hello I'm John Furrier with thecube and welcome to this special presentation of the cube and Horizon 3.ai they're announcing a global partner first approach expanding their successful pen testing product Net Zero you're going to hear from leading experts in their staff their CEO positioning themselves for a successful Channel distribution expansion internationally in Europe Middle East Africa and Asia Pacific in this Cube special presentation you'll hear about the expansion the expanse partner program giving Partners a unique opportunity to offer Net Zero to their customers Innovation and Pen testing is going International with Horizon 3.ai enjoy the program [Music] welcome back everyone to the cube and Horizon 3.ai special presentation I'm John Furrier host of thecube we're here with Jennifer Lee head of Channel sales at Horizon 3.ai Jennifer welcome to the cube thanks for coming on great well thank you for having me so big news around Horizon 3.aa driving Channel first commitment you guys are expanding the channel partner program to include all kinds of new rewards incentives training programs help educate you know Partners really drive more recurring Revenue certainly cloud and Cloud scale has done that you got a great product that fits into that kind of Channel model great Services you can wrap around it good stuff so let's get into it what are you guys doing what are what are you guys doing with this news why is this so important yeah for sure so um yeah we like you said we recently expanded our Channel partner program um the driving force behind it was really just um to align our like you said our Channel first commitment um and creating awareness around the importance of our partner ecosystems um so that's it's really how we go to market is is through the channel and a great International Focus I've talked with the CEO so you know about the solution and he broke down all the action on why it's important on the product side but why now on the go to market change what's the what's the why behind this big this news on the channel yeah for sure so um we are doing this now really to align our business strategy which is built on the concept of enabling our partners to create a high value high margin business on top of our platform and so um we offer a solution called node zero it provides autonomous pen testing as a service and it allows organizations to continuously verify their security posture um so we our company vision we have this tagline that states that our pen testing enables organizations to see themselves Through The Eyes of an attacker and um we use the like the attacker's perspective to identify exploitable weaknesses and vulnerabilities so we created this partner program from a perspective of the partner so the partner's perspective and we've built It Through The Eyes of our partner right so we're prioritizing really what the partner is looking for and uh will ensure like Mutual success for us yeah the partners always want to get in front of the customers and bring new stuff to them pen tests have traditionally been really expensive uh and so bringing it down in one to a service level that's one affordable and has flexibility to it allows a lot of capability so I imagine people getting excited by it so I have to ask you about the program What specifically are you guys doing can you share any details around what it means for the partners what they get what's in it for them can you just break down some of the mechanics and mechanisms or or details yeah yep um you know we're really looking to create business alignment um and like I said establish Mutual success with our partners so we've got two um two key elements that we were really focused on um that we bring to the partners so the opportunity the profit margin expansion is one of them and um a way for our partners to really differentiate themselves and stay relevant in the market so um we've restructured our discount model really um you know highlighting profitability and maximizing profitability and uh this includes our deal registration we've we've created deal registration program we've increased discount for partners who take part in our partner certification uh trainings and we've we have some other partner incentives uh that we we've created that that's going to help out there we've we put this all so we've recently Gone live with our partner portal um it's a Consolidated experience for our partners where they can access our our sales tools and we really view our partners as an extension of our sales and Technical teams and so we've extended all of our our training material that we use internally we've made it available to our partners through our partner portal um we've um I'm trying I'm thinking now back what else is in that partner portal here we've got our partner certification information so all the content that's delivered during that training can be found in the portal we've got deal registration uh um co-branded marketing materials pipeline management and so um this this portal gives our partners a One-Stop place to to go to find all that information um and then just really quickly on the second part of that that I mentioned is our technology really is um really disruptive to the market so you know like you said autonomous pen testing it's um it's still it's well it's still still relatively new topic uh for security practitioners and um it's proven to be really disruptive so um that on top of um just well recently we found an article that um that mentioned by markets and markets that reports that the global pen testing markets really expanding and so it's expected to grow to like 2.7 billion um by 2027. so the Market's there right the Market's expanding it's growing and so for our partners it's just really allows them to grow their revenue um across their customer base expand their customer base and offering this High profit margin while you know getting in early to Market on this just disruptive technology big Market a lot of opportunities to make some money people love to put more margin on on those deals especially when you can bring a great solution that everyone knows is hard to do so I think that's going to provide a lot of value is there is there a type of partner that you guys see emerging or you aligning with you mentioned the alignment with the partners I can see how that the training and the incentives are all there sounds like it's all going well is there a type of partner that's resonating the most or is there categories of partners that can take advantage of this yeah absolutely so we work with all different kinds of Partners we work with our traditional resale Partners um we've worked we're working with systems integrators we have a really strong MSP mssp program um we've got Consulting partners and the Consulting Partners especially with the ones that offer pen test services so we they use us as a as we act as a force multiplier just really offering them profit margin expansion um opportunity there we've got some technology partner partners that we really work with for co-cell opportunities and then we've got our Cloud Partners um you'd mentioned that earlier and so we are in AWS Marketplace so our ccpo partners we're part of the ISP accelerate program um so we we're doing a lot there with our Cloud partners and um of course we uh we go to market with uh distribution Partners as well gotta love the opportunity for more margin expansion every kind of partner wants to put more gross profit on their deals is there a certification involved I have to ask is there like do you get do people get certified or is it just you get trained is it self-paced training is it in person how are you guys doing the whole training certification thing because is that is that a requirement yeah absolutely so we do offer a certification program and um it's been very popular this includes a a seller's portion and an operator portion and and so um this is at no cost to our partners and um we operate both virtually it's it's law it's virtually but live it's not self-paced and we also have in person um you know sessions as well and we also can customize these to any partners that have a large group of people and we can just we can do one in person or virtual just specifically for that partner well any kind of incentive opportunities and marketing opportunities everyone loves to get the uh get the deals just kind of rolling in leads from what we can see if our early reporting this looks like a hot product price wise service level wise what incentive do you guys thinking about and and Joint marketing you mentioned co-sell earlier in pipeline so I was kind of kind of honing in on that piece sure and yes and then to follow along with our partner certification program we do incentivize our partners there if they have a certain number certified their discount increases so that's part of it we have our deal registration program that increases discount as well um and then we do have some um some partner incentives that are wrapped around meeting setting and um moving moving opportunities along to uh proof of value gotta love the education driving value I have to ask you so you've been around the industry you've seen the channel relationships out there you're seeing companies old school new school you know uh Horizon 3.ai is kind of like that new school very cloud specific a lot of Leverage with we mentioned AWS and all the clouds um why is the company so hot right now why did you join them and what's why are people attracted to this company what's the what's the attraction what's the vibe what do you what do you see and what what do you use what did you see in in this company well this is just you know like I said it's very disruptive um it's really in high demand right now and um and and just because because it's new to Market and uh a newer technology so we are we can collaborate with a manual pen tester um we can you know we can allow our customers to run their pen test um with with no specialty teams and um and and then so we and like you know like I said we can allow our partners can actually build businesses profitable businesses so we can they can use our product to increase their services revenue and um and build their business model you know around around our services what's interesting about the pen test thing is that it's very expensive and time consuming the people who do them are very talented people that could be working on really bigger things in the in absolutely customers so bringing this into the channel allows them if you look at the price Delta between a pen test and then what you guys are offering I mean that's a huge margin Gap between street price of say today's pen test and what you guys offer when you show people that they follow do they say too good to be true I mean what are some of the things that people say when you kind of show them that are they like scratch their head like come on what's the what's the catch here right so the cost savings is a huge is huge for us um and then also you know like I said working as a force multiplier with a pen testing company that offers the services and so they can they can do their their annual manual pen tests that may be required around compliance regulations and then we can we can act as the continuous verification of their security um um you know that that they can run um weekly and so it's just um you know it's just an addition to to what they're offering already and an expansion so Jennifer thanks for coming on thecube really appreciate you uh coming on sharing the insights on the channel uh what's next what can we expect from the channel group what are you thinking what's going on right so we're really looking to expand our our Channel um footprint and um very strategically uh we've got um we've got some big plans um for for Horizon 3.ai awesome well thanks for coming on really appreciate it you're watching thecube the leader in high tech Enterprise coverage [Music] [Music] hello and welcome to the Cube's special presentation with Horizon 3.ai with Raina Richter vice president of emea Europe Middle East and Africa and Asia Pacific APAC for Horizon 3 today welcome to this special Cube presentation thanks for joining us thank you for the invitation so Horizon 3 a guy driving Global expansion big international news with a partner first approach you guys are expanding internationally let's get into it you guys are driving this new expanse partner program to new heights tell us about it what are you seeing in the momentum why the expansion what's all the news about well I would say uh yeah in in international we have I would say a similar similar situation like in the US um there is a global shortage of well-educated penetration testers on the one hand side on the other side um we have a raising demand of uh network and infrastructure security and with our approach of an uh autonomous penetration testing I I believe we are totally on top of the game um especially as we have also now uh starting with an international instance that means for example if a customer in Europe is using uh our service node zero he will be connected to a node zero instance which is located inside the European Union and therefore he has doesn't have to worry about the conflict between the European the gdpr regulations versus the US Cloud act and I would say there we have a total good package for our partners that they can provide differentiators to their customers you know we've had great conversations here on thecube with the CEO and the founder of the company around the leverage of the cloud and how successful that's been for the company and honestly I can just Connect the Dots here but I'd like you to weigh in more on how that translates into the go to market here because you got great Cloud scale with with the security product you guys are having success with great leverage there I've seen a lot of success there what's the momentum on the channel partner program internationally why is it so important to you is it just the regional segmentation is it the economics why the momentum well there are it's there are multiple issues first of all there is a raising demand in penetration testing um and don't forget that uh in international we have a much higher level in number a number or percentage in SMB and mid-market customers so these customers typically most of them even didn't have a pen test done once a year so for them pen testing was just too expensive now with our offering together with our partners we can provide different uh ways how customers could get an autonomous pen testing done more than once a year with even lower costs than they had with with a traditional manual paint test so and that is because we have our uh Consulting plus package which is for typically pain testers they can go out and can do a much faster much quicker and their pain test at many customers once in after each other so they can do more pain tests on a lower more attractive price on the other side there are others what even the same ones who are providing um node zero as an mssp service so they can go after s p customers saying okay well you only have a couple of hundred uh IP addresses no worries we have the perfect package for you and then you have let's say the mid Market let's say the thousands and more employees then they might even have an annual subscription very traditional but for all of them it's all the same the customer or the service provider doesn't need a piece of Hardware they only need to install a small piece of a Docker container and that's it and that makes it so so smooth to go in and say okay Mr customer we just put in this this virtual attacker into your network and that's it and and all the rest is done and within within three clicks they are they can act like a pen tester with 20 years of experience and that's going to be very Channel friendly and partner friendly I can almost imagine so I have to ask you and thank you for calling the break calling out that breakdown and and segmentation that was good that was very helpful for me to understand but I want to follow up if you don't mind um what type of partners are you seeing the most traction with and why well I would say at the beginning typically you have the the innovators the early adapters typically Boutique size of Partners they start because they they are always looking for Innovation and those are the ones you they start in the beginning so we have a wide range of Partners having mostly even um managed by the owner of the company so uh they immediately understand okay there is the value and they can change their offering they're changing their offering in terms of penetration testing because they can do more pen tests and they can then add other ones or we have those ones who offer 10 tests services but they did not have their own pen testers so they had to go out on the open market and Source paint testing experts um to get the pen test at a particular customer done and now with node zero they're totally independent they can't go out and say okay Mr customer here's the here's the service that's it we turn it on and within an hour you're up and running totally yeah and those pen tests are usually expensive and hard to do now it's right in line with the sales delivery pretty interesting for a partner absolutely but on the other hand side we are not killing the pain testers business we do something we're providing with no tiers I would call something like the foundation work the foundational work of having an an ongoing penetration testing of the infrastructure the operating system and the pen testers by themselves they can concentrate in the future on things like application pen testing for example so those Services which we we're not touching so we're not killing the paint tester Market we're just taking away the ongoing um let's say foundation work call it that way yeah yeah that was one of my questions I was going to ask is there's a lot of interest in this autonomous pen testing one because it's expensive to do because those skills are required are in need and they're expensive so you kind of cover the entry level and the blockers that are in there I've seen people say to me this pen test becomes a blocker for getting things done so there's been a lot of interest in the autonomous pen testing and for organizations to have that posture and it's an overseas issue too because now you have that that ongoing thing so can you explain that particular benefit for an organization to have that continuously verifying an organization's posture yep certainly so I would say um typically you are you you have to do your patches you have to bring in new versions of operating systems of different Services of uh um operating systems of some components and and they are always bringing new vulnerabilities the difference here is that with node zero we are telling the customer or the partner package we're telling them which are the executable vulnerabilities because previously they might have had um a vulnerability scanner so this vulnerability scanner brought up hundreds or even thousands of cves but didn't say anything about which of them are vulnerable really executable and then you need an expert digging in one cve after the other finding out is it is it really executable yes or no and that is where you need highly paid experts which we have a shortage so with notes here now we can say okay we tell you exactly which ones are the ones you should work on because those are the ones which are executable we rank them accordingly to the risk level how easily they can be used and by a sudden and then the good thing is convert it or indifference to the traditional penetration test they don't have to wait for a year for the next pain test to find out if the fixing was effective they weren't just the next scan and say Yes closed vulnerability is gone the time is really valuable and if you're doing any devops Cloud native you're always pushing new things so pen test ongoing pen testing is actually a benefit just in general as a kind of hygiene so really really interesting solution really bring that global scale is going to be a new new coverage area for us for sure I have to ask you if you don't mind answering what particular region are you focused on or plan to Target for this next phase of growth well at this moment we are concentrating on the countries inside the European Union Plus the United Kingdom um but we are and they are of course logically I'm based into Frankfurt area that means we cover more or less the countries just around so it's like the total dark region Germany Switzerland Austria plus the Netherlands but we also already have Partners in the nordics like in Finland or in Sweden um so it's it's it it's rapidly we have Partners already in the UK and it's rapidly growing so I'm for example we are now starting with some activities in Singapore um um and also in the in the Middle East area um very important we uh depending on let's say the the way how to do business currently we try to concentrate on those countries where we can have um let's say um at least English as an accepted business language great is there any particular region you're having the most success with right now is it sounds like European Union's um kind of first wave what's them yes that's the first definitely that's the first wave and now we're also getting the uh the European instance up and running it's clearly our commitment also to the market saying okay we know there are certain dedicated uh requirements and we take care of this and and we're just launching it we're building up this one uh the instance um in the AWS uh service center here in Frankfurt also with some dedicated Hardware internet in a data center in Frankfurt where we have with the date six by the way uh the highest internet interconnection bandwidth on the planet so we have very short latency to wherever you are on on the globe that's a great that's a great call outfit benefit too I was going to ask that what are some of the benefits your partners are seeing in emea and Asia Pacific well I would say um the the benefits is for them it's clearly they can they can uh talk with customers and can offer customers penetration testing which they before and even didn't think about because it penetrates penetration testing in a traditional way was simply too expensive for them too complex the preparation time was too long um they didn't have even have the capacity uh to um to support a pain an external pain tester now with this service you can go in and say even if they Mr customer we can do a test with you in a couple of minutes within we have installed the docker container within 10 minutes we have the pen test started that's it and then we just wait and and I would say that is we'll we are we are seeing so many aha moments then now because on the partner side when they see node zero the first time working it's like this wow that is great and then they work out to customers and and show it to their typically at the beginning mostly the friendly customers like wow that's great I need that and and I would say um the feedback from the partners is that is a service where I do not have to evangelize the customer everybody understands penetration testing I don't have to say describe what it is they understand the customer understanding immediately yes penetration testing good about that I know I should do it but uh too complex too expensive now with the name is for example as an mssp service provided from one of our partners but it's getting easy yeah it's great and it's great great benefit there I mean I gotta say I'm a huge fan of what you guys are doing I like this continuous automation that's a major benefit to anyone doing devops or any kind of modern application development this is just a godsend for them this is really good and like you said the pen testers that are doing it they were kind of coming down from their expertise to kind of do things that should have been automated they get to focus on the bigger ticket items that's a really big point so we free them we free the pain testers for the higher level elements of the penetration testing segment and that is typically the application testing which is currently far away from being automated yeah and that's where the most critical workloads are and I think this is the nice balance congratulations on the international expansion of the program and thanks for coming on this special presentation really I really appreciate it thank you you're welcome okay this is thecube special presentation you know check out pen test automation International expansion Horizon 3 dot AI uh really Innovative solution in our next segment Chris Hill sector head for strategic accounts will discuss the power of Horizon 3.ai and Splunk in action you're watching the cube the leader in high tech Enterprise coverage foreign [Music] [Music] welcome back everyone to the cube and Horizon 3.ai special presentation I'm John Furrier host of thecube we're with Chris Hill sector head for strategic accounts and federal at Horizon 3.ai a great Innovative company Chris great to see you thanks for coming on thecube yeah like I said uh you know great to meet you John long time listener first time caller so excited to be here with you guys yeah we were talking before camera you had Splunk back in 2013 and I think 2012 was our first splunk.com and boy man you know talk about being in the right place at the right time now we're at another inflection point and Splunk continues to be relevant um and continuing to have that data driving Security in that interplay and your CEO former CTO of his plug as well at Horizon who's been on before really Innovative product you guys have but you know yeah don't wait for a breach to find out if you're logging the right data this is the topic of this thread Splunk is very much part of this new international expansion announcement uh with you guys tell us what are some of the challenges that you see where this is relevant for the Splunk and Horizon AI as you guys expand uh node zero out internationally yeah well so across so you know my role uh within Splunk it was uh working with our most strategic accounts and so I looked back to 2013 and I think about the sales process like working with with our small customers you know it was um it was still very siled back then like I was selling to an I.T team that was either using this for it operations um we generally would always even say yeah although we do security we weren't really designed for it we're a log management tool and we I'm sure you remember back then John we were like sort of stepping into the security space and and the public sector domain that I was in you know security was 70 of what we did when I look back to sort of uh the transformation that I was witnessing in that digital transformation um you know when I look at like 2019 to today you look at how uh the IT team and the security teams are being have been forced to break down those barriers that they used to sort of be silent away would not commute communicate one you know the security guys would be like oh this is my box I.T you're not allowed in today you can't get away with that and I think that the value that we bring to you know and of course Splunk has been a huge leader in that space and continues to do Innovation across the board but I think what we've we're seeing in the space and I was talking with Patrick Coughlin the SVP of uh security markets about this is that you know what we've been able to do with Splunk is build a purpose-built solution that allows Splunk to eat more data so Splunk itself is ulk know it's an ingest engine right the great reason people bought it was you could build these really fast dashboards and grab intelligence out of it but without data it doesn't do anything right so how do you drive and how do you bring more data in and most importantly from a customer perspective how do you bring the right data in and so if you think about what node zero and what we're doing in a horizon 3 is that sure we do pen testing but because we're an autonomous pen testing tool we do it continuously so this whole thought I'd be like oh crud like my customers oh yeah we got a pen test coming up it's gonna be six weeks the week oh yeah you know and everyone's gonna sit on their hands call me back in two months Chris we'll talk to you then right not not a real efficient way to test your environment and shoot we saw that with Uber this week right um you know and that's a case where we could have helped oh just right we could explain the Uber thing because it was a contractor just give a quick highlight of what happened so you can connect the doctor yeah no problem so um it was uh I got I think it was yeah one of those uh you know games where they would try and test an environment um and with the uh pen tester did was he kept on calling them MFA guys being like I need to reset my password we need to set my right password and eventually the um the customer service guy said okay I'm resetting it once he had reset and bypassed the multi-factor authentication he then was able to get in and get access to the building area that he was in or I think not the domain but he was able to gain access to a partial part of that Network he then paralleled over to what I would assume is like a VA VMware or some virtual machine that had notes that had all of the credentials for logging into various domains and So within minutes they had access and that's the sort of stuff that we do you know a lot of these tools like um you know you think about the cacophony of tools that are out there in a GTA architect architecture right I'm gonna get like a z-scale or I'm going to have uh octum and I have a Splunk I've been into the solar system I mean I don't mean to name names we have crowdstriker or Sentinel one in there it's just it's a cacophony of things that don't work together they weren't designed work together and so we have seen so many times in our business through our customer support and just working with customers when we do their pen tests that there will be 5 000 servers out there three are misconfigured those three misconfigurations will create the open door because remember the hacker only needs to be right once the defender needs to be right all the time and that's the challenge and so that's what I'm really passionate about what we're doing uh here at Horizon three I see this my digital transformation migration and security going on which uh we're at the tip of the spear it's why I joined sey Hall coming on this journey uh and just super excited about where the path's going and super excited about the relationship with Splunk I get into more details on some of the specifics of that but um you know well you're nailing I mean we've been doing a lot of things on super cloud and this next gen environment we're calling it next gen you're really seeing devops obviously devsecops has already won the it role has moved to the developer shift left is an indicator of that it's one of the many examples higher velocity code software supply chain you hear these things that means that it is now in the developer hands it is replaced by the new Ops data Ops teams and security where there's a lot of horizontal thinking to your point about access there's no more perimeter huge 100 right is really right on things one time you know to get in