customers you don't even see that, but we don't want to try to reinvent the wheel, like I had mentioned with SQL data stores for metadata, perhaps let's build on top of what of these three large cloud providers have already perfected. And we can then focus on our platform engineering and we can have our developers then focus on the influx data, software, influx, cloud software. >>So take it to the customer level, what does it mean for them? What's the value that they're gonna get out of all these innovations that we've been been talking about today and what can they expect in the future? >>So first of all, people who use the OSS product are really gonna be at home on our cloud platform. You can run it on your desktop machine, on a single server, what have you, but then you want to scale up. We have some 270 terabytes of data across, over 4 billion series keys that people have stored. So there's a proven ability to scale now in terms of the open source, open source software and how we've developed the platform. You're getting highly available high cardinality time series platform. We manage it and, and really as, as I mentioned earlier, we can keep up with the state of the art. We keep reinventing, we keep deploying things in real time. We deploy to our platform every day repeatedly all the time. And it's that continuous deployment that allows us to continue testing things in flight, rolling things out that change new features, better ways of doing deployments, safer ways of doing deployments. >>All of that happens behind the scenes. And like we had mentioned earlier, Kubernetes, I mean that, that allows us to get that done. We couldn't do it without having that platform as a, as a base layer for us to then put our software on. So we, we iterate quickly. When you're on the, the Influx cloud platform, you really are able to, to take advantage of new features immediately. We roll things out every day and as those things go into production, you have, you have the ability to, to use them. And so in the end we want you to focus on getting actual insights from your data instead of running infrastructure, you know, let, let us do that for you. So, >>And that makes sense, but so is the, is the, are the innovations that we're talking about in the evolution of Influx db, do, do you see that as sort of a natural evolution for existing customers? I, is it, I'm sure the answer is both, but is it opening up new territory for customers? Can you add some color to that? >>Yeah, it really is it, it's a little bit of both. Any engineer will say, well, it depends. So cloud native technologies are, are really the hot thing. Iot, industrial iot especially, people want to just shove tons of data out there and be able to do queries immediately and they don't wanna manage infrastructure. What we've started to see are people that use the cloud service as their, their data store backbone and then they use edge computing with R OSS product to ingest data from say, multiple production lines and downsample that data, send the rest of that data off influx cloud where the heavy processing takes place. So really us being in all the different clouds and iterating on that and being in all sorts of different regions allows for people to really get out of the, the business of man trying to manage that big data, have us take care of that. And of course as we change the platform end users benefit from that immediately. And, >>And so obviously taking away a lot of the heavy lifting for the infrastructure, would you say the same thing about security, especially as you go out to IOT and the Edge? How should we be thinking about the value that you bring from a security perspective? >>Yeah, we take, we take security super seriously. It, it's built into our dna. We do a lot of work to ensure that our platform is secure, that the data we store is, is kept private. It's of course always a concern. You see in the news all the time, companies being compromised, you know, that's something that you can have an entire team working on, which we do to make sure that the data that you have, whether it's in transit, whether it's at rest, is always kept secure, is only viewable by you. You know, you look at things like software, bill of materials, if you're running this yourself, you have to go vet all sorts of different pieces of software. And we do that, you know, as we use new tools. That's something that, that's just part of our jobs to make sure that the platform that we're running it has, has fully vetted software and, and with open source especially, that's a lot of work. And so it's, it's definitely new territory. Supply chain attacks are, are definitely happening at a higher clip than they used to, but that is, that is really just part of a day in the, the life for folks like us that are, are building platforms. >>Yeah, and that's key. I mean especially when you start getting into the, the, you know, we talk about IOT and the operations technologies, the engineers running the, that infrastructure, you know, historically, as you know, Tim, they, they would air gap everything. That's how they kept it safe. But that's not feasible anymore. Everything's >>That >>Connected now, right? And so you've gotta have a partner that is again, take away that heavy lifting to r and d so you can focus on some of the other activities. Right. Give us the, the last word and the, the key takeaways from your perspective. >>Well, you know, from my perspective I see it as, as a a two lane approach with, with influx, with Anytime series data, you know, you've got a lot of stuff that you're gonna run on-prem, what you had mentioned, air gaping. Sure there's plenty of need for that, but at the end of the day, people that don't want to run big data centers, people that want torus their data to, to a company that's, that's got a full platform set up for them that they can build on, send that data over to the cloud, the cloud is not going away. I think more hybrid approach is, is where the future lives and that's what we're prepared for. >>Tim, really appreciate you coming to the program. Great stuff. Good to see you. >>Thanks very much. Appreciate it. >>Okay, in a moment I'll be back to wrap up. Today's session, you're watching The Cube. >>Are you looking for some help getting started with InfluxDB Telegraph or Flux Check >>Out Influx DB University >>Where you can find our entire catalog of free training that will help you make the most of your time series data >>Get >>Started for free@influxdbu.com. >>We'll see you in class. >>Okay, so we heard today from three experts on time series and data, how the Influx DB platform is evolving to support new ways of analyzing large data sets very efficiently and effectively in real time. And we learned that key open source components like Apache Arrow and the Rust Programming environment Data fusion par K are being leveraged to support realtime data analytics at scale. We also learned about the contributions in importance of open source software and how the Influx DB community is evolving the platform with minimal disruption to support new workloads, new use cases, and the future of realtime data analytics. Now remember these sessions, they're all available on demand. You can go to the cube.net to find those. Don't forget to check out silicon angle.com for all the news related to things enterprise and emerging tech. And you should also check out influx data.com. There you can learn about the company's products. You'll find developer resources like free courses. You could join the developer community and work with your peers to learn and solve problems. And there are plenty of other resources around use cases and customer stories on the website. This is Dave Valante. Thank you for watching Evolving Influx DB into the smart data platform, made possible by influx data and brought to you by the Cube, your leader in enterprise and emerging tech coverage.

(upbeat music) >> Okay, we're back with Tim Yoakum, who is the Director of Engineering at Influx Data. Tim, welcome. Good to see you. >> Good to see you. Thanks for having me. >> You're really welcome. Listen, we've been covering open source software on the Cube for more than a decade, and we've kind of watched the innovation from the big data ecosystem, the cloud is being built out on open source, mobile social platforms, key databases, and of course Influx DB, and Influx Data has been a big consumer and contributor of open source software. So my question to you is where have you seen the biggest bang for the buck from open source software? >> So, yeah, you know, Influx, really, we thrive at the intersection of commercial services and open source software. So OSS keeps us on the cutting edge. We benefit from OSS in delivering our own service, from our core storage engine technologies to web services, templating engines. Our team stays lean and focused because we build on proven tools. We really build on the shoulders of giants. And like you've mentioned, even better, we contribute a lot back to the projects that we use as well as our own product, Influx DB. >> You know, but I got to ask you, Tim, because one of the challenge that we've seen, in particular, you saw this in the heyday of Hadoop. The innovations come so fast and furious, and as a software company, you got to place bets, you got to, you know, commit people, and sometimes those bets can be risky and not pay off. How have you managed this challenge? >> Oh, it moves fast, yeah. That's a benefit though, because the community moves so quickly that today's hot technology can be tomorrow's dinosaur. And what we tend to do is we fail fast and fail often. We try a lot of things. You know, you look at Kubernetes for example. That ecosystem is driven by thousands of intelligent developers, engineers, builders. They're adding value every day. So we have to really keep up with that. And as the stack changes, we try different technologies, we try different methods, and at the end of the day, we come up with a better platform as a result of just the constant change in the environment. It is a challenge for us, but it's something that we just do every day. >> So we have a survey partner down in New York City called Enterprise Technology Research, ETR, and they do these quarterly surveys of about 1500 CIOs, IT practitioners, and they really have a good pulse on what's happening with spending. And the data shows that containers generally, but specifically Kubernetes, is one of the areas that has kind of, it's been off the charts and seen the most significant adoption and velocity, particularly, you know, along with cloud. But really Kubernetes is just, you know, still up and to the right consistently, even with, you know the macro headwinds and all of the other stuff that we're sick of talking about. So what are you doing with Kubernetes in the platform? >> Yeah, it's really central to our ability to run the product. When we first started out, we were just on AWS, and the way we were running was a little bit like containers junior. Now we're running Kubernetes everywhere, at AWS, Azure, Google Cloud. It allows us to have a consistent experience across three different cloud providers, and we can manage that in code. So our developers can focus on delivering services, not trying to learn the intricacies of Amazon, Azure, and Google, and figure out how to deliver services on those three clouds with all of their differences. >> Just a follow up on that, is it, now, so I presume it sounds like there's a PaaS layer there to allow you guys to have a consistent experience across clouds and up to the edge, you know, wherever. Is that, is that correct? >> Yeah, so we've basically built, more or less, platform engineering. This is the new hot phrase. You know, Kubernetes has made a lot of things easy for us because we've built a platform that our developers can lean on, and they only have to learn one way of deploying their application, managing their application. And so that just gets all of the underlying infrastructure out of the way and lets them focus on delivering Influx Cloud. >> Yeah, and I know I'm taking a little bit of a tangent, but is that, I'll call it a PaaS layer if I can use that term, are there specific attributes to Influx DB, or is it kind of just generally off the shelf PaaS? You know, is there any purpose built capability there that is value add, or is it pretty much generic? >> So we really build, we look at things with a build versus buy, through a build versus buy lens. Some things we want to leverage, cloud provider services for instance, Postgres databases for metadata perhaps, get that off of our plate, let someone else run that. We're going to deploy a platform that our engineers can deliver on, that has consistency, that is all generated from code that we can, as an SRE group, as an ops team, that we can manage with very few people really, and we can stamp out clusters across multiple regions in no time. >> So how, so sometimes you build, sometimes you buy it. How do you make those decisions, and what does that mean for the platform and for customers? >> Yeah, so what we're doing is, it's like everybody else will do. We're looking for trade offs that make sense. You know, we really want to protect our customers' data. So we look for services that support our own software with the most uptime, reliability, and durability we can get. Some things are just going to be easier to have a cloud provider take care of on our behalf. We make that transparent for our own team. And of course for customers, you don't even see that, but we don't want to try to reinvent the wheel. Like I had had mentioned with SQL data storage for metadata perhaps. Let's build on top of what these three large cloud providers have already perfected, and we can then focus on our platform engineering, and we can have our developers then focus on the Influx Data software, Influx Cloud software. >> So take it to the customer level. What does it mean for them? What's the value that they're going to get out of all these innovations that we've been been talking about today? And what can they expect in the future? >> So first of all, people who use the OSS product are really going to be at home on our cloud platform. You can run it on your desktop machine, on a single server, what have you. But then you want to scale up. We have some 270 terabytes of data across over 4 billion series keys that people have stored. So there's a proven ability to scale. Now, in terms of the open source software, and how we've developed the platform, you're getting highly available, high cardinality time series platform. We manage it, and really as I mentioned earlier, we can keep up with the state of the art. We keep reinventing. We keep deploying things in real time. We deploy to our platform every day repeatedly, all the time. And it's that continuous deployment that allows us to continue testing things in flight, rolling things out that change, new features, better ways of doing deployments, safer ways of doing deployments. All of that happens behind the scenes. And we had mentioned earlier Kubernetes, I mean that allows us to get that done. We couldn't do it without having that platform as a base layer for us to then put our software on. So we iterate quickly. When you're on the Influx Cloud platform, you really are able to take advantage of new features immediately. We roll things out every day. And as those things go into production, you have the ability to use them. And so in the end, we want you to focus on getting actionable insights from your data instead of running infrastructure. You know, let us do that for you. >> And that makes sense, but so is the, are the innovations that we're talking about in the evolution of Influx DB, do you see that as sort of a natural evolution for existing customers? Is it, I'm sure the answer is both, but is it opening up new territory for customers? Can you add some color to that? >> Yeah, it really is. It's a little bit of both. Any engineer will say, well, it depends. So cloud native technologies are really the hot thing. IoT, industrial IoT especially, people want to just shove tons of data out there and be able to do queries immediately, and they don't want to manage infrastructure. What we've started to see are people that use the cloud service as their data store backbone, and then they use edge computing with our OSS product to ingest data from say multiple production lines and down-sample that data, send the rest of that data off to Influx Cloud where the heavy processing takes place. So really us being in all the different clouds and iterating on that, and being in all sorts of different regions allows for people to really get out of the business of trying to manage that big data, have us take care of that. And of course, as we change the platform, end users benefit from that immediately. >> And so obviously, taking away a lot of the heavy lifting for the infrastructure, would you say the same thing about security, especially as you go out to IoT and the edge? How should we be thinking about the value that you bring from a security perspective? >> Yeah, we take security super seriously. It's built into our DNA. We do a lot of work to ensure that our platform is secure, that the data we store is kept private. It's of course always a concern. You see in the news all the time companies being compromised. You know, that's something that you can have an entire team working on, which we do, to make sure that the data that you have, whether it's in transit, whether it's at rest, is always kept secure, is only viewable by you. You look at things like software bill of materials. If you're running this yourself, you have to go vet all sorts of different pieces of software. And we do that, you know, as we use new tools. That's something that's just part of our jobs, to make sure that the platform that we're running has fully vetted software. And with open source especially, that's a lot of work. And so it's definitely new territory. Supply chain attacks are definitely happening at a higher clip than they used to. But that is really just part of a day in the life for folks like us that are building platforms. >> Yeah, and that's key. I mean, especially when you start getting into the, you know, we talk about IoT and the operations technologies, the engineers running that infrastructure. You know, historically, as you know, Tim, they would air gap everything. That's how they kept it safe. But that's not feasible anymore. Everything's >> Can't do that. >> connected now, right? And so you've got to have a partner that is, again, take away that heavy lifting to R and D so you can focus on some of the other activities. All right. Give us the last word and the key takeaways from your perspective. >> Well, you know, from my perspective, I see it as a a two lane approach. With Influx, with any any time series data, you know, you've got a lot of stuff that you're going to run on-prem. What you mentioned, air gaping, sure there's plenty of need for that, but at the end of the day, people that don't want to run big data centers, people that want to entrust their data to a company that's got a full platform set up for them that they can build on, send that data over to the cloud. The cloud is not going away. I think a more hybrid approach is where the future lives, and that's what we're prepared for. >> Tim, really appreciate you coming to the program. Great stuff. Good to see you. >> Thanks very much. Appreciate it. >> Okay, in a moment, I'll be back to wrap up today's session. You're watching the Cube. (gentle music)

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

we're back at vemma in 2022 we're here at the aria hotel in las vegas this is thecube's continuous coverage we're day two welcome to the cxo session we have ceo cto cso chief strategy officer brett diamond is the ceo justin jardina is the cto and dante orsini is the chief strategy officer for 11 11 systems recently named i guess today the impact cloud service provider of the year congratulations guys welcome thank you welcome back to the cube great to see you again thank you great likewise so okay brett let's start with you tell give us the overview of 11 1111 uh your focus area talk about the the the island acquisition what that what that's all about give us the setup yeah so we started 11-11 uh really with a focus on taking the three core pillars of our business which are cloud connectivity and security bring them together into one platform allowing a much easier way for our customers and our partners to procure those three solution sets through a single company and really focus on uh the three main drivers of the business uh which you know have a litany of other services associated with them under each platform okay so so justin cloud connectivity and security they all dramatically changed in march of 2020 everybody had to go to the cloud the rather rethink the network had a secure remote worker so what did you see from a from a cto's perspective what changed and how did 11 respond sure so early on when we built our cloud even back into 2008 we really focused on enterprise great features one of which being uh very flexible in the networking so we found early on was that we would be able to architect solutions for customers that were dipping their toe in the cloud and set ourselves apart from some of the vendors at the time so if you fast forward from 2008 until today we still see that as a main component for iaz and draz and the ability to start taking into some of the things brett talked about where customers may need a point-to-point circuit to offload data connectivity to us or develop sd-wan and multi-cloud solutions to connect to their resources in the cloud in my opinion it's just the natural progression of what we set out to do in 2008 and to couple that with the security um if you think about what that opens up from a security landscape now you have multiple clouds you have different ingress and egress points you have different people accessing workloads in each one of these clouds so the idea or our idea is that we can layer a comprehensive security solution over this new multi-cloud networking world and then provide visibility and manageability to our customer base so what does that mean specifically for your customers because i mean we saw obviously a rapid move toward endpoint um cloud security uh identity access you know people really started thinking rethinking that as opposed to trying to just you know build a moat around the castle right um what does that mean for for your customer you take care of all that you partner with whomever you need to partner in the ecosystem and then you provide the managed service how does that work right it does and that's a great analogy you know we have a picture of a hamburger in our office exploded with all the components and they say a good security policy is all the pieces and it's really synonymous with what you said so to answer your question yes we have all that baked in the platform we can offer managed services around it but we also give the consumer the ability to access that data whether it's a ui or api so dante i know you talk to a lot of customers all you do is watch the stock market go like this and like that you say okay the pandemic drove all these but but when you talk to csos and customers a lot of things are changing permanently first of all they were forced to march to digital when previously they were like we'll get there i mean a lot of customers were let's face it i mean some were serious about it but many weren't now if you're not a digital business you're out of business what have you seen when you talk to customers in terms of the permanence of some of these changes what are they telling you well i think we go through this for ourselves right the business continues to grow you've got tons of people that are working remotely and that are going to continue to work remotely right as much as we'd like to offer up hybrid workspace and things like that some folks are like hey i've worked it out i'm working out great from home right and also i think what justin was saying also is we've seen time go on that operating environment has gotten much more complex you've got stuff in the data center stuff it's somebody's you know endpoint you've got various different public clouds different sas services right that's why it's been phenomenal to work with veeam because we can protect that data regardless of where it exists but when you start to look at some of the managed security services that we're talking about we're helping those csos you get better visibility better control and take proactive action against the infrastructure um when we look at threat mitigation and how to actually respond when when something does happen right and i think that's the key because there's no shortage of great security vendors right but how do you tie it all together into a single solution right with a vendor that you can actually partner with to help secure the environment while you go focus on the things they're more strategic to the business i was talking to jim mercer at um red hat summit last week he's an idc analyst and he said we did a survey i think it was last summer and we asked customers to your point about there's no shortage of security tools how do you want to buy your security and you know do you want you know best to breed bespoke tools and you sort of put it together or do you kind of want your platform provider to do it now surprisingly they said platform provider the the problem is that's aspirational for a lot of platforms providers so they've got to look to a managed service provider so brett talk about the the island acquisition what green cloud is how that all fits together so we acquired island and green cloud last year and the reality is that the people at both of those companies and the technology is what drove us to making those acquisitions they were the foundational pieces to eleven eleven uh obviously the things that justin has been able to create from an automation and innovation perspective uh at the company is transforming this business in a litany of different ways as well so those two acquisitions allow us at this point to take a cloud environment on a geographic footprint not only throughout the us but globally uh have a security product that was given to us from from the green cloud acquisition of cascade and add-on connectivity to allow us to have all three platforms in one all three pillars so i like 11 11 11 is near and dear to my heart i am so where'd the name come from uh everybody asked me this question i think five times a day so uh growing up as a kid everyone in my family would always say 11 11 make a wish whenever you'd see it on the clock and uh during coven we were coming up with a new name for the business my daughter looked at the microwave said dad it's 11 11. make a wish the reality was though i had no idea why i'd been doing it for all that time and when you look up kind of the background origination derivation of the word uh it means the time of day when everything's in line um and when things are complex especially with running all the different businesses that we have aligning them so that they're working together it seemed like a perfect man when i had the big corner office at idc i had my staff meetings at 11 11. because the universe was aligned and then the other thing was nobody could forget the time so they gave him 11 minutes to be there now you'll see it all the time even when you don't want to so justin we've been talking a lot about ransomware and and not just backup but recovery my friend fred moore who you know coined the phrase backup is one thing recovery is everything and recovery time network speeds and and the like are critical especially when you're thinking cloud how are you architecting recovery for your clients maybe you could dig into that a little bit sure so it's really a multitude of things you know you mentioned ransomware seeing the ransomware landscape evolve over time especially in our business with backup and dr it's very singular you know people protecting against host nodes now we're seeing ransomware be able to get into an environment land and expand actually delete backups target backup vendors so the ransomware point i guess um trying to battle that is a multi-step process right you need to think about how data flows into the organization from a security perspective from a networking perspective you need to think about how your workloads are protected and then when you think about backups i know we're at veeam vmon now talking about veeam there's a multitude of ways to protect that data whether it's retention whether it's immutability air gapping data so while i know we focus a lot sometimes on protecting data it's really that hamburg analogy where the sum of the parts make up the protection so how do you provide services i mean you say okay you want immutability there's a there's a line item for that um you want faster or you know low rpo fast rto how does that all work for as a customer what what am i buying from you is it just a managed service we'll take care of everything platinum gold silver or is it if if you don't mind so i'm glad you asked that question because this is something that's very unique about us years ago his team actually built the ip because we were scaling at such an incredible rate globally through all our joint partners with veeam that how do we take all the intelligence that we have in his team and all of our solution architects and scale it so they actually developed a tool called catalyst and it's a pre-sales tool it's an application you download it you install it it basically takes a snapshot of your environment you start to manipulate the data what are you trying to do dave are you trying to protect that data are you backing up to us are you trying to replicate for dr purposes um you know what are you doing for production or maybe it's a migration it analyzes the network it analyzes all your infrastructure it helps the ses know immediately if we're a feasible solution based on what you are trying to do so nobody in the space is doing this and that's been a huge key to our growth because the channel community as well as the customer they're working with real data so we can get past all the garbage and get right to what's important for them for the outcome yeah that's huge who do you guys sell to is it is it more mid-sized businesses that maybe don't have the large teams is it larger enterprises who want to complement to their business is it both well i would say with the two acquisitions that we made the go-to-market sales strategies and the clientele were very different when you look at green cloud they're selling predominantly wholesale through msps and those msps are mostly selling to smbs right so we covered that smb market for the most part through our acquisition of green cloud island on the other hand was more focused on selling direct inbound through vars through the channel mid enterprise big enterprise so really those two acquisitions outside of the ip that we got from the systems we have every single go-to-market sale strategy and we're aligned from smb all the way up to the fortune 500. i heard a stat a couple months ago that that less than 50 of enterprises have a sock it blew me away and you know even small businesses need one they may not be able to afford but certainly a medium size or larger business should have some kind of sock is it does that stat jive with what you're seeing in the marketplace 100 if that's true the need for a managed service like this is just it's going to explode it is exploding yeah i mean 100 right there is zero unemployment in the cyberspace right just north america alone there's about a million or so folks in that space and right now you've got about 600 000 open wrecks just in north america right so earlier we talked about no shortage of tools right but the shortage of head count is a significant challenge big time right most importantly the people that you do have on staff they've got alert fatigue from the tools that they do have that's why you're seeing this massive insurgence in the managed security services provider lack of talent is number one challenge for csos that's what they'll tell you and there's no end in sight to that and it's you know another tool and and it's amazing because you see security companies popping up all the time billion dollar evaluations i mean lacework did a billion dollar raise and so so there's no shortage of funding now maybe that'll change you know with the market but i wanted to turn our attention to the keynotes this morning you guys got some serious love up on stage um there was a demo uh it was a pretty pretty cool demo fast recovery very very tight rpo as i recall it was i think four minutes of data loss is that right was that the right knit stat i was happy it wasn't zero data loss because there's really you know no such thing uh but so you got to feel good about that tell us about um how that all came about your relationship with with veeam who wants to take it sure i can i can take a step at it so one of the or two of the things that i'm um most excited about at least with this vmon is our team was able to work with veeam on that demo and what that demo was showing was some cdp-based features for cloud providers so we're really happy to see that and the reason why we're happy to see that is that with the veeam platform it's now given the customers the ability to do things like snapshot replication cdp replication on-prem backup cloud backup immutability air gap the list goes on and on and in our opinion having a singular software vendor that can provide all that through you know with a cloud provider on prem or not is really like the icing on the cake so for us it's very exciting to see that and then also coupled with a lot of the innovation that veeam's doing in the sas space right so again having that umbrella product that can cover all those use cases i'll tell you if you guys can get a that was a very cool demo if we can get a youtube of that that that demo i'll make sure we put it in the the show notes and uh of this video or maybe pop it into one of the blogs that we write about it um so so how you guys feel i mean this is a new chapter for you very cool with a couple of acquisitions that are now the main mainspring of your strategy so the first veeam on in a couple years so what's the vibe been like for you what's the nighttime activity the customer interaction i know you guys are running a lot of the back end demos so you're everywhere what's the what's the vibe like at veeamon and how does it feel to be back look at that one at dante as far as yeah you got a lot of experience here yeah let me loose on this one dave i'm like so excited about this right it's been it's been far too long to get face to face again and um veeam always does it right and i think that uh for years we've been back-ending like all the hands-on lab infrastructure here but forget about that i think the part that's really exciting is getting face-to-face with such a great team right we have phenomenal architects that we work with at veeam day in and day out they put up with us pushing them pushing and pushing them and together we've been able to create a lot of magic together right but i think it's you can't replace the human interaction that we've all been starving for for the last two years but the vibe's always fantastic at veeam if you're going to be around tonight i'll be looking forward to enjoying some of that veeam love with you at the after party yeah that's well famous after parties we'll see if that culture continues i have a feeling it will um brett where do you want to take 11 11. a new new phase in all of your careers you got a great crew out here it looks like i i love that you're all out and uh make some noise here people let's hear it all right let's see you this is the biggest audience we've had all week where do you want to take 11 11. i think you know if uh if you look at what we've done so far in the short six months since the acquisitions of green cloud and ireland obviously the integration is a key piece we're going to be laser focused on growing organically across those three pillars we've got to put more capital and resources into the incredible ip like i said earlier that just and his team have created on those front ends the user experience but you know we made two large acquisitions obviously mna is a is a key piece for us we're going to be diligent and we're probably going to be very aggressive on that front as well to be able to grow this business into the global leader of cloud connectivity and security and i think we've really hit a void in the industry that's been looking for this for a very long time and we want to be the first ones to be able to collaborate and combine those three into one when the when the cloud started to hit the steep part of the s-curve kind of early part of the last decade people thought oh wow these managed service providers are toast the exact opposite happened it created such a tailwind and need for consistent services and integration and managed services we've seen it all across the stack so guys wish you best of luck congratulations on the acquisitions thank you uh hope to have you back soon yeah thank you around the block all right keep it right there everybody dave vellante for the cube's coverage of veeamon 2022 we'll be right back after this short break

(pleasant music) >> We're back at Veeamon 2022. We're here at the Aria hotel in Las Vegas. This is theCube's continuous coverage. We're in day two. Welcome to the CXO session. We have CEO, CTO, CSO, chief strategy officer. Brett Diamond is the CEO, Justin Giardina is the CTO, and Dante Orsini is the chief strategy officer for 11:11 Systems recently named, I guess today, the impact cloud service provider of the year. Congratulations, guys. Welcome to theCube. Welcome back to theCube. Great to see you again. >> Thank you. >> Great. >> Likewise. >> Thanks for having us. Okay, Brett, let's start with you. Give us the overview of 11:11, your focus area, talk about the Island acquisition, what that's all about, give us the setup. >> Yeah, so we started 11:11, really, with a focus on taking the three core pillars of our business, which are cloud, connectivity, and security, bring them together into one platform, allowing a much easier way for our customers and our partners to procure those three solution sets through a single company and really focus on the three main drivers of the business, which, you know, have a litany of other services associated with them under each platform. >> Okay, so Justin, cloud connectivity and security, they all dramatically changed in March of 2020. Everybody had to go to the cloud, had to rethink the network, had to secure remote workers. So what did you see, from a CTO's perspective, what changed and how did 11:11 respond? >> Sure, so early on, when we built our cloud, even back into 2008, we really focused on enterprise grade features, one of which being very flexible in the networking. So we found early on was that we would be able to architect solutions for customers that were dipping their toe in the cloud and set ourselves apart from some of the vendors at the time. So if you fast forward from 2008 until today, we still see that as a main component for IaaS and DRaaS and the ability to start taking into some of the things Brett talked about, where customers may need a point to point circuit to offload data connectivity to us, or develop SD-WAN and multi-cloud solutions to connect to their resources in the cloud. In my opinion, it's just the natural progression of what we set out to do in 2008. And to couple that with the security, if you think about what that opens up from a security landscape, now you have multiple clouds, you have different ingress and egress points, you have different people accessing workloads in each one of these clouds, so the idea or our idea is that we can layer a comprehensive security solution over this new multi-cloud networking world and then provide visibility and manageability to our customer base. >> So what does that mean specifically for your customers? Because, I mean, we saw obviously a rapid move toward end point, cloud security, identity access. You know, people really started rethinking that as opposed to trying to just, you know, build a moat around the castle. >> Right. >> What does that mean for your customer? You take care of all that? You partner with whomever you need to partner in the ecosystem and then you provide the managed service? How does that work? >> Right. It does and that's a great analogy. You know, we have a picture of a hamburger in our office, exploded with all the components and they say, a good security policy has all the pieces and it's really synonymous with what you said. So to answer your question, yes. We have all that baked in the platform. We can offer managed services around it, but we also give the consumer the ability to access that data, whether it's a UI or API. >> So Dante, I know you talked to a lot of customers. All you do is watch the stock market go like this and like that and you say, okay, the pandemic drove all these, but when you talk to CISOs and customers, a lot of things are changing permanently. First of all, they were forced to march to digital when previously, they were like, eh, we'll get there. I mean, a lot of customers were. Let's face it. I mean, some were serious about it, but many weren't. Now, if you're not a digital business, you're out of business. What have you seen when you talk to customers in terms of the permanence of some of these changes? What are they telling you? >> Well, I think, you know, we go through this ourselves, right? The business continues to grow. You've got tons of people that are working remotely and they are going to continue to work remotely, right? As much as we'd like to offer up hybrid workspace and things like that, some folks are like, hey, I've worked it out. I'm working out great from home, right? And also, I think what Justin was saying also is, as we've seen time go on, that operating environment has gotten much more complex. You've got stuff in the data center, stuff in somebody's, you know, endpoint, you've got various different public clouds, different SAS services, right? That's why it's been phenomenal to work with Veeam because we can protect that data regardless of where it exists. But when you start to look at some of the managed security services that we're talking about, we're helping those CSOs, you know, get better visibility, better control, and take proactive action against the infrastructure when we look at threat mitigation and how to actually respond when something does happen, right? And I think that's the key because there's no shortage of great security vendors, right? But how do you tie it all together into a single solution, right, with a vendor that you can actually partner with to help secure the environment while you go focus on the things that are more strategic to the business? >> I was talking to Jim Mercer at Red Hat Summit last week. He's an IDC analyst and we did a survey, I think it was last summer, and we asked customers to your point about, there's no shortage of security tools. How do you want to buy your security? And, you know, do you want, you know, best to breed bespoke tools and you sort of put it together or do you kind of want your platform provider to do it? Now surprisingly, they said platform provider. The problem is, that's aspirational for a lot of platform providers, so they got to look to a managed service provider. So Brett, talk about the Island acquisition, what Green Cloud is, how that all fits together. >> So we acquired Island and Green Cloud last year and the reality is, the people at both of those companies and the technology is what drove us to making those acquisitions. They were the foundational pieces to 11:11. Obviously, the things that Justin has been able to create from an automation and innovation perspective at the company is transforming this business in a litany of different ways, as well. So, those two acquisitions allow us at this point to take a cloud environment on a geographic footprint, not only throughout the US but globally, have a security product that was given to us from the Green Cloud acquisition of Cascade, and add on connectivity to allow us to have all three platforms in one, all three pillars in one. >> So I like 11:11. 11:11 is near and dear to my heart. So where'd the name come from? >> Everybody asked me this question, I think, five times a day. So growing up as a kid, everyone in my family would always say 11:11 make a wish whenever you'd see it on the clock. And during COVID, we were coming up with a new name for the business. My daughter looked at the microwave, said, dad, it's 11:11, make a wish. The reality was though, I had no idea why I'd been doing it for all that time and when you look up kind of the background origination, derivation of the word, it means the time of day when everything's in line and when things are complex, especially with running all the different businesses that we have, aligning them so that they're working together, it seemed like the perfect thing >> So when I had the big corner office at IDC, I had my staff meetings at 11:11. >> Yep. >> Because the universe was aligned and then the other thing was, nobody could forget the time. So they gave me 11 minutes to be there, so they were never late. >> And now you'll see it all the time, even when you don't want to. (chuckles) >> So Justin, we've been talking a lot about ransomware and not just backup, but recovery. My friend, Fred Moore, who, you know, coined the phrase backup is one thing, recovery is everything, and recovery time, network speeds and the like are critical, especially when you're thinking cloud. How are you architecting recovery for your clients? Maybe you could dig into that a little bit. >> Sure. So it's really a multitude of things. You know, you mention ransomware. Seeing the ransomware landscape evolve over time, especially in our business with backup NDR, is very singular, you know, people protecting against host nodes. Now we're seeing ransomware be able to get into an environment, land and expand, actually delete backups, target backup vendors. So the ransomware point, I guess, trying to battle that is a multi-step process, right? You need to think about how data flows into the organization from a security perspective, from a networking perspective, you need to think about how your workloads are protected, and then when you think about backups, I know we're at Veeamon now talking about Veeam, there's a multitude of ways to protect that data, whether it's retention, whether it's immutability, air gapping data. So, while I know we focus a lot sometimes on protecting data, it's really that hamburger analogy where the sum of the parts make up the protection. >> So how do you provide services? I mean, do you say, okay, do you want immutability? There's a line item for that. You want low RPO, fast RTO? How does that all work as a customer? What am I buying from you? Is it just a managed service? We'll take care of everything, platinum, gold, silver, or is it? >> If you don't mind, so I'm glad you asked that question because this is something that's very unique about us. Years ago, his team actually built the IP because we were scaling at such an incredible rate globally through all our joint partners with Veeam that, how do we take all the intelligence that we have and his team and all of our solution architects and scale it? So they actually developed a tool called Catalyst, and it's a pre-sales tool. It's an application. You download it, you install it. It basically takes a snapshot of your environment. You start to manipulate the data. What are you trying to do, Dave? Are you trying to protect that data? Are you backing up to us? Are you trying to replicate it for DR purposes? You know, what are you doing for production, or maybe it's a migration? It analyzes the network. It analyzes all your infrastructure. It helps the SEs know immediately if we're a feasible solution based on what you are trying to do. So, nobody in the space is doing this and that's been a huge key to our growth because the channel community, as well as the customer, they're working with real data. So we can get past all the garbage, you get right to what's important for them for the outcome. >> Yeah, that's huge. Who do you guys sell to? Is it more mid-size businesses that maybe don't have the large teams? Is it larger enterprises who want to compliment to their business? Is it both? >> Well, I would say with the two acquisitions that we made to go to market sales strategies and the clientele were very different, when you look at Green Cloud, they're selling predominantly wholesale through MSPs and those MSPs are mostly selling to SMBs, right? So we covered that SMB market for the most part through our acquisition of Green Cloud. Island, on the other hand, was more focused on selling direct, inbound, through VARs through the channel, mid-enterprise, big enterprise. So really, those two acquisitions outside of the IP that we got from the systems, we have every single go to market sales strategy and we're aligned from SMB all the way up to the Fortune 500. >> I heard a stat a couple months ago that less than 50% of enterprises have a SAQ. That blew me away. And, you know, even small businesses need one. They may not be able to afford, but there's certainly a medium size or a larger business should have some kind of SAQ. Does that stat jive with what you're seeing in the marketplace? >> A hundred percent. >> If that's true, the need for a managed service like this, it's going to explode. It is exploding, I mean. >> Yeah, I mean, a hundred percent, right? There is zero unemployment in the cyberspace, right? Just North America alone, there's about a million or so folks in that space and right now you've got about 600,000 open recs just in North America, right? So earlier, we talked about no shortage of tools, right? But the shortage of headcount is a significant challenge, big time, right? Most importantly, the people that you do have on staff, they've got alert fatigue from the tools that they do have. That's why you're seeing this massive surgence in the managed security services provider. >> Lack of talent is number one challenge for CISOs. That's what they'll tell you and there's no end in sight to that. And it's, you know, another tool and it's amazing 'cause you see security companies popping up all the time. I mean, billion dollar valuations, I mean, Lacework did a billion dollar raise. And so, there's no shortage of funding. Now, maybe that'll change, you know, with the market but I wanted to turn our attention to the keynotes this morning. You guys got some serious love up on stage. There was a demo. It was a pretty cool demo, fast recovery, very tight RPO, as I recall. It was, I think, four minutes of, of data loss? Is that right? Is that the right stat? I was happy it wasn't zero data loss 'cause there's really, you know, no such thing, but so you got to feel good about that. Tell us about how that all came about, your relationship with Veeam. Who wants to take it? >> Sure, I can take a stab at it. So two of the things that I'm most excited about, at least with this Veeamon, is our team was able to work with Veeam on that demo, and what that demo was showing was some CDP based features for cloud providers. So we're really happy to see that and the reason why we're happy to see that is that with the Veeam platform, it's now given the customers the ability to do things like snapshot replication, CDP replication, on-prem backup, cloud backup, immutability air gap, the list goes on and on. And in our opinion, having a singular software vendor that can provide all that, you know, with a cloud provider on-prem or not is really like, the icing on the cake. So for us, it's very exciting to see that, and then also coupled with a lot of the innovation that's Veeam's doing in the SAS space, right? So again, having that umbrella product that can cover all those use cases. >> I'll tell you, that was a very cool demo. If you can get a YouTube of that demo, I'll make sure we put it in the show notes of this video or maybe pop it into one of the blogs that we write about it. So, how do you guys feel? I mean, this is a new chapter for you. Very cool, with a couple of acquisitions that are now the main spring of your strategy, so the first Veeamon in a couple years. So what's the vibe been like for you? What's the nighttime activity, the customer interaction? I know you guys are running a lot of the backend demos, so you're everywhere. What's the vibe like at Veeamon and how does it feel to be back? >> I'll give that one to Dante as far as the vibes, so far. >> Yeah, yeah, you got a lot of experience. >> Yeah, let me loose on this one, Dave. I'm like, so excited about this, right? It's been far too long to get face to face again and Veeam always does it right. And I think that for years, we've been back ending like, all the hands on lab infrastructure here, but forget about that. I think the part that's really exciting is getting face to face with such a great team, right? We have phenomenal architects that we work with at Veeam day in and day out. They put up with us, pushing them, pushing them, pushing them and together, we've been able to create a lot of magic together, right? But I think you can't replace the human interaction that we've all been starving for, for the last two years. But the vibe's always fantastic at Veeam. If you're going to be around tonight, I'll be looking forward to enjoying some of that Veeam love with you at the after party. >> Yeah, well, famous after parties. We'll see if that culture continues. I have a feeling it will. Brett, where do you want to take 11:11? New phase in all of your careers. You got a great crew out here, it looks like. I love that you're all out and, make some noise here, people. Let's hear it! (audience cheering) You see, this is the biggest audience we've had all week. Where do you want to take 11:11? >> I think, you know, if you look at what we've done so far in the short six months since the acquisitions of Green Cloud and Island, obviously the integration is a key piece. We're going to be laser focused on growing organically across those three pillars. We've got to put more capital and resources into the incredible IP, like I said earlier, that Justin and his team have created on those front ends, the user experience. But, you know, we made two large acquisitions, obviously M and A is a key piece for us. We're going to be diligent and we're probably going to be very aggressive on that front as well, to be able to grow this business into the global leader of cloud connectivity and security. And I think we've really hit a void in the industry that's been looking for this for a very long time and we want to be the first ones to be able to collaborate and combine those three into one. >> When the cloud started to hit the steep part of the S-curve, kind of early part of last decade, people thought, oh wow, these managed service providers are toast. The exact opposite happened. It created such a tailwind and need for consistent services and integration and managed services. We've seen it all across the stacks. So guys, wish you best of luck. Congratulations on the acquisitions, >> Thank you. >> And hope to have you back soon. >> Absolutely, thanks for having us. >> All right, keep it right there everybody. Dave Vellante for theCube's coverage of Veeamon 2022. We'll be right back after this short break. (pleasant music)

>>we're back, we're assessing the as a service space. H. P. S. Green Lake announcements, my name is Dave balanta, you're watching the cube die on Hinchcliffe is here along with Holger muller, these are the constellation kids, extraordinary analysts guys. Great to see you again. I mean it super experienced. You guys, you deal with practitioners, you deal your technologist, you've been following this business for a long time. Diane, We spoke to Holger earlier, I want to start with you uh when you look at this whole trend to as a service, you see a lot of traditional enterprise companies, hard traditionally hardware companies making that move for for a lot of obvious reasons are they sort of replicating in your view, a market that you know well and sas what's your take on how they're doing generally that trend and how HP is >>operating well. Hp has had a unique heritage. They're coming at the whole cloud story and you know the Hyper Scaler story from a different angle than a lot of their competitors and that's mostly a good thing because most of the world is not yet on the cloud, They actually came from H. P. S original world, their line of servers and networks and so on. Um and and so they bring a lot of credibility saying we really understand the world you live in now but we want to take you to that that as a service future. Uh and and you know, since we understand you so well and we also understand where this is going and we can adapt that to that world. Have a very compelling story and I think that with green like you know, was first started about four years ago, it was off to the side uh you know, with all the other offerings now it's it's really grown up, it's matured a lot and I think you know, as we talked about the announcements, we'll see that a lot of key pieces have fallen into place to make it a very compelling hybrid cloud option for the enterprise. >>Let's talk about the announcement. Was there anything in particular that stood out the move to data management? I think it's pretty interesting is a tam expansion strategy. What's your take on the >>announcement? Well, the you know, the unified analytics uh story I think is really important now. That's the technology piece where they say, they say we can give you a data fabric, you can access your data outside of its silos. It doesn't address a lot of the process and cultural issues around data ownership inside the enterprise, but it's you know, having in the actual platform and as you articulating it as a platform, that's one of the things that was also evident, they were getting better and better at saying this is a hybrid cloud platform and it has all the pieces that you would expect, especially the things like being able to bring your data from wherever it is to wherever people needed to be. Uh you know, that's the Holy Grail, so really glad to see that component in particular. I also like the cloud adoption framework saying we understand how to take you from this parochial world of servers that you have and do a cloud date of hybrid world and then maybe eventually get you get you to a public cloud. We understand all the steps and all the components uh I think that's uh you know, I have a study that fully in depth but it seems to have all the moving parts >>chime in anything stand out to, you >>know, I think it's great announcements and the most important things H. P. S and transformation and when you and transformation people realize who you've been, the old and they're here. Maybe the mass of the new but an experienced technology but I will not right away saying oh it's gonna happen right. It's going to happen like this is gonna be done, it's ready, it's materials ready to use and so on. So this is going to give more data points, more proof points, more capabilities that HB is moving away from whatever they were before. That's not even say that to a software services as a service as you mentioned provider. It's >>been challenging, you look at the course of history for companies that try to go from being a hardware company to a software company, uh HP itself, you know, sort of gave up on that IBM you could say, you know semi succeeded but they've they've struggled what's different >>That will spend 30 billion, >>30 >>four. Exactly. So and of course Cisco is making that transition. I mean every traditional large companies in that transition. What about today? Well, first of all, what do you think about HP es, prospects of doing so? And are there things today in the business that make that, you know more faster, whether it's containers or the cloud itself or just the scale of the internet? >>I mean it's fascinating topic, right? And I think many of the traditional players in the space failed because they wanted to mimic the cloud players and they simply couldn't muster up the Capex, which you need to build up public cloud. Right? Because if you think of the public cloud players then didn't put it up for the cloud offering, they put it up because they need themselves right, amazon is an online retailer google as a search and advertising giant Microsoft is organic load from from from office, which they had to bring to the cloud. So it was easier for them to do that. So no wonder they failed. The good news is they haven't lost much of their organic load. Hp customers are still HP customer service, celebrity security in their own premises and now they're bringing the qualities of the cloud as a service, the pay as you go capabilities to the on premise stack, which helps night leader to reduce complexity and go to what everybody in the post pandemic world wants to get to, which is I only pay for what I use and that's super crucial because business goes up and down. We're riding all the waves in a much, much faster way than ever before. Right before we had seven year cycles, it was kind of like cozy almost now we're down to seven weeks, sometimes seven days, sometimes seven hour cycles. And I don't want to pay for it infrastructure, which was great for how my business was two years ago. I want to pay for it as I use it now as a pivot now and I'm going to use >>Diane. How much of this? Thank you for that whole girl. How much of this is what customers want and need versus sort of survival tactics on the vendors >>part. So I think that there, if you look at where customers want to go, they know they have to go cloud, they had to go as a service. Um, and that they need to make multiple steps to get there. And for the most part, I see green light is being a, a highly credible market response to say, you know, we understand IT better, we helped build you guys up over the last 30 years. We can take you the rest of the way, here's all the evidence and the proof points, which I think a lot of the announcements provide uh, and they're very good on cloud native, but the area where the story, um, you may not be the fullest strength it needs to be is around things like multi cloud. So when I talked to almost any large organization C I O. They have all the clouds need to know, how do I make all this fit together? How do I reconcile that? So for the most part, I think it's closely aligned with actual customer requirements and customer needs. I think these have additional steps to go >>is that, do you feel like that's a a priority? In other words, they got to kind of take a linear path. They got to solve the problem for their core customer base or is it, do you feel like that's not even necessarily an aspiration? And it seems like customers, I want them to go. There is what I'm >>inferring that you're, so I do. Well let's go back to the announcement specifically. So there's there are two great operational announcements, one around the cloud physics and the other one around info site. It gives a wealth of data, you know, full stack about how things are operating, where the needs are, how you might be able to get more efficiencies, how you can shut down silicon, you're not using a lot of really great information, but all that has to live with a whole bunch of other consoles and everybody is really craving the single piece of glass. That's what they want is they want to reduce complexity as holder was saying and say, I want to be able to get my arms around my data center and all of my cloud assets. But I don't want to have to check each cloud. I want it in one place. So uh, but it's great to see those announcements position them for that next step. They have these essential components that are that look, you know, uh, they look best to breed in terms of their capabilities are certainly very modern now. They have to get the rest of that story. >>Hope you were mentioning Capex. I added it up I think last year the big four include Alibaba, spent 100 billion on the Capex and generally the traditional on prem players have been defensive around cloud. Not everything is moving to the cloud, we all know that. But I, I see that as a gift in a way that the companies like HP can build on top of into Diane's point that, you know, extend cross clouds out to the edge, which is, you know, a trillion dollar opportunity, which is just just massive. What are your thoughts on HBs opportunities there and chances of maybe breaking away from the pack >>I think definitely well there's no matter pack left, like there's only 23, it's a triumvirate of maybe it's a good thing from a marketing standpoint. There's not a long list of people who give me hardware in my data center. But I think it increases their chances, right? Like I said, it's a transformation, there's more credibility, there's more data point, there's more usage. I can put more workloads on this. And I see, I also will pay attention to that and look at that for the transformation. No question. >>Yeah. And speaking of C. I. O. S. What are you hearing these days? What's their reaction to this whole trend toward as a service? Do they, do they welcome it? Do they feel like okay it's a wait and see. Uh I need more proof points. What's the sentiment? >>Well, you have to divide the Ceo market basically two large groups. One is the the ones that are highly mature. They tend to be in larger organizations are very sophisticated consumers of everything. They see the writing on the wall and that for most things certainly not everything as a service makes the most sense for all the reasons we know, agility and and and speed, you know, time to value scalability, elasticity, all those great things. Uh And then you have the the other side of the market which they really crave control. They have highly parochial worlds that they've built up um that are hard to move to the cloud because they're so complex and intertwined because they haven't had that high maturity. They have a lot of spaghetti architecture. They're not really ready to move the cloud very quickly. So the the second audience though is the largest one and it's uh you know, the hyper scales are probably getting a lot of the first ones. Um, but the bigger markets, really the second one where the folks that need a lot of help and they have a lot of legacy hardware and software that they need to move and that H P. E understands very well. And so I think from that standpoint they're well positioned to take advantage of an untapped market are relatively untapped market in comparison. Hey, >>in our business we all get pulled in different directions because it would get to eat. But what are some of the cool things you guys are working on in your research that you might want people to know about? >>Uh, I just did a market overview for enterprise application platforms. I'm a strong believer that you should not build all your enterprise software yourself, but you can't use everything that you get from your typical SAs provider. So it's focusing on the extent integration and build capabilities. Bill is very, very important to create the differentiation in the marketplace and all the known sauce players basically for their past. Right? My final example is always to speak in cartoons, right? The peanuts, right? There's Linus of this comfort blanket. Right? The past capability of the SARS player is the comfort blanket, right? You don't fit 100% there or you want to build something strategic or we'll never get to that micro vertical. We have a great enterprise application, interesting topic. >>Especially when you see what's happening with Salesforce and Service now trying to be the platform platforms. I have to check that out. How about >>Diane? Well and last year I had a survey conducted a survey with the top 100 C IOS and at least in my view about what they're gonna do to get through this year. And so I'm redoing that again to say, you know, what are they gonna do in 2022? Because there's so many changes in the world and so, you know, last year digital transformation, automation cybersecurity, we're at the top of the list and it'll be very interesting. Cloud was there too in the top five. So we're gonna see what, how it's all going to change because next year is the year of hybrid work where we're all we have to figure out how half of our businesses are in the office and half are at home and how we're gonna connect those together and what tools we're gonna make, that everybody's trying to figure >>out how to get hybrid. Right, so definitely want to check out that research guys. Thanks so much for coming to the cubes. Great to see you. >>Thanks. Thanks Dave >>Welcome. Okay and thank you for watching everybody keep it right there for more great content from H. P. S. Green Lake announcement. You're watching the cube. Mm this wasn't