there once you're in then you can hang out move around move laterally big problem okay so we get that now the challenges for these teams as they are transitioning organizationally how do they figure out what to do okay this is the next step they already have Splunk so now they're kind of in transition while protecting for a hundred percent ratio of success so how would you look at that and describe the challenge is what do they do what is it what are the teams facing with their data and what's next what are they what are they what action do they take so let's use some vernacular that folks will know so if I think about devsecops right we both know what that means that I'm going to build security into the app it normally talks about sec devops right how am I building security around the perimeter of what's going inside my ecosystem and what are they doing and so if you think about what we're able to do with somebody like Splunk is we can pen test the entire environment from Soup To Nuts right so I'm going to test the end points through to its I'm going to look for misconfigurations I'm going to I'm going to look for um uh credential exposed credentials you know I'm going to look for anything I can in the environment again I'm going to do it at light speed and and what what we're doing for that SEC devops space is to you know did you detect that we were in your environment so did we alert Splunk or the Sim that there's someone in the environment laterally moving around did they more importantly did they log us into their environment and when do they detect that log to trigger that log did they alert on us and then finally most importantly for every CSO out there is going to be did they stop us and so that's how we we do this and I think you when speaking with um stay Hall before you know we've come up with this um boils but we call it fine fix verifying so what we do is we go in is we act as the attacker right we act in a production environment so we're not going to be we're a passive attacker but we will go in on credentialed on agents but we have to assume to have an assumed breach model which means we're going to put a Docker container in your environment and then we're going to fingerprint the environment so we're going to go out and do an asset survey now that's something that's not something that Splunk does super well you know so can Splunk see all the assets do the same assets marry up we're going to log all that data and think and then put load that into this long Sim or the smoke logging tools just to have it in Enterprise right that's an immediate future ad that they've got um and then we've got the fix so once we've completed our pen test um we are then going to generate a report and we can talk about these in a little bit later but the reports will show an executive summary the assets that we found which would be your asset Discovery aspect of that a fix report and the fixed report I think is probably the most important one it will go down and identify what we did how we did it and then how to fix that and then from that the pen tester or the organization should fix those then they go back and run another test and then they validate like a change detection environment to see hey did those fixes taste play take place and you know snehaw when he was the CTO of jsoc he shared with me a number of times about it's like man there would be 15 more items on next week's punch sheet that we didn't know about and it's and it has to do with how we you know how they were uh prioritizing the cves and whatnot because they would take all CBDs it was critical or non-critical and it's like we are able to create context in that environment that feeds better information into Splunk and whatnot that brings that brings up the efficiency for Splunk specifically the teams out there by the way the burnout thing is real I mean this whole I just finished my list and I got 15 more or whatever the list just can keeps growing how did node zero specifically help Splunk teams be more efficient like that's the question I want to get at because this seems like a very scale way for Splunk customers and teams service teams to be more so the question is how does node zero help make Splunk specifically their service teams be more efficient so so today in our early interactions we're building customers we've seen are five things um and I'll start with sort of identifying the blind spots right so kind of what I just talked about with you did we detect did we log did we alert did they stop node zero right and so I would I put that you know a more Layman's third grade term and if I was going to beat a fifth grader at this game would be we can be the sparring partner for a Splunk Enterprise customer a Splunk Essentials customer someone using Splunk soar or even just an Enterprise Splunk customer that may be a small shop with three people and just wants to know where am I exposed so by creating and generating these reports and then having um the API that actually generates the dashboard they can take all of these events that we've logged and log them in and then where that then comes in is number two is how do we prioritize those logs right so how do we create visibility to logs that that um are have critical impacts and again as I mentioned earlier not all cves are high impact regard and also not all or low right so if you daisy chain a bunch of low cves together boom I've got a mission critical AP uh CPE that needs to be fixed now such as a credential moving to an NT box that's got a text file with a bunch of passwords on it that would be very bad um and then third would be uh verifying that you have all of the hosts so one of the things that splunk's not particularly great at and they'll literate themselves they don't do asset Discovery so dude what assets do we see and what are they logging from that um and then for from um for every event that they are able to identify one of the cool things that we can do is actually create this low code no code environment so they could let you know Splunk customers can use Splunk sword to actually triage events and prioritize that event so where they're being routed within it to optimize the Sox team time to Market or time to triage any given event obviously reducing MTR and then finally I think one of the neatest things that we'll be seeing us develop is um our ability to build glass cables so behind me you'll see one of our triage events and how we build uh a Lockheed Martin kill chain on that with a glass table which is very familiar to the community we're going to have the ability and not too distant future to allow people to search observe on those iocs and if people aren't familiar with it ioc it's an instant of a compromise so that's a vector that we want to drill into and of course who's better at Drilling in the data and smoke yeah this is a critter this is an awesome Synergy there I mean I can see a Splunk customer going man this just gives me so much more capability action actionability and also real understanding and I think this is what I want to dig into if you don't mind understanding that critical impact okay is kind of where I see this coming got the data data ingest now data's data but the question is what not to log you know where are things misconfigured these are critical questions so can you talk about what it means to understand critical impact yeah so I think you know going back to the things that I just spoke about a lot of those cves where you'll see um uh low low low and then you daisy chain together and they're suddenly like oh this is high now but then your other impact of like if you're if you're a Splunk customer you know and I had it I had several of them I had one customer that you know terabytes of McAfee data being brought in and it was like all right there's a lot of other data that you probably also want to bring but they could only afford wanted to do certain data sets because that's and they didn't know how to prioritize or filter those data sets and so we provide that opportunity to say hey these are the critical ones to bring in but there's also the ones that you don't necessarily need to bring in because low cve in this case really does mean low cve like an ILO server would be one that um that's the print server uh where the uh your admin credentials are on on like a printer and so there will be credentials on that that's something that a hacker might go in to look at so although the cve on it is low is if you daisy chain with somebody that's able to get into that you might say Ah that's high and we would then potentially rank it giving our AI logic to say that's a moderate so put it on the scale and we prioritize those versus uh of all of these scanners just going to give you a bunch of CDs and good luck and translating that if I if I can and tell me if I'm wrong that kind of speaks to that whole lateral movement that's it challenge right print serve a great example looks stupid low end who's going to want to deal with the print server oh but it's connected into a critical system there's a path is that kind of what you're getting at yeah I use Daisy Chain I think that's from the community they came from uh but it's just a lateral movement it's exactly what they're doing in those low level low critical lateral movements is where the hackers are getting in right so that's the beauty thing about the uh the Uber example is that who would have thought you know I've got my monthly Factor authentication going in a human made a mistake we can't we can't not expect humans to make mistakes we're fallible right the reality is is once they were in the environment they could have protected themselves by running enough pen tests to know that they had certain uh exposed credentials that would have stopped the breach and they did not had not done that in their environment and I'm not poking yeah but it's an interesting Trend though I mean it's obvious if sometimes those low end items are also not protected well so it's easy to get at from a hacker standpoint but also the people in charge of them can be fished easily or spearfished because they're not paying attention because they don't have to no one ever told them hey be careful yeah for the community that I came from John that's exactly how they they would uh meet you at a uh an International Event um introduce themselves as a graduate student these are National actor States uh would you mind reviewing my thesis on such and such and I was at Adobe at the time that I was working on this instead of having to get the PDF they opened the PDF and whoever that customer was launches and I don't know if you remember back in like 2008 time frame there was a lot of issues around IP being by a nation state being stolen from the United States and that's exactly how they did it and John that's or LinkedIn hey I want to get a joke we want to hire you double the salary oh I'm gonna click on that for sure you know yeah right exactly yeah the one thing I would say to you is like uh when we look at like sort of you know because I think we did 10 000 pen tests last year is it's probably over that now you know we have these sort of top 10 ways that we think and find people coming into the environment the funniest thing is that only one of them is a cve related vulnerability like uh you know you guys know what they are right so it's it but it's it's like two percent of the attacks are occurring through the cves but yeah there's all that attention spent to that and very little attention spent to this pen testing side which is sort of this continuous threat you know monitoring space and and this vulnerability space where I think we play a such an important role and I'm so excited to be a part of the tip of the spear on this one yeah I'm old enough to know the movie sneakers which I loved as a you know watching that movie you know professional hackers are testing testing always testing the environment I love this I got to ask you as we kind of wrap up here Chris if you don't mind the the benefits to Professional Services from this Alliance big news Splunk and you guys work well together we see that clearly what are what other benefits do Professional Services teams see from the Splunk and Horizon 3.ai Alliance so if you're I think for from our our from both of our uh Partners uh as we bring these guys together and many of them already are the same partner right uh is that uh first off the licensing model is probably one of the key areas that we really excel at so if you're an end user you can buy uh for the Enterprise by the number of IP addresses you're using um but uh if you're a partner working with this there's solution ways that you can go in and we'll license as to msps and what that business model on msps looks like but the unique thing that we do here is this C plus license and so the Consulting plus license allows like a uh somebody a small to mid-sized to some very large uh you know Fortune 100 uh consulting firms use this uh by buying into a license called um Consulting plus where they can have unlimited uh access to as many IPS as they want but you can only run one test at a time and as you can imagine when we're going and hacking passwords and um checking hashes and decrypting hashes that can take a while so but for the right customer it's it's a perfect tool and so I I'm so excited about our ability to go to market with uh our partners so that we understand ourselves understand how not to just sell to or not tell just to sell through but we know how to sell with them as a good vendor partner I think that that's one thing that we've done a really good job building bring it into the market yeah I think also the Splunk has had great success how they've enabled uh partners and Professional Services absolutely you know the services that layer on top of Splunk are multi-fold tons of great benefits so you guys Vector right into that ride that way with friction and and the cool thing is that in you know in one of our reports which could be totally customized uh with someone else's logo we're going to generate you know so I I used to work in another organization it wasn't Splunk but we we did uh you know pen testing as for for customers and my pen testers would come on site they'd do the engagement and they would leave and then another release someone would be oh shoot we got another sector that was breached and they'd call you back you know four weeks later and so by August our entire pen testings teams would be sold out and it would be like well even in March maybe and they're like no no I gotta breach now and and and then when they do go in they go through do the pen test and they hand over a PDF and they pack on the back and say there's where your problems are you need to fix it and the reality is that what we're going to generate completely autonomously with no human interaction is we're going to go and find all the permutations of anything we found and the fix for those permutations and then once you've fixed everything you just go back and run another pen test it's you know for what people pay for one pen test they can have a tool that does that every every Pat patch on Tuesday and that's on Wednesday you know triage throughout the week green yellow red I wanted to see the colors show me green green is good right not red and one CIO doesn't want who doesn't want that dashboard right it's it's exactly it and we can help bring I think that you know I'm really excited about helping drive this with the Splunk team because they get that they understand that it's the green yellow red dashboard and and how do we help them find more green uh so that the other guys are in red yeah and get in the data and do the right thing and be efficient with how you use the data know what to look at so many things to pay attention to you know the combination of both and then go to market strategy real brilliant congratulations Chris thanks for coming on and sharing um this news with the detail around the Splunk in action around the alliance thanks for sharing John my pleasure thanks look forward to seeing you soon all right great we'll follow up and do another segment on devops and I.T and security teams as the new new Ops but and super cloud a bunch of other stuff so thanks for coming on and our next segment the CEO of horizon 3.aa will break down all the new news for us here on thecube you're watching thecube the leader in high tech Enterprise coverage [Music] yeah the partner program for us has been fantastic you know I think prior to that you know as most organizations most uh uh most Farmers most mssps might not necessarily have a a bench at all for penetration testing uh maybe they subcontract this work out or maybe they do it themselves but trying to staff that kind of position can be incredibly difficult for us this was a differentiator a a new a new partner a new partnership that allowed us to uh not only perform services for our customers but be able to provide a product by which that they can do it themselves so we work with our customers in a variety of ways some of them want more routine testing and perform this themselves but we're also a certified service provider of horizon 3 being able to perform uh penetration tests uh help review the the data provide color provide analysis for our customers in a broader sense right not necessarily the the black and white elements of you know what was uh what's critical what's high what's medium what's low what you need to fix but are there systemic issues this has allowed us to onboard new customers this has allowed us to migrate some penetration testing services to us from from competitors in the marketplace But ultimately this is occurring because the the product and the outcome are special they're unique and they're effective our customers like what they're seeing they like the routineness of it many of them you know again like doing this themselves you know being able to kind of pen test themselves parts of their networks um and the the new use cases right I'm a large organization I have eight to ten Acquisitions per year wouldn't it be great to have a tool to be able to perform a penetration test both internal and external of that acquisition before we integrate the two companies and maybe bringing on some risk it's a very effective partnership uh one that really is uh kind of taken our our Engineers our account Executives by storm um you know this this is a a partnership that's been very valuable to us [Music] a key part of the value and business model at Horizon 3 is enabling Partners to leverage node zero to make more revenue for themselves our goal is that for sixty percent of our Revenue this year will be originated by partners and that 95 of our Revenue next year will be originated by partners and so a key to that strategy is making us an integral part of your business models as a partner a key quote from one of our partners is that we enable every one of their business units to generate Revenue so let's talk about that in a little bit more detail first is that if you have a pen test Consulting business take Deloitte as an example what was six weeks of human labor at Deloitte per pen test has been cut down to four days of Labor using node zero to conduct reconnaissance find all the juicy interesting areas of the of the Enterprise that are exploitable and being able to go assess the entire organization and then all of those details get served up to the human to be able to look at understand and determine where to probe deeper so what you see in that pen test Consulting business is that node zero becomes a force multiplier where those Consulting teams were able to cover way more accounts and way more IPS within those accounts with the same or fewer consultants and so that directly leads to profit margin expansion for the Penn testing business itself because node 0 is a force multiplier the second business model here is if you're an mssp as an mssp you're already making money providing defensive cyber security operations for a large volume of customers and so what they do is they'll license node zero and use us as an upsell to their mssb business to start to deliver either continuous red teaming continuous verification or purple teaming as a service and so in that particular business model they've got an additional line of Revenue where they can increase the spend of their existing customers by bolting on node 0 as a purple team as a service offering the third business model or customer type is if you're an I.T services provider so as an I.T services provider you make money installing and configuring security products like Splunk or crowdstrike or hemio you also make money reselling those products and you also make money generating follow-on services to continue to harden your customer environments and so for them what what those it service providers will do is use us to verify that they've installed Splunk correctly improved to their customer that Splunk was installed correctly or crowdstrike was installed correctly using our results and then use our results to drive follow-on services and revenue and then finally we've got the value-added reseller which is just a straight up reseller because of how fast our sales Cycles are these vars are able to typically go from cold email to deal close in six to eight weeks at Horizon 3 at least a single sales engineer is able to run 30 to 50 pocs concurrently because our pocs are very lightweight and don't require any on-prem customization or heavy pre-sales post sales activity so as a result we're able to have a few amount of sellers driving a lot of Revenue and volume for us well the same thing applies to bars there isn't a lot of effort to sell the product or prove its value so vars are able to sell a lot more Horizon 3 node zero product without having to build up a huge specialist sales organization so what I'm going to do is talk through uh scenario three here as an I.T service provider and just how powerful node zero can be in driving additional Revenue so in here think of for every one dollar of node zero license purchased by the IT service provider to do their business it'll generate ten dollars of additional revenue for that partner so in this example kidney group uses node 0 to verify that they have installed and deployed Splunk correctly so Kitty group is a Splunk partner they they sell it services to install configure deploy and maintain Splunk and as they deploy Splunk they're going to use node 0 to attack the environment and make sure that the right logs and alerts and monitoring are being handled within the Splunk deployment so it's a way of doing QA or verifying that Splunk has been configured correctly and that's going to be internally used by kidney group to prove the quality of their services that they've just delivered then what they're going to do is they're going to show and leave behind that node zero Report with their client and that creates a resell opportunity for for kidney group to resell node 0 to their client because their client is seeing the reports and the results and saying wow this is pretty amazing and those reports can be co-branded where it's a pen testing report branded with kidney group but it says powered by Horizon three under it from there kidney group is able to take the fixed actions report that's automatically generated with every pen test through node zero and they're able to use that as the starting point for a statement of work to sell follow-on services to fix all of the problems that node zero identified fixing l11r misconfigurations fixing or patching VMware or updating credentials policies and so on so what happens is node 0 has found a bunch of problems the client often lacks the capacity to fix and so kidney group can use that lack of capacity by the client as a follow-on sales opportunity for follow-on services and finally based on the findings from node zero kidney group can look at that report and say to the customer you know customer if you bought crowdstrike you'd be able to uh prevent node Zero from attacking and succeeding in the way that it did for if you bought humano or if you bought Palo Alto networks or if you bought uh some privileged access management solution because of what node 0 was able to do with credential harvesting and attacks and so as a result kidney group is able to resell other security products within their portfolio crowdstrike Falcon humano Polito networks demisto Phantom and so on based on the gaps that were identified by node zero and that pen test and what that creates is another feedback loop where kidney group will then go use node 0 to verify that crowdstrike product has actually been installed and configured correctly and then this becomes the cycle of using node 0 to verify a deployment using that verification to drive a bunch of follow-on services and resell opportunities which then further drives more usage of the product now the way that we licensed is that it's a usage-based license licensing model so that the partner will grow their node zero Consulting plus license as they grow their business so for example if you're a kidney group then week one you've got you're going to use node zero to verify your Splunk install in week two if you have a pen testing business you're going to go off and use node zero to be a force multiplier for your pen testing uh client opportunity and then if you have an mssp business then in week three you're going to use node zero to go execute a purple team mssp offering for your clients so not necessarily a kidney group but if you're a Deloitte or ATT these larger companies and you've got multiple lines of business if you're Optive for instance you all you have to do is buy one Consulting plus license and you're going to be able to run as many pen tests as you want sequentially so now you can buy a single license and use that one license to meet your week one client commitments and then meet your week two and then meet your week three and as you grow your business you start to run multiple pen tests concurrently so in week one you've got to do a Splunk verify uh verify Splunk install and you've got to run a pen test and you've got to do a purple team opportunity you just simply expand the number of Consulting plus licenses from one license to three licenses and so now as you systematically grow your business you're able to grow your node zero capacity with you giving you predictable cogs predictable margins and once again 10x additional Revenue opportunity for that investment in the node zero Consulting plus license my name is Saint I'm the co-founder and CEO here at Horizon 3. I'm going to talk to you today about why it's important to look at your Enterprise Through The Eyes of an attacker the challenge I had when I was a CIO in banking the CTO at Splunk and serving within the Department of Defense is that I had no idea I was Secure until the bad guys had showed up am I logging the right data am I fixing the right vulnerabilities are my security tools that I've paid millions of dollars for actually working together to defend me and the answer is I don't know does my team actually know how to respond to a breach in the middle of an incident I don't know I've got to wait for the bad guys to show up and so the challenge I had was how do we proactively verify our security posture I tried a variety of techniques the first was the use of vulnerability scanners and the challenge with vulnerability scanners is being vulnerable doesn't mean you're exploitable I might have a hundred thousand findings from my scanner of which maybe five or ten can actually be exploited in my environment the other big problem with scanners is that they can't chain weaknesses together from machine to machine so if you've got a thousand machines in your environment or more what a vulnerability scanner will do is tell you you have a problem on machine one and separately a problem on machine two but what they can tell you is that an attacker could use a load from machine one plus a low from machine two to equal to critical in your environment and what attackers do in their tactics is they chain together misconfigurations dangerous product defaults harvested credentials and exploitable vulnerabilities into attack paths across different machines so to address the attack pads across different machines I tried layering in consulting-based pen testing and the issue is when you've got thousands of hosts or hundreds of thousands of hosts in your environment human-based pen testing simply doesn't scale to test an infrastructure of that size moreover when they actually do execute a pen test and you get the report oftentimes you lack the expertise within your team to quickly retest to verify that you've actually fixed the problem and so what happens is you end up with these pen test reports that are incomplete snapshots and quickly going stale and then to mitigate that problem I tried using breach and attack simulation tools and the struggle with these tools is one I had to install credentialed agents everywhere two I had to write my own custom attack scripts that I didn't have much talent for but also I had to maintain as my environment changed and then three these types of tools were not safe to run against production systems which was the the majority of my attack surface so that's why we went off to start Horizon 3. so Tony and I met when we were in Special Operations together and the challenge we wanted to solve was how do we do infrastructure security testing at scale by giving the the power of a 20-year pen testing veteran into the hands of an I.T admin a network engineer in just three clicks and the whole idea is we enable these fixers The Blue Team to be able to run node Zero Hour pen testing product to quickly find problems in their environment that blue team will then then go off and fix the issues that were found and then they can quickly rerun the attack to verify that they fixed the problem and the whole idea is delivering this without requiring custom scripts be developed without requiring credential agents be installed and without requiring the use of external third-party consulting services or Professional Services self-service pen testing to quickly Drive find fix verify there are three primary use cases that our customers use us for the first is the sock manager that uses us to verify that their security tools are actually effective to verify that they're logging the right data in Splunk or in their Sim to verify that their managed security services provider is able to quickly detect and respond to an attack and hold them accountable for their slas or that the sock understands how to quickly detect and respond and measuring and verifying that or that the variety of tools that you have in your stack most organizations have 130 plus cyber security tools none of which are designed to work together are actually working together the second primary use case is proactively hardening and verifying your systems this is when the I that it admin that network engineer they're able to run self-service pen tests to verify that their Cisco environment is installed in hardened and configured correctly or that their credential policies are set up right or that their vcenter or web sphere or kubernetes environments are actually designed to be secure and what this allows the it admins and network Engineers to do is shift from running one or two pen tests a year to 30 40 or more pen tests a month and you can actually wire those pen tests into your devops process or into your detection engineering and the change management processes to automatically trigger pen tests every time there's a change in your environment the third primary use case is for those organizations lucky enough to have their own internal red team they'll use node zero to do reconnaissance and exploitation at scale and then use the output as a starting point for the humans to step in and focus on the really hard juicy stuff that gets them on stage at Defcon and so these are the three primary use cases and what we'll do is zoom into the find fix verify Loop because what I've found in my experience is find fix verify is the future operating model for cyber security organizations and what I mean here is in the find using continuous pen testing what you want to enable is on-demand self-service pen tests you want those pen tests to find attack pads at scale spanning your on-prem infrastructure your Cloud infrastructure and your perimeter because attackers don't only state in one place they will find ways to chain together a perimeter breach a credential from your on-prem to gain access to your cloud or some other permutation and then the third part in continuous pen testing is attackers don't focus on critical vulnerabilities anymore they know we've built vulnerability Management Programs to reduce those vulnerabilities so attackers have adapted and what they do is chain together misconfigurations in your infrastructure and software and applications with dangerous product defaults with exploitable vulnerabilities and through the collection of credentials through a mix of techniques at scale once you've found those problems the next question is what do you do about it well you want to be able to prioritize fixing problems that are actually exploitable in your environment that truly matter meaning they're going to lead to domain compromise or domain user compromise or access your sensitive data the second thing you want to fix is making sure you understand what risk your crown jewels data is exposed to where is your crown jewels data is in the cloud is it on-prem has it been copied to a share drive that you weren't aware of if a domain user was compromised could they access that crown jewels data you want to be able to use the attacker's perspective to secure the critical data you have in your infrastructure and then finally as you fix these problems you want to quickly remediate and retest that you've actually fixed the issue and this fine fix verify cycle becomes that accelerator that drives purple team culture the third part here is verify and what you want to be able to do in the verify step is verify that your security tools and processes in people can effectively detect and respond to a breach you want to be able to integrate that into your detection engineering processes so that you know you're catching the right security rules or that you've deployed the right configurations you also want to make sure that your environment is adhering to the best practices around systems hardening in cyber resilience and finally you want to be able to prove your security posture over a time to your board to your leadership into your regulators so what I'll do now is zoom into each of these three steps so when we zoom in to find here's the first example using node 0 and autonomous pen testing and what an attacker will do is find a way to break through the perimeter in this example it's very easy to misconfigure kubernetes to allow an attacker to gain remote code execution into your on-prem kubernetes environment and break through the perimeter and from there what the attacker is going to do is conduct Network reconnaissance and then find ways to gain code execution on other machines in the environment and as they get code execution they start to dump credentials collect a bunch of ntlm hashes crack those hashes using open source and dark web available data as part of those attacks and then reuse those credentials to log in and laterally maneuver throughout the environment and then as they loudly maneuver they can reuse those credentials and use credential spraying techniques and so on to compromise your business email to log in as admin into your cloud and this is a very common attack and rarely is a CV actually needed to execute this attack often it's just a misconfiguration in kubernetes with a bad credential policy or password policy combined with bad practices of credential reuse across the organization here's another example of an internal pen test and this is from an actual customer they had 5 000 hosts within their environment they had EDR and uba tools installed and they initiated in an internal pen test on a single machine from that single initial access point node zero enumerated the network conducted reconnaissance and found five thousand hosts were accessible what node 0 will do under the covers is organize all of that reconnaissance data into a knowledge graph that we call the Cyber terrain map and that cyber Terrain map becomes the key data structure that we use to efficiently maneuver and attack and compromise your environment so what node zero will do is they'll try to find ways to get code execution reuse credentials and so on in this customer example they had Fortinet installed as their EDR but node 0 was still able to get code execution on a Windows machine from there it was able to successfully dump credentials including sensitive credentials from the lsas process on the Windows box and then reuse those credentials to log in as domain admin in the network and once an attacker becomes domain admin they have the keys to the kingdom they can do anything they want so what happened here well it turns out Fortinet was misconfigured on three out of 5000 machines bad automation the customer had no idea this had happened they would have had to wait for an attacker to show up to realize that it was misconfigured the second thing is well why didn't Fortinet stop the credential pivot in the lateral movement and it turned out the customer didn't buy the right modules or turn on the right services within that particular product and we see this not only with Ford in it but we see this with Trend Micro and all the other defensive tools where it's very easy to miss a checkbox in the configuration that will do things like prevent credential dumping the next story I'll tell you is attackers don't have to hack in they log in so another infrastructure pen test a typical technique attackers will take is man in the middle uh attacks that will collect hashes so in this case what an attacker will do is leverage a tool or technique called responder to collect ntlm hashes that are being passed around the network and there's a variety of reasons why these hashes are passed around and it's a pretty common misconfiguration but as an attacker collects those hashes then they start to apply techniques to crack those hashes so they'll pass the hash and from there they will use open source intelligence common password structures and patterns and other types of techniques to try to crack those hashes into clear text passwords so here node 0 automatically collected hashes it automatically passed the hashes to crack those credentials and then from there it starts to take the domain user user ID passwords that it's collected and tries to access different services and systems in your Enterprise in this case node 0 is able to successfully gain access to the Office 365 email environment because three employees didn't have MFA configured so now what happens is node 0 has a placement and access in the business email system which sets up the conditions for fraud lateral phishing and other techniques but what's especially insightful here is that 80 of the hashes that were collected in this pen test were cracked in 15 minutes or less 80 percent 26 of the user accounts had a password that followed a pretty obvious pattern first initial last initial and four random digits the other thing that was interesting is 10 percent of service accounts had their user ID the same as their password so VMware admin VMware admin web sphere admin web Square admin so on and so forth and so attackers don't have to hack in they just log in with credentials that they've collected the next story here is becoming WS AWS admin so in this example once again internal pen test node zero gets initial access it discovers 2 000 hosts are network reachable from that environment if fingerprints and organizes all of that data into a cyber Terrain map from there it it fingerprints that hpilo the integrated lights out service was running on a subset of hosts hpilo is a service that is often not instrumented or observed by security teams nor is it easy to patch as a result attackers know this and immediately go after those types of services so in this case that ILO service was exploitable and were able to get code execution on it ILO stores all the user IDs and passwords in clear text in a particular set of processes so once we gain code execution we were able to dump all of the credentials and then from there laterally maneuver to log in to the windows box next door as admin and then on that admin box we're able to gain access to the share drives and we found a credentials file saved on a share Drive from there it turned out that credentials file was the AWS admin credentials file giving us full admin authority to their AWS accounts not a single security alert was triggered in this attack because the customer wasn't observing the ILO service and every step thereafter was a valid login in the environment and so what do you do step one patch the server step two delete the credentials file from the share drive and then step three is get better instrumentation on privileged access users and login the final story I'll tell is a typical pattern that we see across the board with that combines the various techniques I've described together where an attacker is going to go off and use open source intelligence to find all of the employees that work at your company from there they're going to look up those employees on dark web breach databases and other forms of information and then use that as a starting point to password spray to compromise a domain user all it takes is one employee to reuse a breached password for their Corporate email or all it takes is a single employee to have a weak password that's easily guessable all it takes is one and once the attacker is able to gain domain user access in most shops domain user is also the local admin on their laptop and once your local admin you can dump Sam and get local admin until M hashes you can use that to reuse credentials again local admin on neighboring machines and attackers will start to rinse and repeat then eventually they're able to get to a point where they can dump lsas or by unhooking the anti-virus defeating the EDR or finding a misconfigured EDR as we've talked about earlier to compromise the domain and what's consistent is that the fundamentals are broken at these shops they have poor password policies they don't have least access privilege implemented active directory groups are too permissive where domain admin or domain user is also the local admin uh AV or EDR Solutions are misconfigured or easily unhooked and so on and what we found in 10 000 pen tests is that user Behavior analytics tools never caught us in that lateral movement in part because those tools require pristine logging data in order to work and also it becomes very difficult to find that Baseline of normal usage versus abnormal usage of credential login another interesting Insight is there were several Marquee brand name mssps that were defending our customers environment and for them it took seven hours to detect and respond to the pen test seven hours the pen test was over in less than two hours and so what you had was an egregious violation of the service level agreements that that mssp had in place and the customer was able to use us to get service credit and drive accountability of their sock and of their provider the third interesting thing is in one case it took us seven minutes to become domain admin in a bank that bank had every Gucci security tool you could buy yet in 7 minutes and 19 seconds node zero started as an unauthenticated member of the network and was able to escalate privileges through chaining and misconfigurations in lateral movement and so on to become domain admin if it's seven minutes today we should assume it'll be less than a minute a year or two from now making it very difficult for humans to be able to detect and respond to that type of Blitzkrieg attack so that's in the find it's not just about finding problems though the bulk of the effort should be what to do about it the fix and the verify so as you find those problems back to kubernetes as an example we will show you the path here is the kill chain we took to compromise that environment we'll show you the impact here is the impact or here's the the proof of exploitation that we were able to use to be able to compromise it and there's the actual command that we executed so you could copy and paste that command and compromise that cubelet yourself if you want and then the impact is we got code execution and we'll actually show you here is the impact this is a critical here's why it enabled perimeter breach affected applications will tell you the specific IPS where you've got the problem how it maps to the miter attack framework and then we'll tell you exactly how to fix it we'll also show you what this problem enabled so you can accurately prioritize why this is important or why it's not important the next part is accurate prioritization the hardest part of my job as a CIO was deciding what not to fix so if you take SMB signing not required as an example by default that CVSs score is a one out of 10. but this misconfiguration is not a cve it's a misconfig enable an attacker to gain access to 19 credentials including one domain admin two local admins and access to a ton of data because of that context this is really a 10 out of 10. you better fix this as soon as possible however of the seven occurrences that we found it's only a critical in three out of the seven and these are the three specific machines and we'll tell you the exact way to fix it and you better fix these as soon as possible for these four machines over here these didn't allow us to do anything of consequence so that because the hardest part is deciding what not to fix you can justifiably choose not to fix these four issues right now and just add them to your backlog and surge your team to fix these three as quickly as possible and then once you fix these three you don't have to re-run the entire pen test you can select these three and then one click verify and run a very narrowly scoped pen test that is only testing this specific issue and what that creates is a much faster cycle of finding and fixing problems the other part of fixing is verifying that you don't have sensitive data at risk so once we become a domain user we're able to use those domain user credentials and try to gain access to databases file shares S3 buckets git repos and so on and help you understand what sensitive data you have at risk so in this example a green checkbox means we logged in as a valid domain user we're able to get read write access on the database this is how many records we could have accessed and we don't actually look at the values in the database but we'll show you the schema so you can quickly characterize that pii data was at risk here and we'll do that for your file shares and other sources of data so now you can accurately articulate the data you have at risk and prioritize cleaning that data up especially data that will lead to a fine or a big news issue so that's the find that's the fix now we're going to talk about the verify the key part in verify is embracing and integrating with detection engineering practices so when you think about your layers of security tools you've got lots of tools in place on average 130 tools at any given customer but these tools were not designed to work together so when you run a pen test what you want to do is say did you detect us did you log us did you alert on us did you stop us and from there what you want to see is okay what are the techniques that are commonly used to defeat an environment to actually compromise if you look at the top 10 techniques we use and there's far more than just these 10 but these are the most often executed nine out of ten have nothing to do with cves it has to do with misconfigurations dangerous product defaults bad credential policies and it's how we chain those together to become a domain admin or compromise a host so what what customers will do is every single attacker command we executed is provided to you as an attackivity log so you can actually see every single attacker command we ran the time stamp it was executed the hosts it executed on and how it Maps the minor attack tactics so our customers will have are these attacker logs on one screen and then they'll go look into Splunk or exabeam or Sentinel one or crowdstrike and say did you detect us did you log us did you alert on us or not and to make that even easier if you take this example hey Splunk what logs did you see at this time on the VMware host because that's when node 0 is able to dump credentials and that allows you to identify and fix your logging blind spots to make that easier we've got app integration so this is an actual Splunk app in the Splunk App Store and what you can come is inside the Splunk console itself you can fire up the Horizon 3 node 0 app all of the pen test results are here so that you can see all of the results in one place and you don't have to jump out of the tool and what you'll show you as I skip forward is hey there's a pen test here are the critical issues that we've identified for that weaker default issue here are the exact commands we executed and then we will automatically query into Splunk all all terms on between these times on that endpoint that relate to this attack so you can now quickly within the Splunk environment itself figure out that you're missing logs or that you're appropriately catching this issue and that becomes incredibly important in that detection engineering cycle that I mentioned earlier so how do our customers end up using us they shift from running one pen test a year to 30 40 pen tests a month oftentimes wiring us into their deployment automation to automatically run pen tests the other part that they'll do is as they run more pen tests they find more issues but eventually they hit this inflection point where they're able to rapidly clean up their environment and that inflection point is because the red and the blue teams start working together in a purple team culture and now they're working together to proactively harden their environment the other thing our customers will do is run us from different perspectives they'll first start running an RFC 1918 scope to see once the attacker gained initial access in a part of the network that had wide access what could they do and then from there they'll run us within a specific Network segment okay from within that segment could the attacker break out and gain access to another segment then they'll run us from their work from home environment could they Traverse the VPN and do something damaging and once they're in could they Traverse the VPN and get into my cloud then they'll break in from the outside all of these perspectives are available to you in Horizon 3 and node zero as a single SKU and you can run as many pen tests as you want if you run a phishing campaign and find that an intern in the finance department had the worst phishing behavior you can then inject their credentials and actually show the end-to-end story of how an attacker fished gained credentials of an intern and use that to gain access to sensitive financial data so what our customers end up doing is running multiple attacks from multiple perspectives and looking at those results over time I'll leave you two things one is what is the AI in Horizon 3 AI those knowledge graphs are the heart and soul of everything that we do and we use machine learning reinforcement techniques reinforcement learning techniques Markov decision models and so on to be able to efficiently maneuver and analyze the paths in those really large graphs we also use context-based scoring to prioritize weaknesses and we're also able to drive collective intelligence across all of the operations so the more pen tests we run the smarter we get and all of that is based on our knowledge graph analytics infrastructure that we have finally I'll leave you with this was my decision criteria when I was a buyer for my security testing strategy what I cared about was coverage I wanted to be able to assess my on-prem cloud perimeter and work from home and be safe to run in production I want to be able to do that as often as I wanted I want to be able to run pen tests in hours or days not weeks or months so I could accelerate that fine fix verify loop I wanted my it admins and network Engineers with limited offensive experience to be able to run a pen test in a few clicks through a self-service experience and not have to install agent and not have to write custom scripts and finally I didn't want to get nickeled and dimed on having to buy different types of attack modules or different types of attacks I wanted a single annual subscription that allowed me to run any type of attack as often as I wanted so I could look at my Trends in directions over time so I hope you found this talk valuable uh we're easy to find and I look forward to seeing seeing you use a product and letting our results do the talking when you look at uh you know kind of the way no our pen testing algorithms work is we dynamically select uh how to compromise an environment based on what we've discovered and the goal is to become a domain admin compromise a host compromise domain users find ways to encrypt data steal sensitive data and so on but when you look at the the top 10 techniques that we ended up uh using to compromise environments the first nine have nothing to do with cves and that's the reality cves are yes a vector but less than two percent of cves are actually used in a compromise oftentimes it's some sort of credential collection credential cracking uh credential pivoting and using that to become an admin and then uh compromising environments from that point on so I'll leave this up for you to kind of read through and you'll have the slides available for you but I found it very insightful that organizations and ourselves when I was a GE included invested heavily in just standard vulnerability Management Programs when I was at DOD that's all disa cared about asking us about was our our kind of our cve posture but the attackers have adapted to not rely on cves to get in because they know that organizations are actively looking at and patching those cves and instead they're chaining together credentials from one place with misconfigurations and dangerous product defaults in another to take over an environment a concrete example is by default vcenter backups are not encrypted and so as if an attacker finds vcenter what they'll do is find the backup location and there are specific V sender MTD files where the admin credentials are parsippled in the binaries so you can actually as an attacker find the right MTD file parse out the binary and now you've got the admin credentials for the vcenter environment and now start to log in as admin there's a bad habit by signal officers and Signal practitioners in the in the Army and elsewhere where the the VM notes section of a virtual image has the password for the VM well those VM notes are not stored encrypted and attackers know this and they're able to go off and find the VMS that are unencrypted find the note section and pull out the passwords for those images and then reuse those credentials across the board so I'll pause here and uh you know Patrick love you get some some commentary on on these techniques and other things that you've seen and what we'll do in the last say 10 to 15 minutes is uh is rolled through a little bit more on what do you do about it yeah yeah no I love it I think um I think this is pretty exhaustive what I like about what you've done here is uh you know we've seen we've seen double-digit increases in the number of organizations that are reporting actual breaches year over year for the last um for the last three years and it's often we kind of in the Zeitgeist we pegged that on ransomware which of course is like incredibly important and very top of mind um but what I like about what you have here is you know we're reminding the audience that the the attack surface area the vectors the matter um you know has to be more comprehensive than just thinking about ransomware scenarios yeah right on um so let's build on this when you think about your defense in depth you've got multiple security controls that you've purchased and integrated and you've got that redundancy if a control fails but the reality is that these security tools aren't designed to work together so when you run a pen test what you want to ask yourself is did you detect node zero did you log node zero did you alert on node zero and did you stop node zero and when you think about how to do that every single attacker command executed by node zero is available in an attacker log so you can now see you know at the bottom here vcenter um exploit at that time on that IP how it aligns to minor attack what you want to be able to do is go figure out did your security tools catch this or not and that becomes very important in using the attacker's perspective to improve your defensive security controls and so the way we've tried to make this easier back to like my my my the you know I bleed Green in many ways still from my smoke background is you want to be able to and what our customers do is hey we'll look at the attacker logs on one screen and they'll look at what did Splunk see or Miss in another screen and then they'll use that to figure out what their logging blind spots are and what that where that becomes really interesting is we've actually built out an integration into Splunk where there's a Splunk app you can download off of Splunk base and you'll get all of the pen test results right there in the Splunk console and from that Splunk console you're gonna be able to see these are all the pen tests that were run these are the issues that were found um so you can look at that particular pen test here are all of the weaknesses that were identified for that particular pen test and how they categorize out for each of those weaknesses you can click on any one of them that are critical in this case and then we'll tell you for that weakness and this is where where the the punch line comes in so I'll pause the video here for that weakness these are the commands that were executed on these endpoints at this time and then we'll actually query Splunk for that um for that IP address or containing that IP and these are the source types that surface any sort of activity so what we try to do is help you as quickly and efficiently as possible identify the logging blind spots in your Splunk environment based on the attacker's perspective so as this video kind of plays through you can see it Patrick I'd love to get your thoughts um just seeing so many Splunk deployments and the effectiveness of those deployments and and how this is going to help really Elevate the effectiveness of all of your Splunk customers yeah I'm super excited about this I mean I think this these kinds of purpose-built integration snail really move the needle for our customers I mean at the end of the day when I think about the power of Splunk I think about a product I was first introduced to 12 years ago that was an on-prem piece of software you know and at the time it sold on sort of Perpetual and term licenses but one made it special was that it could it could it could eat data at a speed that nothing else that I'd have ever seen you can ingest massively scalable amounts of data uh did cool things like schema on read which facilitated that there was this language called SPL that you could nerd out about uh and you went to a conference once a year and you talked about all the cool things you were splunking right but now as we think about the next phase of our growth um we live in a heterogeneous environment where our customers have so many different tools and data sources that are ever expanding and as you look at the as you look at the role of the ciso it's mind-blowing to me the amount of sources Services apps that are coming into the ciso span of let's just call it a span of influence in the last three years uh you know we're seeing things like infrastructure service level visibility application performance monitoring stuff that just never made sense for the security team to have visibility into you um at least not at the size and scale which we're demanding today um and and that's different and this isn't this is why it's so important that we have these joint purpose-built Integrations that um really provide more prescription to our customers about how do they walk on that Journey towards maturity what does zero to one look like what does one to two look like whereas you know 10 years ago customers were happy with platforms today they want integration they want Solutions and they want to drive outcomes and I think this is a great example of how together we are stepping to the evolving nature of the market and also the ever-evolving nature of the threat landscape and what I would say is the maturing needs of the customer in that environment yeah for sure I think especially if if we all anticipate budget pressure over the next 18 months due to the economy and elsewhere while the security budgets are not going to ever I don't think they're going to get cut they're not going to grow as fast and there's a lot more pressure on organizations to extract more value from their existing Investments as well as extracting more value and more impact from their existing teams and so security Effectiveness Fierce prioritization and automation I think become the three key themes of security uh over the next 18 months so I'll do very quickly is run through a few other use cases um every host that we identified in the pen test were able to score and say this host allowed us to do something significant therefore it's it's really critical you should be increasing your logging here hey these hosts down here we couldn't really do anything as an attacker so if you do have to make trade-offs you can make some trade-offs of your logging resolution at the lower end in order to increase logging resolution on the upper end so you've got that level of of um justification for where to increase or or adjust your logging resolution another example is every host we've discovered as an attacker we Expose and you can export and we want to make sure is every host we found as an attacker is being ingested from a Splunk standpoint a big issue I had as a CIO and user of Splunk and other tools is I had no idea if there were Rogue Raspberry Pi's on the