>>from around the globe. It's >>the cube >>with coverage of >>Kublai khan and >>Cloud Native Con, Europe 2021 virtual brought >>to you by red hat, >>the cloud Native >>Computing foundation and ecosystem partners. Hello, welcome back to the cubes coverage of Kublai khan. Cloud Native Con 2021 part of the CNC. S continuing cube partnership virtual here because we're not in person soon, we'll be out of the pandemic and hopefully in person for the next event. I'm john for your host of the key. We're here with ricardo. Roach computing engineers sir. In CUBA. I'm not great to see you ricardo. Thanks for remote ng in all the way across the world. Thanks for coming in. >>Hello, Pleasure. Happy to be here. >>I saw your talk with Priyanka on linkedin and all around the web. Great stuff as always, you guys do great work over there at cern. Talk about what's going on with you and the two speaking sessions you have it coop gone pretty exciting news and exciting sessions happening here. So take us through the sessions. >>Yeah. So actually the two sessions are kind of uh showing the two types of things we do with kubernetes. We we are doing we have a lot of uh services moving to kubernetes, but the first one is more on the services we have in the house. So certain is known for having a lot of data and requests, requiring a lot of computing capacity to analyze all this data. But actually we have also very large community and we have a lot of users and people interested in the stuff we do. So the first question will actually show how we've been uh migrating our group of infrastructure into the into communities and in this case actually open shift. And uh the challenge there is to to run a very large amount of uh global websites on coordinators. Uh we run more than 1000 websites and there will be a demonstration on how we do all the management of the website um life cycle, including upgrading and deploying new new websites and an operator that was developed for this purpose. And then more on the other side will give with a colleague also talk about machine learning. Machine learning has been a big topic for us. A lot of our workloads are migrating to accelerators and can benefit a lot from machine learning. So we're giving a talk about a new service that we've deployed on top of Cuban areas where we try to manage to uh lifecycle of machine learning workloads from data preparation all the way to serving the bottles, also exploring the communities features and integrating accelerators and a lot of accelerators. >>So one part of the one session, it's a large scale deployment kubernetes key to there and now the machine learning essentially service for other people to use that. Right? Like take me through the first large scale deployment. What's the key innovation there in your opinion? >>Yeah, I think compared to the infrastructure we had before, is this notion that we can develop an operator that will uh, manage resource, in this case a website. And this is uh, something that is not always obvious when people start with kubernetes, it's not just an orchestra, it's really the ap and the capability of managing a huge amount of resources, including custom resources. So the possibility to develop this operator and then uh, manage the lifecycle of uh, something that was defined in the house and that fits our needs. Uh, There are challenges there because we have a large amount of websites and uh, they can be pretty active. Uh, we also have to some scaling issues on the storage that serves these these websites and we'll give some details uh during the talk as well, >>so kubernetes storage, this is all kind of under the covers, making this easier. Um and the machine learning, it plays nicely in that what if you take us for the machine learning use case, what's going on there, wow, what was the discovery, How did you guys put that together? What's the key elements there? >>Right, so the main challenge there has been um that machine learning is is quite popular but it's quite spread as well, so we have multiple groups focusing on this, but there's no obvious way to centralize not only the resource usage and make it more efficient, but also centralize the knowledge of how these procedures can be done. So what we are trying to do is just offer a service to all our users where we help them with infrastructure so that they don't have to focus on that and they could focus just on their workloads and we do everything from exposing the data systems that we have in the house so that they can do access to the data and data preparation and then doing um some iteration using notebooks and then doing distributed training with potentially large amount of gps and that storage and serving up the models and all of this is uh is managed with the coordinates cluster underneath. Uh We had a lot of knowledge of how to handle kubernetes and uh all the features that everyone likes scalability. The reliability out of scaling is very important for this type of workload. This is, this is key. >>Yeah, it's interesting to see how kubernetes is maturing, um congratulations on the projects. Um they're going to probably continue to scale. Remember this reminds me of when I was uh you know coming into the business in the 98 late eighties early nineties with TCP I. P. And the S. I. Model, you saw the standards evolve and get settled in and then boom innovation everywhere. And that took about a year to digest state and scale up. It's happening much faster now with kubernetes I have to ask you um what's your experience with the question that people are looking to get answered? Which is as kubernetes goes, the next generation of the next step? Um People want to integrate. So how is kubernetes exposing a. P. I. S. To say integration points for tools and other things? Can you share your experience and where this is going, what's happening now and where it goes? Because we know there's no debate. People like the kubernetes aspect of it, but now it's integration is the conversation. Can you share your thoughts on that? >>I can try. Uh So it's uh I would say it's a moving target, but I would say the fact that there's such a rich ecosystem around kubernetes with all the cloud, David projects, uh it's it's uh like a real proof that the popularity of the A. P. I. And this is also something that we after we had the first step of uh deploying and understanding kubernetes, we started seeing the potential that it's not reaching only the infrastructure itself, it's reaching all the layers, all the stack that we support in house and premises. And also it's opening up uh doors to easily scale into external resources as as well. So what we've been trying to tell our users is to rely on these integrations as much as possible. So this means like the application lifecycle being managed with things like Helmand getups, but also like the monitoring being managed with Prometheus and once you're happy with your deployment in house we have ways to scale out to external resources including public clouds. And this is really like see I don't know a proof that all these A. P. I. S are not only popular but incredibly useful because there's such a rich ecosystem around it. >>So talk about the role of data in this obviously machine learning pieces something that everyone is interested in as you get infrastructure as code and devops um and def sec ops as everything's shifting left. I love that, love that narrative day to our priests. All this is all proving mature, mature ization. Um data is critical. Right? So now you get real time information, real time data. The expectations for the apps is to integrate the data. What's your view on how this is progressing from your standpoint because machine learning and you mentioned you know acceleration or being part of another system. Cashing has always done that would say databases. Right. So you've got now is databases get slower, caches are getting faster now they're all the ones so it's all changing. So what's your thoughts on this next level data equation into kubernetes? Because you know stateless is cool but now you've got state issues. >>Yeah so uh yeah we we've always had huge needs for for data we store and I I think we are over half an exhibit of data available on the premises but we we kind of have our own storage systems which are external and that's for for like the physics data, the raw data and one particular charity that we had with our workloads until recently is that we we call them embarrassing parallel in the sense that they don't really need uh very tight connectivity between the different workloads. So if it's people always say tens of thousands of jobs to do some analysis, they're actually quite independent, they will produce a lot more data but we can store them independently. Machine learning is is posing a challenge in the sense that this is a training tends to be a lot more interconnected. Um so it can be a benefit from from um systems that we are not so familiar with. So for us it's it's maybe not so much the cashing layers themselves is really understanding how our infrastructure needs to evolve on premises to support this kind of workloads. We had some smallish uh more high performance computing clusters with things like infinite and for low latency. But this is not the bulk of our workloads. This is not what we are experts on these days. This is the transition we are doing towards uh supporting this machine learning workers >>um just as a reference for the folks watching you mentioned embarrassing parallel and that's a quote that you I read on your certain tech blog. So if you go to tech blog dot web dot search dot ch or just search cern tech blog, you'll see the post there um and good stuff there and in there you go, you lay out a bunch of other things too where you start to see the deployment services and customer resource definitions being part of this, is it going to get to the point where automation is a bigger part of the cluster management setting stuff up quicker. Um As you look at some of the innovations you're doing with machines and Coubertin databases and thousands of other point things that you're working on there, I mean I know you've got a lot going on there, it's in the post but um you know, we don't want to have the problem of it's so hard to stand up and manage and this is what people want to make simpler. How do you how do you answer that when people say say we want to make it easier? >>Yeah. So uh for us it's it's really automate everything and up to now it has been automate the deployment in the kubernetes clusters right now we are looking at automating the kubernetes clusters themselves. So there's some really interesting projects, uh So people are used to using things like terra form to manage the deployment of clusters, but there are some projects like cross playing, for example, that allows us to have the clusters themselves being resources within kubernetes. Uh and this is something we are exploring quite a bit. Uh This allows us to also abstract the kubernetes clusters themselves uh as uh as carbonated resources. So this this idea of having a central cluster that will manage a much larger infrastructure. So this is something that we're exploring the getups part is really key for us to, it's something that eases the transition from from from people that are used already to manage large scale systems but are not necessarily experts on core NATO's. Uh they see that there's an easier past there if they if they can be introduced slowly through through the centralized configuration. >>You know, you mentioned cross plane, I had some on earlier, he's awesome dude, great guy and I was smiling because you know I still have you know flashbacks and trigger episodes from the Hadoop world, you know when it was such so promising that technology but it was just so hard to stand up and managed to be like really an expert to do that. And I think you mentioned cross plane, this comes up to the whole operator notion of operating the clusters, right? So you know, this comes back down to provisioning and managing the infrastructure, which is, you know, we all know is key, right? But when you start getting into multi cloud and multiple environments, that's where it becomes challenging. And I think I like what they're doing is that something that's on your mind to around hybrid and multi cloud? Can you share your thoughts on that whole trajectory? >>Absolutely. So I actually gave an internal seminar just last week describing what we've been playing with in this area and I showed some demo of using cross plane to manage clusters on premises but also manage clusters running on public clouds. A. W. S. Uh google cloud in nature and it's really like the goal there. There are many reasons we we want to explore external resources. We are kind of used to this because we have a lot of sites around the world that collaborate with us, but specifically for public clouds. Uh there are some some motivations there. The first one is this idea that we have periodic load spikes. So we knew we have international conferences, the number of analysis and job requests goes up quite a bit, so we need to be able to like scale on demand for short periods instead of over provisioning this uh in house. The second one is again coming back to machine learning this idea of accelerators. We have a lot of Cpus, we have a lot less gPS uh so it would be nice to go on fish uh for those in the public clouds. And then there's also other accelerators that are quite interesting, like CPUs and I p u s that will definitely play a role and we probably, or maybe we will never have among premises, will only be able to to use them externally. So in that, in that respect, actually coming back to your previous question, this idea of storage then becomes quite important. So what we've been playing with is not only managing this external cluster centrally, but also managing the wall infrastructure from a central place. So this means uh, making all the clusters, whatever they are look very, very much the same, including like the monitoring and the aggregation of the monitoring centrally. And then as we talked about storage, this idea of having local storage that that will be allow us to do really quick software distribution but also access to the data, >>what you guys are doing as we say, cool. And relevant projects. I mean you got the large scale deployments and the machine learning to really kind of accelerate which will drive a lot of adoption in terms of automation. And as that kicks in when you got to get the foundational work done, I see that clearly the right trajectory, you know, reminds me ricardo, um you know, again not do a little history lesson here, but you know, back when network protocols were moving from proprietary S N A for IBM deck net for digital back in the history the old days the os I Open Systems Interconnect Standard stack was evolving and you know when TCP I P came around that really opened up this interoperability, right? And SAM and I were talking about this kind of cross cloud connections or inter clouding as lou lou tucker. And I talked that open stack in 2013 about inter networking or interconnections and it's about integration and interoperability. This is like the next gen conversation that kubernetes is having. So as you get to scale up which is happening very fast as you get machine learning which can handle data and enable modern applications really it's connecting networks and connecting systems together. This is a huge architectural innovation direction. Could you share your reaction to that? >>Yeah. So actually we are starting the easy way, I would say we are starting with the workloads that are loosely coupled that we don't necessarily have to have this uh tighten inter connectivity between the different deployments, I would say that this is this is already giving us a lot because our like the bulk of our workloads are this kind of batch, embarrassing parallel, uh and we are also doing like co location when we have large workloads that made this kind of uh close inter connectivity then we kind of co locate them in the same deployment, same clouds in region. Um I think like what you describe of having cross clouds interconnectivity, this will be like a huge topic. It is already, I would say so we started investigating a lot of service measure options to try to learn what we can gain from it. There is clearly a benefit for managing services but there will be definitely also potential to allow us to kind of more easily scale out across regions. There's we've seen this by using the public cloud. Some things that we found is for example, this idea of infinite, infinite capacity which is kind of sometimes uh it feels kind of like that even at the scale we have for Cpus But when you start using accelerators, Yeah, you start negotiating like maybe use multiple regions because there's not enough capacity in a single region and you start having to talk to the cloud providers to negotiate this. And this makes the deployments more complicated of course. So this, this interconnectivity between regions and clouds will be a big thing. >>And, and again, low hanging fruit is just a kind of existing market but has thrown the vision out there mainly to kind of talk about what what we're seeing which is the world's are distributed computer. And if you have the standards, good things happen. Open systems, open innovating in the open really could make a big difference is going to be the difference between real value for the society of global society or are we going to get into the silo world? So I think the choice is the industry and I think, you know, Cern and C and C. F and Lennox Foundation and all the companies that are investing in open really is a key inflection point for us right now. So congratulations. Thanks for coming on the cube. Yeah, appreciate it. Thank you. Okay, Ricardo, rocha computing engineer cern here in the cube coverage of the CN Cf cube con cloud, native con europe. I'm john for your host of the cube. Thanks for watching.

(upbeat music) >> Narrator: From around the globe it's theCUBE with digital coverage of IBM Think 2021, brought to you by IBM. >> Hi everyone, welcome back to theCUBE's coverage of IBM Think 2021 virtual. I'm John Furrier your host of theCUBE. We're here, virtual again, in real life soon. It's right around the corner, but we've got a great guests here. Cameron Art Managing Director at AT&T for IBM. Cameron manages the AT&T Global Account for IBM. Cameron, great to see you. Thanks for coming on the CUBE. >> Thank you very much, John. It's great to be here. >> I can almost imagine how complicated and big and large AT&T is with respect to IBM and the history and AT&T is a very large company. What's the relationship with IBM and AT&T over the years? How has that evolved and how do you approach that role as the Managing Director? >> Well, it's been fascinating. As you said, we've got two large complex companies, but also two brand names that are synonymous for innovation, whether it be in compute or technology or communications. But the most fascinating thing is, if you look back at our relationship, and this is two brands that have been around for well over a hundred years, our relationship actually has some fascinating backdrop to it. My favorite is in 1924, AT&T sent a picture of Thomas Watson Sr, over a telephone wire to IBM. And Thomas Watson said, "they sent this over the telephone?" We are United in a community of interest. They want to make it easier for businesses to transact as do I, we need to work together. And since then, there has been a number of advances, that both of us have driven collectively and individually. And it's been a long running and treasured relationship in the IBM company. >> It's such a storied relationship on both sides. I mean, the history is just amazing. They could do a whole history channel segment on both AT&T and IBM. But together it's kind of the better together story. As you pointed out from that example, going back to sending a picture with a phone line, it's like, "Oh, my God, that's Instagram on the internet happening!" But how are they responding to the relationship, now? Obviously with Cloud native exploding with the ability to get more access, and you're seeing a lot more things evolve, more complexities emerging that needs to be abstracted away. You're seeing businesses saying, "Hey, I can do more with less, I can connect more. There's more access." But then also services more potential opportunities and challenges. How are you responding with AT&T? How are they responding to that dynamic with you guys? >> Yeah, I think it's fascinating because, when I originally approached this relationship and I've been doing this for 12 months now, little over 12 months, and when I originally approached it as with anything else, many times you're trying to enter something that is quite special and make it even better. And my approach at least initially with AT&T was very much one of. We're going to provide even better service. We're going to jointly grow together in the market and strengthen each of our businesses. And we're going to work for something broader than ourselves. And I'll get into, a little more, the last point later. But those first two things, from an AT&T response perspective. And I think this is a common perspective among many clients is, "we'll see if your actions follow your words". And so it's been a process we've gone through to understand that I'm a champion for AT&T, inside of IBM. And those interests, that we share individually and collectively, will be represented at the highest levels. And we will mature this relationship into one of, not just kind of supply chain partners, because we're very complimentary to each other, but more ecosystem partners. And my belief in my core, and you see this much with many of the business strategies that are out there, the ecosystem strategy, this sum is greater than the parts. It's not a zero sum game. Is something that's absolutely blooming in the market. >> Yeah, that ecosystem message is one of the things that's resonating and coming clearly out of the IBM Think 2021 this year and in the industry your seeing the success of network effects, ecosystem changes. That is the constant that's happening. Certainly with the pandemic and now coming out of it, people want to have a growth strategy. That's going to be relevant current and impactful. And you, you pointed that out, growth with each other, it's interesting. And you shared some perspective on this just recently with an example of what is underway there. Where are you heading with that? I mean, talk more about this growth with each other, 'cause that really is an ecosystem dynamic. What is underway and where are you heading? >> It's a fascinating ecosystem dynamic and it's something that we've adopted wholeheartedly within AT&T in terms of not only how we work. So, there are very basic examples, examples like, we rather than answering RFPs and responding to requirements, we're co-creating with our clients. We have multiple Cloud Garages going with AT&T where we identify outcomes that we believe could be possible. And then we show and allow the client to experience the outcome of that rather, than a PowerPoint slide. So, there's this kind of base of how do you work with each other, but then much more broadly in the market. It didn't take long for us to realize that, you know, the addressable market, if I were selling AT&T, everything I could ever sell them. And AT&T was selling IBM everything they could ever sell us. The addressable market is, let's say, $10 billion. But the moment at which we pointed ourselves outside to the external market, we realized that that market opportunity expands by a factor of 20 or by a factor of 50. We have the opportunity to create unique value together. And I think that kind of comes from the core of how we work together. >> I'm also intrigued by your comments about working together for a greater purpose. You said you'd address that later. What do you mean by that? I mean, that's little. Is there higher purpose, North star and obviously you mentioned working together in the ecosystem. That kind of seems tactical and strategic as well, but what's this greater purpose? What does that mean? >> Well, my belief, and it's something I learned actually, is I got indoctrinated into the work that AT&T does, the work that IBM does, and how we do it, but we share many common purposes in terms of what we believe on the whole, in terms of progress in society. So for example, equality in the workplace. We hosted a women's day luncheon, actually multiple Women's days luncheons across the United States. Where we had hundreds of female leaders from both IBM and AT&T collaborating together, talking about how tips and tricks, for how they continue to advance in the workplace. Another example is inequality in diversity and inclusion. Both AT&T and IBM have a strong commitment. And if you'll see, IBM just published their diversity data inclusion study where we actually demonstrate, here are the numbers, here's our targets, here's where we want to get. AT&T has exactly that same belief. Finally, in STEM education for educating our future leaders. In science and technology, engineering and math. Both, AT&T and IBM, for our future need those skills showing up in the marketplace. And Corey Anthony, just a quick spot, for any of you at Think, Corey Anthony, who's the Diversity and Development Officer at AT&T is going to give a great presentation on AT&Ts work in STEM for younger generations. So, there are many things that are, I would say, societal on a broader purpose statement, that we share a belief in together. >> That's awesome. And also people want to work on a team that's mission driven, has impact beyond just the profit and loss. I mean, I love capitalism, personally myself. I'm an entrepreneur, but been there done that but we're living in a cultural shift now. We're starting to see remote work. We're starting to see virtual teams, new use cases that have different expectations and experiences in the work place and also at home. So, you know, with mobile, I could be on the side of the soccer fields or, you know, skiing or running or jogging and take a message, pull over, do a chat, jump into an audio chat, listen to a podcast, engage. So we're all tethered now. This is exchanging experiences, and this is going to change the game for how you work together. >> A hundred percent. And by the way, we're all tethered hopefully through AT&T mobile connectivity devices. It was kind of amusing how much that has become a part of our lives and the core value. One of the core value propositions of AT&T is obviously connecting businesses to each other but also consumers through their mobile brand. But also then to entertainment I will say when I was in Augusta at the masters, you know people that have been there know that, you're not allowed to have cell phones. It was amazing just in conversations how often whoever it was I was having a conversation with and myself would say, well, I'd like to look that up, hold on, can I get that statistic? And we realized we're missing a big part of our lives in terms of the communication but those requirements of connecting people in new ways and in their homes or remotely actually only reinforce this shared value proposition of when you have the technology and you have it securely between our company IBM and AT&T we play a massive part in that. And it's something I'm quite proud of. >> Yeah, and you guys have a really interesting position there with the history of, with the relationship. And as you pointed out AT&T has to be on the forefront of cutting edge user experience technology they're bringing, I mean, they are the edge. I mean, they ultimately from base station down to the device, to the person, to the account, you're talking about a real edge. There that's a person's consumer. They got to provide these new services. So I got to ask you, you mentioned at the top of this interview, that your goal is to provide even better service to AT&T pretty big pressure point for IBM. You know, you got to deliver step up and their expectations must be high. Can you take us through perspectives on that kind of even better service when you've got a client that's on the cutting edge of having to deliver new kinds of things like better notifications, smarter devices smarter software, more fault-tolerant highly available services. These are things that, you know there's a lot of pressure take us through that. What's, what's it like? >> There is a lot of pressure but there's a lot of consistency in terms of expectations. And it's something that both of us understand very well. And I would argue that it's probably the reason we work so well together. Both AT&T and IBM for years, namely 50, 100's of years have understood that if we're transacting for business, we're transacting on something that has to get done. So on both sides of the equation not only do we push the edge of what can be done technically or for business, but we also understand the expectations of the business clients that are, it works every time and it works in every way I need it to. So for us, when we work together, I think that healthy balance of part musician, part engineer comes out very, very strongly in both teams. >> Cameron, great insight and great to talk to you. I love to get the perspective on, you know, the kind of challenges and opportunities that you're seizing at IBM with AT&T. Again, the history is amazing. The impact to the industry at both levels. You mentioned Tom Watson Senior, then you got Junior that in that generation just carries forward. You got that vibe back now with hybrid cloud Irvin loves cloud. So, you know, you got a lot of things happening that's really strong over at IBM and the theme this year generally is better together. So, awesome, awesome work. Congratulations. >> Thank you very much. I will tell you, I don't want to miss the opportunity to talk a bit about the future, because from an AT&T and IBM perspective we're doing a load of work around private 5G or 5G in general. This is something that provides an absolutely low latency huge bandwidth with a lot of actually characteristics from a business perspective that are manageable. And it will enable what I believe is a another big wave in the technology and business industry which is new business models. Very similar to that, of the internet originally, it allows with IBM technology and AT&T technology they have something called Multi-Access Edge Computing. These are absolutely blazing, fast 5G boxes that will be in, not only businesses, but universities, sports stadiums, you name it, changing the experience of how people consume technology or the benefits of technology, which I couldn't be more excited about. >> Awesome future ahead, great. Its a big wave certainly a wave we'd never seen before. Cameron, our managing director AT&T at IBM. Great insight, thanks for sharing, thanks for coming on. >> Thanks, John. >> Okay, CUBE coverage of IBM Think 2021. I'm John Furrier, thanks for watching. (upbeat music)