network or if a new box was installed and whether Splunk was installed on it or not so now you can quickly start to correlate what hosts did we see and how does that reconcile with what you're logging from uh finally or second to last use case here on the Splunk integration side is for every single problem we've found we give multiple options for how to fix it this becomes a great way to prioritize what fixed actions to automate in your soar platform and what we want to get to eventually is being able to automatically trigger soar actions to fix well-known problems like automatically invalidating passwords for for poor poor passwords in our credentials amongst a whole bunch of other things we could go off and do and then finally if there is a well-known kill chain or attack path one of the things I really wish I could have done when I was a Splunk customer was take this type of kill chain that actually shows a path to domain admin that I'm sincerely worried about and use it as a glass table over which I could start to layer possible indicators of compromise and now you've got a great starting point for glass tables and iocs for actual kill chains that we know are exploitable in your environment and that becomes some super cool Integrations that we've got on the roadmap between us and the Splunk security side of the house so what I'll leave with actually Patrick before I do that you know um love to get your comments and then I'll I'll kind of leave with one last slide on this wartime security mindset uh pending you know assuming there's no other questions no I love it I mean I think this kind of um it's kind of glass table's approach to how do you how do you sort of visualize these workflows and then use things like sore and orchestration and automation to operationalize them is exactly where we see all of our customers going and getting away from I think an over engineered approach to soar with where it has to be super technical heavy with you know python programmers and getting more to this visual view of workflow creation um that really demystifies the power of Automation and also democratizes it so you don't have to have these programming languages in your resume in order to start really moving the needle on workflow creation policy enforcement and ultimately driving automation coverage across more and more of the workflows that your team is seeing yeah I think that between us being able to visualize the actual kill chain or attack path with you know think of a of uh the soar Market I think going towards this no code low code um you know configurable sore versus coded sore that's going to really be a game changer in improve or giving security teams a force multiplier so what I'll leave you with is this peacetime mindset of security no longer is sustainable we really have to get out of checking the box and then waiting for the bad guys to show up to verify that security tools are are working or not and the reason why we've got to really do that quickly is there are over a thousand companies that withdrew from the Russian economy over the past uh nine months due to the Ukrainian War there you should expect every one of them to be punished by the Russians for leaving and punished from a cyber standpoint and this is no longer about financial extortion that is ransomware this is about punishing and destroying companies and you can punish any one of these companies by going after them directly or by going after their suppliers and their Distributors so suddenly your attack surface is no more no longer just your own Enterprise it's how you bring your goods to Market and it's how you get your goods created because while I may not be able to disrupt your ability to harvest fruit if I can get those trucks stuck at the border I can increase spoilage and have the same effect and what we should expect to see is this idea of cyber-enabled economic Warfare where if we issue a sanction like Banning the Russians from traveling there is a cyber-enabled counter punch which is corrupt and destroy the American Airlines database that is below the threshold of War that's not going to trigger the 82nd Airborne to be mobilized but it's going to achieve the right effect ban the sale of luxury goods disrupt the supply chain and create shortages banned Russian oil and gas attack refineries to call a 10x spike in gas prices three days before the election this is the future and therefore I think what we have to do is shift towards a wartime mindset which is don't trust your security posture verify it see yourself Through The Eyes of the attacker build that incident response muscle memory and drive better collaboration between the red and the blue teams your suppliers and Distributors and your information uh sharing organization they have in place and what's really valuable for me as a Splunk customer was when a router crashes at that moment you don't know if it's due to an I.T Administration problem or an attacker and what you want to have are different people asking different questions of the same data and you want to have that integrated triage process of an I.T lens to that problem a security lens to that problem and then from there figuring out is is this an IT workflow to execute or a security incident to execute and you want to have all of that as an integrated team integrated process integrated technology stack and this is something that I very care I cared very deeply about as both a Splunk customer and a Splunk CTO that I see time and time again across the board so Patrick I'll leave you with the last word the final three minutes here and I don't see any open questions so please take us home oh man see how you think we spent hours and hours prepping for this together that that last uh uh 40 seconds of your talk track is probably one of the things I'm most passionate about in this industry right now uh and I think nist has done some really interesting work here around building cyber resilient organizations that have that has really I think helped help the industry see that um incidents can come from adverse conditions you know stress is uh uh performance taxations in the infrastructure service or app layer and they can come from malicious compromises uh Insider threats external threat actors and the more that we look at this from the perspective of of a broader cyber resilience Mission uh in a wartime mindset uh I I think we're going to be much better off and and will you talk about with operationally minded ice hacks information sharing intelligence sharing becomes so important in these wartime uh um situations and you know we know not all ice acts are created equal but we're also seeing a lot of um more ad hoc information sharing groups popping up so look I think I think you framed it really really well I love the concept of wartime mindset and um I I like the idea of applying a cyber resilience lens like if you have one more layer on top of that bottom right cake you know I think the it lens and the security lens they roll up to this concept of cyber resilience and I think this has done some great work there for us yeah you're you're spot on and that that is app and that's gonna I think be the the next um terrain that that uh that you're gonna see vendors try to get after but that I think Splunk is best position to win okay that's a wrap for this special Cube presentation you heard all about the global expansion of horizon 3.ai's partner program for their Partners have a unique opportunity to take advantage of their node zero product uh International go to Market expansion North America channel Partnerships and just overall relationships with companies like Splunk to make things more comprehensive in this disruptive cyber security world we live in and hope you enjoyed this program all the videos are available on thecube.net as well as check out Horizon 3 dot AI for their pen test Automation and ultimately their defense system that they use for testing always the environment that you're in great Innovative product and I hope you enjoyed the program again I'm John Furrier host of the cube thanks for watching

(upbeat music) >> Welcome back, everyone, to theCUBE's coverage here live on the floor at AWS re:MARS 2022. I'm John Furrier, host for theCUBE. Great event, machine learning, automation, robotics, space, that's MARS. It's part of the re-series of events, re:Invent's the big event at the end of the year, re:Inforce, security, re:MARS, really intersection of the future of space, industrial, automation, which is very heavily DevOps machine learning, of course, machine learning, which is AI. We have Luis Ceze here, who's the CEO co-founder of OctoML. Welcome to theCUBE. >> Thank you very much for having me in the show, John. >> So we've been following you guys. You guys are a growing startup funded by Madrona Venture Capital, one of your backers. You guys are here at the show. This is a, I would say small show relative what it's going to be, but a lot of robotics, a lot of space, a lot of industrial kind of edge, but machine learning is the centerpiece of this trend. You guys are in the middle of it. Tell us your story. >> Absolutely, yeah. So our mission is to make machine learning sustainable and accessible to everyone. So I say sustainable because it means we're going to make it faster and more efficient. You know, use less human effort, and accessible to everyone, accessible to as many developers as possible, and also accessible in any device. So, we started from an open source project that began at University of Washington, where I'm a professor there. And several of the co-founders were PhD students there. We started with this open source project called Apache TVM that had actually contributions and collaborations from Amazon and a bunch of other big tech companies. And that allows you to get a machine learning model and run on any hardware, like run on CPUs, GPUs, various GPUs, accelerators, and so on. It was the kernel of our company and the project's been around for about six years or so. Company is about three years old. And we grew from Apache TVM into a whole platform that essentially supports any model on any hardware cloud and edge. >> So is the thesis that, when it first started, that you want to be agnostic on platform? >> Agnostic on hardware, that's right. >> Hardware, hardware. >> Yeah. >> What was it like back then? What kind of hardware were you talking about back then? Cause a lot's changed, certainly on the silicon side. >> Luis: Absolutely, yeah. >> So take me through the journey, 'cause I could see the progression. I'm connecting the dots here. >> So once upon a time, yeah, no... (both chuckling) >> I walked in the snow with my bare feet. >> You have to be careful because if you wake up the professor in me, then you're going to be here for two hours, you know. >> Fast forward. >> The average version here is that, clearly machine learning has shown to actually solve real interesting, high value problems. And where machine learning runs in the end, it becomes code that runs on different hardware, right? And when we started Apache TVM, which stands for tensor virtual machine, at that time it was just beginning to start using GPUs for machine learning, we already saw that, with a bunch of machine learning models popping up and CPUs and GPU's starting to be used for machine learning, it was clear that it come opportunity to run on everywhere. >> And GPU's were coming fast. >> GPUs were coming and huge diversity of CPUs, of GPU's and accelerators now, and the ecosystem and the system software that maps models to hardware is still very fragmented today. So hardware vendors have their own specific stacks. So Nvidia has its own software stack, and so does Intel, AMD. And honestly, I mean, I hope I'm not being, you know, too controversial here to say that it kind of of looks like the mainframe era. We had tight coupling between hardware and software. You know, if you bought IBM hardware, you had to buy IBM OS and IBM database, IBM applications, it all tightly coupled. And if you want to use IBM software, you had to buy IBM hardware. So that's kind of like what machine learning systems look like today. If you buy a certain big name GPU, you've got to use their software. Even if you use their software, which is pretty good, you have to buy their GPUs, right? So, but you know, we wanted to help peel away the model and the software infrastructure from the hardware to give people choice, ability to run the models where it best suit them. Right? So that includes picking the best instance in the cloud, that's going to give you the right, you know, cost properties, performance properties, or might want to run it on the edge. You might run it on an accelerator. >> What year was that roughly, when you were going this? >> We started that project in 2015, 2016 >> Yeah. So that was pre-conventional wisdom. I think TensorFlow wasn't even around yet. >> Luis: No, it wasn't. >> It was, I'm thinking like 2017 or so. >> Luis: Right. So that was the beginning of, okay, this is opportunity. AWS, I don't think they had released some of the nitro stuff that the Hamilton was working on. So, they were already kind of going that way. It's kind of like converging. >> Luis: Yeah. >> The space was happening, exploding. >> Right. And the way that was dealt with, and to this day, you know, to a large extent as well is by backing machine learning models with a bunch of hardware specific libraries. And we were some of the first ones to say, like, know what, let's take a compilation approach, take a model and compile it to very efficient code for that specific hardware. And what underpins all of that is using machine learning for machine learning code optimization. Right? But it was way back when. We can talk about where we are today. >> No, let's fast forward. >> That's the beginning of the open source project. >> But that was a fundamental belief, worldview there. I mean, you have a world real view that was logical when you compare to the mainframe, but not obvious to the machine learning community. Okay, good call, check. Now let's fast forward, okay. Evolution, we'll go through the speed of the years. More chips are coming, you got GPUs, and seeing what's going on in AWS. Wow! Now it's booming. Now I got unlimited processors, I got silicon on chips, I got, everywhere >> Yeah. And what's interesting is that the ecosystem got even more complex, in fact. Because now you have, there's a cross product between machine learning models, frameworks like TensorFlow, PyTorch, Keras, and like that and so on, and then hardware targets. So how do you navigate that? What we want here, our vision is to say, folks should focus, people should focus on making the machine learning models do what they want to do that solves a value, like solves a problem of high value to them. Right? So another deployment should be completely automatic. Today, it's very, very manual to a large extent. So once you're serious about deploying machine learning model, you got a good understanding where you're going to deploy it, how you're going to deploy it, and then, you know, pick out the right libraries and compilers, and we automated the whole thing in our platform. This is why you see the tagline, the booth is right there, like bringing DevOps agility for machine learning, because our mission is to make that fully transparent. >> Well, I think that, first of all, I use that line here, cause I'm looking at it here on live on camera. People can't see, but it's like, I use it on a couple couple of my interviews because the word agility is very interesting because that's kind of the test on any kind of approach these days. Agility could be, and I talked to the robotics guys, just having their product be more agile. I talked to Pepsi here just before you came on, they had this large scale data environment because they built an architecture, but that fostered agility. So again, this is an architectural concept, it's a systems' view of agility being the output, and removing dependencies, which I think what you guys were trying to do. >> Only part of what we do. Right? So agility means a bunch of things. First, you know-- >> Yeah explain. >> Today it takes a couple months to get a model from, when the model's ready, to production, why not turn that in two hours. Agile, literally, physically agile, in terms of walk off time. Right? And then the other thing is give you flexibility to choose where your model should run. So, in our deployment, between the demo and the platform expansion that we announced yesterday, you know, we give the ability of getting your model and, you know, get it compiled, get it optimized for any instance in the cloud and automatically move it around. Today, that's not the case. You have to pick one instance and that's what you do. And then you might auto scale with that one instance. So we give the agility of actually running and scaling the model the way you want, and the way it gives you the right SLAs. >> Yeah, I think Swami was mentioning that, not specifically that use case for you, but that use case generally, that scale being moving things around, making them faster, not having to do that integration work. >> Scale, and run the models where they need to run. Like some day you want to have a large scale deployment in the cloud. You're going to have models in the edge for various reasons because speed of light is limited. We cannot make lights faster. So, you know, got to have some, that's a physics there you cannot change. There's privacy reasons. You want to keep data locally, not send it around to run the model locally. So anyways, and giving the flexibility. >> Let me jump in real quick. I want to ask this specific question because you made me think of something. So we're just having a data mesh conversation. And one of the comments that's come out of a few of these data as code conversations is data's the product now. So if you can move data to the edge, which everyone's talking about, you know, why move data if you don't have to, but I can move a machine learning algorithm to the edge. Cause it's costly to move data. I can move computer, everyone knows that. But now I can move machine learning to anywhere else and not worry about integrating on the fly. So the model is the code. >> It is the product. >> Yeah. And since you said, the model is the code, okay, now we're talking even more here. So machine learning models today are not treated as code, by the way. So do not have any of the typical properties of code that you can, whenever you write a piece of code, you run a code, you don't know, you don't even think what is a CPU, we don't think where it runs, what kind of CPU it runs, what kind of instance it runs. But with machine learning model, you do. So what we are doing and created this fully transparent automated way of allowing you to treat your machine learning models if you were a regular function that you call and then a function could run anywhere. >> Yeah. >> Right. >> That's why-- >> That's better. >> Bringing DevOps agility-- >> That's better. >> Yeah. And you can use existing-- >> That's better, because I can run it on the Artemis too, in space. >> You could, yeah. >> If they have the hardware. (both laugh) >> And that allows you to run your existing, continue to use your existing DevOps infrastructure and your existing people. >> So I have to ask you, cause since you're a professor, this is like a masterclass on theCube. Thank you for coming on. Professor. (Luis laughing) I'm a hardware guy. I'm building hardware for Boston Dynamics, Spot, the dog, that's the diversity in hardware, it's tends to be purpose driven. I got a spaceship, I'm going to have hardware on there. >> Luis: Right. >> It's generally viewed in the community here, that everyone I talk to and other communities, open source is going to drive all software. That's a check. But the scale and integration is super important. And they're also recognizing that hardware is really about the software. And they even said on stage, here. Hardware is not about the hardware, it's about the software. So if you believe that to be true, then your model checks all the boxes. Are people getting this? >> I think they're starting to. Here is why, right. A lot of companies that were hardware first, that thought about software too late, aren't making it. Right? There's a large number of hardware companies, AI chip companies that aren't making it. Probably some of them that won't make it, unfortunately just because they started thinking about software too late. I'm so glad to see a lot of the early, I hope I'm not just doing our own horn here, but Apache TVM, the infrastructure that we built to map models to different hardware, it's very flexible. So we see a lot of emerging chip companies like SiMa.ai's been doing fantastic work, and they use Apache TVM to map algorithms to their hardware. And there's a bunch of others that are also using Apache TVM. That's because you have, you know, an opening infrastructure that keeps it up to date with all the machine learning frameworks and models and allows you to extend to the chips that you want. So these companies pay attention that early, gives them a much higher fighting chance, I'd say. >> Well, first of all, not only are you backable by the VCs cause you have pedigree, you're a professor, you're smart, and you get good recruiting-- >> Luis: I don't know about the smart part. >> And you get good recruiting for PhDs out of University of Washington, which is not too shabby computer science department. But they want to make money. The VCs want to make money. >> Right. >> So you have to make money. So what's the pitch? What's the business model? >> Yeah. Absolutely. >> Share us what you're thinking there. >> Yeah. The value of using our solution is shorter time to value for your model from months to hours. Second, you shrink operator, op-packs, because you don't need a specialized expensive team. Talk about expensive, expensive engineers who can understand machine learning hardware and software engineering to deploy models. You don't need those teams if you use this automated solution, right? Then you reduce that. And also, in the process of actually getting a model and getting specialized to the hardware, making hardware aware, we're talking about a very significant performance improvement that leads to lower cost of deployment in the cloud. We're talking about very significant reduction in costs in cloud deployment. And also enabling new applications on the edge that weren't possible before. It creates, you know, latent value opportunities. Right? So, that's the high level value pitch. But how do we make money? Well, we charge for access to the platform. Right? >> Usage. Consumption. >> Yeah, and value based. Yeah, so it's consumption and value based. So depends on the scale of the deployment. If you're going to deploy machine learning model at a larger scale, chances are that it produces a lot of value. So then we'll capture some of that value in our pricing scale. >> So, you have direct sales force then to work those deals. >> Exactly. >> Got it. How many customers do you have? Just curious. >> So we started, the SaaS platform just launched now. So we started onboarding customers. We've been building this for a while. We have a bunch of, you know, partners that we can talk about openly, like, you know, revenue generating partners, that's fair to say. We work closely with Qualcomm to enable Snapdragon on TVM and hence our platform. We're close with AMD as well, enabling AMD hardware on the platform. We've been working closely with two hyperscaler cloud providers that-- >> I wonder who they are. >> I don't know who they are, right. >> Both start with the letter A. >> And they're both here, right. What is that? >> They both start with the letter A. >> Oh, that's right. >> I won't give it away. (laughing) >> Don't give it away. >> One has three, one has four. (both laugh) >> I'm guessing, by the way. >> Then we have customers in the, actually, early customers have been using the platform from the beginning in the consumer electronics space, in Japan, you know, self driving car technology, as well. As well as some AI first companies that actually, whose core value, the core business come from AI models. >> So, serious, serious customers. They got deep tech chops. They're integrating, they see this as a strategic part of their architecture. >> That's what I call AI native, exactly. But now there's, we have several enterprise customers in line now, we've been talking to. Of course, because now we launched the platform, now we started onboarding and exploring how we're going to serve it to these customers. But it's pretty clear that our technology can solve a lot of other pain points right now. And we're going to work with them as early customers to go and refine them. >> So, do you sell to the little guys, like us? Will we be customers if we wanted to be? >> You could, absolutely, yeah. >> What we have to do, have machine learning folks on staff? >> So, here's what you're going to have to do. Since you can see the booth, others can't. No, but they can certainly, you can try our demo. >> OctoML. >> And you should look at the transparent AI app that's compiled and optimized with our flow, and deployed and built with our flow. That allows you to get your image and do style transfer. You know, you can get you and a pineapple and see how you look like with a pineapple texture. >> We got a lot of transcript and video data. >> Right. Yeah. Right, exactly. So, you can use that. Then there's a very clear-- >> But I could use it. You're not blocking me from using it. Everyone's, it's pretty much democratized. >> You can try the demo, and then you can request access to the platform. >> But you get a lot of more serious deeper customers. But you can serve anybody, what you're saying. >> Luis: We can serve anybody, yeah. >> All right, so what's the vision going forward? Let me ask this. When did people start getting the epiphany of removing the machine learning from the hardware? Was it recently, a couple years ago? >> Well, on the research side, we helped start that trend a while ago. I don't need to repeat that. But I think the vision that's important here, I want the audience here to take away is that, there's a lot of progress being made in creating machine learning models. So, there's fantastic tools to deal with training data, and creating the models, and so on. And now there's a bunch of models that can solve real problems there. The question is, how do you very easily integrate that into your intelligent applications? Madrona Venture Group has been very vocal and investing heavily in intelligent applications both and user applications as well as enablers. So we say an enable of that because it's so easy to use our flow to get a model integrated into your application. Now, any regular software developer can integrate that. And that's just the beginning, right? Because, you know, now we have CI/CD integration to keep your models up to date, to continue to integrate, and then there's more downstream support for other features that you normally have in regular software development. >> I've been thinking about this for a long, long, time. And I think this whole code, no one thinks about code. Like, I write code, I'm deploying it. I think this idea of machine learning as code independent of other dependencies is really amazing. It's so obvious now that you say it. What's the choices now? Let's just say that, I buy it, I love it, I'm using it. Now what do I got to do if I want to deploy it? Do I have to pick processors? Are there verified platforms that you support? Is there a short list? Is there every piece of hardware? >> We actually can help you. I hope we're not saying we can do everything in the world here, but we can help you with that. So, here's how. When you have them all in the platform you can actually see how this model runs on any instance of any cloud, by the way. So we support all the three major cloud providers. And then you can make decisions. For example, if you care about latency, your model has to run on, at most 50 milliseconds, because you're going to have interactivity. And then, after that, you don't care if it's faster. All you care is that, is it going to run cheap enough. So we can help you navigate. And also going to make it automatic. >> It's like tire kicking in the dealer showroom. >> Right. >> You can test everything out, you can see the simulation. Are they simulations, or are they real tests? >> Oh, no, we run all in real hardware. So, we have, as I said, we support any instances of any of the major clouds. We actually run on the cloud. But we also support a select number of edge devices today, like ARMs and Nvidia Jetsons. And we have the OctoML cloud, which is a bunch of racks with a bunch Raspberry Pis and Nvidia Jetsons, and very soon, a bunch of mobile phones there too that can actually run the real hardware, and validate it, and test it out, so you can see that your model runs performant and economically enough in the cloud. And it can run on the edge devices-- >> You're a machine learning as a service. Would that be an accurate? >> That's part of it, because we're not doing the machine learning model itself. You come with a model and we make it deployable and make it ready to deploy. So, here's why it's important. Let me try. There's a large number of really interesting companies that do API models, as in API as a service. You have an NLP model, you have computer vision models, where you call an API and then point in the cloud. You send an image and you got a description, for example. But it is using a third party. Now, if you want to have your model on your infrastructure but having the same convenience as an API you can use our service. So, today, chances are that, if you have a model that you know that you want to do, there might not be an API for it, we actually automatically create the API for you. >> Okay, so that's why I get the DevOps agility for machine learning is a better description. Cause it's not, you're not providing the service. You're providing the service of deploying it like DevOps infrastructure as code. You're now ML as code. >> It's your model, your API, your infrastructure, but all of the convenience of having it ready to go, fully automatic, hands off. >> Cause I think what's interesting about this is that it brings the craftsmanship back to machine learning. Cause it's a craft. I mean, let's face it. >> Yeah. I want human brains, which are very precious resources, to focus on building those models, that is going to solve business problems. I don't want these very smart human brains figuring out how to scrub this into actually getting run the right way. This should be automatic. That's why we use machine learning, for machine learning to solve that. >> Here's an idea for you. We should write a book called, The Lean Machine Learning. Cause the lean startup was all about DevOps. >> Luis: We call machine leaning. No, that's not it going to work. (laughs) >> Remember when iteration was the big mantra. Oh, yeah, iterate. You know, that was from DevOps. >> Yeah, that's right. >> This code allowed for standing up stuff fast, double down, we all know the history, what it turned out. That was a good value for developers. >> I could really agree. If you don't mind me building on that point. You know, something we see as OctoML, but we also see at Madrona as well. Seeing that there's a trend towards best in breed for each one of the stages of getting a model deployed. From the data aspect of creating the data, and then to the model creation aspect, to the model deployment, and even model monitoring. Right? We develop integrations with all the major pieces of the ecosystem, such that you can integrate, say with model monitoring to go and monitor how a model is doing. Just like you monitor how code is doing in deployment in the cloud. >> It's evolution. I think it's a great step. And again, I love the analogy to the mainstream. I lived during those days. I remember the monolithic propriety, and then, you know, OSI model kind of blew it. But that OSI stack never went full stack, and it only stopped at TCP/IP. So, I think the same thing's going on here. You see some scalability around it to try to uncouple it, free it. >> Absolutely. And sustainability and accessibility to make it run faster and make it run on any deice that you want by any developer. So, that's the tagline. >> Luis Ceze, thanks for coming on. Professor. >> Thank you. >> I didn't know you were a professor. That's great to have you on. It was a masterclass in DevOps agility for machine learning. Thanks for coming on. Appreciate it. >> Thank you very much. Thank you. >> Congratulations, again. All right. OctoML here on theCube. Really important. Uncoupling the machine learning from the hardware specifically. That's only going to make space faster and safer, and more reliable. And that's where the whole theme of re:MARS is. Let's see how they fit in. I'm John for theCube. Thanks for watching. More coverage after this short break. >> Luis: Thank you. (gentle music)

>>Everyone welcome back from the cubes coverage here in Las Vegas for Aus re Mars. It's one of the re shows, as we know, reinvent is the big show. Now they have focus, shows reinforces coming up that security Remar is here. Machine learning, automation, robotics, and space. I'm John for your host, Michael Mike Miller here, director of machine learning thought leadership with AWS. Great to see you again. Yeah. Give alumni welcome back here. Back every time we got deep racer, always to talk >>About, Hey John, thanks for having me once again. It's great to be here. I appreciate it. >>So I want to get into the deep racer in context here, but first re Mars is a show. That's getting a lot of buzz, a lot of press. Um, not a lot of news, cuz it's not a newsy show. It's more of a builder kind of a convergence show, but a lot is happening here. It's almost a, a moment in time that I think's gonna be one of those timeless moments where we're gonna look back and saying that year at re Mars was an inflection point. It just seems like everything's pumping machine learning, scaling robotics is hot. It's now transforming fast. Just like the back office data center did years ago. Yeah. And so like a surge is coming. >>Yeah. >>What, what's your take of this show? >>Yeah. And all of these three or four components are all coming together. Right. And they're intersecting rather than just being in silos. Right. So we're seeing machine learning, enabled perception sort of on robots, um, applied to space and sort of these, uh, extra sort of application initiatives. Um, and that's, what's really exciting about this show is seeing all these things come together and all the industry-wide examples, um, of amazing perception and robotics kind of landing together. So, >>So the people out there that aren't yet inside the ropes of the show, what does it mean to them? This show? What, what, what they're gonna be what's in it for me, what's all this show. What does it mean? >>Yeah. It's just a glimpse into where things are headed. Right. And it's sort of the tip of the iceberg. It's sort of the beginning of the wave of, um, you know, these sort of advanced capabilities that we're gonna see imbued in applications, um, across all different industries. >>Awesome. Well, great to have you in the cube. Every time we have an event we wanna bring you on because deep racers become a, the hottest, I won't say cult following because it's no longer cult following. It's become massive following. Um, and which started out as an IOT, I think raspberry pie first time was like a, like >>A, we did a little camera initially camera >>And it was just a kind of a fun, little clever, I won't say hack, but just having a project that just took on a life OFS own, where are we? What's the update with racer you're here with the track. Yeah, >>Possibly >>You got the track and competing with the big dogs, literally dog, you got spot over there. Boston dynamics. >>Well we'll, we'll invite them over to the track later. Yeah. So deep razor, you know, is the fastest way to get hands on with machine learning. You know, we designed it as, uh, a way for developers to have fun while learning about this particular machine learning technique called reinforcement learning, which is all about using, uh, a simulation, uh, to teach the robot how to learn via trial and error. So deep racer includes a 3d racing simulator where you can train your model via trial and error. It includes the physical car. So you can take, uh, the model that you trained in the cloud, download it to this one 18th scale, um, kind of RC car. That's been imbued with an extra sensor. So we have a camera on the front. We've got an extra, uh, Intel, X, 86 processor inside here. Um, and this thing will drive itself, autonomously around the track. And of course what's a track and uh, some cars driving around it without a little competition. So we've got the deep racer league that sort of sits on top of this and adds a little spice to the whole thing. It's >>It's, it's like formula one for nerds. It really is. It's so good because a lot of people will have to readjust their models cuz they go off the track and I see people and it's oh my, then they gotta reset. This has turned into quite the phenomenon and it's fun to watch and every year it gets more competitive. I know you guys have a cut list that reinvent, it's almost like a, a super score gets you up. Yeah. Take, take us through the reinvents coming up. Sure. What's going on with the track there and then we'll get into some of the new adoption in terms of the people. >>Yeah, absolutely. So, uh, you know, we have monthly online races where we have a new track every month that challenges our, our developers to retrain their model or sort of tweak the existing model that they've trained to adapt for those new courses. Then at physical events like here at re Mars and at our AWS summits around the world, we have physical, uh, races. Um, and we crown a champion at each one of those races. You may have heard some cheering a minute ago. Yeah. That was our finals over there. We've got some really fast cars, fast models racing today. Um, so we take the winners from each of those two circuits, the virtual and the physical and they, the top ones of them come together at reinvent every year in November, December. Um, and we have a set of knockout rounds, championship rounds where these guys get the field gets narrowed to 10 racers and then those 10 racers, uh, race to hold up the championship cup and, um, earn, earn, uh, you know, a whole set of prizes, either cash or, or, you know, scholarships or, you know, tuition funds, whatever the, uh, the developer is most interested >>In. You know, I ask you this question every time you come on the cube because I I'm smiling. That's, it's so much fun. I mean, if I had not been with the cube anyway, I'd love to do this. Um, would you ever imagine when you first started this, that it would be such so popular and at the rise of eSports? So, you know, discord is booming. Yeah. The QB has a discord channel now. Sure, sure. Not that good on it yet, but we'll get there, but just the gaming culture, the nerd culture, the robotics clubs, the young people, just nerds who wanna compete. You never thought that would be this big. We, >>We were so surprised by a couple key things after we launched deep racer, you know, we envisioned this as a way for, you know, developers who had already graduated from school. They were in a company they wanted to grow their machine learning skills. Individuals could adopt this. What we saw was individuals were taking these devices and these concepts back to their companies. And they're saying, this is really fun. Like we should do something around this. And we saw companies like JPMC and Accenture and Morningstar into it and national Australia bank all adopting deep racer as a way to engage, excite their employees, but then also create some fun collaboration opportunities. Um, the second thing that was surprising was the interest from students. And it was actually really difficult for students to use deep racer because you needed an AWS account. You had to have a credit card. You might, you might get billed. There was a free tier involved. Um, so what we did this past year was we launched the deep racer student league, um, which caters to students 16 or over in high school or in college, uh, deep Razer student includes 10 hours a month of free training, um, so that they can train their models in the cloud. And of course the same series of virtual monthly events for them to race against each other and win, win prizes. >>So they don't have to go onto the dark web hack someone's credit card, get a proton email account just to get a deep Razer that's right. They can now come in on their own. >>That's right. That's right. They can log into that virtual the virtual environment, um, and get access. And, and one of the other things that we realized, um, and, and that's a common kind of, uh, realization across the industry is both the need for the democratization of machine learning. But also how can we address the skills gap for future ML learners? Um, and this applies to the, the, the world of students kind of engaging. And we said, Hey, you know, um, the world's gonna see the most successful and innovative ideas come from the widest possible range of participants. And so we knew that there were some issues with, um, you know, underserved and underrepresented minorities accessing this technology and getting the ML education to be successful. So we partnered with Intel and Udacity and launched the AI and ML scholarship program this past year. And it's also built on top of deep Bracer student. So now students, um, can register and opt into the scholarship program and we're gonna give out, uh, Udacity scholarships to 2000 students, um, at the end of this year who compete in AWS deep racer student racers, and also go through all of the learning modules online. >>Okay. Hold on, lets back up. Cuz it sounds, this sounds pretty cool. All right. So we kind went fast on that a little bit slow today at the end of the day. So if they sign up for the student account, which is lowered the batteries for, and they Intel and a desk, this is a courseware for the machine learning that's right. So in order to participate, you gotta take some courseware, check the boxes and, and, and Intel is paying for this or you get rewarded with the scholarship after the fact. >>So Intel's a partner of ours in, in putting this on. So it's both, um, helping kind of fund the scholarships for students, but also participating. So for the students who, um, get qualified for the scholarship and, and win one of those 2000 Udacity Nanodegree scholarships, uh, they also will get mentoring opportunities. So AWS and Intel, um, professionals will help mentor these students, uh, give them career advice, give them technical advice. C >>They'll they're getting smarter. Absolutely. So I'm just gonna get to data here. So is it money or credits for the, for the training? >>That's the scholarship or both? Yes. So, so the, the student training is free for students. Yep. They get 10 hours a month, no credits they need to redeem or anything. It's just, you log in and you get your account. Um, then the 2000, uh, Udacity scholarships, those are just scholarships that are awarded to, to the winners of the student, um, scholarship program. It's a four month long, uh, class on Python programming for >>AI so's real education. Yeah. It's like real, real, so ones here's 10 hours. Here's check the box. Here's here's the manual. Yep. >>Everybody gets access to that. That's >>Free. >>Yep. >>To the student over 16. Yes. Free. So that probably gonna increase the numbers. What kind of numbers are you looking at now? Yeah. In terms of scope to scale here for me. Yeah. Scope it >>Out. What's the numbers we've, we've been, uh, pleasantly surprised. We've got over 55,000 students from over 180 countries around the world that have signed up for the deep racer student program and of those over 30,000 have opted into that scholarship program. So we're seeing huge interest, um, from across the globe in, in this virtual students, um, opportunity, you know, and students are taking advantage of those 20 hours of learning. They're taking advantage of the fun, deep racer kind of hands on racing. Um, and obviously a large number of them are also interested in this scholarship opportunity >>Or how many people are in the AWS deep racer, um, group. Now, because now someone's gotta work on this stuff. It's went from a side hustle to like a full initiative. Well, >>You know, we're pretty efficient with what we, you know, we're pretty efficient. You've probably read about the two pizza teams at Amazon. So we keep ourselves pretty streamlined, but we're really proud of, um, what we've been able to bring to the table. And, you know, over those pandemic years, we really focused on that virtual experience in viewing it with those gaming kind of gamification sort of elements. You know, one of the things we did for the students is just like you guys, we have a discord channel, so not only can the students get hands on, but they also have this built in community of other students now to help support them bounce ideas off of and, you know, improve their learning. >>Awesome. So what's next, take us through after this event and what's going on for you more competitions. >>Yeah. So we're gonna be at the remainder of the AWS summits around the world. So places like Mexico city, you know, uh, this week we were in Milan, um, you know, we've got some AWS public sector, um, activities that are happening. Some of those are focused on students. So we've had student events in, um, Ottawa in Canada. We've had a student event in Japan. We've had a student event in, um, Australia, New Zealand. And so we've got events, both for students as well as for the professionals who wanna compete in the league happening around the world. And again, culminating at reinvent. So we'll be back here in Vegas, um, at the beginning of December where our champions will, uh, compete to ho to come. >>So you guys are going to all the summits, absolutely. Most of the summits or >>All of them, anytime there's a physical summit, we'll be there with a track and cars and give developers the opportunity to >>The track is always open. >>Absolutely. All >>Right. Well, thanks for coming on the cube with the update. Appreciate it, >>Mike. Thanks, John. It was great to be >>Here. Pleasure to know you appreciate it. Love that program. All right. Cube coverage here. Deep race are always the hit. It's a fixture at all the events, more exciting than the cube. Some say, but uh, almost great to have you on Mike. Uh, great success. Check it out free to students. The barrier's been lower to get in every robotics club. Every math club, every science club should be signing up for this. Uh, it's a lot of fun and it's cool. And of course you learn machine learning. I mean, come on. There's one to learn that. All right. Cube coverage. Coming back after this short break.

>> The introduction of the modern public cloud in the mid 2000s, permanently changed the way we think about IT. At the heart of it, the cloud operating model attacked one of the biggest problems in enterprise infrastructure, human labor costs. More than half of IT budgets were spent on people, and much of that effort added little or no differentiable value to the business. The automation of provisioning, management, recovery, optimization, and decommissioning infrastructure resources has gone mainstream as organizations demand a cloud-like model across all their application infrastructure, irrespective of its physical location. This has not only cut cost, but it's also improved quality and reduced human error. Hello everyone, my name is Dave Vellante and welcome to Simplifying Hybrid Cloud, made possible by Cisco. Today, we're going to explore Hybrid Cloud as an operating model for organizations. Now the definite of cloud is expanding. Cloud is no longer an abstract set of remote services, you know, somewhere out in the clouds. No, it's an operating model that spans public cloud, on-premises infrastructure, and it's also moving to edge locations. This trend is happening at massive scale. While at the same time, preserving granular control of resources. It's an entirely new game where IT managers must think differently to deal with this complexity. And the environment is constantly changing. The growth and diversity of applications continues. And now, we're living in a world where the workforce is remote. Hybrid work is now a permanent state and will be the dominant model. In fact, a recent survey of CIOs by Enterprise Technology Research, ETR, indicates that organizations expect 36% of their workers will be operating in a hybrid mode. Splitting time between remote work and in office environments. This puts added pressure on the application infrastructure required to support these workers. The underlying technology must be more dynamic and adaptable to accommodate constant change. So the challenge for IT managers is ensuring that modern applications can be run with a cloud-like experience that spans on-prem, public cloud, and edge locations. This is the future of IT. Now today, we have three segments where we're going to dig into these issues and trends surrounding Hybrid Cloud. First up, is DD Dasgupta, who will set the stage and share with us how Cisco is approaching this challenge. Next, we're going to hear from Manish Agarwal and Darren Williams, who will help us unpack HyperFlex which is Cisco's hyperconverged infrastructure offering. And finally, our third segment will drill into Unified Compute. More than a decade ago, Cisco pioneered the concept of bringing together compute with networking in a single offering. Cisco frankly, changed the legacy server market with UCS, Unified Compute System. The X-Series is Cisco's next generation architecture for the coming decade and we'll explore how it fits into the world of Hybrid Cloud, and its role in simplifying the complexity that we just discussed. So, thanks for being here. Let's go. (upbeat music playing) Okay, let's start things off. DD Dasgupta is back on theCUBE to talk about how we're going to simplify Hybrid Cloud complexity. DD welcome, good to see you again. >> Hey Dave, thanks for having me. Good to see you again. >> Yeah, our pleasure. Look, let's start with big picture. Talk about the trends you're seeing from your customers. >> Well, I think first off, every customer these days is a public cloud customer. They do have their on-premise data centers, but, every customer is looking to move workloads, new services, cloud native services from the public cloud. I think that's one of the big things that we're seeing. While that is happening, we're also seeing a pretty dramatic evolution of the application landscape itself. You've got, you know, bare metal applications, you always have virtualized applications, and then most modern applications are containerized, and, you know, managed by Kubernetes. So I think we're seeing a big change in, in the application landscape as well. And, probably, you know, triggered by the first two things that I mentioned, the execution venue of the applications, and then the applications themselves, it's triggering a change in the IT organizations in the development organizations and sort of not only how they work within their organizations, but how they work across all of these different organizations. So I think those are some of the big things that, that I hear about when I talk to customers. >> Well, so it's interesting. I often say Cisco kind of changed the game in server and compute when it developed the original UCS. And you remember there were organizational considerations back then bringing together the server team and the networking team and of course the storage team as well. And now you mentioned Kubernetes, that is a total game changer with regard to whole the application development process. So you have to think about a new strategy in that regard. So how have you evolved your strategy? What is your strategy to help customers simplify, accelerate their hybrid cloud journey in that context? >> No, I think you're right Dave, back to the origins of UCS and we, you know, why did a networking company build a server? Well, we just enabled with the best networking technologies so, would do compute better. And now, doing something similar on the software, actually the managing software for our hyperconvergence, for our, you know, Rack server, for our blade servers. And, you know, we've been on this journey for about four years. The software is called Intersight, and, you know, we started out with Intersight being just the element manager, the management software for Cisco's compute and hyperconverged devices. But then we've evolved it over the last few years because we believe that a customer shouldn't have to manage a separate piece of software, would do manage the hardware, the underlying hardware. And then a separate tool to connect it to a public cloud. And then a third tool to do optimization, workload optimization or performance optimization, or cost optimization. A fourth tool to now manage, you know, Kubernetes and like, not just in one cluster, one cloud, but multi-cluster, multi-cloud. They should not have to have a fifth tool that does, goes into observability anyway. I can go on and on, but you get the idea. We wanted to bring everything onto that same platform that manage their infrastructure. But it's also the platform that enables the simplicity of hybrid cloud operations, automation. It's the same platform on which you can use to manage the, the Kubernetes infrastructure, Kubernetes clusters, I mean, whether it's on-prem or in a cloud. So, overall that's the strategy. Bring it to a single platform, and a platform is a loaded word we'll get into that a little bit, you know, in this conversation, but, that's the overall strategy, simplify. >> Well, you know, you brought platform. I like to say platform beats products, but you know, there was a day, and you could still point to some examples today in the IT industry where, hey, another tool we can monetize that. And another one to solve a different problem, we can monetize that. And so, tell me more about how Intersight came about. You obviously sat back, you saw what your customers were going through, you said, "We can do better." So tell us the story there. >> Yeah, absolutely. So, look, it started with, you know, three or four guys in getting in a room and saying, "Look, we've had this, you know, management software, UCS manager, UCS director." And these are just the Cisco's management, you know, for our, softwares for our own platforms. And every company has their own flavor. We said, we took on this bold goal of like, we're not, when we rewrite this or we improve on this, we're not going to just write another piece of software. We're going to create a cloud service. Or we're going to create a SaaS offering. Because the same, the infrastructure built by us whether it's on networking or compute, or the cyber cloud software, how do our customers use it? Well, they use it to write and run their applications, their SaaS services, every customer, every customer, every company today is a software company. They live and die by how their applications work or don't. And so, we were like, "We want to eat our own dog food here," right? We want to deliver this as a SaaS offering. And so that's how it started, we've being on this journey for about four years, tens of thousands of customers. But it was a pretty big, bold ambition 'cause you know, the big change with SaaS as you're familiar Dave is, the job of now managing this piece of software, is not on the customer, it's on the vendor, right? This can never go down. We have a release every Thursday, new capabilities, and we've learned so much along the way, whether it's to announce scalability, reliability, working with, our own company's security organizations on what can or cannot be in a SaaS service. So again, it's been a wonderful journey, but, I wanted to point out, we are in some ways eating our own dog food 'cause we built a SaaS application that helps other companies deliver their SaaS applications. >> So Cisco, I look at Cisco's business model and I compare, of course compare it to other companies in the infrastructure business and, you're obviously a very profitable company, you're a large company, you're growing faster than most of the traditional competitors. And, so that means that you have more to invest. You, can afford things, like to you know, stock buybacks, and you can invest in R&D you don't have to make those hard trade offs that a lot of your competitors have to make, so-- >> You got to have a talk with my boss on the whole investment. >> Yeah, right. You'd never enough, right? Never enough. But in speaking of R&D and innovations that you're intro introducing, I'm specifically interested in, how are you dealing with innovations to help simplify hybrid cloud, the operations there, improve flexibility, and things around Cloud Native initiatives as well? >> Absolutely, absolutely. Well, look, I think, one of the fundamentals where we're kind of philosophically different from a lot of options that I see in the industry is, we don't need to build everything ourselves, we don't. I just need to create a damn good platform with really good platform services, whether it's, you know, around, searchability, whether it's around logging, whether it's around, you know, access control, multi-tenants. I need to create a really good platform, and make it open. I do not need to go on a shopping spree to buy 17 and 1/2 companies and then figure out how to stich it all together. 'Cause it's almost impossible. And if it's impossible for us as a vendor, it's three times more difficult for the customer who then has to consume it. So that was the philosophical difference and how we went about building Intersight. We've created a hardened platform that's always on, okay? And then you, then the magic starts happening. Then you get partners, whether it is, you know, infrastructure partners, like, you know, some of our storage partners like NetApp or PR, or you know, others, who want their conversion infrastructures also to be managed, or their other SaaS offerings and software vendors who have now become partners. Like we did not write Terraform, you know, but we partnered with Hashi and now, you know, Terraform service's available on the Intersight platform. We did not write all the algorithms for workload optimization between a public cloud and on-prem. We partner with a company called Turbonomic and so that's now an offering on the Intersight platform. So that's where we're philosophically different, in sort of, you know, how we have gone about this. And, it actually dovetails well into, some of the new things that I want to talk about today that we're announcing on the Intersight platform where we're actually announcing the ability to attach and be able to manage Kubernetes clusters which are not on-prem. They're actually on AWS, on Azure, soon coming on GC, on GKE as well. So it really doesn't matter. We're not telling a customer if you're comfortable building your applications and running Kubernetes clusters on, you know, in AWS or Azure, stay there. But in terms of monitoring, managing it, you can use Intersight, and since you're using it on-prem you can use that same piece of software to manage Kubernetes clusters in a public cloud. Or even manage DMS in a EC2 instance. So. >> Yeah so, the fact that you could, you mentioned Storage Pure, NetApp, so Intersight can manage that infrastructure. I remember the Hashi deal and I, it caught my attention. I mean, of course a lot of companies want to partner with Cisco 'cause you've got such a strong ecosystem, but I thought that was an interesting move, Turbonomic you mentioned. And now you're saying Kubernetes in the public cloud. So a lot different than it was 10 years ago. So my last question is, how do you see this hybrid cloud evolving? I mean, you had private cloud and you had public cloud, and it was kind of a tug of war there. We see these two worlds coming together. How will that evolve on for the next few years? >> Well, I think it's the evolution of the model and I, really look at Cloud, you know, 2.0 or 3.0, or depending on, you know, how you're keeping terms. But, I think one thing has become very clear again, we, we've be eating our own dog food, I mean, Intersight is a hybrid cloud SaaS application. So we've learned some of these lessons ourselves. One thing is for sure that the customers are looking for a consistent model, whether it's on the edge, on the COLO, public cloud, on-prem, no data center, it doesn't matter. They're looking for a consistent model for operations, for governance, for upgrades, for reliability. They're looking for a consistent operating model. What (indistinct) tells me I think there's going to be a rise of more custom clouds. It's still going to be hybrid, so applications will want to reside wherever it most makes most sense for them which is obviously data, 'cause you know, data is the most expensive thing. So it's going to be complicated with the data goes on the edge, will be on the edge, COLO, public cloud, doesn't matter. But, you're basically going to see more custom clouds, more industry specific clouds, you know, whether it's for finance, or transportation, or retail, industry specific, I think sovereignty is going to play a huge role, you know, today, if you look at the cloud provider there's a handful of, you know, American and Chinese companies, that leave the rest of the world out when it comes to making, you know, good digital citizens of their people and you know, whether it's data latency, data gravity, data sovereignty, I think that's going to play a huge role. Sovereignty's going to play a huge role. And the distributor cloud also called Edge, is going to be the next frontier. And so, that's where we are trying line up our strategy. And if I had to sum it up in one sentence, it's really, your cloud, your way. Every customer is on a different journey, they will have their choice of like workloads, data, you know, upgrade reliability concern. That's really what we are trying to enable for our customers. >> You know, I think I agree with you on that custom clouds. And I think what you're seeing is, you said every company is a software company. Every company is also becoming a cloud company. They're building their own abstraction layers, they're connecting their on-prem to their public cloud. They're doing that across clouds, and they're looking for companies like Cisco to do the hard work, and give me an infrastructure layer that I can build value on top of. 