>>from around the globe. It's the Cube presenting innovation for good, brought to you by on shape. >>Hello, everyone, and welcome to Innovation for Good Program, hosted by the Cuban. Brought to You by on Shape, which is a PTC company. My name is Dave Valentin. I'm coming to you from our studios outside of Boston. I'll be directing the conversations today. It's a very exciting, all live program. We're gonna look at how product innovation has evolved and where it's going and how engineers, entrepreneurs and educators are applying cutting edge, cutting edge product development techniques and technology to change our world. You know, the pandemic is, of course, profoundly impacted society and altered how individuals and organizations they're gonna be thinking about an approaching the coming decade. Leading technologists, engineers, product developers and educators have responded to the new challenges that we're facing from creating lifesaving products to helping students learn from home toe how to apply the latest product development techniques and solve the world's hardest problems. And in this program, you'll hear from some of the world's leading experts and practitioners on how product development and continuous innovation has evolved, how it's being applied toe positive positively affect society and importantly where it's going in the coming decades. So let's get started with our first session fueling Tech for good. And with me is John Hirschbeck, who is the president of the Suffers, a service division of PTC, which acquired on shape just over a year ago, where John was the CEO and co founder, and Dana Grayson is here. She is the co founder and general partner at Construct Capital, a new venture capital firm. Folks, welcome to the program. Thanks so much for coming on. >>Great to be here, Dave. >>All right, John. >>You're very welcome. Dana. Look, John, let's get into it for first Belated congratulations on the acquisition of Von Shape. That was an awesome seven year journey for your company. Tell our audience a little bit about the story of on shape, but take us back to Day zero. Why did you and your co founders start on shape? Well, >>actually, start before on shaping the You know, David, I've been in this business for almost 40 years. The business of building software tools for product developers and I had been part of some previous products in the industry and companies that had been in their era. Big changes in this market and about, you know, a little Before founding on shape, we started to see the problems product development teams were having with the traditional tools of that era years ago, and we saw the opportunity presented by Cloud Web and Mobile Technology. And we said, Hey, we could use Cloud Web and Mobile to solve the problems of product developers make their Their business is run better. But we have to build an entirely new system, an entirely new company, to do it. And that's what on shapes about. >>Well, so notwithstanding the challenges of co vid and difficulties this year, how is the first year been as, Ah, division of PTC for you guys? How's business? Anything you can share with us? >>Yeah, our first year of PTC has been awesome. It's been, you know, when you get acquired, Dave, you never You know, you have great optimism, but you never know what life will really be like. It's sort of like getting married or something, you know, until you're really doing it, you don't know. And so I'm happy to say that one year into our acquisition, um, PTC on shape is thriving. It's worked out better than I could have imagined a year ago. Along always, I mean sales are up. In Q four, our new sales rate grew 80% vs Excuse me, our fiscal Q four Q three. In the calendar year, it grew 80% compared to the year before. Our educational uses skyrocketing with around 400% growth, most recently year to year of students and teachers and co vid. And we've launched a major cloud platform using the core of on shape technology called Atlas. So, um, just tons of exciting things going on a TTC. >>That's awesome. But thank you for sharing some of those metrics. And of course, you're very humble individual. You know, people should know a little bit more about you mentioned, you know, we founded Solid Works, co founded Solid where I actually found it solid works. You had a great exit in the in the late nineties. But what I really appreciate is, you know, you're an entrepreneur. You've got a passion for the babies that you you helped birth. You stayed with the salt systems for a number of years. The company that quiet, solid works well over a decade. And and, of course, you and I have talked about how you participated in the the M I T. Blackjack team. You know, back in the day, a zai say you're very understated, for somebody was so accomplished. Well, >>that's kind of you, but I tend to I tend Thio always keep my eye more on what's ahead. You know what's next, then? And you know, I look back Sure to enjoy it and learn from it about what I can put to work making new memories, making new successes. >>Love it. Okay, let's bring Dana into the conversation. Hello, Dana. You look you're a fairly early investor in in on shape when you were with any A And and I think it was like it was a serious B, but it was very right close after the A raise. And and you were and still are a big believer in industrial transformation. So take us back. What did you see about on shape back then? That excited you. >>Thanks. Thanks for that. Yeah. I was lucky to be a early investment in shape. You know, the things that actually attracted me. Don shape were largely around John and, uh, the team. They're really setting out to do something, as John says humbly, something totally new, but really building off of their background was a large part of it. Um, but, you know, I was really intrigued by the design collaboration side of the product. Um, I would say that's frankly what originally attracted me to it. What kept me in the room, you know, in terms of the industrial world was seeing just if you start with collaboration around design what that does to the overall industrial product lifecycle accelerating manufacturing just, you know, modernizing all the manufacturing, just starting with design. So I'm really thankful to the on shape guys, because it was one of the first investments I've made that turned me on to the whole sector. And while just such a great pleasure to work with with John and the whole team there. Now see what they're doing inside PTC. >>And you just launched construct capital this year, right in the middle of a pandemic and which is awesome. I love it. And you're focused on early stage investing. Maybe tell us a little bit about construct capital. What your investment thesis is and you know, one of the big waves that you're hoping to ride. >>Sure, it construct it is literally lifting out of any what I was doing there. Um uh, for on shape, I went on to invest in companies such as desktop metal and Tulip, to name a couple of them form labs, another one in and around the manufacturing space. But our thesis that construct is broader than just, you know, manufacturing and industrial. It really incorporates all of what we'd call foundational industries that have let yet to be fully tech enabled or digitized. Manufacturing is a big piece of it. Supply chain, logistics, transportation of mobility or not, or other big pieces of it. And together they really drive, you know, half of the GDP in the US and have been very under invested. And frankly, they haven't attracted really great founders like they're on in droves. And I think that's going to change. We're seeing, um, entrepreneurs coming out of the tech world orthe Agnelli into these industries and then bringing them back into the tech world, which is which is something that needs to happen. So John and team were certainly early pioneers, and I think, you know, frankly, obviously, that voting with my feet that the next set, a really strong companies are going to come out of the space over the next decade. >>I think it's a huge opportunity to digitize the sort of traditionally non digital organizations. But Dana, you focused. I think it's it's accurate to say you're focused on even Mawr early stage investing now. And I want to understand why you feel it's important to be early. I mean, it's obviously riskier and reward e er, but what do you look for in companies and and founders like John >>Mhm, Um, you know, I think they're different styles of investing all the way up to public market investing. I've always been early stage investors, so I like to work with founders and teams when they're, you know, just starting out. Um, I happened to also think that we were just really early in the whole digital transformation of this world. You know, John and team have been, you know, back from solid works, etcetera around the space for a long time. But again, the downstream impact of what they're doing really changes the whole industry. And and so we're pretty early and in digitally transforming that market. Um, so that's another reason why I wanna invest early now, because I do really firmly believe that the next set of strong companies and strong returns for my own investors will be in the spaces. Um, you know, what I look for in Founders are people that really see the world in a different way. And, you know, sometimes some people think of founders or entrepreneurs is being very risk seeking. You know, if you asked John probably and another successful entrepreneurs, they would call themselves sort of risk averse, because by the time they start the company, they really have isolated all the risk out of it and think that they have given their expertise or what they're seeing their just so compelled to go change something, eh? So I look for that type of attitude experience a Z. You can also tell from John. He's fairly humble. So humility and just focus is also really important. Um, that there's a That's a lot of it. Frankly, >>Excellent. Thank you, John. You got such a rich history in the space. Uh, and one of you could sort of connect the dots over time. I mean, when you look back, what were the major forces that you saw in the market in in the early days? Particularly days of on shape on? And how is that evolved? And what are you seeing today? Well, >>I think I touched on it earlier. Actually, could I just reflect on what Dana said about risk taking for just a quick one and say, throughout my life, from blackjack to starting solid works on shape, it's about taking calculated risks. Yes, you try to eliminate the risk Sa's much as you can, but I always say, I don't mind taking a risk that I'm aware of, and I've calculated through as best I can. I don't like taking risks that I don't know I'm taking. That's right. You >>like to bet on >>sure things as much as you sure things, or at least where you feel you. You've done the research and you see them and you know they're there and you know, you, you you keep that in mind in the room, and I think that's great. And Dana did so much for us. Dana, I want to thank you again. For all that, you did it every step of the way, from where we started to to, you know, your journey with us ended formally but continues informally. Now back to you, Dave, I think, question about the opportunity and how it's shaped up. Well, I think I touched on it earlier when I said It's about helping product developers. You know, our customers of the people build the future off manufactured goods. Anything you think of that would be manufacturing factory. You know, the chair you're sitting in machine that made your coffee. You know, the computer you're using, the trucks that drive by on the street, all the covert product research, the equipment being used to make vaccines. All that stuff is designed by someone, and our job is given the tools to do it better. And I could see the problems that those product developers had that we're slowing them down with using the computing systems of the time. When we built solid works, that was almost 30 years ago. If people don't realize that it was in the early >>nineties and you know, we did the >>best we could for the early nineties, but what we did. We didn't anticipate the world of today. And so people were having problems with just installing the systems. Dave, you wouldn't believe how hard it is to install these systems. You need toe speck up a special windows computer, you know, and make sure you've got all the memory and graphics you need and getting to get that set up. You need to make sure the device drivers air, right, install a big piece of software. Ah, license key. I'm not making this up. They're still around. You may not even know what those are. You know, Dennis laughing because, you know, zero cool people do things like this anymore. Um, and it only runs some windows. You want a second user to use it? They need a copy. They need a code. Are they on the same version? It's a nightmare. The teams change, you know? You just say, Well, get everyone on the software. Well, who's everyone? You know, you got a new vendor today? A new customer tomorrow, a new employee. People come on and off the team. The other problem is the data stored in files, thousands of files. This isn't like a spreadsheet or word processor, where there's one file to pass around these air thousands of files to make one, even a simple product. People were tearing their hair out. John, what do we do? I've got copies everywhere. I don't know where the latest version is. We tried like, you know, locking people out so that only one person can change it At the time that works against speed, it works against innovation. We saw what was happening with Cloud Web and mobile. So what's happened in the years since is every one of the forces that product developers experience the need for speed, the need for innovation, the need to be more efficient with their people in their capital. Resource is every one of those trends have been amplified since we started on shape by a lot of forces in the world. And covert is amplified all those the need for agility and remote work cove it is amplified all that the same time, The acceptance of cloud. You know, a few years ago, people were like cloud, you know, how is that gonna work now They're saying to me, You know, increasingly, how would you ever even have done this without the cloud. How do you make solid works work without the cloud? How would that even happen? You know, once people understand what on shapes about >>and we're the >>Onley full SAS solution software >>as a service, >>full SAS solution in our industry. So what's happened in those years? Same problems we saw earlier, but turn up the gain, their bigger problems. And with cloud, we've seen skepticism of years ago turn into acceptance. And now even embracement in the cova driven new normal. >>Yeah. So a lot of friction in the previous environments cloud obviously a huge factor on, I guess. I guess Dana John could see it coming, you know, in the early days of solid works with, you know, had Salesforce, which is kind of the first major independent SAS player. Well, I guess that was late nineties. So his post solid works, but pre in shape and their work day was, you know, pre on shape in the mid two thousands. And and but But, you know, the bet was on the SAS model was right for Crick had and and product development, you know, which maybe the time wasn't a no brainer. Or maybe it was, I don't know, but Dana is there. Is there anything that you would invest in today? That's not Cloud based? >>Um, that's a great question. I mean, I think we still see things all the time in the manufacturing world that are not cloud based. I think you know, the closer you get to the shop floor in the production environment. Um e think John and the PTC folks would agree with this, too, but that it's, you know, there's reliability requirements, performance requirements. There's still this attitude of, you know, don't touch the printing press. So the cloud is still a little bit scary sometimes. And I think hybrid cloud is a real thing for those or on premise. Solutions, in some cases is still a real thing. What what we're more focused on. And, um, despite whether it's on premise or hybrid or or SAS and Cloud is a frictionless go to market model, um, in the companies we invest in so sass and cloud, or really make that easy to adopt for new users, you know, you sign up, started using a product, um, but whether it's hosted in the cloud, whether it's as you can still distribute buying power. And, um, I would I'm just encouraging customers in the customer world and the more industrial environment to entrust some of their lower level engineers with more budget discretionary spending so they can try more products and unlock innovation. >>Right? The unit economics are so compelling. So let's bring it, you know, toe today's you know, situation. John, you decided to exit about a year ago. You know? What did you see in PTC? Other than the obvious money? What was the strategic fit? >>Yeah, Well, David, I wanna be clear. I didn't exit anything. Really? You >>know, I love you and I don't like that term exit. I >>mean, Dana had exit is a shareholder on and so it's not It's not exit for me. It's just a step in the journey. What we saw in PTC was a partner. First of all, that shared our vision from the top down at PTC. Jim Hempleman, the CEO. He had a great vision for for the impact that SAS can make based on cloud technology and really is Dana of highlighted so much. It's not just the technology is how you go to market and the whole business being run and how you support and make the customers successful. So Jim shared a vision for the potential. And really, really, um said Hey, come join us and we can do this bigger, Better, faster. We expanded the vision really to include this Atlas platform for hosting other SAS applications. That P D. C. I mean, David Day arrived at PTC. I met the head of the academic program. He came over to me and I said, You know, and and how many people on your team? I thought he'd say 5 40 people on the PTC academic team. It was amazing to me because, you know, we were we were just near about 100 people were required are total company. We didn't even have a dedicated academic team and we had ah, lot of students signing up, you know, thousands and thousands. Well, now we have hundreds of thousands of students were approaching a million users and that shows you the power of this team that PTC had combined with our product and technology whom you get a big success for us and for the teachers and students to the world. We're giving them great tools. So so many good things were also putting some PTC technology from other parts of PTC back into on shape. One area, a little spoiler, little sneak peek. Working on taking generative design. Dana knows all about generative design. We couldn't acquire that technology were start up, you know, just to too much to do. But PTC owns one of the best in the business. This frustrated technology we're working on putting that into on shaping our customers. Um, will be happy to see it, hopefully in the coming year sometime. >>It's great to see that two way exchange. Now, you both know very well when you start a company, of course, a very exciting time. You know, a lot of baggage, you know, our customers pulling you in a lot of different directions and asking you for specials. You have this kind of clean slate, so to speak in it. I would think in many ways, John, despite you know, your install base, you have a bit of that dynamic occurring today especially, you know, driven by the forced march to digital transformation that cove it caused. So when you sit down with the team PTC and talk strategy. You now have more global resource is you got cohorts selling opportunities. What's the conversation like in terms of where you want to take the division? >>Well, Dave, you actually you sounds like we should have you coming in and talking about strategy because you've got the strategy down. I mean, we're doing everything said global expansion were able to reach across selling. We got some excellent PTC customers that we can reach reach now and they're finding uses for on shape. I think the plan is to, you know, just go, go, go and grow, grow, grow where we're looking for this year, priorities are expand the product. I mentioned the breath of the product with new things PTC did recently. Another technology that they acquired for on shape. We did an acquisition. It was it was small, wasn't widely announced. It, um, in an area related to interfacing with electrical cad systems. So So we're doing We're expanding the breath of on shape. We're going Maura, depth in the areas were already in. We have enormous opportunity to add more features and functions that's in the product. Go to market. You mentioned it global global presence. That's something we were a little light on a year ago. Now we have a team. Dana may not even know what we have. A non shape, dedicated team in Barcelona, based in Barcelona but throughout Europe were doing multiple languages. Um, the academic program just introduced a new product into that space that z even fueling more success and growth there. Um, and of course, continuing to to invest in customer success and this Atlas platform story I keep mentioning, we're going to soon have We're gonna soon have four other major PTC brands shipping products on our Atlas Saas platform. And so we're really excited about that. That's good for the other PTC products. It's also good for on shape because now there's there's. There's other interesting products that are on shape customers can use take advantage of very easily using, say, a common log in conventions about user experience there, used to invest of all they're SAS based, so they that makes it easier to begin with. So that's some of the exciting things going on. I think you'll see PTC, um, expanding our lead in SAS based applications for this sector for our our target, uh, sectors not just in, um, in cat and data management, but another area. PTC's Big and his augmented reality with of euphoria, product line leader and industrial uses of a R. That's a whole other story we should do. A whole nother show augmented reality. But these products are amazing. You can you can help factory workers people on, uh, people who are left out of the digital transformation. Sometimes we're standing from machine >>all day. >>They can't be sitting like we are doing Zoom. They can wear a R headset in our tools, let them create great content. This is an area Dana is invested in other companies. But what I wanted to note is the new releases of our authoring software. For this, our content getting released this month, used through the Atlas platform, the SAS components of on shape for things like revision management and collaboration on duh workflow activity. All that those are tools that we're able to share leverage. We get a lot of synergy. It's just really good. It's really fun to have a good time. That's >>awesome. And then we're gonna be talking to John MacLean later about that. Let's do a little deeper Dive on that. And, Dana, what is your involvement today with with on shape? But you're looking for you know, which of their customers air actually adopting. And they're gonna disrupt their industries. And you get good pipeline from that. How do you collaborate today? >>That sounds like a great idea. Um, Aziz, John will tell you I'm constantly just asking him for advice and impressions of other entrepreneurs and picking his brain on ideas. No formal relationship clearly, but continue to count John and and John and other people in on shaping in the circle of experts that I rely on for their opinions. >>All right, so we have some questions from the crowd here. Uh, one of the questions is for the dream team. You know, John and Dana. What's your next next collective venture? I don't think we're there yet, are we? No. >>I just say, as Dana said, we love talking to her about. You know, Dana, you just returned the compliment. We would try and give you advice and the deals you're looking at, and I'm sort of casually mentoring at least one of your portfolio entrepreneurs, and that's been a lot of fun for May on, hopefully a value to them. But also Dana. We uran important pipeline to us in the world of some new things that are happening that we wouldn't see if you know you've shown us some things that you've said. What do you think of this business? And for us, it's like, Wow, it's cool to see that's going on And that's what's supposed to work in an ecosystem like this. So we we deeply value the ongoing relationship. And no, we're not starting something new. I got a lot of work left to do with what I'm doing and really happy. But we can We can collaborate in this way on other ventures. >>I like this question to somebody asking With the cloud options like on shape, Wilmore students have stem opportunities s Oh, that's a great question. Are you because of sass and cloud? Are you able to reach? You know, more students? Much more cost effectively. >>Yeah, Dave, I'm so glad that that that I was asked about this because Yes, and it's extremely gratified us. Yes, we are because of cloud, because on shape is the only full cloud full SAS system or industry were able to reach. Stem education brings able to be part of bringing step education to students who couldn't get it otherwise. And one of most gratifying gratifying things to me is the emails were getting from teachers, um, that that really, um, on the phone calls that were they really pour their heart out and say We're able to get to students in areas that have very limited compute resource is that don't have an I T staff where they don't know what computer that the students can have at home, and they probably don't even have a computer. We're talking about being able to teach them on a phone to have an android phone a low end android phone. You can do three D modeling on there with on shape. Now you can't do it any other system, but with on shape, you could do it. And so the teacher can say to the students, They have to have Internet access, and I know there's a huge community that doesn't even have Internet access, and we're not able, unfortunately to help that. But if you have Internet and you have even an android phone, we can enable the educator to teach them. And so we have case after case of saving a stem program or expanding it into the students that need it most is the ones we're helping here. So really excited about that. And we're also able to let in addition to the run on run on whatever computing devices they have, we also offer them the tools they need for remote teaching with a much richer experience. Could you teach solid works remotely? Well, maybe if the student ran it had a windows workstation. You know, big, big, high end workstation. Maybe it could, but it would be like the difference between collaborating with on shape and collaborate with solid works. Like the difference between a zoom video call and talking on the landline phone. You know, it's a much richer experience, and that's what you need. And stem teaching stem is hard, So yeah, we're super super. Um, I'm excited about bringing stem to more students because of cloud yond >>we're talking about innovation for good, and then the discussion, John, you just had it. Really? There could be a whole another vector here. We could discuss on diversity, and I wanna end with just pointing out. So, Dana, your new firm, it's a woman led firm, too. Two women leaders, you know, going forward. So that's awesome to see, so really? Yeah, thumbs up on that. Congratulations on getting that off the ground. >>Thank you. Thank you. >>Okay, so thank you guys. Really appreciate It was a great discussion. I learned a lot and I'm sure the audience did a swell in a moment. We're gonna talk with on shaped customers to see how they're applying tech for good and some of the products that they're building. So keep it right there. I'm Dave Volonte. You're watching innovation for good on the Cube, the global leader in digital tech event coverage. Stay right there. >>Oh, yeah, it's >>yeah, yeah, around >>the globe. It's the Cube presenting innovation for good. Brought to you by on shape. >>Okay, we're back. This is Dave Volonte and you're watching innovation for good. A program on Cuba 3 65 made possible by on shape of PTC company. We're live today really live tv, which is the heritage of the Cube. And now we're gonna go to the sources and talkto on shape customers to find out how they're applying technology to create real world innovations that are changing the world. So let me introduce our panel members. Rafael Gomez Furberg is with the Chan Zuckerberg bio hub. A very big idea. And collaborative nonprofit was initiative that was funded by Mark Zuckerberg and his wife, Priscilla Chan, and really around diagnosing and curing and better managing infectious diseases. So really timely topic. Philip Tabor is also joining us. He's with silver side detectors, which develops neutron detective detection systems. Yet you want to know if early, if neutrons and radiation or in places where you don't want them, So this should be really interesting. And last but not least, Matthew Shields is with the Charlottesville schools and is gonna educate us on how he and his team are educating students in the use of modern engineering tools and techniques. Gentlemen, welcome to the Cuban to the program. This should be really interesting. Thanks for coming on. >>Hi. Or pleasure >>for having us. >>You're very welcome. Okay, let me ask each of you because you're all doing such interesting and compelling work. Let's start with Rafael. Tell us more about the bio hub and your role there, please. >>Okay. Yeah. So you said that I hope is a nonprofit research institution, um, funded by Mark Zuckerberg and his wife, Priscilla Chan. Um, and our main mission is to develop new technologies to help advance medicine and help, hopefully cure and manage diseases. Um, we also have very close collaborations with Universe California, San Francisco, Stanford University and the University California Berkeley on. We tried to bring those universities together, so they collaborate more of biomedical topics. And I manage a team of engineers. They by joining platform. Um, and we're tasked with creating instruments for the laboratory to help the scientist boats inside the organization and also in the partner universities Do their experiments in better ways in ways that they couldn't do before >>in this edition was launched Well, five years ago, >>it was announced at the end of 2016, and we actually started operation with at the beginning of 2017, which is when I joined, um, So this is our third year. >>And how's how's it going? How does it work? I mean, these things take time. >>It's been a fantastic experience. Uh, the organization works beautifully. Um, it was amazing to see it grow From the beginning, I was employee number 12, I think eso When I came in, it was just a nem P office building and empty labs. And very quickly we had something running about. It's amazing eso I'm very proud of the work that we have done to make that possible. Um And then, of course, that's you mentioned now with co vid, um, we've been able to do a lot of very cool work attire being of the pandemic in March, when there was a deficit of testing, uh, capacity in California, we spun up a testing laboratory in record time in about a week. It was crazy. It was a crazy project, Um, but but incredibly satisfying. And we ended up running all the way until the beginning of November, when the lab was finally shut down. We could process about 3000 samples a day. I think at the end of it all, we were able to test about 100 on the order of 100 and 50,000 samples from all over the state. We were providing free testing toe all of the Department of Public Health Department of Public Health in California, which at the media pandemic, had no way to do testing affordably and fast. So I think that was a great service to the state. Now the state has created that testing system that would serve those departments. So then we decided that it was unnecessary to keep going with testing in the other biopsy that would shut down. >>All right. Thank you for that. Now, Now, Philip, you What you do is mind melting. You basically helped keep the world safe. Maybe describe a little bit more about silver sod detectors and what your role is there and how it all works. >>Tour. So we make a nuclear bomb detectors and we also make water detectors. So we try and do our part thio keep the world from blowing up and make it a better place at the same time. Both of these applications use neutron radiation detectors. That's what we make. Put them out by import border crossing places like that. They can help make sure that people aren't smuggling. Shall we say very bad things. Um, there's also a burgeoning field of research and application where you can use neutrons with some pretty cool physics to find water so you could do things. Like what? A detector up in the mountains and measure snowpack. Put it out in the middle of the field and measure soil moisture content. And as you might imagine, there's some really cool applications in, uh, research and agronomy and public policy for this. >>All right, so it's OK, so it's a It's much more than, you know, whatever fighting terrorism, it's there's a riel edge or I kind of i o t application for what you guys >>do. We do both its's to plowshares. You might >>say a mat. I I look at your role is kind of scaling the brain power for for the future. Maybe tell us more about Charlottesville schools and in the mission that you're pursuing and what you do. >>Thank you. Um, I've been in Charlottesville City schools for about 11 or 12 years. I started their teaching, um, a handful of classes, math and science and things like that. But Thescore board and my administration had the crazy idea of starting an engineering program about seven years ago. My background is an engineering is an engineering. My masters is in mechanical and aerospace engineering and um, I basically spent a summer kind of coming up with what might be a fun engineering curriculum for our students. And it started with just me and 30 students about seven years ago, Um, kind of a home spun from scratch curriculum. One of my goals from the outset was to be a completely project based curriculum, and it's now grown. We probably have about six or 700 students, five or six full time teachers. We now have pre engineering going on at the 5th and 6th grade level. I now have students graduating. Uh, you know, graduating after senior year with, like, seven years of engineering under their belt and heading off to doing some pretty cool stuff. So it's It's been a lot of fun building a program and, um, and learning a lot in the process. >>That's awesome. I mean, you know, Cuba's. We've been passionate about things like women in tech, uh, diversity stem. You know, not only do we need more, more students and stem, we need mawr underrepresented women, minorities, etcetera. We were just talking to John Herstek and integrate gration about this is Do you do you feel is though you're I mean, first of all, the work that you do is awesome, but but I'll go one step further. Do you feel as though it's reaching, um, or diverse base? And how is that going? >>That's a great question. I think research shows that a lot of people get funneled into one kind of track or career path or set of interests really early on in their educational career, and sometimes that that funnel is kind of artificial. And so that's one of the reasons we keep pushing back. Um, so our school systems introducing kindergartners to programming on DSO We're trying to push back how we expose students to engineering and to stem fields as early as possible. And we've definitely seen the first of that in my program. In fact, my engineering program, uh, sprung out of an after school in Extracurricular Science Club that actually three girls started at our school. So I think that actually has helped that three girls started the club that eventually is what led to our engineering programs that sort of baked into the DNA and also our eyes a big public school. And we have about 50% of the students are under the poverty line and we e in Charlottesville, which is a big refugee town. And so I've been adamant from Day one that there are no barriers to entry into the program. There's no test you have to take. You don't have to have be taking a certain level of math or anything like that. That's been a lot of fun. To have a really diverse set of kids enter the program and be successful, >>that's final. That's great to hear. So, Philip, I wanna come back to you. You know, I think about maybe some day we'll be able to go back to a sporting events, and I know when I when I'm in there, there's somebody up on the roof looking out for me, you know, watching the crowd, and they have my back. And I think in many ways, the products that you build, you know, our similar. I may not know they're there, but they're keeping us safe or they're measuring things that that that I don't necessarily see. But I wonder if you could talk about a little bit more detail about the products you build and how they're impacting society. >>Sure, so There are certainly a lot of people who are who are watching, trying to make sure things were going well in keeping you safe that you may or may not be aware of. And we try and support ah lot of them. So we have detectors that are that are deployed in a variety of variety of uses, with a number of agencies and governments that dio like I was saying, ports and border crossing some other interesting applications that are looking for looking for signals that should not be there and working closely to fit into the operations these folks do. Onda. We also have a lot of outreach to researchers and scientists trying to help them support the work they're doing. Um, using neutron detection for soil moisture monitoring is a some really cool opportunities for doing it at large scale and with much less, um, expense or complication than would have been done. Previous technologies. Um, you know, they were talking about collaboration in the previous segment. We've been able to join a number of conferences for that, virtually including one that was supposed to be held in Boston, but another one that was held out of the University of Heidelberg in Germany. And, uh, this is sort of things that in some ways, the pandemic is pushing people towards greater collaboration than they would have been able to do. Had it all but in person. >>Yeah, we did. Uh, the cube did live works a couple years ago in Boston. It was awesome show. And I think, you know, with this whole trend toward digit, I call it the Force march to digital. Thanks to cove it I think that's just gonna continue. Thio grow. Rafael. What if you could describe the process that you use to better understand diseases? And what's your organization's involvement? Been in more detail, addressing the cove in pandemic. >>Um, so so we have the bio be structured in, Um um in a way that foster so the combination of technology and science. So we have to scientific tracks, one about infectious diseases and the other one about understanding just basic human biology, how the human body functions, and especially how the cells in the human body function on how they're organized to create tissues in the body. On Ben, it has this set of platforms. Um, mind is one of them by engineering that are all technology rated. So we have data science platform, all about data analysis, machine learning, things like that. Um, we have a mass spectrometry platform is all about mass spectrometry technologies to, um, exploit those ones in service for the scientist on. We have a genomics platform that it's all about sequencing DNA and are gonna, um and then an advanced microscopy. It's all about developing technologies, uh, to look at things with advanced microscopes and developed technologies to marry computation on microscopy. So, um, the scientists set the agenda and the platforms, we just serve their needs, support their needs, and hopefully develop technologies that help them do their experiments better, faster, or allow them to the experiment that they couldn't do in any other way before. Um And so with cove, it because we have that very strong group of scientists that work on have been working on infectious disease before, and especially in viruses, we've been able to very quickly pivot to working on that s O. For example, my team was able to build pretty quickly a machine to automatically purified proteins on is being used to purify all these different important proteins in the cove. It virus the SARS cov to virus Onda. We're sending some of those purified proteins all over the world. Two scientists that are researching the virus and trying to figure out how to develop vaccines, understand how the virus affects the body and all that. Um, so some of the machines we built are having a very direct impact on this. Um, Also for the copy testing lab, we were able to very quickly develop some very simple machines that allowed the lab to function sort of faster and more efficiently. Sort of had a little bit of automation in places where we couldn't find commercial machines that would do it. >>Um, eso Matt. I mean, you gotta be listening to this and thinking about Okay, So someday your students are gonna be working at organizations like like, like Bio Hub and Silver Side. And you know, a lot of young people they're just don't know about you guys, but like my kids, they're really passionate about changing the world. You know, there's way more important than you know, the financial angles and it z e. I gotta believe you're seeing that you're right in the front lines there. >>Really? Um, in fact, when I started the curriculum six or seven years ago, one of the first bits of feedback I got from my students is they said Okay, this is a lot of fun. So I had my students designing projects and programming microcontrollers raspberry, PiS and order we nose and things like that. The first bit of feedback I got from students was they said Okay, when do we get to impact the world? I've heard engineering >>is about >>making the world a better place, and robots are fun and all, but, you know, where is the real impact? And so um, dude, yeah, thanks to the guidance of my students, I'm baking that Maurin. Now I'm like day one of engineering one. We talk about how the things that the tools they're learning and the skills they're gaining, uh, eventually, you know, very soon could be could be used to make the world a better place. >>You know, we all probably heard that famous line by Jeff Hammer Barker. The greatest minds of my generation are trying to figure out how to get people to click on ads. I think we're really generally generationally, finally, at the point where young students and engineering a really, you know, a passionate about affecting society. I wanna get into the product, you know, side and understand how each of you are using on shape and and the value that that it brings. Maybe Raphael, you could start how long you've been using it. You know, what's your experience with it? Let's let's start there. >>I begin for about two years, and I switched to it with some trepidation. You know, I was used to always using the traditional product that you have to install on your computer, that everybody uses that. So I was kind of locked into that. But I started being very frustrated with the way it worked, um, and decided to give on ship chance. Which reputation? Because any change always, you know, causes anxiety. Um, but very quickly my engineers started loving it, Uh, just because it's it's first of all, the learning curve wasn't very difficult at all. You can transfer from one from the traditional product to entree very quickly and easily. You can learn all the concepts very, very fast. It has all the functionality that we needed and and what's best is that it allows to do things that we couldn't do before or we couldn't do easily. Now we can access the our cat documents from anywhere in the world. Um, so when we're in the lab fabricating something or testing a machine, any computer we have next to us or a tablet or on iPhone, we can pull it up and look at the cad and check things or make changes. That's something that couldn't do before because before you had to pay for every installation off the software for the computer, and I couldn't afford to have 20 installations to have some computers with the cat ready to use them like once every six months would have been very inefficient. So we love that part. And the collaboration features are fantastic, especially now with Kobe, that we have to have all the remote meetings eyes fantastic, that you can have another person drive the cad while the whole team is watching that person change the model and do things and point to things that is absolutely revolutionary. We love it. The fact that you have very, very sophisticated version control before it was always a challenge asking people, please, if you create anniversary and apart, how do we name it so that people find it? And then you end up with all these collection of files with names that nobody ever remembers, what they are, the person left. And now nobody knows which version is the right one. A mess with on shape on the version ING system it has, and the fact that you can go back in history off the document and go back to previous version so easily and then go back to the press and version and explore the history of the part that is truly, um, just world changing for us, that we can do that so easily on for me as a manager to manage this collection of information that is critical for our operations. It makes it so much easier because everything is in one place. I don't have to worry about file servers that go down that I have to administer that have to have I t taken care off that have to figure how to keep access to people to those servers when they're at home, and they need a virtual private network and all of that mess disappears. I just simply give give a person in accounting on shape and then magically, they have access to everything in the way I want. And we can manage the lower documents and everything in a way that is absolutely fantastic. >>Feel what was your what? What were some of the concerns you had mentioned? You had some trepidation. Was it a performance? Was it security? You know some of the traditional cloud stuff, and I'm curious as to how, How, whether any of those act manifested really that you had to manage. What were your concerns? >>Look, the main concern is how long is it going to take for everybody in the team to learn to use the system like it and buy into it? Because I don't want to have my engineers using tools against their will write. I want everybody to be happy because that's how they're productive. They're happy, and they enjoyed the tools they have. That was my main concern. I was a little bit worried about the whole concept of not having the files in a place where I couldn't quote unquote seat in some server and on site, but that That's kind of an outdated concept, right? So that took a little bit of a mind shift, but very quickly. Then I started thinking, Look, I have a lot of documents on Google Drive. Like, I don't worry about that. Why would I worry about my cat on on shape, right? Is the same thing. So I just needed to sort of put things in perspective that way. Um, the other, um, you know, the concern was the learning curve, right? Is like, how is he Will be for everybody to and for me to learn it on whether it had all of the features that we needed. And there were a few features that I actually discussed with, um uh, Cody at on shape on, they were actually awesome about using their scripting language in on shape to sort of mimic some of the features of the old cat, uh, in on, shaped in a way that actually works even better than the old system. So it was It was amazing. Yeah, >>Great. Thank you for that, Philip. What's your experience been? Maybe you could take us through your journey within shape. >>Sure. So we've been we've been using on shaped silver side for coming up on about four years now, and we love it. We're very happy with it. We have a very modular product line, so we make anything from detectors that would go into backpacks. Two vehicles, two very large things that a shipping container would go through and saw. Excuse me. Shape helps us to track and collaborate faster on the design. Have multiple people working a same time on a project. And it also helps us to figure out if somebody else comes to us and say, Hey, I want something new how we congrats modules from things that we already have put them together and then keep track of the design development and the different branches and ideas that we have, how they all fit together. A za design comes together, and it's just been fantastic from a mechanical engineering background. I will also say that having used a number of different systems and solid works was the greatest thing since sliced bread. Before I got using on shape, I went, Wow, this is amazing and I really don't want to design in any other platform. After after getting on Lee, a little bit familiar with it. >>You know, it's funny, right? I'll have the speed of technology progression. I was explaining to some young guns the other day how I used to have a daytime er and that was my life. And if I lost that daytime, er I was dead. And I don't know how we weigh existed without, you know, Google maps eso we get anywhere, I don't know, but, uh but so So, Matt, you know, it's interesting to think about, you know, some of the concerns that Raphael brought up, you hear? For instance, you know, all the time. Wow. You know, I get my Amazon bill at the end of the month that zip through the roof in, But the reality is that Yeah, well, maybe you are doing more, but you're doing things that you couldn't have done before. And I think about your experience in teaching and educating. I mean, you so much more limited in terms of the resource is that you would have had to be able to educate people. So what's your experience been with With on shape and what is it enabled? >>Um, yeah, it was actually talking before we went with on shape. We had a previous CAD program, and I was talking to my vendor about it, and he let me know that we were actually one of the biggest CAD shops in the state. Because if you think about it a really big program, you know, really big company might employ. 5, 10, 15, 20 cad guys, right? I mean, when I worked for a large defense contractor, I think there were probably 20 of us as the cad guys. I now have about 300 students doing cat. So there's probably more students with more hours of cat under their belt in my building than there were when I worked for the big defense contractor. Um, but like you mentioned, uh, probably our biggest hurdle is just re sources. And so we want We want one of things I've always prided myself and trying to do in this. Programs provide students with access two tools and skills that they're going to see either in college or in the real world. So it's one of the reason we went with a big professional cad program. There are, you know, sort of K 12 oriented software and programs and things. But, you know, I want my kids coding and python and using slack and using professional type of tools on DSO when it comes to cat. That's just that That was a really hurt. I mean, you know, you could spend $30,000 on one seat of, you know, professional level cad program, and then you need a $30,000 computer to run it on if you're doing a heavy assemblies, Um and so one of my dreams And it was always just a crazy dream. And I was the way I would always pitcher in my school system and say, someday I'm gonna have a kid on a school issued chromebook in subsidized housing, on public WiFi doing professional level bad and that that was a crazy statement until a couple of years ago. So we're really excited that I literally and you know, March and you said the forced march, the forced march into, you know, modernity, March 13th kids sitting in my engineering lab that we spent a lot of money on doing cad March 14th. Those kids were at home on their school issued chromebooks on public WiFi, uh, keeping their designs going and collaborating. And then, yeah, I could go on and on about some of the things you know, the features that we've learned since then they're even better. So it's not like this is some inferior, diminished version of Academy. There's so much about it. Well, I >>wanna I wanna ask you that I may be over my skis on this, but we're seeing we're starting to see the early days of the democratization of CAD and product design. It is the the citizen engineer, I mean, maybe insulting to the engineers in the room, But but is that we're beginning to see that >>I have to believe that everything moves into the cloud. Part of that is democratization that I don't need. I can whether you know, I think artists, you know, I could have a music studio in my basement with a nice enough software package. And Aiken, I could be a professional for now. My wife's a photographer. I'm not allowed to say that I could be a professional photographer with, you know, some cloud based software, and so, yeah, I do think that's part of what we're seeing is more and more technology is moving to the cloud. >>Philip. Rafael Anything you Dad, >>I think I mean, yeah, that that that combination of cloud based cat and then three d printing that is becoming more and more affordable on ubiquitous It's truly transformative, and I think for education is fantastic. I wish when I was a kid I had the opportunity to play with those kinds of things because I was always the late things. But, you know, the in a very primitive way. So, um, I think this is a dream for kids. Teoh be able to do this. And, um, yeah, there's so many other technologies coming on, like Arduino on all of these electronic things that live kids play at home very cheaply with things that back in my day would have been unthinkable. >>So we know there's a go ahead. Philip, please. >>We had a pandemic and silver site moved to a new manufacturing facility this year. I was just on the shop floor, talking with contractors, standing 6 ft apart, pointing at things. But through it all, our CAD system was completely unruffled. Nothing stopped in our development work. Nothing stopped in our support for existing systems in the field. We didn't have to think about it. We had other server issues, but none with our, you know, engineering cad, platform and product development in support world right ahead, which was cool, but also a in that's point. I think it's just really cool what you're doing with the kids. The most interesting secondary and college level engineering work that I did was project based, taken important problem to the world. Go solve it and that is what we do here. That is what my entire career has been. And I'm super excited to see. See what your students are going to be doing, uh, in there home classrooms on their chromebooks now and what they do building on that. >>Yeah, I'm super excited to see your kids coming out of college with engineering degrees because, yeah, I think that Project based experience is so much better than just sitting in a classroom, taking notes and doing math problems on day. I think it will give the kids a much better flavor. What engineering is really about Think a lot of kids get turned off by engineering because they think it's kind of dry because it's just about the math for some very abstract abstract concept on they are there. But I think the most important thing is just that hands on a building and the creativity off, making things that you can touch that you can see that you can see functioning. >>Great. So, you know, we all know the relentless pace of technology progression. So when you think about when you're sitting down with the folks that on shape and there the customer advisor for one of the things that that you want on shape to do that it doesn't do today >>I could start by saying, I just love some of the things that does do because it's such a modern platform. And I think some of these, uh, some some platforms that have a lot of legacy and a lot of history behind them. I think we're dragging some of that behind them. So it's cool to see a platform that seemed to be developed in the modern era, and so that Z it is the Google docks. And so the fact that collaboration and version ing and link sharing is and like platform agnostic abilities, the fact that that seems to be just built into the nature of the thing so far, That's super exciting. As far as things that, uh, to go from there, Um, I don't know, >>Other than price. >>You can't say >>I >>can't say lower price. >>Yeah, so far on P. D. C. S that work with us. Really? Well, so I'm not complaining. There you there, >>right? Yeah. Yeah. No gaps, guys. Whitespace, Come on. >>We've been really enjoying the three week update. Cadence. You know, there's a new version every three weeks and we don't have to install it. We just get all the latest and greatest goodies. One of the trends that we've been following and enjoying is the the help with a revision management and release work flows. Um, and I know that there's more than on shape is working on that we're very excited for, because that's a big important part about making real hardware and supporting it in the field. Something that was cool. They just integrated Cem markup capability. In the last release that took, we were doing that anyway, but we were doing it outside of on shapes. And now we get to streamline our workflow and put it in the CAD system where We're making those changes anyway when we're reviewing drawings and doing this kind of collaboration. And so I think from our perspective, we continue to look forward. Toa further progress on that. There's a lot of capability in the cloud that I think they're just kind of scratching the surface on you, >>right? I would. I mean, you're you're asking to knit. Pick. I would say one of the things that I would like to see is is faster regeneration speed. There are a few times with convicts, necessities that regenerating the document takes a little longer than I would like. It's not a serious issue, but anyway, I I'm being spoiled, >>you know? That's good. I've been doing this a long time, and I like toe ask that question of practitioners and to me, it It's a signal like when you're nit picking and that's what you're struggling to knit. Pick that to me is a sign of a successful product, and and I wonder, I don't know, uh, have the deep dive into the architecture. But are things like alternative processors. You're seeing them hit the market in a big way. Uh, you know, maybe helping address the challenge, But I'm gonna ask you the big, chewy question now. Then we maybe go to some audience questions when you think about the world's biggest problems. I mean, we're global pandemics, obviously top of mind. You think about nutrition, you know, feeding the global community. We've actually done a pretty good job of that. But it's not necessarily with the greatest nutrition, climate change, alternative energy, the economic divides. You've got geopolitical threats and social unrest. Health care is a continuing problem. What's your vision for changing the world and how product innovation for good and be applied to some of the the problems that that you all are passionate about? Big question. Who wants toe start? >>Not biased. But for years I've been saying that if you want to solve the economy, the environment, uh, global unrest, pandemics, education is the case. If you wanna. If you want to, um, make progress in those in those realms, I think funding funding education is probably gonna pay off pretty well. >>Absolutely. And I think Stam is key to that. I mean, all of the ah lot of the well being that we have today and then industrialized countries. Thanks to science and technology, right improvements in health care, improvements in communication, transportation, air conditioning. Um, every aspect of life is touched by science and technology. So I think having more kids studying and understanding that is absolutely key. Yeah, I agree, >>Philip, you got anything to add? >>I think there's some big technical problems in the world today, Raphael and ourselves there certainly working on a couple of them. Think they're also collaboration problems and getting everybody to be able to pull together instead of pulling separately and to be able to spur the ideas on words. So that's where I think the education side is really exciting. What Matt is doing and it just kind of collaboration in general when we could do provide tools to help people do good work. Uh, that is, I think, valuable. >>Yeah, I think that's a very good point. And along those lines, we have some projects that are about creating very low cost instruments for low research settings, places in Africa, Southeast Asia, South America, so that they can do, um, um, biomedical research that it's difficult to do in those place because they don't have the money to buy the fancy lab machines that cost $30,000 an hour. Um, so we're trying to sort of democratize some of those instruments. And I think thanks to tools like Kahn shape then is easier, for example, to have a conversation with somebody in Africa and show them the design that we have and discuss the details of it with them on. But it's amazing, right to have somebody, you know, 10 time zones away, Um, looking really life in real time with you about your design and discussing the details or teaching them how to build a machine, right? Because, um, you know, they have a three D printer. You can you can just give them the design and say like, you build it yourself, uh, even cheaper than and, you know, also billing and shipping it there. Um, so all that that that aspect of it is also super important. I think for any of these efforts to improve some of the hardest part was in the world for climate change. Do you say, as you say, poverty, nutrition issues? Um, you know, availability of water. You have that project at about finding water. Um, if we can also help deploy technologies that teach people remotely how to create their own technologies or how to build their own systems that will help them solve those forms locally. I think that's very powerful. >>Yeah, the point about education is right on. I think some people in the audience may be familiar with the work of Erik Brynjolfsson and Andrew McAfee, the second machine age where they sort of put forth the premise that, uh, is it laid it out. Look, for the first time in history, machines air replacing humans from a cognitive perspective. Machines have always replaced humans, but that's gonna have an impact on jobs. But the answer is not toe protect the past from the future. The answer is education and public policy that really supports that. So I couldn't agree more. I think it's a really great point. Um, we have We do have some questions from the audience. If if we could If I can ask you guys, um, you know, this one kind of stands out. How do you see artificial intelligence? I was just talking about machine intelligence. Um, how do you see that? Impacting the design space guys trying to infuse a I into your product development. Can you tell me? >>Um, absolutely, like, we're using AI for some things, including some of these very low cost instruments that will hopefully help us diagnose certain diseases, especially this is that are very prevalent in the Third World. Um, and some of those diagnostics are these days done by thes armies of technicians that are trained to look under the microscope. But, um, that's a very slow process. Is very error prone and having machine learning systems that can to the same diagnosis faster, cheaper and also little machines that can be taken to very remote places to these villages that have no access to a fancy microscope. To look at a sample from a patient that's very powerful. And I we don't do this, but I have read quite a bit about how certain places air using a Tribune attorneys to actually help them optimize designs for parts. So you get these very interesting looking parts that you would have never thought off a person would have never thought off, but that are incredibly light ink. Earlier, strong and I have all sort of properties that are interesting thanks to artificial intelligence machine learning in particular >>yet another. The advantage you get when when your work is in the cloud I've seen. I mean, there's just so many applications that so if the radiology scan is in the cloud and the radiologist is goes to bed at night, Radiologist could come in in the morning and and say, Oh, the machine while you were sleeping was using artificial intelligence to scan these 40,000 images. And here's the five that we picked out that we think you should take a closer look at. Or like Raphael said, I can design my part. My, my, my, my, my you know, mount or bracket or whatever and go to sleep. And then I wake up in the morning. The machine has improved. It for me has made it strider strider stronger and lighter. Um And so just when your when your work is in the cloud, that's just that's a really cool advantage that you get that you can have machines doing some of your design work for you. >>Yeah, we've been watching, uh, you know, this week is this month, I guess is AWS re invent and it's just amazing to see how much effort is coming around machine learning machine intelligence. You know Amazon has sage maker Google's got, you know, embedded you no ML and big query. Uh, certainly Microsoft with Azure is doing tons of stuff and machine learning. I think the point there is that that these things will be infused in tow R and D and in tow software product by the vendor community. And you all will apply that to your business and and build value through the unique data that your collecting, you know, in your ecosystems. And and that's how you add value. You don't have to be necessarily, you know, developers of artificial intelligence, but you have to be practitioners to apply that. Does that make sense to you, Philip? >>Yeah, absolutely. And I think your point about value is really well chosen. We see AI involved from the physics simulations all the way up to interpreting radiation data, and that's where the value question, I think, is really important because it's is the output of the AI giving helpful information that the people that need to be looking at it. So if it's curating a serious of radiation alert, saying, Hey, like these air the anomalies. You need to look at eyes it, doing that in a way that's going to help a good response on. In some cases, the II is only as good as the people. That sort of gave it a direction and turn it loose. And you want to make sure that you don't have biases or things like that underlying your AI that they're going to result in less than helpful outcomes coming from it. So we spend quite a lot of time thinking about how do we provide the right outcomes to people who are who are relying on our systems? >>That's a great point, right? Humans air biased and humans build models, so models are inherently biased. But then the software is hitting the market. That's gonna help us identify those biases and help us, you know? Of course. Correct. So we're entering Cem some very exciting times, guys. Great conversation. I can't thank you enough for spending the time with us and sharing with our audience the innovations that you're bringing to help the world. So thanks again. >>Thank you so much. >>Thank you. >>Okay. Welcome. Okay. When we come back, John McElheny is gonna join me. He's on shape. Co founder. And he's currently the VP of strategy at PTC. He's gonna join the program. We're gonna take a look at what's next and product innovation. I'm Dave Volonte and you're watching innovation for good on the Cube, the global leader. Digital technology event coverage. We'll be right back. >>Okay? Okay. Yeah. Okay. >>From around >>the globe, it's the Cube. Presenting innovation for good. Brought to you by on shape. >>Okay, welcome back to innovation. For good. With me is John McElheny, who is one of the co founders of On Shape and is now the VP of strategy at PTC. John, it's good to see you. Thanks for making the time to come on the program. Thanks, Dave. So we heard earlier some of the accomplishments that you've made since the acquisition. How has the acquisition affected your strategy? Maybe you could talk about what resource is PTC brought to the table that allowed you toe sort of rethink or evolve your strategy? What can you share with us? >>Sure. You know, a year ago, when when John and myself met with Jim Pepperman early on is we're we're pondering. Started joining PTC one of things became very clear is that we had a very clear shared vision about how we could take the on shape platform and really extended for, for all of the PTC products, particular sort of their augmented reality as well as their their thing works or the i o. T business and their product. And so from the very beginning there was a clear strategy about taking on shape, extending the platform and really investing, um, pretty significantly in the product development as well as go to market side of things, uh, toe to bring on shape out to not only the PTC based but sort of the broader community at large. So So So PTC has been a terrific, terrific, um, sort of partner as we've we've gonna go on after this market together. Eso We've added a lot of resource and product development side of things. Ah, lot of resource and they go to market and customer success and support. So, really, on many fronts, that's been both. Resource is as well a sort of support at the corporate level from from a strategic standpoint and then in the field, we've had wonderful interactions with many large enterprise customers as well as the PTC channels. So it's been really a great a great year. >>Well, and you think about the challenges of in your business going to SAS, which you guys, you know, took on that journey. You know, 78 years ago. Uh, it's not trivial for a lot of companies to make that transition, especially a company that's been around as long as PTC. So So I'm wondering how much you know, I was just asking you How about what PCP TC brought to the table? E gotta believe you're bringing a lot to the table to in terms of the mindset, uh, even things is, is mundane is not the right word, but things like how you compensate salespeople, how you interact with customers, the notion of a service