'Cause I'm going to take my financial services business to my cloud model, or my healthcare business. I don't want to mess around with, I'm not going to develop, you know, custom infrastructure like an Amazon does. I'm going to look to Cisco and your R&D to do that. Do you buy that? >> Absolutely. I think again, it goes back to what I was talking about with platform. You got to give the world a solid open, flexible platform. And flexible in terms of the technology, flexible in how they want to consume it. Some of our customers are fine with the SaaS, you know, software. But if I talk to, you know, my friends in the federal team, no, that does not work. And so, how they want to consume it, they want to, you know, (indistinct) you know, sovereignty we talked about. So, I think, you know, job for an infrastructure vendor like ourselves is to give the world a open platform, give them the knobs, give them the right API tool kit. But the last thing I will mention is, you know, there's still a place for innovation in hardware. And I think some of my colleagues are going to get into some of those, you know, details, whether it's on our X-Series, you know, platform or HyperFlex, but it's really, it's going to be software defined, it's a SaaS service and then, you know, give the world an open rock solid platform. >> Got to run on something All right, Thanks DD, always a pleasure to have you on the, theCUBE, great to see you. >> Thanks for having me. >> You're welcome. In a moment, I'll be back to dig into hyperconverged, and where HyperFlex fits, and how it may even help with addressing some of the supply chain challenges that we're seeing in the market today. >> It used to be all your infrastructure was managed here. But things got more complex in distributing, and now IT operations need to be managed everywhere. But what if you could manage everywhere from somewhere? One scalable place that brings together your teams, technology, and operations. Both on-prem and in the cloud. One automated place that provides full stack visibility to help you optimize performance and stay ahead of problems. One secure place where everyone can work better, faster, and seamlessly together. That's the Cisco Intersight cloud operations platform. The time saving, cost reducing, risk managing solution for your whole IT environment, now and into the future of this ever-changing world of IT. (upbeat music) >> With me now are Manish Agarwal, senior director of product management for HyperFlex at Cisco, @flash4all, number four, I love that, on Twitter. And Darren Williams, the director of business development and sales for Cisco. MrHyperFlex, @MrHyperFlex on Twitter. Thanks guys. Hey, we're going to talk about some news and HyperFlex, and what role it plays in accelerating the hybrid cloud journey. Gentlemen, welcome to theCUBE, good to see you. >> Thanks a lot Dave. >> Thanks Dave. >> All right Darren, let's start with you. So, for a hybrid cloud, you got to have on-prem connection, right? So, you got to have basically a private cloud. What are your thoughts on that? >> Yeah, we agree. You can't have a hybrid cloud without that prime element. And you've got to have a strong foundation in terms of how you set up the whole benefit of the cloud model you're building in terms of what you want to try and get back from the cloud. You need a strong foundation. Hyperconversions provides that. We see more and more customers requiring a private cloud, and they're building it with Hyperconversions, in particular HyperFlex. Now to make all that work, they need a good strong cloud operations model to be able to connect both the private and the public. And that's where we look at Intersight. We've got solution around that to be able to connect that around a SaaS offering. That looks around simplified operations, gives them optimization, and also automation to bring both private and public together in that hybrid world. >> Darren let's stay with you for a minute. When you talk to your customers, what are they thinking these days when it comes to implementing hyperconverged infrastructure in both the enterprise and at the edge, what are they trying to achieve? >> So there's many things they're trying to achieve, probably the most brutal honesty is they're trying to save money, that's probably the quickest answer. But, I think they're trying to look in terms of simplicity, how can they remove layers of components they've had before in their infrastructure? We see obviously collapsing of storage into hyperconversions and storage networking. And we've got customers that have saved 80% worth of savings by doing that collapse into a hyperconversion infrastructure away from their Three Tier infrastructure. Also about scalability, they don't know the end game. So they're looking about how they can size for what they know now, and how they can grow that with hyperconvergence very easy. It's one of the major factors and benefits of hyperconversions. They also obviously need performance and consistent performance. They don't want to compromise performance around their virtual machines when they want to run multiple workloads. They need that consistency all all way through. And then probably one of the biggest ones is that around the simplicity model is the management layer, ease of management. To make it easier for their operations, yeah, we've got customers that have told us, they've saved 50% of costs in their operations model on deploying HyperFlex, also around the time savings they make massive time savings which they can reinvest in their infrastructure and their operations teams in being able to innovate and go forward. And then I think probably one of the biggest pieces we've seen as people move away from three tier architecture is the deployment elements. And the ease of deployment gets easy with hyperconverged, especially with Edge. Edge is a major key use case for us. And, what I want, what our customers want to do is get the benefit of a data center at the edge, without A, the big investment. They don't want to compromise in performance, and they want that simplicity in both management and deployment. And, we've seen our analysts recommendations around what their readers are telling them in terms of how management deployment's key for our IT operations teams. And how much they're actually saving by deploying Edge and taking the burden away when they deploy hyperconversions. And as I said, the savings elements is the key bit, and again, not always, but obviously those are case studies around about public cloud being quite expensive at times, over time for the wrong workloads. So by bringing them back, people can make savings. And we again have customers that have made 50% savings over three years compared to their public cloud usage. So, I'd say that's the key things that customers are looking for. Yeah. >> Great, thank you for that Darren. Manish, we have some hard news, you've been working a lot on evolving the HyperFlex line. What's the big news that you've just announced? >> Yeah, thanks Dave. So there are several things that we are announcing today. The first one is a new offer called HyperFlex Express. This is, you know, Cisco Intersight led and Cisco Intersight managed eight HyperFlex configurations. That we feel are the fastest path to hybrid cloud. The second is we are expanding our server portfolio by adding support for HX on AMD Rack, UCS AMD Rack. And the third is a new capability that we are introducing, that we are calling, local containerized witness. And let me take a minute to explain what this is. This is a pretty nifty capability to optimize for Edge environments. So, you know, this leverages the, Cisco's ubiquitous presence of the networking, you know, products that we have in the environments worldwide. So the smallest HyperFlex configuration that we have is a 2-node configuration, which is primarily used in Edge environments. Think of a, you know, a backroom in a departmental store or a oil rig, or it might even be a smaller data center somewhere around the globe. For these 2-node configurations, there is always a need for a third entity that, you know, industry term for that is either a witness or an arbitrator. We had that for HyperFlex as well. And the problem that customers face is, where you host this witness. It cannot be on the cluster because the job of the witness is to, when the infrastructure is going down, it basically breaks, sort of arbitrates which node gets to survive. So it needs to be outside of the cluster. But finding infrastructure to actually host this is a problem, especially in the Edge environments where these are resource constraint environments. So what we've done is we've taken that witness, we've converted it into a container reform factor. And then qualified a very large slew of Cisco networking products that we have, right from ISR, ASR, Nexus, Catalyst, industrial routers, even a Raspberry Pi that can host this witness. Eliminating the need for you to find yet another piece of infrastructure, or doing any, you know, care and feeding of that infrastructure. You can host it on something that already exists in the environment. So those are the three things that we are announcing today. >> So I want to ask you about HyperFlex Express. You know, obviously the whole demand and supply chain is out of whack. Everybody's, you know, global supply chain issues are in the news, everybody's dealing with it. Can you expand on that a little bit more? Can HyperFlex Express help customers respond to some of these issues? >> Yeah indeed Dave. You know the primary motivation for HyperFlex Express was indeed an idea that, you know, one of the folks are on my team had, which was to build a set of HyperFlex configurations that are, you know, would have a shorter lead time. But as we were brainstorming, we were actually able to tag on multiple other things and make sure that, you know, there is in it for, something in it for our customers, for sales, as well as our partners. So for example, you know, for our customers, we've been able to dramatically simplify the configuration and the install for HyperFlex Express. These are still HyperFlex configurations and you would at the end of it, get a HyperFlex cluster. But the part to that cluster is much, much simplified. Second is that we've added in flexibility where you can now deploy these, these are data center configurations, but you can deploy these with or without fabric interconnects, meaning you can deploy with your existing top of rack. We've also, you know, added attractive price point for these, and of course, you know, these will have better lead times because we've made sure that, you know, we are using components that are, that we have clear line of sight from our supply perspective. For partner and sales, this is, represents a high velocity sales motion, a faster turnaround time, and a frictionless sales motion for our distributors. This is actually a set of disty-friendly configurations, which they would find very easy to stalk, and with a quick turnaround time, this would be very attractive for the distys as well. >> It's interesting Manish, I'm looking at some fresh survey data, more than 70% of the customers that were surveyed, this is the ETR survey again, we mentioned 'em at the top. More than 70% said they had difficulty procuring server hardware and networking was also a huge problem. So that's encouraging. What about, Manish, AMD? That's new for HyperFlex. What's that going to give customers that they couldn't get before? >> Yeah Dave, so, you know, in the short time that we've had UCS AMD Rack support, we've had several record making benchmark results that we've published. So it's a powerful platform with a lot of performance in it. And HyperFlex, you know, the differentiator that we've had from day one is that it has the industry leading storage performance. So with this, we are going to get the fastest compute, together with the fastest storage. And this, we are hoping that we'll, it'll basically unlock, you know, a, unprecedented level of performance and efficiency, but also unlock several new workloads that were previously locked out from the hyperconverged experience. >> Yeah, cool. So Darren, can you give us an idea as to how HyperFlex is doing in the field? >> Sure, absolutely. So, both me and Manish been involved right from the start even before it was called HyperFlex, and we've had a great journey. And it's very exciting to see where we are taking, where we've been with the technology. So we have over 5,000 customers worldwide, and we're currently growing faster year over year than the market. The majority of our customers are repeat buyers, which is always a good sign in terms of coming back when they've proved the technology and are comfortable with the technology. They, repeat buyer for expanded capacity, putting more workloads on. They're using different use cases on there. And from an Edge perspective, more numbers of science. So really good endorsement of the technology. We get used across all verticals, all segments, to house mission critical applications, as well as the traditional virtual server infrastructures. And we are the lifeblood of our customers around those, mission critical customers. I think one big example, and I apologize for the worldwide audience, but this resonates with the American audience is, the Super Bowl. So, the SoFi stadium that housed the Super Bowl, actually has Cisco HyperFlex running all the management services, through from the entire stadium for digital signage, 4k video distribution, and it's completely cashless. So, if that were to break during Super Bowl, that would've been a big news article. But it was run perfectly. We, in the design of the solution, we're able to collapse down nearly 200 servers into a few nodes, across a few racks, and have 120 virtual machines running the whole stadium, without missing a heartbeat. And that is mission critical for you to run Super Bowl, and not be on the front of the press afterwards for the wrong reasons, that's a win for us. So we really are, really happy with HyperFlex, where it's going, what it's doing, and some of the use cases we're getting involved in, very, very exciting. >> Hey, come on Darren, it's Super Bowl, NFL, that's international now. And-- >> Thing is, I follow NFL. >> The NFL's, it's invading London, of course, I see the, the picture, the real football over your shoulder. But, last question for Manish. Give us a little roadmap, what's the future hold for HyperFlex? >> Yeah. So, you know, as Darren said, both Darren and I have been involved with HyperFlex since the beginning. But, I think the best is yet to come. There are three main pillars for HyperFlex. One is, Intersight is central to our strategy. It provides a, you know, lot of customer benefit from a single pane of class management. But we are going to take this beyond the lifecycle management, which is for HyperFlex, which is integrated into Intersight today, and element management. We are going to take it beyond that and start delivering customer value on the dimensions of AI Ops, because Intersight really provides us a ideal platform to gather stats from all the clusters across the globe, do AI/ML and do some predictive analysis with that, and return back as, you know, customer valued, actionable insights. So that is one. The second is UCS expand the HyperFlex portfolio, go beyond UCS to third party server platforms, and newer UCS server platforms as well. But the highlight there is one that I'm really, really excited about and think that there is a lot of potential in terms of the number of customers we can help. Is HX on X-Series. X-Series is another thing that we are going to, you know, add, we're announcing a bunch of capabilities on in this particular launch. But HX on X-Series will have that by the end of this calendar year. And that should unlock with the flexibility of X-Series of hosting a multitude of workloads and the simplicity of HyperFlex. We're hoping that would bring a lot of benefits to new workloads that were locked out previously. And then the last thing is HyperFlex data platform. This is the heart of the offering today. And, you'll see the HyperFlex data platform itself it's a distributed architecture, a unique distributed architecture. Primarily where we get our, you know, record baring performance from. You'll see it can foster more scalable, more resilient, and we'll optimize it for you know, containerized workloads, meaning it'll get granular containerized, container granular management capabilities, and optimize for public cloud. So those are some things that we are, the team is busy working on, and we should see that come to fruition. I'm hoping that we'll be back at this forum in maybe before the end of the year, and talking about some of these newer capabilities. >> That's great. Thank you very much for that, okay guys, we got to leave it there. And you know, Manish was talking about the HX on X-Series that's huge, customers are going to love that and it's a great transition 'cause in a moment, I'll be back with Vikas Ratna and Jim Leach, and we're going to dig into X-Series. Some real serious engineering went into this platform, and we're going to explore what it all means. You're watching Simplifying Hybrid Cloud on theCUBE, your leader in enterprise tech coverage. >> The power is here, and here, but also here. And definitely here. Anywhere you need the full force and power of your infrastructure hyperconverged. It's like having thousands of data centers wherever you need them, powering applications anywhere they live, but manage from the cloud. So you can automate everything from here. (upbeat music) Cisco HyperFlex goes anywhere. Cisco, the bridge to possible. (upbeat music) >> Welcome back to theCUBE's special presentation, Simplifying Hybrid Cloud brought to you by Cisco. We're here with Vikas Ratna who's the director of product management for UCS at Cisco and James Leach, who is director of business development at Cisco. Gents, welcome back to theCUBE, good to see you again. >> Hey, thanks for having us. >> Okay, Jim, let's start. We know that when it comes to navigating a transition to hybrid cloud, it's a complicated situation for a lot of customers, and as organizations as they hit the pavement for their hybrid cloud journeys, what are the most common challenges that they face? What are they telling you? How is Cisco, specifically UCS helping them deal with these problems? >> Well, you know, first I think that's a, you know, that's a great question. And you know, customer centric view is the way that we've taken, is kind of the approach we've taken from day one. Right? So I think that if you look at the challenges that we're solving for that our customers are facing, you could break them into just a few kind of broader buckets. The first would definitely be applications, right? That's the, that's where the rubber meets your proverbial road with the customer. And I would say that, you know, what we're seeing is, the challenges customers are facing within applications come from the the way that applications have evolved. So what we're seeing now is more data centric applications for example. Those require that we, you know, are able to move and process large data sets really in real time. And the other aspect of applications I think to give our customers kind of some, you know, pause some challenges, would be around the fact that they're changing so quickly. So the application that exists today or the day that they, you know, make a purchase of infrastructure to be able to support that application, that application is most likely changing so much more rapidly than the infrastructure can keep up with today. So, that creates some challenges around, you know, how do I build the infrastructure? How do I right size it without over provisioning, for example? But also, there's a need for some flexibility around life cycle and planning those purchase cycles based on the life cycle of the different hardware elements. And within the infrastructure, which I think is the second bucket of challenges, we see customers who are being forced to move away from the, like a modular or blade approach, which offers a lot of operational and consolidation benefits, and they have to move to something like a Rack server model for some applications because of these needs that these data centric applications have, and that creates a lot of you know, opportunity for siloing the infrastructure. And those silos in turn create multiple operating models within the, you know, a data center environment that, you know, again, drive a lot of complexity. So that, complexity is definitely the enemy here. And then finally, I think life cycles. We're seeing this democratization of processing if you will, right? So it's no longer just CPU focused, we have GPU, we have FPGA, we have, you know, things that are being done in storage and the fabrics that stitch them together that are all changing rapidly and have very different life cycles. So, when those life cycles don't align for a lot of our customers, they see a challenge in how they can manage this, you know, these different life cycles and still make a purchase without having to make too big of a compromise in one area or another because of the misalignment of life cycles. So, that is a, you know, kind of the other bucket. And then finally, I think management is huge, right? So management, you know, at its core is really right size for our customers and give them the most value when it meets the mark around scale and scope. You know, back in 2009, we weren't meeting that mark in the industry and UCS came about and took management outside the chassis, right? We put it at the top of the rack and that worked great for the scale and scope we needed at that time. However, as things have changed, we're seeing a very new scale and scope needed, right? So we're talking about a hybrid cloud world that has to manage across data centers, across clouds, and, you know, having to stitch things together for some of our customers poses a huge challenge. So there are tools for all of those operational pieces that touch the application, that touch the infrastructure, but they're not the same tool. They tend to be disparate tools that have to be put together. >> Right. >> So our customers, you know, don't really enjoy being in the business of, you know, building their own tools, so that creates a huge challenge. And one where I think that they really crave that full hybrid cloud stack that has that application visibility but also can reach down into the infrastructure. >> Right. You know Jim, I said in my open that you guys, Cisco sort of changed the server game with the original UCS, but the X-Series is the next generation, the generation for the next decade which is really important 'cause you touched on a lot of things, these data intensive workload, alternative processors to sort of meet those needs. The whole cloud operating model and hybrid cloud has really changed. So, how's it going with with the X-Series? You made a big splash last year, what's the reception been in the field? >> Actually, it's been great. You know, we're finding that customers can absolutely relate to our, you know, UCS X-Series story. I think that, you know, the main reason they relate to it is they helped create it, right? It was their feedback and their partnership that gave us really the, those problem areas, those areas that we could solve for the customer that actually add, you know, significant value. So, you know, since we brought UCS to market back in 2009, you know, we had this unique architectural paradigm that we created, and I think that created a product which was the fastest in Cisco history in terms of growth. What we're seeing now is X-Series is actually on a faster trajectory. So we're seeing a tremendous amount of uptake. We're seeing all, you know, both in terms of, you know, the number of customers, but also more importantly, the number of workloads that our customers are using, and the types of workloads are growing, right? So we're growing this modular segment that exist, not just, you know, bringing customers onto a new product, but we're actually bring them into the product in the way that we had envisioned, which is one infrastructure that can run any application and do it seamlessly. So we're really excited to be growing this modular segment. I think the other piece, you know, that, you know, we judge ourselves is, you know, sort of not just within Cisco, but also within the industry. And I think right now is a, you know, a great example, you know, our competitors have taken kind of swings and misses over the past five years at this, at a, you know, kind of the new next architecture. And, we're seeing a tremendous amount of growth even faster than any of our competitors have seen when they announced something that was new to this space. So, I think that the ground up work that we did is really paying off. And I think that what we're also seeing is it's not really a leap frog game, as it may have been in the past. X-Series is out in front today, and, you know, we're extending that lead with some of the new features and capabilities we have. So we're delivering on the story that's already been resonating with customers and, you know, we're pretty excited that we're seeing the results as well. So, as our competitors hit walls, I think we're, you know, we're executing on the plan that we laid out back in June when we launched X-Series to the world. And, you know, as we continue to do that, we're seeing, you know, again, tremendous uptake from our customers. >> So thank you for that Jim. So Vikas, I was just on Twitter just today actually talking about the gravitational pull, you've got the public clouds pulling CXOs one way and you know, on-prem folks pulling the other way and hybrid cloud. So, organizations are struggling with a lot of different systems and architectures and ways to do things. And I said that what they're trying to do is abstract all that complexity away and they need infrastructure to support that. And I think your stated aim is really to try to help with that confusion with the X series, right? I mean, so how so can you explain that? >> Sure. And, that's the right, the context that you built up right there Dave. If you walk into enterprise data center you'll see plethora of compute systems spread all across. Because, every application has its unique needs, and, hence you find drive node, drive-dense system, memory dense system, GPU dense system, core dense system, and variety of form factors, 1U, 2U, 4U, and, every one of them typically come with, you know, variety of adapters and cables and so forth. This creates the siloness of resources. Fabric is (indistinct), the adapter is (indistinct). The power and cooling implication. The Rack, you know, face challenges. And, above all, the multiple management plane that they come up with, which makes it very difficult for IT to have one common center policy, and enforce it all across, across the firmware and software and so forth. And then think about upgrade challenges of the siloness makes it even more complex as these go through the upgrade processes of their own. As a result, we observe quite a few of our customers, you know, really seeing an inter, slowness in that agility, and high burden in the cost of overall ownership. This is where with the X-Series powered by Intersight, we have one simple goal. We want to make sure our customers get out of that complexities. They become more agile, and drive lower TCOs. And we are delivering it by doing three things, three aspects of simplification. First, simplify their whole infrastructure by enabling them to run their entire workload on single infrastructure. An infrastructure which removes the siloness of form factor. An infrastructure which reduces the Rack footprint that is required. An infrastructure where power and cooling budgets are in the lower. Second, we want to simplify by delivering a cloud operating model, where they can and create the policy once across compute network storage and deploy it all across. And third, we want to take away the pain they have by simplifying the process of upgrade and any platform evolution that they're going to go through in the next two, three years. So that's where the focus is on just driving down the simplicity, lowering down their TCOs. >> Oh, that's key, less friction is always a good thing. Now, of course, Vikas we heard from the HyperFlex guys earlier, they had news not to be outdone. You have hard news as well. What innovations are you announcing around X-Series today? >> Absolutely. So we are following up on the exciting X-Series announcement that we made in June last year, Dave. And we are now introducing three innovation on X-Series with the goal of three things. First, expand the supported workload on X-Series. Second, take the performance to new levels. Third, dramatically reduce the complexities in the data center by driving down the number of adapters and cables that are needed. To that end, three new innovations are coming in. First, we are introducing the support for the GPU node using a cableless and very unique X-Fabric architecture. This is the most elegant design to add the GPUs to the compute node in the modular form factor. Thereby, our customers can now power in AI/ML workload, or any workload that need many more number of GPUs. Second, we are bringing in GPUs right onto the compute node, and thereby our customers can now fire up the accelerated VDI workload for example. And third, which is what you know, we are extremely proud about, is we are innovating again by introducing the fifth generation of our very popular unified fabric technology. With the increased bandwidth that it brings in, coupled with the local drive capacity and densities that we have on the compute node, our customers can now fire up the big data workload, the FCI workload, the SDS workload. All these workloads that have historically not lived in the modular form factor, can be run over there and benefit from the architectural benefits that we have. Second, with the announcement of fifth generation fabric, we've become the only vendor to now finally enable 100 gig end to end single port bandwidth, and there are multiple of those that are coming in there. And we are working very closely with our CI partners to deliver the benefit of these performance through our Cisco Validated Design to our CI franchise. And third, the innovations in the fifth gen fabric will again allow our customers to have fewer physical adapters made with ethernet adapter, made with power channel adapters, or made with, the other storage adapters. They've reduced it down and coupled with the reduction in the cable. So very, very excited about these three big announcements that we are making in this month's release. >> Great, a lot there, you guys have been busy, so thank you for that Vikas. So, Jim, you talked a little bit about the momentum that you have, customers are adopting, what problems are they telling you that X-Series addresses, and how do they align with where they want to go in the future? >> That's a great question. I think if you go back to, and think about some of the things that we mentioned before, in terms of the problems that we originally set out to solve, we're seeing a lot of traction. So what Vikas mentioned I think is really important, right? Those pieces that we just announced really enhance that story and really move again, to the, kind of, to the next level of taking advantage of some of these, you know, problem solving for our customers. You know, if you look at, you know, I think Vikas mentioned accelerated VDI. That's a great example. These are where customers, you know, they need to have this dense compute, they need video acceleration, they need tight policy management, right? And they need to be able to deploy these systems anywhere in the world. Well, that's exactly what we're hitting on here with X-Series right now. We're hitting the market in every single way, right? We have the highest compute config density that we can offer across the, you know, the very top end configurations of CPUs, and a lot of room to grow. We have the, you know, the premier cloud based management, you know, hybrid cloud suite in the industry, right? So check there. We have the flexible GPU accelerators that Vikas just talked about that we're announcing both on the system and also adding additional ones to the, through the use of the X-Fabric, which is really, really critical to this launch as well. And, you know, I think finally, the fifth generation of fabric interconnect and virtual interface card, and, intelligent fabric module go hand in hand in creating this 100 gig end to end bandwidth story, that we can move a lot of data. Again, you know, having all this performance is only as good as what we can get in and out of it, right? So giving customers the ability to manage it anywhere, to be able to get the bandwidth that they need, to be able to get the accelerators that are flexible that it fit exactly their needs, this is huge, right? This solves a lot of the problems we can tick off right away. With the infrastructure as I mentioned, X-Fabric is really critical here because it opens a lot of doors here, you know, we're talking about GPUs today, but in the future, there are other elements that we can disaggregate, like the GPUs that solve these life cycle mismanagement issues. They solve issues around the form factor limitations. It solves all these issues for like, it does for GPU we can do that with storage or memory in the future. So that's going to be huge, right? This is disaggregation that actually delivers, right? It's not just a gimmicky bar trick here that we're doing, this is something that customers can really get value out of day one. And then finally, I think the, you know, the future readiness here, you know, we avoid saying future proof because we're kind of embracing the future here. We know that not only are the GPUs going to evolve, the CPUs are going to evolve, the drives, you know, the storage modules are going to evolve. All of these things are changing very rapidly. The fabric that stitches them together is critical, and we know that we're just on the edge of some of the development that are coming with CXL, with some of the PCI Express changes that are coming in the very near future, so we're ready to go. And the X-Fabric is exactly the vehicle that's going to be able to deliver those technologies to our customers, right? Our customers are out there saying that, you know, they want to buy into to something like X-Series that has all the operational benefits, but at the same time, they have to have the comfort in knowing that they're protected against being locked out of some technology that's coming in the future, right? We want our customers to take these disruptive technologies and not be disrupted, but use them to disrupt their competition as well. So, you know, we're really excited about the pieces today, and, I think it goes a long way towards continuing to tell the customer benefit story that X-Series brings, and, you know, again, you know, stay tuned because it's going to keep getting better as we go. >> Yeah, a lot of headroom for scale and the management piece is key there. Just have time for one more question Vikas. Give us some nuggets on the roadmap. What's next for X-Series that we can look forward to? >> Absolutely Dave. As we talked about, and as Jim also hinted, this is a future ready architecture. A lot of focus and innovation that we are going through is about enabling our customers to seamlessly and painlessly adopt very disruptive hardware technologies that are coming up, no refund replace. And, there we are looking into, enabling the customer's journey as they transition from PCI generation four, to five to six without driven replace, as they embrace CXL without driven replace. As they embrace the newer paradigm of computing through the disaggregated memory, disaggregated PCIe or NVMe based dense drives, and so forth. We are also looking forward to X-Fabric next generation, which will allow dynamic assignment of GPUs anywhere within the chassis and much more. So this is again, all about focusing on the innovation that will make the enterprise data center operations a lot more simpler, and drive down the TCO by keeping them not only covered for today, but also for future. So that's where some of the focus is on Dave. >> Okay. Thank you guys we'll leave it there, in a moment, I'll have some closing thoughts. (upbeat music) We're seeing a major evolution, perhaps even a bit of a revolution in the underlying infrastructure necessary to support hybrid work. Look, virtualizing compute and running general purpose workloads is something IT figured out a long time ago. But just when you have it nailed down in the technology business, things change, don't they? You can count on that. The cloud operating model has bled into on-premises locations. And is creating a new vision for the future, which we heard a lot about today. It's a vision that's turning into reality. And it supports much more diverse and data intensive workloads and alternative compute modes. It's one where flexibility is a watch word, enabling change, attacking complexity, and bringing a management capability that allows for a granular management of resources at massive scale. I hope you've enjoyed this special presentation. Remember, all these videos are available on demand at thecube.net. And if you want to learn more, please click on the information link. Thanks for watching Simplifying Hybrid Cloud brought to you by Cisco and theCUBE, your leader in enterprise tech coverage. This is Dave Vellante, be well and we'll see you next time. (upbeat music)

>>mhm. >>With me now are Manish Agarwal, senior director of product management for Hyper Flex at Cisco at Flash for all number four. Love that on Twitter And Deron Williams, the director of business development and sales for Cisco Mister Hyper flex at Mr Hyper Flex on Twitter. Thanks, guys. Hey, we're going to talk about some news and and hyper flex and what role it plays in accelerating the hybrid cloud journey. Gentlemen, welcome to the Cube. Good to see you. >>Thanks, David. >>Thanks. Hi, >>Daryn. Let's start with you. So for hybrid cloud you gotta have on Prem Connection. Right? So you've got to have basically a private cloud. What are your thoughts on that? >>Yeah, we agree. You can't, but you can't have a hybrid cloud without that private element. And you've got to have a strong foundation in terms of how you set up the whole benefit of the cloud model you're building in terms of what you want to try and get back from the cloud, you need a strong foundation. I'm conversions provides that we see more and more customers requiring a private cloud, and they're building with hyper convergence in particular hyper flex no to make all that work. They need a good, strong Cloud operations model to be able to connect both the private and the public. And that's where we look at insight. We've got solution around that. To be able to connect that around a Saas offering that looks around simplified operations, gives them optimisation and also automation to bring both private and public together in that hybrid world. >>Darren, let's stay with you for a minute when you talk to your customers. What are they thinking these days, when it comes to implementing hyper converged infrastructure in both the the enterprise and and at the edge? What are they trying to achieve? >>So there's many things they're trying to achieve? Probably the most brutal honesty is they're trying to save money. That's probably the quickest answer, but I think they're trying to look at in terms of simplicity. How can they remove layers of components they've had before in their infrastructure? We see obviously collapsing of storage into hyper conversions and storage networking, and we've got customers that have saved 80% worth of savings by doing that, a collapse into hyper conversion infrastructure away from their three tier infrastructure. Also about scalability. They don't know the end game, so they're looking about how they can size for what they know now and how they can grow that with hyper conversions. Very easy is one of the major factors and benefits of hyper conversions. They also obviously need performance and consistent performance. They don't want to compromise performance around their virtual machines when they want to run multiple workloads. They need that consistency all the way through. And then probably one of the biggest ones is that around. The simplicity model is the management layer ease of management to make it easier for their operations that we've got customers that have told us they've saved 50% of costs in their operations model, deploying out flex also around the time savings. They make massive time savings which they can reinvest in their infrastructure and their operations teams in being able to innovate and go forward. And then I think that we one of the biggest pieces we've seen as people move away from three tier architecture is the deployment elements, and the ease of deployment gets easy with hyper converged, especially with edge edges of major key use case for us and what I want. What our customers want to do is get the benefit of the data centre at the edge without a big investment. They don't compromise in performance, and they want that simplicity in both management employment. And we've seen analysts recommendations around what their readers are telling them in terms of how management deployments key for it, operations teams and how much they're actually saving by deploying edge and taking the burden away when they deployed hyper conversions. As I said, the savings elements to keep it and again, not always, but obviously those are his studies around about public Cloud being quite expensive at times over time for the wrong workloads. So by bringing them back, people can make savings. We again have customers that have made 50% savings over three years compared to their public cloud usage. So I'd say that's the key things that customers looking for >>Great. Thank you for that, Darrin minutes. We have some hard news. You've been working a lot on evolving the hyper flex line. What's the big news that you've just announced? >>Yeah, Thanks. Leave. So there are several things that we are announcing today. the first one is a new offer, um, called hyper Flex Express. This is, you know, Cisco Inter site lead and Cisco and decide managed it Hyper flex configurations that we feel are the fastest part to hybrid cloud. The second is we're expanding our server portfolio by adding support for HX on AM Iraq, U. C s and Iraq. And the third is a new capability that we're introducing that we're calling local contemporaries witness. And let me take a minute to explain what this is. This is a very nifty capability to optimise for forage environments. So, you know, this leverages the Ciscos ubiquitous presence. Uh, the networking, um, you know, products that we have in the environments worldwide. So the smallest hyper flex configuration that we have is, uh it do not configuration, which is primarily used in edge environment. Think of a, you know, a back home in a department store or a oil rig. Or it might even be a smaller data centre, uh, somewhere, uh, on the globe. For these two not configurations. There is always a need for a third entity that, you know, industry term for that is either a witness or an arbitrator. Uh, we had that for hyper flex as well. The problem that customers faces where you host this witness it cannot be on the cluster because it's the job of the witnesses to when the when the infrastructure is going down, it basically breaks, um, sort of upgrade rates. Which note gets to survive, so it needs to be outside of the cluster. But finding infrastructure, uh, to actually host this is a problem, especially in the edge environments where these are resource constrained environment. So what we've done is we've taken that witness. We've converted it into a container reform factor and then qualified a very large a slew of Cisco networking products that we have right from S. R. S R. Texas catalyst, industrial routers, even even a raspberry pi that can host host this witness, eliminating the need for you to find yet another piece of infrastructure or doing any, um, you know, care and feeding of that infrastructure. You can host it on something that already exists in the environment. So those are the three things that we're announcing today. >>So I want to ask you about hyper Flex Express. You know, obviously the whole demand and supply chain is out of whack. Everybody's global supply chain issues are in the news. Everybody's dealing with it. Can you expand on that? A little bit more Can can hyper flex express help customers respond to some of these issues. >>Yeah, indeed. The, uh, you know, the primary motivation for hyper Flex Express was indeed, uh, an idea that, you know, one of the folks around my team had, which was to build a set of hyper flex configurations that are, you know, would have a shorter lead time. But as we were brainstorming, we were actually able to tag on multiple other things and make sure that, you know, there is in it for something in it for customers, for sales as well as our partners. So, for example, you know, for customers, we've been able to dramatically simplify the configuration and the instal for hyper flex express. These are still hypertext configurations, and you would, at the end of it, get a hyper flex cluster. But the part to that cluster is much much simplifying. Second is that we've added in flexibility where you can now deploy these, uh, these are data centre configurations But you can deploy these with or without fabric interconnects, meaning you can deploy it with your existing top of rack. Um, we've also, you know, already attract attractive price point for these. And of course, you know these will have better lead times because we made sure that, you know, we are using components that are that we have clear line of sight from a supply perspective for partner and sales. This is represents a high velocity sales motion, a faster turnaround time, Uh, and a frictionless sales motion for our distributors. Uh, this is actually a settled, risky, friendly configurations, which they would find very easy to stalk and with a quick turnaround time, this would be very attractive for the deceased as well. >>It's interesting many. So I'm looking at some fresh survey data. More than 70% of the customers that were surveyed this GTR survey again mentioned at the top. More than 70% said they had difficulty procuring, uh, server hardware and networking was also a huge problem. So so that's encouraging. What about Manisha AMG that's new for hyper flex? What's that going to give customers that they couldn't get before? >>Yeah, so you know, in the short time that we've had UCS am direct support, we've had several record breaking benchmark results that we've published. So it's a it's a It's a powerful platform with a lot of performance in it and hyper flex. Uh, you know, the differentiator that we've had from Day one is that it is. It has the industry leading storage performance. So with this, we're going to get the fastest compute together with the fastest storage and this we are hoping that will basically unlock, you know, a unprecedented level of performance and efficiency, but also unlock several new workloads that were previously locked out from the hyper converged experience. >>Yeah, cool. Uh, so, Darren, can >>you can you give us >>an idea as to how hyper flexes is doing in the field? >>Sure, Absolutely So both me and my initial been involved right from the start and before it was called Hyper Flex, and we've had a great journey, and it's very excited to see where we're taking where we've been with the technology. So we have over 5000 customers worldwide, and we're currently growing faster year over year than the market. The majority of our customers are repeat buyers, which is always a good sign in terms of coming back when they approved the technology and are comfortable with technology. They repeat by for expanding capacity, putting more workloads on. They're using different use cases on there. And from an energy perspective, more numbers of science so really good. Endorsement the technology. We get used across all verticals or segments, um, to house mission critical applications as well as the traditional virtual server infrastructures. Uh, and we are the lifeblood of our customers around those mission critical customers think one example, and I apologise for the worldwide audience. But this resonates with the American audiences the Super Bowl. So the sofa like stadium that housed the Super Bowl actually has Cisco hyper Flex running all the management services through from the entire stadium for digital signage. Four K video distribution, and it's complete completely cashless. So if that were to break during Super Bowl, that would have been a big, uh, news article, but it was run perfectly. We in the design of the solution, we're able to collapse down nearly 200 servers into a few notes across a few racks and have 100 120 virtual machines running the whole stadium without missing a heartbeat. And that is mission critical for you to run Super Bowl and not be on the front of the press afterwards for the wrong reasons. That's a win for us. So we really are really happy with High Flex where it's going, what it's doing. And some of the use cases were getting involved in very, very excited. >>Come on, Darren. It's Super Bowl NFL. That's a That's international now. And, you know, the NFL >>NFL. It's >>invading London. Of course I see the picture of the real football over your shoulder, But last question for many is give us a little roadmap. What's the future hold for hyper flex? >>Yeah, so you know, as Darren said, both Darren and I have been involved the type of flicks since the beginning, Uh, but I think the best is yet to come. There are three main pillars for for hyper Flex. One is in. The site is central to our strategy. It provides a lot of customer benefit from a single pane of glass management. But we're going to take this beyond the Lifecycle management, which is for hyper flex, which is integrated in winter side today and element management. We're going to take it beyond that and start delivering customer value on the dimensions of a job. Because Interstate really provides us an ideal platform to gather starts from all the clusters across the globe. Do AML and do some predictive analysis with that and return it back as, uh, you know, customer valued, um, actionable insights. So that is one. The second is you'll see us expand the hyper flex portfolio. Go beyond you see us to third party server platforms, and newer, you see a server platforms as well. But the highlight there is one that I'm really really excited about and think that there is a lot of potential in terms of the number of customers we can help is a checks on X CDs. Experience is another thing that we're able to, uh you know, uh, announcing a bunch of capabilities on in this particular launch. But a check sonic series. We'll have that by the end of this calendar year, and that should unlock with the flexibility of X series of hosting a multitude of workloads and the simplicity of hyper flex. We're hoping that would bring a lot of benefits to new workloads, that we're locked out previously. And then the last thing is hyper flex leader platform. This is the heart of the offering today, Uh, and you'll see the hyper flex data platform itself. It's a distributed architecture, unique distributed architecture primarily where we get our, you know, record breaking performance from you'll see it get faster, more scalable, more resilient. And we'll optimise it for, you know, containerised workloads, meaning it will get granular containerised container granular management capabilities and optimised for public. So those are some things that were the team is busy working on, and we should see that come to fruition. I'm hoping that we'll be back at this forum and maybe before the end of the year and talking about some of these new capabilities. >>That's great. Thank you very much for that. Okay, guys, we got to leave it there and you know many She was talking about the HX on X Series. That's huge. Customers are gonna love that, and it's a great transition because in a moment I'll be back with Vikas Ratna and Jim Leach and we're gonna dig into X series. Some real serious engineering went into this platform, and we're gonna explore what it all means. You're watching simplifying hybrid cloud on the cube, your leader in enterprise tech coverage.

>>Mhm. Yes. Hello. Welcome back to the cubes coverage of dr khan 2021 virtual. I'm john for your host of the cube. We're messing my fair principal technologist at AWS amazon Web services messman. Thank you for coming on the cube, appreciate it. Um >>Thank you. Thank you for having me. >>Great to see you love this amazon integration with doctor want to get into that in a second. Um Been great to see the amazon cloud native integration working well. E. C. S very popular. Every interview I've done at reinvent uh every year it gets better and better more adoption every year. Um Tell us what's going on with amazon E. C. S because you have Pcs anywhere and now that's being available. >>Yeah that's fine, that's correct, join and uh yeah so customers has been appreciating the value and the simplicity of VCS for many years now. I mean we we launched GCS back in 2014 and we have seen great adoption of the product and customers has always been appreciating. Uh the fact that it was easy to operate and easy to use. Uh This is a journey with the CS anywhere that started a few years ago actually. And we started this journey uh listening to customers that had particular requirements. Um I'd like to talk about, you know, the the law of the land and the law um uh of the physic where customers wanted to go all in into uh into the cloud, but they did have this exception that they need to uh deal with with the application that could not move to the cloud. So as I said, this journey started three years ago when we launched outpost. Um and outpost is our managed infrastructure that customers can deploy in their own data centers. And we supported Pcs on day one on outpost. Um having that said, there are lots of customers that came to us and said we love outputs but there are certain applications and certain requirements, uh such as compliance or the fact simply that we have like assets that we need to reuse in our data center uh that we want to use and before we move into into the cloud. So they were asking us, we love the simplicity of Vcs but we have to use gears that we have in our data center. That is when we started thinking about Pcs anywhere. So basically the idea of VCS anywhere is that you can use e c s E C as part of that, you know, and love um uh appreciated the simplicity of using Pcs but using your customer managed infrastructure as the data plane, basically what you could do is you can define your application within the Ec. S country plane and deploy those applications on customer own um infrastructure. What that means from a very practical perspective is that you can deploy this application on your managed infrastructure ranging from uh raspberry pis this is the demo that we show the invent when we pronounce um e c s anywhere all the way up to bare metal server, we don't really care about the infrastructure underneath. As long as it supported, the OS is supported. Um we're fine with that. >>Okay, so let's take this to the next level and actually the big theme at dr Connors developer experience, you know, that's kind of want to talk about that and obviously developer productivity and innovation have to go hand in hand. You don't want to stunt the innovation equation, which is cloud, native and scale. Right. So how does the developer experience improve with amazon ECs and anywhere now that I'm on, on premises or in the cloud? Can you take me through? What's the improvements around pcs and the developer? >>Yeah I would argue that the the what you see as anywhere solved is more for operational aspect and the requirements that more that are more akin to the operation team that that they need to meet. Uh We're working very hard to um to improve the developing experience on top of the CS beyond what we're doing with the CS anywhere. So um I'd like to step back a little bit and maybe tell a little bit of a story of why we're working on those things. So um the customer as I said before, continue to appreciate the simplicity and the easier views of E. C. S. However what we learn um over the years is that as we added more features to E. C. S, we ended up uh leveraging more easy. Um AWS services um example uh would be a load balancer integration or secret manager or Fc. Or um other things like service discovery that uses underneath other AWS products like um clubman for around 53. And what happened is that the end user experience, the developer experience became a little bit more complicated because now customers opportunity easy of use of these fully managed services. However they were responsible for time and watering all uh together in the application definition. So what we're working on to simplify this experience is we're working on tools that kind of abstract these um this verbal city that you get with pcs. Um uh An example is a confirmation template that a developer we need to use uh to deploy an application leveraging all of these features. Could then could end up being uh many hundreds of transformation lines um in the in the in the definition of the service. So we're working on new tools and new capabilities to make this experience better. Uh Some of them are C d k uh the copilot cli, dws, copilot cli those are all instruments and technologies and tools that we're building to abstract that um uh verbosity that I was alluding to and this is where actually also the doctor composed integration with the CS falls in. >>Yeah, I'm just gonna ask you that the doctor piece because actually it's dr khan all the developers love containers, they love what they do. Um This is a native, you know, mindset of shifting left with security. How is the relationship with the Docker container ecosystem going with you guys? Can you take him in to explain for the folks here watching this event and participating in the community, explain the relationship with Docker container specifically. >>Yeah, absolutely. Uh so basically we started working with dR many, many years ago, um uh Pcs was based on on DR technology when we launch it. Uh and it's still using uh DR technology and last year we started to collaborate with dR more closely um when DR releases the doctor composed specification um as an open source projects. So basically doctor is trying to use the doctor composed specification to create uh infrastructure product gnostic, uh way to deploy Docker application um uh using those specification in multiple infrastructure as part of these journey, we work with dr to support pcs as a back end um for um for the specification, basically what this means from a very practical perspective, is that you can take a doctor composed an existing doctor composed file. Um and doctor says that there are 650,000 doctor composed files spread across the top and all um uh lose control uh system um over the world. And basically you can take those doctor composed file and uh composed up and deploy transparently um into E. C. S Target on AWS. So basically if we go back to what I was alluding to before, the fact that the developer would need to author many 100 line of confirmation template to be able to take their application and deploy it into the cloud. What they need to do now is um offering a new file, a um a file uh with a very clear and easy to use dr composed syntax composed up and deploy automatically on AWS. Um and using Pcs Fargate um and many other AWS services in the back end. >>And what's the expectation in your mind as you guys look at the container service to anywhere model the on premise and without post, what does he what's the vision? Because that's again, another question mark for me, it's like, okay, I get it totally makes sense. Um, but containers are showing the mainstream enterprises, not the hyper skills. You guys always been kind of the forward thinkers, but you know, main street enterprise, I call it. They're picking up adoption of containers in a massive way. They're looking at cloud native specifically as the place for modern application development period. That's happening. What's the story? Say it again? Because I want to make sure I get this right e C s anywhere if I want to get on premises hybrid, What's it mean for me? >>Uh, this goes back to what I was saying at the beginning. So there are there are there when we have been discussing here are mostly to or token of things. Right. So the fact that we enable these big enterprises to meet their requirements and meet their um their um checkboxes sometimes to be able to deploy outside of AWS when there is a need to do that. This could be for edge use cases or for um using years that exist in the data center. So this is where e c s anywhere is basically trying, this is what uh pcs anywhere is trying to address. There is another orthogonal discussion which is developer experience, uh and that development experience is being addressed by these additional tools. Um what I like to say is that uh the confirmation is becoming a little bit like assembler in a sense, right? It's becoming very low level, super powerful, but very low level and we want to abstract and bring the experience to the next level and make it simple for developers to leverage the simplicity of some of these tools including Docker compose um and and and being able to deploy into the cloud um and getting all the benefits of the cloud scalability, electricity and security. >>I love the assembler analogy because you think about it. A lot of the innovation has been kind of like low level foundational and if you start to see all the open source activity and the customers, the tooling does matter. And I think that's where the ease of use comes in. So the simplicity totally makes sense. Um can you give an example of some simplicity piece? Because I