versus a product. I wonder if you could address >>that. Yeah, it's a it's a really great point. In fact, after we had met Jim last year, John and I one of the things we walked out in the seaport area in Boston, one of things we sort of said is, you know, Jim really gets what we're trying to do here and and part of let me bring you into the thinking early on. Part of what Jim talked about is there's lots of, you know, installed base sort of software that's inside of PTC base. That's helped literally thousands of customers around the world. But the idea of moving to sass and all that it entails both from a technology standpoint but also a cultural standpoint. Like How do you not not just compensate the sales people as an example? But how do you think about customer success? In the past, it might have been that you had professional services that you bring out to a customer, help them deploy your solutions. Well, when you're thinking about a SAS based offering, it's really critical that you get customers successful with it. Otherwise, you may have turned, and you know it will be very expensive in terms of your business long term. So you've got to get customers success with software in the very beginning. So you know, Jim really looked at on shape and he said that John and I, from a cultural standpoint, you know, a lot of times companies get acquired and they've acquired technology in the past that they integrate directly into into PTC and then sort of roll it out through their products, are there just reached channel, he said. In some respects, John John, think about it as we're gonna take PTC and we want to integrate it into on shape because we want you to share with us both on the sales side and customer success on marketing on operations. You know all the things because long term, we believe the world is a SAS world, that the whole industry is gonna move too. So really, it was sort of an inverse in terms of the thought process related to normal transactions >>on That makes a lot of sense to me. You mentioned Sharon turns the silent killer of a SAS company, and you know, there's a lot of discussion, you know, in the entrepreneurial community because you live this, you know what's the best path? I mean today, You see, you know, if you watch Silicon Valley double, double, triple triple, but but there's a lot of people who believe, and I wonder, if you come in there is the best path to, you know, in the X Y axis. If if it's if it's uh, growth on one and retention on the other axis. What's the best way to get to the upper right on? Really? The the best path is probably make sure you've nailed obviously the product market fit, But make sure that you can retain customers and then throw gas on the fire. You see a lot of companies they burn out trying to grow too fast, but they haven't figured out, you know that. But there's too much churn. They haven't figured out those metrics. I mean, obviously on shape. You know, you were sort of a pioneer in here. I gotta believe you've figured out that customer retention before you really, You know, put the pedal to the >>metal. Yeah, and you know, growth growth can mask a lot of things, but getting getting customers, especially the engineering space. Nobody goes and sits there and says, Tomorrow we're gonna go and and, you know, put 100 users on this and and immediately swap out all of our existing tools. These tools are very rich and deep in terms of capability, and they become part of the operational process of how a company designs and builds products. So any time anybody is actually going through the purchasing process. Typically, they will run a try along or they'll run a project where they look at. Kind of What? What is this new solution gonna help them dio. How are we gonna orient ourselves for success? Longer term. So for us, you know, getting new customers and customer acquisition is really critical. But getting those customers to actually deploy the solution to be successful with it. You know, we like to sort of, say, the marketing or the lead generation and even some of the initial sales. That's sort of like the Kindle ing. But the fire really starts when customers deploy it and get successful. The solution because they bring other customers into the fold. And then, of course, if they're successful with it, you know, then in fact, you have negative turn which, ironically, means growth in terms of your inside of your install. Bates. >>Right? And you've seen that with some of the emerging, you know, SAS companies, where you're you're actually you know, when you calculate whatever its net retention or renew ALS, it's actually from a dollar standpoint. It's up in the high nineties or even over 100%. >>So >>and that's a trend we're gonna continue. See, I >>wonder >>if we could sort of go back. Uh, and when you guys were starting on shape, some of the things that you saw that you were trying to strategically leverage and what's changed, you know, today we were talking. I was talking to John earlier about in a way, you kinda you kinda got a blank slate is like doing another startup. >>You're >>not. Obviously you've got installed base and customers to service, but But it's a new beginning for you guys. So one of the things that you saw then you know, cloud and and sas and okay, but that's we've been there, done that. What are you seeing? You know today? >>Well, you know, So So this is a journey, of course, that that on shape on its own has gone through it had I'll sort of say, you know, several iterations, both in terms of of of, you know, how do you How do you get customers? How do you How do you get them successful? How do you grow those customers? And now that we've been part of PTC, the question becomes okay. One, There is certainly a higher level of credibility that helps us in terms of our our megaphone is much bigger than it was when we're standalone company. But on top of that now, figuring out how to work with their channel with their direct sales force, you know, they have, um, for example, you know, very large enterprises. Well, many of those customers are not gonna go in forklift out their existing solution to replace it with with on shape. However, many of them do have challenges in their supply chain and communications with contractors and vendors across the globe. And so, you know, finding our fit inside of those large enterprises as they extend out with their their customers is a very interesting area that we've really been sort of incremental to to PTC. And then, you know, they they have access to lots of other technology, like the i o. T business. And now, of course, the augmented reality business that that we can bring things to bear. For example, in the augmented reality world, they've they've got something called expert capture. And this is essentially imagine, you know, in a are ah, headset that allows you to be ableto to speak to it, but also capture images still images in video. And you could take somebody who's doing their task and capture literally the steps that they're taking its geo location and from their builds steps for new employees to be, we'll learn and understand how todo use that technology to help them do their job better. Well, when they do that, if there is replacement products or variation of of some of the tools that that they built the original design instruction set for they now have another version. Well, they have to manage multiple versions. Well, that's what on shape is really great at doing and so taking our technology and helping their solutions as well. So it's not only expanding our customer footprint, it's expanding the application footprint in terms of how we can help them and help customers. >>So that leads me to the tam discussion and again, as part of your strategist role. How do you think about that? Was just talking to some of your customers earlier about the democratization of cat and engineering? You know, I kind of joked, sort of like citizen engineering, but but so that you know, the demographics are changing the number of users potentially that can access the products because the it's so much more of a facile experience. How are you thinking about the total available market? >>It really is a great question, You know, it used to be when you when you sold boxes of software, it was how many engineers were out there. And that's the size of the market. The fact that matter is now when, When you think about access to that information, that data is simply a pane of glass. Whether it's a computer, whether it's a laptop, UH, a a cell phone or whether it's a tablet, the ability to to use different vehicles, access information and data expands the capabilities and power of a system to allow feedback and iteration. I mean, one of the one of the very interesting things is in technology is when you can take something and really unleash it to a larger audience and builds, you know, purpose built applications. You can start to iterate, get better feedback. You know there's a classic case in the clothing industry where Zara, you know, is a fast sort of turnaround. Agile manufacturer. And there was a great New York Times article written a couple years ago. My wife's a fan of Zara, and I think she justifies any purchases by saying, You know, Zara, you gotta purchase it now. Otherwise it may not be there the next time. Yet you go back to the store. They had some people in a store in New York that had this woman's throw kind of covering Shaw. And they said, Well, it would be great if we could have this little clip here so we can hook it through or something. And they sent a note back toe to the factory in Spain, and literally two weeks later they had, you know, 4000 of these things in store, and they sold out because they had a closed loop and iterative process. And so if we could take information and allow people access in multiple ways through different devices and different screens, that could be very specific information that, you know, we remove a lot of the engineering data book, bring the end user products conceptually to somebody that would have had to wait months to get the actual physical prototype, and we could get feedback well, Weaken have a better chance of making sure whatever product we're building is the right product when it ultimately gets delivered to a customer. So it's really it's a much larger market that has to be thought of rather than just the kind of selling A boxes software to an engineer. >>That's a great story. And again, it's gonna be exciting for you guys to see that with. The added resource is that you have a PTC, Um, so let's talk. I promise people we wanna talk about Atlas. Let's talk about the platform. A little bit of Atlas was announced last year. Atlas. For those who don't know it's a SAS space platform, it purports to go beyond product lifecycle management and you You're talking cloud like agility and scale to CAD and product design. But John, you could do a better job than I. What do >>we need to know about Atlas? Well, I think Atlas is a great description because it really is metaphorically sort of holding up all of the PTC applications themselves. But from the very beginning, when John and I met with Jim, part of what we were intrigued about was that he shared a vision that on shape was more than just going to be a cad authoring tool that, in fact, you know, in the past these engineering tools were very powerful, but they were very narrow in their purpose and focus. And we had specialty applications to manage the versions, etcetera. What we did in on shape is we kind of inverted that thinking. We built this collaboration and sharing engine at the core and then kind of wrap the CAD system around it. But that collaboration sharing and version ING engine is really powerful. And it was that vision that Jim had that he shared that we had from the beginning, which was, how do we take this thing to make a platform that could be used for many other applications inside of inside of any company? And so not only do we have a partner application area that is is much like the APP store or Google play store. Uh, that was sort of our first Stan Shih ation of this. This this platform. But now we're extending out to broader applications and much meatier applications. And internally, that's the thing works in the in the augmented reality. But there'll be other applications that ultimately find its way on top of this platform. And so they'll get all the benefits of of the collaboration, sharing the version ing the multi platform, multi device. And that's an extremely extremely, um, strategic leverage point for the company. >>You know, it's interesting, John, you mentioned the seaport before. So PTC, for those who don't know, built a beautiful facility down at the Seaport in Boston. And, of course, when PTC started, you know, back in the mid 19 eighties, there was nothing at the seaport s. >>So it's >>kind of kind of ironic, you know, we were way seeing the transformation of the seaport. We're seeing the transformation of industry and of course, PTC. And I'm sure someday you'll get back into that beautiful office, you know? Wait. Yeah, I'll bet. And, uh and but I wanna bring this up because I want I want you to talk about the future. How you how you see that our industry and you've observed this has moved from very product centric, uh, plat platform centric with sass and cloud. And now we're seeing ecosystems form around those products and platforms and data flowing through the ecosystem powering, you know, new innovation. I wonder if you could paint a picture for us of what the future looks like to you from your vantage point. >>Yeah, I think one of the key words you said there is data because up until now, data for companies really was sort of trapped in different applications. And it wasn't because people were nefarious and they want to keep it limited. It was just the way in which things were built. And, you know, when people use an application like on shape, what ends up happening is there their day to day interaction and everything that they do is actually captured by the platform. And, you know, we don't have access to that data. Of course it's it's the customer's data. But as as an artifact of them using the system than doing their day to day job, what's happening is they're creating huge amounts of information that can then be accessed and analyzed to help them both improve their design process, improve their efficiencies, improve their actual schedules in terms of making sure they can hit delivery times and be able to understand where there might be roadblocks in the future. So the way I see it is companies now are deploying SAS based tools like on shape and an artifact of them. Using that platform is that they have now analytics and tools to better understand and an instrument and manage their business. And then from there, I think you're going to see, because these systems are all you know extremely well. Architected allow through, you know, very structured AP. I calls to connect other SAS based applications. You're gonna start seeing closed loop sort of system. So, for example, people design using on shape, they end up going and deploying their system or installing it, or people use the end using products. People then may call back into the customers support line and report issues, problems, challenges. They'll be able to do traceability back to the underlying design. They'll be able to do trend analysis and defect analysis from the support lines and tie it back and closed loop the product design, manufacture, deployment in the field sort of cycles. In addition, you can imagine there's many things that air sort of as designed. But then when people go on site and they have to install it. There's some alterations modifications. Think about think about like a large air conditioning units for buildings. You go and you go to train and you get a large air conditioning unit that put up on top of building with a crane. They have to build all kinds of adaptors to make sure that that will fit inside of the particulars of that building. You know, with on shape and tools like this, you'll be able to not only take the design of what the air conditioning system might be, but also the all the adapter plates, but also how they installed it. So it sort of as designed as manufactured as stalled. And all these things can be traced, just like if you think about the transformation of customer service or customer contacts. In the early days, you used to have tools that were PC based tools called contact management solution, you know, kind of act or gold mine. And these were basically glorified Elektronik role in Texas. It had a customer names and they had phone numbers and whatever else. And Salesforce and Siebel, you know, these types of systems really broadened out the perspective of what a customer relationship? Waas. So it wasn't just the contact information it was, you know, How did they come to find out about you as a company? So all of the pre sort of marketing and then kind of what happens after they become a customer and it really was a 3 60 view. I think that 3 60 view gets extended to not just to the customers, but also tools and the products they use. And then, of course, the performance information that could come back to the manufacturer. So, you know, as an engineer, one of the things you learn about with systems is the following. And if you remember, when the CD first came out CDs that used to talk about four times over sampling or eight times over sampling and it was really kind of, you know, the fidelity the system. And we know from systems theory that the best way to improve the performance of a system is to actually have more feedback. The more feedback you have, the better system could be. And so that's why you get 16 60 for example, etcetera. Same thing here. The more feedback we have of different parts of a company that a better performance, The company will be better customer relationships. Better, uh, overall financial performance as well. So that's that's the view I have of how these systems all tied together. >>It's a great vision in your point about the data is I think right on. It used to be so fragmented in silos, and in order to take a system view, you've gotta have a system view of the data. Now, for years, we've optimized maybe on one little component of the system and that sometimes we lose sight of the overall outcome. And so what you just described, I think is, I think sets up. You know very well as we exit. Hopefully soon we exit this this covert era on John. I hope that you and I can sit down face to face at a PTC on shape event in the near term >>in the seaport in the >>seaport would tell you that great facility toe have have an event for sure. It >>z wonderful >>there. So So John McElhinney. Thanks so much for for participating in the program. It was really great to have you on, >>right? Thanks, Dave. >>Okay. And I want to thank everyone for participating. Today we have some great guest speakers. And remember, this is a live program. So give us a little bit of time. We're gonna flip this site over toe on demand mode so you can share it with your colleagues and you, or you can come back and and watch the sessions that you heard today. Uh, this is Dave Volonte for the Cube and on shape PTC. Thank you so much for watching innovation for good. Be well, Have a great holiday. And we'll see you next time. Yeah.

>>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 Cubes Coverage of Dell Technologies World 2020. The Digital Experience. I'm Lisa Martin, and I'm pleased to welcome back a Cube alumni and a new Cube member to the program today. China. My Mondal is back with US Director of Solutions Marketing for Dell Technologies China. But it's great to see you at Dell Technologies world, even though we're very specially death. >>Happy to be back. Thank you, Lisa. >>And Thomas Henson is joining us for the first time. Global business development manager for a I and analytics. Thomas, Welcome to the Cube. >>I am excited to be here. It's my first virtual cube. >>Yeah, well, you better make it a good one. All right. I said we're talking about a I so so much has changed John to me. The last time I saw you were probably were sitting a lot closer together. So much has changed in the last 67 months, but a lot has changed with the adoption of Ai Thomas. Kick us off. What are some of the big things feeling ai adoption right now? >>Yeah, I >>would have to >>say the two biggest things right now or as we look at accelerated compute and by accelerated compute we're not just talking about the continuation of Moore's law, but how In Data Analytics, we're actually doing more processing now with GP use, which give us faster insights. And so now we have the ability to get quicker insights in jobs that may have taken, you know, taking weeks to months a song as we were measuring. And then the second portion is when we start to talk about the innovation going on in the software and framework world, right? So no longer do you have toe know C plus plus or a lower level language. You can actually do it in Python and even pull it off of Get Hub. And it's all part of that open source community. So we're seeing Mawr more folks in the field of data science and deep learning that can actually implement some code. And then we've got faster compute to be able to process that. >>Tell me, what are your thoughts? >>Think I want to add? Is the explosive growth off data on that's actually are fulfilling the AI adoption. Think off. Like all the devices we have, the i o t. On age devices are doing data are pumping data into the pipeline. Our high resolution satellite imagery, all social media generating data. No. All of this data are actually helping the adoption off a I because now we have very granular data tow our friend the AI model Make the AI models are much better. Besides, so the combination off both in, uh, data the power off Like GPU, power surfers are coupled with the inefficient in the eye after and tools helping off. Well, the AI growth that we're seeing today >>trying to make one of the things that we've known for a while now is that it's for a I to be valuable. It's about extracting value from that. Did it? You talked about the massive explosion and data, but yet we know for a long time we've been talking about AI for decades. Initiatives can fail. What can Dell Technologies do now to help companies have successfully I project? >>Yeah, eso As you were saying, Lisa, what we're seeing is the companies are trying to add up AI Technologies toe Dr Value and extract value from their data set. Now the way it needs to be framed is there is a business challenge that customers air trying to solve. The business challenge gets transformed into a data science problem. That data scientist is going toe work with the high technology, trained them on it. That data science problem gets to the data science solution on. Then it needs to be mapped to production deployment as a business solution. What happens? Ah, lot off. The time is the companies do not plan for output transition from all scale proof of concept that it a scientists are playing with, like a smaller set of data two, when it goes toe the large production deployment dealing with terabytes toe terabyte self data. Now that's where we come in. At their technologies, we have into end solutions for the, uh for the ai for pollution in the customers journeys starting from proof of concept to production. And it is all a seamless consular and very scalable. >>So if some of the challenges there are just starting with iterations. Thomas question for you as business development manager, those folks that John um I talked about the data scientists, the business. How are you helping them come together from the beginning so that when the POC is initiated, it actually can go on the right trajectory to be successful? >>No, that's a great point. And just to kind of build off of what Shonda my was talking about, You know, we call it that last mile, right? Like, Hey, I've got a great POC. How do I get into production? Well, if you have executive sponsorship and it's like, Hey, everybody was on board, but it's gonna take six months to a year. It's like, Whoa, you're gonna lose some momentum. So where we help our customers is, you know, by partnering with them to show them how to build, you know, from an i t. And infrastructure perspective what that ai architectural looks like, right? So we have multiple solutions around that, and at the end of the day, it's about just like Sean. Um, I was saying, You know, we may start off with a project that maybe it's only half a terabyte. Maybe it's 10 terabytes, but once you go into production, if it turns out to be three petabytes four petabytes. Nobody really, you know, has the infrastructure built unless they built on those solid practices. And that's where our solutions come in. So we can go from small scale laboratory all the way large scale production without having to move any of that data. Right? So, you know, at the heart of that is power scale and giving you that ability to scale your data and no more data migration so that you can handle one PC or multiple PCs as those models continue to improve as you start to move into production >>and I'm sticking with you 1st. 2nd 0, sorry. Trying to go ahead. >>So I was going to add that, uh, just like posthumous said right. So if you were a data scientist, you are working with this data science workstations, but getting the data from, uh, L M c our scales thes scale out platform and, uh, as it is growing from, you see two large kills production data can stay in place with the power scale platform. You can add notes, and it can grow to petabytes. And you can add in not just the workstations, but also our They'll power it, solve our switches building out our enter A I ready solutions are already solution for your production. Giving are very seamless experience from the data scientist with the i t. >>So China may will stick with you then. I'm curious to know in the last 6 to 7 months since 2020 has gone in a very different direction thing we all would have predicted our last Dell Technologies world together. What are you seeing? China. My in terms of acceleration or maybe different industries. What our customers needs, how they changed. I guess I should say in the in 2020. >>So in 2020 we're seeing the adoption off a I even more rapidly. Uh, if you think about customers ranging from like say, uh, media and entertainment industry toe, uh, the customer services off any organization to, uh the healthcare and life sciences with lots off genome analysts is going on in all of these places where we're dealing with large are datasets. We're seeing ah, lot off adoption foster processing off A. I R. Technologies, uh, giving with, say, the all the research that the's Biosciences organizations are happening. Uh, Thomas, I know like you are working with, like, a customer. So, uh, can you give us a little bit more example in there? >>Yes, one of the areas. You know, we're talking about 2021 of the things that we're seeing Mawr and Mawr is just the expansion of Just look at the need for customer support, right arm or folks working remotely their arm or folks that are learning remote. I know my child is going through virtual schools, So think about your I t organization and how Maney calls you're having now to expand. And so this is a great area where we're starting to see innovation within a I and model building to be ableto have you know, let's call it, you know, the next generation of chatbots rights. You can actually build these models off the data toe, augment those soup sports systems >>because you >>have two choices, right? You can either. You know, you you can either expand out your call center right for for we're not sure how long or you can use AI and analytics to help augment to help maybe answer some of those first baseline questions. The great thing about customers who are choosing power scale and Dell Technologies. Their partner is they already have. The resource is to be able to hold on to that data That's gonna help them train those models to help. >>So, Thomas, whenever we're talking about data, the explosions it brings to mind compliance. Protection, security. We've seen ransom where really skyrocket in 2020. Just you know, the other week there was the VA was hit. Um, I think there was also a social media Facebook instagram ticktock, 235 million users because there was an unsecured cloud database. So that vector is expanding. How can you help customers? Customers accelerate their AI projects? Well, ensuring compliance and protection and security of that data. >>Really? That's the sweet spot for power scale. We're talking with customers, right? You know, built on one FS with all the security features in mind. And I, too, came from the analytics world. So I remember in the early days of Hadoop, where, you know, as a software developer, we didn't need security, right? We you know, we were doing researching stuff, but then when we took it to the customer and and we're pushing to production, But what about all the security features. We needed >>the same thing >>for artificial intelligence, right? We want toe. We want to make sure that we're putting those security features and compliance is in. And that's where you know, from from an AI architecture perspective, by starting with one FS is at the heart of that solution. You can know that you're protecting for you know, all the enterprise features that you need, whether it be from compliance, thio, data strategy, toe backup and recovery as well. >>So when we're talking about big data volumes Chanda, mind we have to talk about the hyper scale er's talk to us about, you know, they each offer azure A W s Google cloud hundreds of AI services. So how does DEL help customers use the public cloud the data that's created outside of it and use all of those use that the right AI services to extract that value? >>Yeah. Now, as you mentioned, all of these hyper scholars are they differentiate with our office is like a i m l r Deep Learning Technologies, right? And as our customer, you want toe leverage based off all the, uh, all the cloud has to offer and not stuck with one particular cloud provider. However, we're talking about terabytes off data, right? So if you are happy with what doing service A from cloud provider say Google what you want to move to take advantage off another surface off from Asia? It comes with a very high English p a migration risk on time it will take to move the data itself. Now that's not good, right? As the customer, we should be able to live for it. Best off breed our cloud services for AI and for that matter, for anything across the board. Now, how we help customers is you can have all of your data say, in a managed, uh, managed cloud service provider running on power scale. But then you can connect from this managed cloud service provider directly toe any off the hyper scholars. You can connect toe aws, azure, Google Cloud and even, like even, uh, the in place analytics that power scale offers you can run. Uh, those, uh I mean, run those clouds AI services directly on that data simultaneously from these three, and I'll add like one more thing, right? Thes keep learning. Technologies need GPU power solvers, right? and cloud even within like one cloud is not homogeneous environment. Like sometimes you'll find a US East has or gp part solvers. But like you are in the West and the same for other providers. No, with our still our technologies cloud power scale for multi cloud our scale is sitting outside off those hyper scholars connected directly to our any off this on. Then you can burst into different clouds, take advantage off our spot. Instances on are like leverage. All the GP is not from one particular service provider part. All of those be our hyper scholars. So those are some examples off the work we're doing in the multi cloud world for a I >>So that's day. You're talking about data there. So powers failed for multi cloud for data that's created outside the public club. But Thomas, what about for data that's created inside the cloud? How does Del help with that? >>Yes. So, this year, we actually released a solution, uh, in conjunction with G C. P. So within Google Cloud, you can have power scale for one fs, right? And so that's that native native feature. So, you know, goes through all the compliance and all the features within being a part of that G c p natively eso counts towards your credits and your GP Google building as well. But it's still all the features that you have. And so we've been running some, actually, some benchmarks. So we've got a couple of white papers out there, that kind of detail. You know what we can do from an artificial intelligence perspective back to Sean Demise Example. We were just talking about, you know, being able to use more and more GPU. So we we've done that to run some of our AI benchmarks against that and then also, you know, jumped into the Hadoop space. But because you know, that's 11 area from a power scale, prospective customers were really interested. Um, and they have been for years. And then, really, the the awesome portion about this is for customers that are looking for a hybrid solution. Or maybe it's their first kickoff to it. So back Lisa to those compliance features that we were talking about those air still inherent within that native Google G C P one fs version, but then also for customers that have it on prim. You can use those same features to burst your data into, um, your isil on cluster using all the same native tools that you've been using for years within your enterprise. >>God, it's so starting out for power. Skill for Google Cloud Trying to get back to you Kind of wrapping things up here. What are some of the things that we're going to see next from Dell from an AI Solutions perspective? >>Yes. So we are working on many different interesting projects ranging from, uh, the latest, uh, in video Salford's that they have announced d d x a 100. And in fact, two weeks ago at GTC, uh, Syria announced take too far parts with, uh, it takes a 100 solvers. We're part off that ecosystem. And we are working with, uh, the leading, uh uh, solutions toe benchmark, our ai, uh, environments, uh, for all the storage, uh, ensuring, like we are providing, like, all the throughput and scalability that we have to offer >>Thomas finishing with you from the customer perspective. As we talked about so many changes this year alone as we approach calendar year 2021 what are some of the things that Dell is doing with its customers with its partners, the hyper scale er's and video, for example, Do you think customers are really going to be able to truly accelerate successful AI projects? >>Yeah. So the first thing I'd like to talk about is what we're doing with the D. G. S A 100. So this month that GTC you saw our solution for a reference architecture for the G s, a 100 plus power scale. So you talk about speed and how we can move customers insights. I mean, some of the numbers that we're seeing off of that are really a really amazing right. And so this is gives the customers the ability to still, you know, take all the features and use use I salon and one f s, um, like they have in the past, but now combined with the speed of the A 100 still be ableto speed up. How fast they're using those building out those deep learning models and then secondly, with that that gives them the ability to scale to. So there's some features inherent within this reference architecture that allow for you to make more use, right? So bring mawr data scientists and more modelers GP use because that's one thing you don't see Data scientist turning away right there always like, Hey, you know, I mean, this this project here needs needs a GPU. And so, you know, from a power scale one fs perspective, we want to be able to make sure that we're supporting that. So that as that data continues to grow, which, you know we're seeing is one of the large factors. Whenever we're talking about artificial intelligence is the scale for the data. We wanna them to be able to continue to build out that data consolidation area for all these multiple different workloads. That air coming in. >>Excellent, Thomas. Thanks for sharing that. Hopefully next time we get to see you guys in person and we can talk about a customer who has done something very successful with you guys. Kind of me. Always great to talk to you. Thank you for joining us. >>Thank you. Thank you >>for China. May Mandel and Thomas Henson. I'm Lisa Martin. You're watching the cubes Coverage of Dell Technologies, World 2020

>> Announcer: From around the globe, it's theCUBE! With digital coverage of AnsibleFest 2020, brought to you by Red Hat. >> Hello, everyone, welcome back to theCUBE's coverage of AnsibleFest 2020. We're not face-to-face this year, we're in virtual remote mode. This is theCUBE virtual and obviously it's AnsibleFest 2020 virtual. We've got a great panel of experts and leaders at Red Hat and Ansible. I want to introduce them. Dave Lindquist, general manager and vice president of engineering of hybrid cloud management at Red Hat. Joe Fernandes, vice president and general manager of the Core Cloud platforms at Red Hat. And Tom Anderson, vice President at Red Hat, Ansible Automation Platform, the big news and feature of this event. Tom, great to see you, Joe and David, thanks for coming on. >> Great to be here. >> Every year I love talking about Red Hat because I remember going back a few years ago, Arvind from IBM was on at Red Hat Summit in San Francisco, and you can see the twinkle in his eye. This was three, four years ago. Cloud native was really gearing up and now it's kind of mainstream. Last year at AnsibleFest, all the buzz was collaboration, collections, and you can start to see that integration piece kicking in, and this year at the event, the big story is the same. More collections, more integrations, a lot of collaboration around code. Content equals code. So it really points to the trend with Kubernetes of multi-cloud, multi-cluster. So the first question for you guys is, why would anyone want to deploy multiple clusters simultaneously and why is multi-cluster such a big deal? Tom, we'll start with you. >> Great, okay, yeah. So why is multi-cluster such a big deal? Basically, Kubernetes and our OpenShift container platform have now become a strategic part of our customers' environments, of their infrastructure for building and deploying cloud native applications on. And as becoming a strategic part of that, when you're deploying production applications you're going to need all kinds of things like scale out, redundancy, cloud location for access to different cloud provider locations for application requirements and whatnot. So there are a bunch of requirements for why customers would deploy OpenShift in a multi-cluster way. And maybe I'll turn it over to Joe Fernandes a little bit 'cause he's got a lot of background on the OpenShift side of this. >> Joe, what's your thoughts? >> Yeah, thanks, Tom. Yeah, so I mean, as Tom mentions, a number of reasons why customers may deploy or need to deploy more than one Kubernetes cluster. So within a cluster, you can certainly have multiple applications, multiple developers, multiple teams work, but as you start to scale your usage you may want additional clusters. It could be because you want to separate your production environments from your dev and test environments. It could be for capacity, right? You have more development teams or more production environments than you want to sort of tie to a single cluster. Then you start expanding out into locations, right? Maybe you started in the data center, then you started doing deployments to one public cloud, then to other public clouds, and then that's only going to grow. We see more and more customers deploying multi-cloud strategies. And then the new thing right now that everybody wants to talk to us about is edge, and as you get into edge deployments, now those, the number of clusters could really explode into the hundreds or thousands. And so it all points back to you need a sane way to manage across all these clusters regardless of where they run and regardless of how many you have, and that's really what we've been working on with the Advanced Cluster Management for Kubernetes. >> What's the big draw? What's drawing the customers in with multi-cluster and multi-cloud? Obviously, the multi-cloud makes a lot of sense, you have multiple clouds. Sounds easier just saying it than doing it. But what is it about multi-cluster and multi-cloud that's drawing customers and people into this concept? >> Yes, I can start. I think what's drawing customers in is the need, the desire to have sort of a common abstraction for the applications that's consistent regardless of where they happen to run, right? So making sure that the developers don't have to worry about what infrastructure the applications are landing on, and they have that consistent experience that it's, abstracts their applications away from that infrastructure. So that gives the developers more flexibility, but it's also about flexibility and agility for those infrastructure owners, right, because they too want to make decisions on where stuff runs. Not because they're particularly tied to an infrastructure, but based on things like cost or security or other concerns. And so these are all drivers for multi-cluster and multi-cloud strategies and I think our hybrid cloud strategy at Red Hat really hits the mark to address those needs. >> Well, you guys had great performance. We've been following the past few years just the OpenShift and beyond, kind of the whole Red Hat, and Ansible specifically too, is doing real well in the marketplace so congratulations. David, I want to ask you about the management piece. This comes up over and over again. It's all good having the abstraction layer, you got all kinds of new sets of services, but multi-cluster management is not, (laughs) is not trivial. There's challenges for ops and automation teams. Could you share your perspective on how you guys are looking at the multi-cluster management? >> Sure, sure. The first thing we saw, and this kind of follows on the points that Joe and Tom are making, is that as customers start embracing the development with containers and leveraging Kubernetes, you start finding that they're putting up clusters across their data centers, across cloud, to support different parts of the life cycle of development, or supporting their own production environment or distributed workloads across clouds, across the data centers. And so the challenges that operations and management run into, and security in particular, is how do you start managing the clusters, their life cycle. It's easy to put 'em up, to provision 'em quickly, but how do you update and upgrade those? How do you make sure they're compliant with your various regulatory compliance like PCI, HIPAA, or the various federal standards? How do you make sure that compliance is adhered to across, and security across those clusters, as well as the applications themselves? How do you manage the applications through their life cycle? How do you have deployment policies? So the challenges for ops and automation and security are to have a consistent policy-driven way to take care of the clusters across these hybrid environments, and making sure they adhere to the compliance and security of the enterprise. >> Tom, multi-cluster deployments is a big part of this integration. We heard a little bit, obviously, compliance and governance is huge. IT's been living this world of policies and governance, but when we start moving fast into these new cutting edge services that are providing a lot of value, integration into existing IT infrastructure is important with clusters. How do you view that because this is where I think maybe collections are other things are, is this an indicator of what's happening? Can you give your thoughts on the customers out there who want to do multiple clusters for all the benefits, but then go, "Oh, I got to integrate it into existing IT infrastructure"? >> Yeah, absolutely. So that's what's happening right now. As Kubernetes and as OpenShift has become a strategic platform for our customers, the idea of, I'm going to say, kind of normalizing the operations of that platform as part of a greater IT ecosystem has become a challenge for them. And for the most part, they've already automated security, network, provisioning, app deployment, application updates, using the Ansible Automation Platform, and so it only makes sense that as Kubernetes and as OpenShift becomes a strategic platform for them, they want to use that same language, that same tool set, that same automation fabric, if you will, to integrate the applications that are running on OpenShift with the rest of the environment. So, for example, when I add a new node to a cluster or more capacity to a cluster or to clusters, I probably want to update my systems of record, right? My CMDBs or my ITSM systems. When I deploy a new app or make an update to an app on a cluster or across clusters, I'm probably going to want to update my load balancer to be able to direct traffic correctly to that, and that load balancer probably isn't running, my enterprise load balancer is kind of platform independent, so I'd need to be able to update that load balancer to properly direct traffic. Well, IT has already automated that function using Ansible. So by creating the collections that we have created for OpenShift and for Kubernetes, it makes it much easier for our customers to be able to just plug that in and adapt that to their existing automation infrastructure. So now it just becomes part of their overall IT environment. >> So just a follow-up real quick, if you don't mind. What are some of the challenges you're hearing from your customers around containerization and that growing space? I just talked to the IDC research analyst earlier at another virtual CUBE session where she says, roughly their estimate is 5 to 10% of enterprises are containerized, which is huge growth opportunities. The headroom in containers is massive, so what are some of the challenges? Is it easy to get started? This seems to be a nice opportunity for you guys. What's your take on that? >> Yeah, I think that the way of looking at it with all that growth space, it's also the speed at which Kubernetes adoption and containerized application adoption is happening. And so, IT organizations are having to respond faster than they ever have before as this environment grows, and it is a multi-cloud environment. They have Kubernetes, OpenShift running on-prem, in the cloud, multiple data centers, as both Joe and Dave have said, and it becomes critical that they automate that correctly and accurately to ensure security, consistency, performance, availability. All of the other things that drive the requirement for automation standardization, all of those things that drive the requirements for automation are applicable to Kubernetes environments and containerized environments as well except they're moving and expanding faster, so teams have to respond quicker to the need. >> Joe, what's your take on this? I mean, to me, I'm the glass half full. I think I've seen containers be great and that maybe I'm looking at the early adopters, but those numbers seem a little bit low to me. What does that mean to you? More people are now getting up to speed. Is it a tipping point? It just seems a little bit low, and David, if you want to comment too, I think this an important number there. Joe, what's your take? >> Yeah, I mean, I think the rate represents an opportunity, but I see the growth as having been tremendous even in just the first few years. But to get to that broader market we did continue making it easier for customers to bring their applications to this new environment, to ride on existing infrastructure, and ultimately for our customers that means an evolution, right? An evolution of how they are going to manage those applications, how they're going to build and deploy them. And so with the integration of OpenShift and our advanced container management platforms with Ansible we can bring that automation to the mix to sort of tie those together, right? So to tie in the existing compute infrastructure, to tie in storage and networking and configure those as needed. And then as Tom mentioned, all those other systems, whether it's an IT service management system, something like a ServiceNow or other ticketing systems or other enterprise systems that exist that you just can't ignore. Because the more you try to go against the grain and do something different, the even harder it'll be. So we need to help customers evolve to take advantage of cloud and cloud native approaches, and the solutions that we're bringing to market are all about enterprise Kubernetes, enterprise container platforms. The combination of those technologies with something like Ansible really helps pave the path for the next phase of growth that we're expecting. >> So, ready for prime time right now. >> Right. >> David, your thoughts real quick on this. Containerization upside. >> Yeah, real quick, the development organizations, development teams, have picked up on containers very rapidly. Everybody is leveraging containers when they develop new applications or modernize the existing applications. So what we found is that a lot of the folks that pushed out very quickly, some greenfield apps, that's the 5, 10, 15, 20% that you're seeing occur. What started getting complex is how you really scale this to your enterprise. How do you really run this at scale from management operations and security perspective? OpenShift is critical, that gives a consistent platform across the hybrid cloud environments. What we're doing with ACM and the Advanced Cluster Management brings in the security and compliance. And what you'll see through AnsibleFest, what we're doing with Ansible is then, how do we then hook these environments right into all the existing IT environments? That's, to me, what's critical to really bring this to scale to the enterprise. >> Yeah, I think this, to me, the number points to exactly what you guys said. Ready for prime time, scale's there, and the demand's there. And I think, Tom and Joe, I want to ask you specifically the relationship between OpenShift and Ansible, but before that, I remember, forget what year it was, we were doing a CUBE event at, I think it might've been OpenStack, going back to the day, but I remember OpenShift and it was a moment where OpenShift adopted containers and then next year Kubernetes. And I remember talking to the team, them saying, "This is going to be a big bet for OpenShift." Looks like it was a good bet. (laughs) It paid out real well, congratulations. And it was good, you guys stayed the course. But you made it easier, and one of the things was is that the complaint at the time was they didn't want Kubernetes to be the next Hadoop. Easy to use but gets out of control. Not that I meant they're comparable, but Hadoop had that problem of it was easy open source but then it was hard to manage. So OpenShift really took advantage of that. You guys, I think, did a good job on that. But now you got Ansible winning the game on developers, on easy to deploy, so as that scales up, automation's there. So I'd like to hear you guys talk about the connection between OpenShift and Ansible and how that expands the scope of what both products can do for customers. >> Yeah, maybe I'll give it a shot first and then let Joe go after me, which is, look, here's what we have, is we have lots and lots and lots of customers, Red Hat customers that are OpenShift users and that are Ansible users, right? So we have this two large pools. They also represent two very large and vibrant open source community projects. The Ansible project and the Kubernetes project are two hugely popular, vibrant communities, and so it just made sense to kind of be a catalyst in those communities, to bring those two things together, to work together, to the benefit of our customers and to kind of capture the innovation that's going on upstream in the communities. So we decided to get really kind of serious about the integration of these two platforms and integrated Ansible in a native way on Kubernetes so that OpenShift and Kubernetes operators, as well as application developers, could take advantage of that integration without having to learn something new or foreign in order to be able to do it. So it was a native integration using operators, which is the right way to integrate with the Kubernetes platform, with OpenShift in particular. And so that's the way we kind of brought it together to the benefit of our customers. Our customers are, like I said, normalizing the operations of OpenShift as a strategic part of their infrastructure, deploying production applications, and want to be able to tie that into their other systems and other parts of their infrastructure, both from an app deployment process as well as from an infrastructure deployment and management process. So it only made sense that it actually, our customers have been asking us for this and talking to us about this, so it only kind of made perfect sense to kind of get out there and do that, get the communities together innovating, and then take that innovation out for our customer. >> Joe. >> Yeah, the only thing I'd add to that, there's really two specific personas at play here, right? When you think of, there's the IT operations and infrastructure teams. They own those clusters, the provisioning, the configuration, the management of those clusters. And with ACM, with Advanced Cluster Management for Kubernetes, we have now an interface that they can use to see and manage the life cycle of all their clusters. So through that we can integrate Ansible as another automation tool in their portfolio to do things that need to happen when those clusters first get configured or when those clusters get updated and so forth. So if they need to update an ITSM system or configure a network or do whatever it needs to, you have Ansible automation scripts that can be plugged in at the appropriate time in that cluster's life cycle to do that. On the other side, you have the developer and DevOps teams that are consumers of these platforms, right? And what they care about is the applications that they're building, but there's a lot that goes into building it, right? There's the source code management systems, there's the CI systems, the CD systems, there's the test environments and stage and prod. And so there's a lot of moving parts, and again, and then there's the services themselves that they're configuring so you have, or building, not configuring, you have Ansible again ready to sort of take on some of those tasks, automation tasks that go beyond what Kubernetes is focused on or what you're trying to do with OpenShift. And again, doing it at the appropriate time in the life cycle, all tied in through Advanced Cluster Management which can actually see out to all those clusters and be in that sort of application deployment workflow across those clusters. So those are sort of some of the specific areas and how they pertain to those specific personas that are driving the activity. >> What's interesting, this automation piece really is key across multiple environments, and we've heard that from some of your customers. 'Cause you got now private clouds out there, you got large scale. But, Dave, I want to ask you, what makes Advanced Cluster Management a natural fit with OpenShift and Ansible? What's your take? >> Yeah, good question, John. First, ACM is purpose-built for the Kubernetes environment. It's a cloud native management system, and as we said earlier, we really focused on managing the cluster life cycles, managing the security compliance, and managing applications deployed into these environments. So it was a very natural extension of OpenShift, to be able to manage OpenShift, multiple clusters of OpenShift in hybrid environments. Within your data center, across data centers, across clouds, and the combination. So, very natural fit with OpenShift. As we've been all talking about, as we looked at how did we then bring OpenShift and these resources closer through automation to many of the other parts of your IT environment, that made it natural from ACM to call out into the playbooks of Ansible. So just a simple example, and I think we circled around this a few times. You're deploying a cluster or you're deploying, say, an application to that cluster. You need to configure that into a firewall. Maybe configure it into a load balancer. Maybe register it with a service management system. That, all those calls, they come out through policy from ACM over into Ansible to take advantage of the wealth of playbooks that are available in Ansible to perform those operations. Whether it's security, network, service management, storage, et cetera. >> Real quick follow-up for you is, how has bringing your ACM team and product into Red Hat changed the scope and approach of what you're trying to do? >> Yeah, well, let me say first of all it's been a great experience bringing the team into Red Hat. The environment, the open culture, it's really been invigorating for the whole team. Also, getting much, much closer into the open communities and open sourcing ACM and doing development in the open has really brought us closer really to users, the ecosystem, the communities, accelerating our delivery quality, as well as really getting much more closer insights, getting insights into what's happening in the community, what's happening with the users. So it's really, it's been a great experience all the way around. >> Joe and Tom, quick comment, what do you think people should pay attention to this year at AnsibleFest 2020? What's the big story? Obviously we're in a pandemic. We're going to come out of the pandemic. People want to have a growth strategy that has the right projects on the right rails. They want to either maybe downplay some of the projects that maybe not be a fit, that were exposed during the pandemic. Best practices that are emerging, shifting left for security is one. You're seeing remote workers. People have kind of had a wake-up call on cloud native being relevant for the modern app. Now they're running as fast as they can to build the infrastructure, and guess what? People are not actually in the workplaces. The workforce, the workplace has all changed. Can you guys share your expertise over the years on what is the best practice and approach to take? Because the clock's ticking. >> Yeah, from my perspective and from an Ansible perspective here, we had always been about kind of automate everything, right? Automate every task that is automatable, right? A repeatable task, automate it. Repeatable task, automate it. And over the past couple of years we've really been focused on automation across teams by using Ansible content, the actual automation code, if you will, itself to bring teams together and to cross teams and cross functions. So not just focused on what a network operations person or a network engineer needs to do in their day-to-day job, but connect that to what a security operations person is doing day-to-day in their job in terms of threat detection and intrusion response, or intrusion detection and threat response, and connecting those two teams together via automation to make both of them more responsive and more effective. So we've been on this bandwagon for the past couple of years around Ansible content, and now Ansible collections and Automation Hub, to try and accelerate the way these teams can collaborate together. The pandemic and the pressures that put on the system with remote users and having to do things in a different way only exacerbated, it only kind of enhanced the requirement for that collaboration, that automation across teams. So in a lot of ways, the past six, seven months, both for our Ansible business as well as for the way our customers have been using the technology, has really been an accelerator for that kind of cross-team collaboration, our subscription business, and our Ansible consumption. >> Yeah, well, I said it last year in-person when we were in Atlanta for AnsibleFest 2019, a platform approach is a great way to go. You start out as a tool, you become a platform. You guys are doin' the work over there. I really appreciate it and I want to call that out 'cause I think it's worth calling out. Joe, cloud platforms. Cloud is certainly an enabler. Red Hat and OpenShift has been a great success and can, only has got more work to do. People still got to build out these platforms, and you're seeing private cloud not going away. I mean, we just had a conversation at OpenStack and you guys got customers with a lot of private cloud everywhere. (laughs) So you got private, you got hybrid, you got multi, and you got public. It's pretty crazy. What's your thoughts on what people should take away from AnsibleFest and then going forward post-pandemic? >> Yeah, so, first Tom hit on a number of key points there, right? COVID-19 and everything going on in the world has really just accelerated a lot of these transformations that were already in the works at many of our enterprise customer accounts, right? And now when we're all working remotely, we're all meeting virtually, we're educating our children remotely, it just exacerbates the need to scale our networks, to extend security out to remote workforces, and to do all of these things at much larger scales than we ever envisioned before, and you can't do that without automation. And I would argue, without taking advantage of some of these modern cloud native platforms and cloud native development approaches. And we always say Red Hat's been a big proponent of hybrid cloud, of our open hybrid cloud strategy. We've been talking about that for years, and what we always say is even if that's a strategy that you aren't specifically looking for, it's something that, everybody ends up there, right? Because nobody's running everything in the data center anymore, but as they move out to public cloud they're not completely shutting those data centers off either. As they expand their consumption of public cloud, they tend to start exploring multi-cloud strategies, and now that hybrid cloud is extending out to the edge. So the hybrid cloud is sort of where everybody is, right? And the ability to sort of manage consistently, to run consistently across all those environments, to be able to secure all those environments and scale those environments, and that's what we're all about here at Red Hat and that's sort of the key to our open hybrid cloud strategy and what we're really trying to do with our entire portfolio. >> Awesome, David, final word. We're in a systems world now. The cloud is one big distributed computer. We got the edge, we heard that. Developers just want to code, they want infrastructure as code, you guys got to help 'em get there. What's your take on the importance of AnsibleFest and this systems world we live in? >> Well, there's probably not a more critical time. We've all been saying this and seeing this the last 10 months now. The transformation digitally that's been going on for years, the development transformations, it's all hit a fever pitch. It's been accelerated through COVID. In particular, how quickly can I adjust to a digital transformation? How quickly can I adjust my business processes? How quickly can I really become a very agile DevOps SRE organization? That is so critical. So at AnsibleFest what we're doing is bringing together platforms with automation with the ability to manage it at scale with security. That's what's going on from Red Hat in a open environment, open world, with communities and huge ecosystems. That, to me, is the critical rallying points, and really necessary to drive this accelerated transformation. >> Yeah, and again, open source continues to power it. One thing I'm impressed with is this concept of content, not content as in a video, but content as code. It's collaboration. It's what people are sharing their playbooks and they're sharing their, are opening things up. I think there's going to be a whole 'nother level of developer collaboration that's going to emerge and you guys are on the front end of all of this. I think it's going to be pretty powerful. I don't think yet clearly understood yet by most folks, but when you start seeing the automation benefits, Tom, I'm sure your team will be like, "Yeah, see, automation platform." Thank you so much for coming on, appreciate it. >> Thank you. >> Thanks a lot. >> Thanks. >> I'm John Furrier with theCUBE, hosting theCUBE virtual for AnsibleFest 2020 virtual. Thanks for watching. (relaxing music)

>>Hi, everyone. My name is my uncle. My uncle Poor I worked with Geo reminds you in India. We call ourselves Geo Platforms. Now on. We've been recently in the news. You've raised a lot off funding from one of the largest, most of the largest tech companies in the world. And I'm here to talk about Geos Cloud Journey, Onda Mantis Partnership. I've titled it the story often, Underdog becoming the largest telecom company in India within four years, which is really special. And we're, of course, held by the cloud. So quick disclaimer. Right. The content shared here is only for informational purposes. Um, it's only for this event. And if you want to share it outside, especially on social media platforms, we need permission from Geo Platforms limited. Okay, quick intro about myself. I am a VP of engineering a geo. I lead the Cloud Services and Platforms team with NGO Andi. I mean the geo since the beginning, since it started, and I've seen our cloud footprint grow from a handful of their models to now eight large application data centers across three regions in India. And we'll talk about how we went here. All right, Let's give you an introduction on Geo, right? Giorgio is on how we became the largest telecom campaign, India within four years from 0 to 400 million subscribers. And I think there are There are a lot of events that defined Geo and that will give you an understanding off. How do you things and what you did to overcome massive problems in India. So the slide that I want to talkto is this one and, uh, I The headline I've given is, It's the Geo is the fastest growing tech company in the world, which is not a new understatement. It's eggs, actually, quite literally true, because very few companies in the world have grown from zero to 400 million subscribers within four years paying subscribers. And I consider Geo Geos growth in three phases, which I have shown on top. The first phase we'll talk about is how geo grew in the smartphone market in India, right? And what we did to, um to really disrupt the telecom space in India in that market. Then we'll talk about the feature phone phase in India and how Geo grew there in the future for market in India. and then we'll talk about what we're doing now, which we call the Geo Platforms phase. Right. So Geo is a default four g lt. Network. Right. So there's no to geo three g networks that Joe has, Um it's a state of the art four g lt voiceover lt Network and because it was designed fresh right without any two D and three G um, legacy technologies, there were also a lot of challenges Lawn geo when we were starting up. One of the main challenges waas that all the smart phones being sold in India NGOs launching right in 2000 and 16. They did not have the voice or lt chip set embedded in the smartphone because the chips it's far costlier to embed in smartphones and India is a very price and central market. So none of the manufacturers were embedding the four g will teach upset in the smartphones. But geos are on Lee a volte in network, right for the all the network. So we faced a massive problem where we said, Look there no smartphones that can support geo. So how will we grow Geo? So in order to solve that problem, we launched our own brand of smartphones called the Life um, smartphones. And those phones were really high value devices. So there were $50 and for $50 you get you You At that time, you got a four g B storage space. A nice big display for inch display. Dual cameras, Andi. Most importantly, they had volte chip sets embedded in them. Right? And that got us our initial customers the initial for the launch customers when we launched. But more importantly, what that enabled other oh, EMS. What that forced the audience to do is that they also had to launch similar smartphones competing smartphones with voltage upset embedded in the same price range. Right. So within a few months, 3 to 4 months, um, all the other way EMS, all the other smartphone manufacturers, the Samsung's the Micromax is Micromax in India, they all had volte smartphones out in the market, right? And I think that was one key step We took off, launching our own brand of smartphone life that helped us to overcome this problem that no smartphone had. We'll teach upsets in India and then in order. So when when we were launching there were about 13 telecom companies in India. It was a very crowded space on demand. In order to gain a foothold in that market, we really made a few decisions. Ah, phew. Key product announcement that really disrupted this entire industry. Right? So, um, Geo is a default for GLT network itself. All I p network Internet protocol in everything. All data. It's an all data network and everything from voice to data to Internet traffic. Everything goes over this. I'll goes over Internet protocol, and the cost to carry voice on our smartphone network is very low, right? The bandwidth voice consumes is very low in the entire Lt band. Right? So what we did Waas In order to gain a foothold in the market, we made voice completely free, right? He said you will not pay anything for boys and across India, we will not charge any roaming charges across India. Right? So we made voice free completely and we offer the lowest data rates in the world. We could do that because we had the largest capacity or to carry data in India off all the other telecom operators. And these data rates were unheard off in the world, right? So when we launched, we offered a $2 per month or $3 per month plan with unlimited data, you could consume 10 gigabytes of data all day if you wanted to, and some of our subscriber day. Right? So that's the first phase off the overgrowth and smartphones and that really disorders. We hit 100 million subscribers in 170 days, which was very, very fast. And then after the smartphone faith, we found that India still has 500 million feature phones. And in order to grow in that market, we launched our own phone, the geo phone, and we made it free. Right? So if you take if you took a geo subscription and you carried you stayed with us for three years, we would make this phone tree for your refund. The initial deposit that you paid for this phone and this phone had also had quite a few innovations tailored for the Indian market. It had all of our digital services for free, which I will talk about soon. And for example, you could plug in. You could use a cable right on RCR HDMI cable plug into the geo phone and you could watch TV on your big screen TV from the geophones. You didn't need a separate cable subscription toe watch TV, right? So that really helped us grow. And Geo Phone is now the largest selling feature phone in India on it. 100 million feature phones in India now. So now now we're in what I call the geo platforms phase. We're growing of a geo fiber fiber to the home fiber toe the office, um, space. And we've also launched our new commerce initiatives over e commerce initiatives and were steadily building platforms that other companies can leverage other companies can use in the Jeon o'clock. Right? So this is how a small startup not a small start, but a start of nonetheless least 400 million subscribers within four years the fastest growing tech company in the world. Next, Geo also helped a systemic change in India, and this is massive. A lot of startups are building on this India stack, as people call it, and I consider this India stack has made up off three things, and the acronym I use is jam. Trinity, right. So, um, in India, systemic change happened recently because the Indian government made bank accounts free for all one billion Indians. There were no service charges to store money in bank accounts. This is called the Jonathan. The J. GenDyn Bank accounts. The J out off the jam, then India is one of the few countries in the world toe have a digital biometric identity, which can be used to verify anyone online, which is huge. So you can simply go online and say, I am my ankle poor on duh. I verify that this is indeed me who's doing this transaction. This is the A in the jam and the last M stands for Mobil's, which which were held by Geo Mobile Internet in a plus. It is also it is. It also stands for something called the U. P I. The United Unified Payments Interface. This was launched by the Indian government, where you can carry digital transactions for free. You can transfer money from one person to the to another, essentially for free for no fee, right so I can transfer one group, even Indian rupee to my friend without paying any charges. That is huge, right? So you have a country now, which, with a with a billion people who are bank accounts, money in the bank, who you can verify online, right and who can pay online without any problems through their mobile connections held by G right. So suddenly our market, our Internet market, exploded from a few million users to now 506 106 100 million mobile Internet users. So that that I think, was a massive such a systemic change that happened in India. There are some really large hail, um, numbers for this India stack, right? In one month. There were 1.6 billion nuclear transactions in the last month, which is phenomenal. So next What is the impact of geo in India before you started, we were 155th in the world in terms off mobile in terms of broadband data consumption. Right. But after geo, India went from one 55th to the first in the world in terms of broadband data, largely consumed on mobile devices were a mobile first country, right? We have a habit off skipping technology generation, so we skip fixed line broadband and basically consuming Internet on our mobile phones. On average, Geo subscribers consumed 12 gigabytes of data per month, which is one of the highest rates in the world. So Geo has a huge role to play in making India the number one country in terms off broad banded consumption and geo responsible for quite a few industry first in the telecom space and in fact, in the India space, I would say so before Geo. To get a SIM card, you had to fill a form off the physical paper form. It used to go toe Ah, local distributor. And that local distributor is to check the farm that you feel incorrectly for your SIM card and then that used to go to the head office and everything took about 48 hours or so, um, to get your SIM card. And sometimes there were problems there also with a hard biometric authentication. We enable something, uh, India enable something called E K Y C Elektronik. Know your customer? We took a fingerprint scan at our point of Sale Reliance Digital stores, and within 15 minutes we could verify within a few minutes. Within a few seconds we could verify that person is indeed my hunk, right, buying the same car, Elektronik Lee on we activated the SIM card in 15 minutes. That was a massive deal for our growth. Initially right toe onboard 100 million customers. Within our and 70 days. We couldn't have done it without be K. I see that was a massive deal for us and that is huge for any company starting a business or start up in India. We also made voice free, no roaming charges and the lowest data rates in the world. Plus, we gave a full suite of cloud services for free toe all geo customers. For example, we give goTV essentially for free. We give GOTV it'll law for free, which people, when we have a launching, told us that no one would see no one would use because the Indians like watching TV in the living rooms, um, with the family on a big screen television. But when we actually launched, they found that GOTV is one off our most used app. It's like 70,000,080 million monthly active users, and now we've basically been changing culture in India where culture is on demand. You can watch TV on the goal and you can pause it and you can resume whenever you have some free time. So really changed culture in India, India on we help people liver, digital life online. Right, So that was massive. So >>I'm now I'd like to talk about our cloud >>journey on board Animal Minorities Partnership. We've been partners that since 2014 since the beginning. So Geo has been using open stack since 2014 when we started with 14 note luster. I'll be one production environment One right? And that was I call it the first wave off our cloud where we're just understanding open stack, understanding the capabilities, understanding what it could do. Now we're in our second wave. Where were about 4000 bare metal servers in our open stack cloud multiple regions, Um, on that around 100,000 CPU cores, right. So it's a which is one of the bigger clouds in the world, I would say on almost all teams, with Ngor leveraging the cloud and soon I think we're going to hit about 10,000 Bama tools in our cloud, which is massive and just to give you a scale off our network, our in French, our data center footprint. Our network introduction is about 30 network data centers that carry just network traffic across there are there across India and we're about eight application data centers across three regions. Data Center is like a five story building filled with servers. So we're talking really significant scale in India. And we had to do this because when we were launching, there are the government regulation and try it. They've gotten regulatory authority of India, mandates that any telecom company they have to store customer data inside India and none of the other cloud providers were big enough to host our clothes. Right. So we we made all this intellectual for ourselves, and we're still growing next. I love to show you how we grown with together with Moran says we started in 2014 with the fuel deployment pipelines, right? And then we went on to the NK deployment. Pipelines are cloud started growing. We started understanding the clouds and we picked up M C p, which has really been a game changer for us in automation, right on DNA. Now we are in the latest release, ofem CPM CPI $2019 to on open stack queens, which on we've just upgraded all of our clouds or the last few months. Couple of months, 2 to 3 months. So we've done about nine production clouds and there are about 50 internal, um, teams consuming cloud. We call as our tenants, right. We have open stack clouds and we have communities clusters running on top of open stack. There are several production grade will close that run on this cloud. The Geo phone, for example, runs on our cloud private cloud Geo Cloud, which is a backup service like Google Drive and collaboration service. It runs out of a cloud. Geo adds G o g S t, which is a tax filing system for small and medium enterprises, our retail post service. There are all these production services running on our private clouds. We're also empaneled with the government off India to provide cloud services to the government to any State Department that needs cloud services. So we were empaneled by Maiti right in their ego initiative. And our clouds are also Easter. 20,000 certified 20,000 Colin one certified for software processes on 27,001 and said 27,017 slash 18 certified for security processes. Our clouds are also P our data centers Alsop a 942 be certified. So significant effort and investment have gone toe These data centers next. So this is where I think we've really valued the partnership with Morantes. Morantes has has trained us on using the concepts of get offs and in fries cold, right, an automated deployments and the tool change that come with the M C P Morantes product. Right? So, um, one of the key things that has happened from a couple of years ago to today is that the deployment time to deploy a new 100 north production cloud has decreased for us from about 55 days to do it in 2015 to now, we're down to about five days to deploy a cloud after the bear metals a racked and stacked. And the network is also the physical network is also configured, right? So after that, our automated pipelines can deploy 100 0 clock in five days flight, which is a massive deal for someone for a company that there's adding bear metals to their infrastructure so fast, right? It helps us utilize our investment, our assets really well. By the time it takes to deploy a cloud control plane for us is about 19 hours. It takes us two hours to deploy a compu track and it takes us three hours to deploy a storage rack. Right? And we really leverage the re class model off M C. P. We've configured re class model to suit almost every type of cloud that we have, right, and we've kept it fairly generous. It can be, um, Taylor to deploy any type of cloud, any type of story, nor any type of compute north. Andi. It just helps us automate our deployments by putting every configuration everything that we have in to get into using infra introduction at school, right plus M. C. P also comes with pipelines that help us run automated tests, automated validation pipelines on our cloud. We also have tempest pipelines running every few hours every three hours. If I recall correctly which run integration test on our clouds to make sure the clouds are running properly right, that that is also automated. The re class model and the pipelines helpers automate day to operations and changes as well. There are very few seventh now, compared toa a few years ago. It very rare. It's actually the exception and that may be because off mainly some user letter as opposed to a cloud problem. We also have contributed auto healing, Prometheus and Manager, and we integrate parameters and manager with our even driven automation framework. Currently, we're using Stack Storm, but you could use anyone or any event driven automation framework out there so that it indicates really well. So it helps us step away from constantly monitoring our cloud control control planes and clothes. So this has been very fruitful for us and it has actually apps killed our engineers also to use these best in class practices like get off like in France cord. So just to give you a flavor on what stacks our internal teams are running on these clouds, Um, we have a multi data center open stack cloud, and on >>top of that, >>teams use automation tools like terra form to create the environments. They also create their own Cuba these clusters and you'll see you'll see in the next slide also that we have our own community that the service platform that we built on top of open stack to give developers development teams NGO um, easy to create an easy to destroy Cuban. It is environment and sometimes leverage the Murano application catalog to deploy using heats templates to deploy their own stacks. Geo is largely a micro services driven, Um um company. So all of our applications are micro services, multiple micro services talking to each other, and the leverage develops. Two sets, like danceable Prometheus, Stack stone from for Otto Healing and driven, not commission. Big Data's tax are already there Kafka, Patches, Park Cassandra and other other tools as well. We're also now using service meshes. Almost everything now uses service mesh, sometimes use link. Erred sometimes are experimenting. This is Theo. So So this is where we are and we have multiple clients with NGO, so our products and services are available on Android IOS, our own Geo phone, Windows Macs, Web, Mobile Web based off them. So any client you can use our services and there's no lock in. It's always often with geo, so our sources have to be really good to compete in the open Internet. And last but not least, I think I love toe talk to you about our container journey. So a couple of years ago, almost every team started experimenting with containers and communities and they were demand for as a platform team. They were demanding community that the service from us a manage service. Right? So we built for us, it was much more comfortable, much more easier toe build on top of open stack with cloud FBI s as opposed to doing this on bare metal. So we built a fully managed community that a service which was, ah, self service portal, where you could click a button and get a community cluster deployed in your own tenant on Do the >>things that we did are quite interesting. We also handle some geo specific use cases. So we have because it was a >>manage service. We deployed the city notes in our own management tenant, right? We didn't give access to the customer to the city. Notes. We deployed the master control plane notes in the tenant's tenant and our customers tenant, but we didn't give them access to the Masters. We didn't give them the ssh key the workers that the our customers had full access to. And because people in Genova learning and experimenting, we gave them full admin rights to communities customers as well. So that way that really helped on board communities with NGO. And now we have, like 15 different teams running multiple communities clusters on top, off our open stack clouds. We even handle the fact that there are non profiting. I people separate non profiting I peoples and separate production 49 p pools NGO. So you could create these clusters in whatever environment that non prod environment with more open access or a prod environment with more limited access. So we had to handle these geo specific cases as well in this communities as a service. So on the whole, I think open stack because of the isolation it provides. I think it made a lot of sense for us to do communities our service on top off open stack. We even did it on bare metal, but that not many people use the Cuban, indeed a service environmental, because it is just so much easier to work with. Cloud FBI STO provision much of machines and covering these clusters. That's it from me. I think I've said a mouthful, and now I love for you toe. I'd love to have your questions. If you want to reach out to me. My email is mine dot capulet r l dot com. I'm also you can also message me on Twitter at my uncouple. So thank you. And it was a pleasure talking to you, Andre. Let let me hear your questions.

>> Narrator: From around the globe, it's theCUBE with digital coverage of AWS Public Sector Online brought to you by Amazon Web Services. >> Hi and welcome back to theCUBE's coverage of AWS Summit Online. I'm Stu Miniman your host for this segment. Always love when we get to talk to the practitioners in this space and of course at AWS Public Sector, broad diversity of backgrounds and areas, everything from government to education and the like, so really happy they were able to bring us Joshua Spence, he is the Chief Technology Officer, from West Virginia in the Office of Technology. Josh, thank you so much for joining us. >> I appreciate the invitation to be here. >> All right so, technology for an entire state, quite a broad mandate, when you talk about that, maybe give our audience a little bit of your background and the role of your organization for West Virginia. >> Yeah, absolutely so in the public sector space, especially at state government, we're involved in a myriad of services for government to the citizens and from a central IT perspective, we're seeking to provide those enterprise services and support structures to keep those costs controlled and efficient and be able to enable these agencies to service the citizens of the state. >> Excellent, maybe just to talk about the role of the state versus more local, from a technology standpoint, how many applications do you manage? How many people do you have? Is everything that you do in the Cloud, or do you also have some data centers? just give us a little thumbnail sketch if you would, of what what's under that umbrella. >> Sure, absolutely I think you'll see at the state level we have... We typically administer a lot of the federal programs that come down through funding, ranging from health and human resources to environmental protection, to public safety you've got, just a broad spectrum of services that are being provided at the state level and so the central office, the Office of Technology, Services approximately 22,000 state employees and their ability to carry out those services to the citizens. And then of course you have like local government, like in State of West Virginia with 55 counties, and then you're following municipalities. The interesting thing though in public sector is from the citizen's perspective, government is government, whether it's local, state or federal. >> Yeah, that's such a good point and right now of course there's a strain on everything. With the global pandemic, services from the public sector are needed more than ever, maybe help us understand a little bit things like work from home and unemployment, I expect, may require a shift and some reaction from your office. So tell us what's been happening in your space the last few months. >> Yeah absolutely, well, the first part you get the work from home piece rate, West Virginia, although the last state to have a confirmed test positive of COVID-19, we were in a little bit of in a position of advantage as we were watching what was happening across the world, across the country and so we didn't hesitate to react in West Virginia and through great leadership here, we shut down the state quickly, we put protections in place to help, show up and prevent the spread of COVID. And to do that though with the government facilities, government services, we had to be able to enable a remote workforce and do so very quickly, at a scale that no one ever anticipated having to do. Coop plans for the most part rejected just picking up from the location you're working at to go work at another centralized location. No one really ever thought, "Well, we wouldn't be able to all congregate to work." So that created our first challenge that we had to respond to. The second challenge was then how do we adjust government services to interface with citizens from a remote perspective and in addition to that a surge of need. And when you look at unemployment all across the country, the demand became exponentially larger than what was ever experienced. The systems were not equipped to take on that type of load. And we had to leverage technology to very quickly adapt to the situation. >> Yeah, I'd love you to drill in a little bit on that technology piece. Obviously you think about certain services, if I had them, just in a data center and I needed it all of a sudden ramp up, do I run into capacity issues? Can I actually get to that environment? How do I scale that up fast? The promise of Cloud always has been well, I should be able to react immediately, I have in theory infinite scale. So what has been your experience, are there certain services that you say, "Oh boy, I'm so glad I have them in the Cloud." and has there been any struggles with being able to react to what you're dealing with. >> Well yeah the struggles have absolutely been there and it's been a combination of not just on-premise infrastructure, but then legacy infrastructure. And that's what we saw when we were dealing with the unemployment surge here in West Virginia, just from a citizen contact perspective, being able to answer the phone calls that were coming in, it was overwhelming and what we found is we unfortunately had a number of phone systems all supporting whether it's the central office or the regional office, they were all disparate, some of which were legacy. We therefore had no visibility on the metrics, we didn't even know how many calls were actually coming in a day. When you compound that the citizen's just trying to find answers, well, they're not going to just call the numbers you provide, they're going to call any numbers. So then they're now also calling other agencies seeking assistance just 'cause they're wanting help and that's understandable. So we needed to make a change, we need to make change very quickly. And that's when we looked to see if a solution in the Cloud might be a better option. And would it enable us to not only correct the situation, get visibility and scale, what could we do so extremely quick because the time to value was what was real important. >> Excellent, so my understanding that you were not using any cloud-based contact center before this hit. >> We were in only... There were some other agencies that had some hosted contact center capabilities, but on a small scale. This was the first large project around a Cloud Contact Center, and needed to run the project from Go Live or decision to go forward on a Friday at one o'clock and to roll over the first call center on the following Monday at 6:00 p.m. was a speed that we had never seen before. >> Oh boy yeah, I think back, I worked in telecom back in the 90s and you talk about a typical deployment you used to measure months and you're talking more like hours for getting something up and running and there's not only the technology, there's the people, the training, all these sorts of things there, so, yeah tell us, how did you come to such a fast decision and deployment? So you walk us through a little bit of that. >> Sure, so we went out to the market and asked several providers to give us their solution proposals and to do so very quickly 'cause we knew we had to move quickly and then when upon evaluation of the options before us, we made our selection and indicate that selection and started working with both the Cloud provider and the integrator, to build out a phased approach deployment of the technology. Phase one was, hey, let's get everybody calling the same 800 number as best as we can. And then where we can't get the 800 number be that focal point, let's forward all other phone numbers to the same call center. Because before we were able to bring the technology and our only solution was to put more people on the phones and we had physical limitations there. So we went after, the Amazon contact center or our integrator a Smartronix and we were able to do so very quickly and get that phase one change in place, which then allowed us to decide what was phase two and what was going to be phase three. >> Josh, you've got some background in cybersecurity, I guess in general, there's been a raised awareness and need for security with the pandemic going on, bad actors are still going in there. I've talked to some when they're rolling out their call centers, they need to worry about... Sounds like you've got everything in your municipality. So might not need to worry about, government per se but, I guess if you could touch on security right now for what's happening in general and anything specific about the contact center that you need to make sure that people working from home were following policy, procedure, not breaking any regulation and guidelines. >> Yeah, absolutely I think the most important piece of the puzzle when you're looking at security is understanding, so it's always a question of risk, right? If you're seeking first and foremost, to put in security with the understanding that now, hey we've put it in we don't have to think about it anymore. That's not the answer 'cause you're not going to stop all risk, right? You have to weigh it and understand which risks you need to address so that's really important piece. The second part that we've looked at in the current situation with the response to COVID is not only do we see threat actors trying to take advantage of the circumstances, right? Because more people are working from home, there are less computers on the hard network, right? They're now either VPN-ing in or they are just simply outside the network and there may be limited visibility that central agency or the central entity has on those devices. So what do you do? We got to extend that protection out to the account and to the devices itself and not worry so much about the boundary, right? 'cause the boundary now is a lot in all and since it purposes the accounts, but then I think an additional piece of the puzzle right now is to look at how important technology is to your organization, look at the role it's performing in enabling your ability to continue to function remotely (indistinct) the risk associated with those devices becoming compromised or unavailable. So, we see that the most important aspects of our security changes were to extend that protection as best we could to push out education to the users on the changing threats that might be coming their way. >> Yeah, it's fascinating to think if this pandemic had hit 10 years ago, you wouldn't have the capability of this. I'm thinking back to like, well, we could forward numbers to a certain place and do some cascading, but the Cloud Contact Center, absolutely wasn't available. Have you had a chance to think about now that you have this capability, what this means as we progress down the road, do you think you'll be keeping a hybrid model or stay fully Cloud once people are moving back to the offices? >> Well, I definitely think that the near future is a hybrid model and we'll see where it goes from there. There's workloads without a doubt that are better served, putting them in the Cloud, giving you that on demand scalability. I mean, if we look at what a project like this would have required, had we had to procure equipment, install equipment, there was just no time to do that. So having the services, the capability, whether it's microservices or VMS or whatever, all available, just don't need be turned on and configure to be used, it's just there's a lot of power there. And as government seeks to develop digital government, right? How do we transition from providing services where citizens stand in line to doing it online? I think Cloud's going to continue to play a key piece in that. >> Yeah I'm wondering if you could speak a little bit to the financial impact of this. So typically you think about, I roll out a project, it's budgeted, we write it off over a certain number of years, Cloud of course by its nature is there's flexibility and I'm paying for what I'm using, but this was something that was unexpected. So how were you... Did you have oversight on this? Was there additional funding put out? How was that financial discussion happening? >> Yeah, so that's a big piece of the puzzle when a government entity like a state is under a state of emergency, the good thing is there's processes and procedures that we leverage regularly to understand how we're going to fund those response activities. And then the Federal Government plays a role also in responding to states of emergency that enable the state and local government to have additional funding to cover during the state of emergency. So that makes things a little easier to start in a sense, I think the bigger challenge is going to be what comes from the following years after COVID, because obviously tax revenues are going to take a hit across the board. And what does that mean to government budgets that then in turn are going to have to be adjusted? So the advantage of Cloud services and other type technology services where they're sold under that OPEX model, do give states flexibility in ways to scale services, scale solutions as needed and give us a little bit more flexibility in adjusting for budget challenges. >> Yeah, it's been fascinating to watch, we know how the speed of adoption in technology, tends to run at a certain pace. The last three months, there are definitely certain technologies that there's been massive acceleration like you've discussed. So, I'm wondering that you've had the modernization, things like the unemployment claims was the immediate requirement that you needed, but have there been other pieces, other use cases and applications that this modernization, leverage of cloud technologies is impacting you today or other things that you see a little bit down the path. >> Yeah, I think it's... We're going to see a modernization of government applications designed to interface directly with the citizen, right? So we're going to want to be able to give the citizen opportunity, whether it's on a smartphone, a tablet, or a computer to interface with government, whether it's communications to inquire about a service, or to get support around a service or to file paperwork around a service. We want to enable that digital interface and so that's going to be a big push, and it's going to be amplified. There was already a look towards that, right? With the smart cities, smart states and some of the initiatives there, but what's happened with COVID basically it's forced the issue of not being able to be physically together, well, how do you do it using technology? So if there was a silver lining in an awful situation that we have with COVID, one might be that, we've been able to stretch our use of technology to better serve the citizens. >> Well, great, really really impressive story. Josh, I want to give you the final word. Just what advice would you give your peers kind of dealing with things in a crisis, and any other advice you'd have in general about managing and leveraging the Cloud? >> I think in a closing comment, I think one of the most important aspects that can be considered is having that translation capability of talking to the business element, the government service component and understand what they're trying to achieve, what their purpose or their mission is and then being able to tie it back to the technology in a way to where all parties, all stakeholders understand their roles and responsibilities, to make that happen. Unfortunately I think what happens too often is on the business side or the non-technical side of the equation, they see the end state, but they don't truly understand their responsibilities to get to the end state. And it's definitely a partnership and the better that partnership's understood at the start, the more successful the project's going to have to get there under budget and on time. >> Well, thank you so much for joining us, best of luck with the project and please stay safe. >> Thank you for having me. >> All right, stay tuned for more coverage from AWS Public Sector Online. I'm Stu Miniman and thank you for watching theCUBE. (soft music)