think, you know, you guys, you know, look at looking at ec. S as the cornerstone for simplicity. I get that. Can you give an example to walk us through a day in the life of of an example >>uh in an example of simplicity? Yeah, supposedly in action. Yeah. Well, one of the examples that I usually do and there is this uh, notion of being served less and I think that there is a little bit of a, of an obsession around surveillance and trying to talk about surveillance for so many things. When I talk about the C. S, I like to use another moniker that is version less. So to me, simplicity also means that I do not have to um update my service. Right? So the way E C. S works is that engineering in the service team keeps producing and keeps delivering new features for PCS overnight for customers to wake up in the morning and consuming those features without having to deal with upgrades and updates. I think that this is a very key, um, very key example of simplicity when it comes to e C s that is very hard to find um in other, um, solutions whether there are on prime or in the cloud. >>That's a great example in one of the big complaints I hear just anecdotally around the industry is, you know, the speed of the minds of business, want the apps to move faster and the iteration with some craft obviously with security and making sure things buttoned up, but things get pulled back. It's almost slowed down because the speed of the innovation is happening faster than the compliance of some sort of old governance model or code reviews. I want to approve everything. So there's a balance between making sure what's approved, whether security or some pipeline procedures and what not. >>So that I could have. I cannot agree more with you. Yeah, no, it's absolutely true because I think that we see these very interesting um, uh, economy, I would say between startups moving super fast and enterprises try to move fast but forced to move at their own speed. So when we when we deliver services based on, for example, open source software uh, that customers need to um, look after in terms of upgrade to latest release. What we usually see is start up asking us can you move faster? There is a new version of that software, can you enable us to deploy that version? And then on the other hand of the spectrum, there are these big enterprises trying to move faster but not so much that are asking us can use lower. Can you slow down a little bit? Right, because I cannot keep that pigs. So it's a very it's a very interesting um, um, a very interesting time to be alive. >>You know, one of the, one of the things that pop up into these conversations when you talk, when I talk to VP of engineering of companies and then enterprises that the operational efficiency, you got developer productivity and you've got innovation right, you've got the three kind of things going on there knobs and they all have to turn up. People want more efficiency of the operations, they want more developed productivity and more innovation. What's interesting is you start seeing, okay, it's not that easy. There's also a team formation and I know Andy Jassy kinda referred to this in his keynote at Reinvent last year around thinking differently around your organizational but you know, that could be applied to technologists too. So I'd love to get your thoughts while you're here. I know you blog about this and you tweet about this but this is kind of like okay if these things are all going to be knobs, we turned up innovation efficiency, operationally and develop productivity. What's the makeup of the team? Because some are saying, you have an SRE embedded, you've got the platform engineering, you've got version lists, you got survival is all these things are going on all goodness. But does that mean that the teams have to change? What's your thoughts on that you want to get your perspective? >>Yeah, no, absolutely. I think that there was a joke going around that um as soon as you see a job like VP of devoPS, I mean that is not going to work, right? Because these things are needs to be like embedded into each team, right? There shouldn't be a DEVOPS team or anything, it would be just a way of working. And I totally agree with you that these knobs needs to go insane, right? And you cannot just push too hard on innovation which are not having um other folks um to uh to be able to, you know, keep that pace um with you. And we're trying to health customers with multiple uh tools and services to try to um have not only developers and making developer experience uh better but also helping people that are building these underneath platforms. Like for example, prod on AWS protein is a good example of this, where we're focusing on helping these um teams that are trying to build platforms because they are not looking themselves as being a giant or very fast. But they're they're they're measured on being secure, being compliant and being, you know, within a guardrail uh that an enterprise um regulated enterprise needs to have. So we need to have all of these people um both organizationally as well as with providing tools and technologies that have them in their specific areas um to succeed. >>Yeah. And what's interesting about all this is that you know I think we're also having conversations and and again you're starting to see things more clearly here at dr khan we saw some things that coop con which the joke there was not joke but the observation was it's less about kubernetes which is now becoming boring, lee reliable to more about cloud native applications under the covers with program ability. So as all this is going on there truly is a flip of the script. You can actually re engineer and re factor everything, not just re platform your applications in I. T. At once. Right now there's a window whether it's security or whatever. Now that the containers and and the doctor ecosystem and the container ecosystem and the The kubernetes, you've got KS and you got six far gay and all the stuff of goodness. Companies can actually do this right now. They can actually change everything. This is a unique time. This window might close are certainly changed if you're not on it now, it's the same argument of the folks who got caught in the pandemic and weren't in the cloud got flat footed. So you're seeing that example of if you weren't in the cloud up during the pandemic before the pandemic, you were probably losing during the pandemic, the ones that one where the already guys are in the cloud. Now the same thing is true with cloud native. You're not getting into it now, you're probably gonna be on the wrong side of history. What's your reaction to that? >>Yeah, No, I I I agree totally. I I like to think about this. I usually uh talk about this if I can stay back step back a little bit and I think that in this industry and I have gray areas and I have seen lots of things, I think that there has been too big Democratisation event in 90 that happened and occurred in the last 30 years. So the first one was from, you know from when um the PC technology has been introduced, distributed computing from the mainframe area and that was the first Democratisation step. Right? So everyone had access to um uh computers so they could do things if you if you fast forward to these days. Um uh what happened is that on top of that computer, whatever that became a server or whatever, there is a state a very complex stack of technologies uh that allow you to deployment and develop and deploy your application. Right. But that stack of technology and the complexity of that stack of technology is daunting in some way. Right? So it is in a bit access and democratic access to technology. So to me this is what cloud enabled, Right? So the next step of democratisation was the introduction of services that allow you to bypass that stack, which we call undifferentiated heavy lifting because you know, um you don't get paid for managing, I don't know any M. R. Server or whatever, you get paid for extracting values through application logic from that big stack. So I totally agree with you that we're in a unique position to enable everyone um with what we're building uh to innovate a lot faster and in a more secure way. >>Yeah. And what comes out, I totally agree. And I think that's a great historical view and I think let's bring this down to the present today and then bring this as the as the bridge to the future. If you're a developer you could. And by the way, no matter whether you're programming infrastructure or just writing software or even just calling a PS and rolling your own, composing your services, it's programmable and it's just all accessible. So I think that that's going to change the again back to the three knobs, developer productivity or just people productivity, operational efficiency, which is scale and then innovation, which is the business logic where I think machine learning starts to come in, right? So if you can get the container thing going, you start tapping into that control plane. It's not so much just the data control plane. It's like a software control plane. >>Yeah, no, absolutely. The fact that you can, I mean as I said, I have great hair. So I've seen a lot of things and back in the days, I mean the, I mean the whole notion of being able to call an api and get 10 servers for example or today, 10 containers. It would be like, you know, almost a joke, right? So we spent a lot of time racking and um, and doing so much manual stuff that was so ever prone because we usually talk about velocity and agility, but we, we rarely talk about, you know, the difficulties and the problems that doing things manually introduced in the process, the way that you can get wrong. >>You know, you know, it reminds me of this industry and I was like finally get off my lawn in the old days. I walk to school with no shoes on in the snow. We had to build our own colonel and our own graphics libraries and then now they have all these tools. It's like, you're just an old, you know, coder, but joking aside, you know that experience, you're bringing up appointments for the younger generation who have never loaded a Linux operating system before or had done anything like that level. It's not so much old versus young, it's more of a systems thinking, he said distributed computing. If you look at all the action, it's essentially distributed computing with new software paradigm and it's a system architecture. It's not so much software engineering, software developer, you know, this that it's just basically all engineering at this point, all software. >>It is, it is very much indeed. It's uh, it's whole software, there is no other um, there is no other way to call it. It's um, I mean we go back to talk about, you know, infrastructure as code and everything is now uh corridor software in in in a way. It's, yeah. >>This is great to have you on. Congratulations. A CS anywhere being available. It's great stuff. Um, and great to see you and, and great to have this conversation. Um, amazon web services obviously, uh, the world has has gone super cloud. Uh, now you have distributed computing with edge iot exploding beautifully, which means a lot of new opportunities. So thanks for coming on. >>Thank you very much for having me. It was a pleasure. Okay, cube >>Coverage of Dr Khan 2021 virtual. This is the Cube. I'm John for your host. Thanks for watching.

>>mhm Yes, everyone, welcome back to the cubes coverage of dr khan 2021. I'm john for your host of the cube. Got a great segment here. One of the big supporters and open source amazon web services returning back second year. Dr khan virtual Deepak Singh, vice president of the compute services at AWS Deepak, Great to see you. Thanks for coming back on remotely again soon. We'll be in real life. Reinvent is going to be in person, we'll be there. Good to see you. >>Good to see you too, john it's always good to do these. I don't know how how often I've been at the cube now, but it's great every single time your >>legend and getting on there, a lot of important things to discuss your in one of the most important areas in the technology industry right now and that is at the confluence of cloud scale and modern development applications as they shift towards as Andy Jassy says, the new guard, right. It's been happening. You guys have been a big proponent of open source and enabling open source is a service creating business models for companies. But more importantly, you guys are powering, making it easier for folks to use software. And doctor has been a big relationship for you. Could you take a minute to first talk about the doctor, a W S relationship and your involvement and what you're doing? >>Yeah, actually it goes back a long way. Uh you know, Justin, we announced PCS had reinvented 2014 and PCS at that time was very much managed orchestration service on top of DACA at that time. I think it was the first really big one out there from a cloud provider. And since then, of course, the world has evolved quite a bit and relationship with DR has evolved a lot. The thing I'd like to talk to is something that we announced that Dr last year, I don't remember if I talked about it on the cube at that time. But last year we started working with DR on how can we go from doctor Run, which customers love or DR desktop, which customers love and make it easy for people to run containers on pcs and Fergie. Uh so most new customers running containers and AWS today start with this Yes and party or half of them and we wanted to make it very easy for them to start with where they are on the laptop which is often bucket to stop and have running services the native US. So we started working with DR and that that collaboration has been very successful. We want to keep you look forward to continuing to work on evolving that where you can use Docker compose doctor, desktop, doctor run the fuel that darker customers used and the labour grand production services on the end of your side, which is the part that we've got that on. So I think that's one area where we work really well together. Uh, the other area where I think the two companies continue to work well together. It's open source in general as some of, you know, AWS has a very strong commitment to contain a. D uh, EKS our community service is moving towards community. Forget it actually runs all on community today and uh, we collaborate dr Rhonda on the Ocr specification because, you know, the Oc I am expect is becoming the de facto packaging format idea. W S. This morning we launched yesterday, we launched a service called Opera. And the main expected input for opera is an Ocr image are being in this Atlanta as well, where those ci images now a way of packaging for lambda. And I think the last one I like to call out and it has been an amazing partnership and it's an area where most people don't pay attention is amid signing. Uh, there's a project called Notary. We do the second version of the Notary Spec for remit signing and AWS Docker and a couple of other companies have been working very closely together on bringing that uh, you know, finalizing no tv too, so that at least in our case we can start building services for our customers on top of that. You know, it's it's a great relationship and I expect to see it continue. >>Well, I think one of the themes this year is developer experience. So good. Good call out there in the new announcements on the tools you have and software because that seems to be a great developer integration with Docker question I have for you is how should the customers think about things like E C. S and versus E K. S. App, Runner lambda uh for kind of running their containers. How do they understand the difference is, what's there? What's the, what's the thought process there? What's >>that? It's a good question actually been announced after. And I think there was one of the questions I started getting on twitter. You know, let's start at the very beginning. Anyone can pick up a Docker container and run it on easy to today. You can run it on easy to, we can run a light sail, but doc around works just fine. It's the limits machine. Then people want to do more complex things. They want to run large scale orchestrated services. They won't run their entire business and containers. We have customers will do that today. Uh, you know, you have people like Vanguard who runs a significant portion of the infrastructure on pcs frg or you have to elope with the heavy user of chaos, our community service. So in general, if you're running large scale systems, you're building your platforms, you're most likely to use the csny Chaos. Um, if you come from a community's background, you're, you're running communities on prem or you want the flexibility and control the communities gives you, you're gonna end up with the chaos. That's what we see our customers doing. If you just want to run containers, you want to use AWS to its fullest extent where you want the continue a P I to be part of the W A S A P. I said then you pick is yes. And I think one of the reasons you see so many customers start with the CSN, Forget is with forget to get the significant ease of use from an operational standpoint. And we see many start ups and you know, enterprises, especially security focus enterprises leaning towards farming. But there's a class of customers that doesn't want to think about orchestration that just wants. Here's my code, here's my container image just run my service for me and that's when things like happen, I can come and that's one of the reasons we launched it. Land is a little bit different. Lambda is a unique service. You buy into an event driven architecture. If you do that, then you can figure our application into this. That's they should start its magic. Uh, the container part, there is what land announced agreement where they now support containers, packaging. So instead of zip files, you can package up your functions as containers. Then lambda will run them for you. The advantage it gives you with all the tooling that you built, that you have to build your containers now works the land as well. So I won't call and a container orchestration service in the same sense of the CSC cso Afrin are but it definitely allows the container image format as a standard packaging format. I think that's the sort of universal common theme that you find across AWS at this point of time. >>You know, one of the things that we're observing at this at this event here is a lot of developers Coop con and Lennox foundations. A lot of operators to kubernetes hits that. But here's developers. And the thing is I want to ease of use, simplicity experience, but also I want the innovation. Yeah, I want all of it. When I ask you what is amazon bring to the table for the new equation, what would you say? >>Yeah, I mean for me it's always you've probably heard me say this 100 times. Many 1000 times. It's foggy fog. It's unique to us. It takes a lot of what we have learned about operating infrastructure scale. The question we asked ourselves, you know, in many ways we talk about forget even before belong pcs but we have to learn on what it meant and what customers really wanted. But the idea was when you are running clusters of instances of machines to run containers on, you have to start thinking about a lot of things that in some ways VMS but BMS in the car were taken away capacity. What kind of infrastructure to run it on? Should have been touched. Should have not been back. You know, where is my container running? Those are things. They suddenly started having to think about those kind of backwards almost. So the idea was how can we make your containerized bundles? So TCS task or community is part of the thing that you talk to and that is the main unit that you operate on. That is the unit that you get built on and meet it on. That's where Forget comes in and it allows us to do many interesting things. We've effectively changed the engine of forget since we've launched it. Uh, we run it on ec two instances and we run it on fire cracker. Uh, we have changed the forget agent architecture. We've made a lot of underneath the hood, uh, changes that even take the take advantage of the broader innovation, the rate of us, We did a whole bunch more to launch acronym trans on top of family customers don't have to think about it. They don't have to worry about it. It happens underneath the hood. It's always your engine as as you go along and it takes away all the operational pain of managing clusters of running into picking which instances to use to getting out, trying to figure out how to bend back and get efficiency. That becomes our problem. So, you know, that is an area where you should expect to see a Stuart done more. It's becoming the fabric of so many things that eight of us now. Uh, it's, you know, in some ways we're just talking a lot more to do. >>Yeah. And it's a really good time. A lot more wave of developers coming in. One of the things that we've been reporting on on Silicon England cube with our cute videos is more developers keep on coming on, more people coming in and contributing to the open source community. Even end users, not just the normal awesome hyper scholars you're talking about like classic, I call main street enterprises. So two things I want to ask you on the customer side because you have kind of to customers, you have the community that open source community and you have enterprise customers that want to make it easier. What are you seeing and hearing from customers? I know you guys work backwards from the customer. So I got to ask you work backwards from the community and work backwards from the enterprise customer. What's going on in their environment? What's the key trends that they're riding? What's the big challenges? What's the big opportunities that they're facing and saying for the community? >>Yeah, I start with the enterprise. That's almost an easier answer. Which is, you know, we're seeing increasingly enterprises moving into the cloud wholesale. Like in some ways you could argue that the pandemic has just accelerated it, but we have started seeing that before. Uh they want to move to the cloud and adult modern best practices. Uh If you see my talk agreement last few years, I've talked about modernization and all the aspects of modernization, and that's 90% of our conversation with enterprises, I've walked into a meeting supposedly to talk about containers, whatever half a conversation is spent on. How does an organization modernize? What does an organization need to do to modernize and containers and serverless play a pretty important part in it, because it gives them an opportunity to step away from the shackles of sort of fixed infrastructure and the methods and approaches that built in. But equally, we are talking about C I C. D, you know, fully automated deployments. What does it mean for developers to run their own services? What are the child, how do you monitor and uh, instrument uh, your services? How do you do observe ability in the modern world? So those are the challenges that enterprises are going towards, and you're spending a ton of time helping them there. But many of them are still running infrastructure on premises. So, you know, we have outpost for them. Uh, you know, just last week, you're talking to a bunch of our customers and they have lots of interesting ideas and things that they want to do without both, but many of them also have their own infrastructure and that's where something like UCS anywhere came from, which is hey, you like using Pcs in the cloud, You like having the safety i that just orchestrates containers for you. It does it on on his in an AWS region. It will do it in an outpost. It'll do it on wavelength, it'll do it on local zone. How about we allow you to do it on whatever infrastructure you bring to us. Uh you want to bring a raspberry pi, you can do that. You want to bring your on premises data center infrastructure, we can do that or a point of sale device, as long as you can get the agent running and you can connect to an AWS region, even though it's okay to lose connectivity every now and then. We can orchestrate a container for you over there and, you know, the same customer that likes the ease of use of Vcs. And the simplicity really resonated with that message really resonates with them. So I think where we are today with the enterprise is we've got some really good solutions for you in eight of us and we are now allowing you to take those a. P. I. S and then launch containers wherever you want to run them, whether it's the edge or whether it's your own data center. I think that's a big part of where the enterprise is going. But by and large, I think yes, a lot of them are still making that change from running infrastructure and applications the way they used to do a modern sort of, if you want to use the word cloud native way and we're helping them a lot. We've done, the community is interesting. They want to be more participatory. Uh that's where things like co pilot comes from. God, honestly, the best thing we've ever done in my order is probably are open road maps where the community can go into the road map and engage with us over there, whether it's an open source project or just trying to tell us what the feature is and how they would like to see it. It's a great engagement and you know, it's not us a lot. It's helped us prioritize correctly and think about what we want to do next. So yeah, I think that's, that >>must be very hard to do for opening up the kimono on the road map because normally that's the crown jewels and its secretive and you know, and um, now it's all out in the open. I think that is a really interesting, um, experiment and what's your reaction to that? What's been the feedback on the road map peace? Because I mean, I definitely want to see, uh, >>we do it pretty much for every service in my organization and we've been doing it now for three years. So years forget, I think about three years and it's been great. Now we are very we are very upfront, which is security and availability. Our job 000 and you know, 100 times out of 100 at altitudes between a new feature and helping our customers be available and safe. We'll do that. And this is why we don't put dates in that we just tell you directionally where we are and what we are prioritizing Uh, there every now and then we'll put something in there that, you know, well not choose not to put a feature in there because we want to keep it secret until it launches. But for the most part, 99% of our own myself there and people engaged with it. And it's not proven to be a problem because you've also been very responsible with how we manage and be very transparent on whether we can commit to something or not. And I think that's not. >>I gotta ask you on as a leader uh threaded leader on this group. Open source is super important, as you know, and you continue to do it from under years. How are you investing in the future? What's your plan? Uh plans for your team, the industry actually very inclusive, Which is very cool. It's gonna resonate well, what's the plans? Give us some details on what you're investing in, what your priorities? What's your first principles? >>Yeah, So it goes in many ways, one when I I also have the luxury also on the amazon open source program office. So, you know, I get the chance to my team, rather not me help amazon engineers participate in open source. That that's the team that helps create the tools for them, makes it easy for them to contribute, creates, you know, manages all the licenses, etcetera. I'll give you a simple example, you know, in there, just think of the cr credential helper that was written by one of our engineers and he kind of distorted because he felt it was something that we needed to do. And we made it open source in general, in in many of our teams. The first question we asked is should something the open why is this thing not open source, especially if it's a utility or some piece of software that runs along with services. So they'll step one. But we've done some big things also, I, you know, a couple of years ago we launched Lennox operating system called bottle Rocket. And right from the beginning it was very clear to us that bottle Rocket was two things. It was both in AWS product. But first it was an open source project. We've already learned a little bit from what we've done at Firecracker. But making bottle rocket and open source operating system is very important. Anyone can take part of Rocket the open source to build tooling. You can run it whatever you want. If you want to take part of Rocket and build a version and manage it for another provider. For another provider wants to do it, go for it. There's nothing stopping you from doing that. So you'll see us do a lot there. Obviously there's multiple areas. You've seen WS investing on the open source side. But to me, the winds come from when engineers can participate in small things, released little helpers or get contributions from outside. I think that's where we're still, we can always have that. We're going to continue to strive to make it better and easier. And uh, you know, I said, I have, you know, me and my team, we have an opportunity to help their inside the company and we continue to do so. But that's what gets me excited. >>Yeah, that's great stuff. And congratulations on investing in the community, really enjoys it and I know it moves the needle for the industry. Deepak, I gotta ask you why I got you here. Dr khan obviously, developers, what's the most important story that they should be paying attention to as a developer because of what's going on shift left for security day two operations also known as a I ops getups, whatever you wanna call it, you know, ongoing, you get server lists, you got land. I mean, all kinds of great things are going on. You mentioned Fargate, >>um >>what should they be paying attention to that's going to really help their life, both innovation wise and just the quality of life. >>Yeah, I would say look at, you know, in the end it is very easy developers in particular, I want to build the buildings and it's very easy to get tempted to try and get learn everything about something. You have access to all the bells and whistles and knobs, but in reality, if you want to run things you want to, you want to focus on what's important, the business application, that and you the application. And I think a lot of what I'll tell developers and I think it's a lot of where the industry is going is we have built a really solid foundation, whether it's humanity, so you CSN forget or you know, continue industries out there. We have very solid foundation that, you know, our customers and develop a goal of the world can use to build upon. But increasingly, and you know, they are going to provide tools that sort of take that wrap them up and providing a nice package solution After another great example, our collaboration, the doctor around Dr desktop are a great example where we get all the mark focus on the application and build on top of that and you can get so much done. I think that's one trend. You'll see more and more. Those things are no longer toys, their production grade systems that you can build real world applications on, even though they're so easy to use. The second thing I would add to that is uh, get uh, it is, you know, you can give it whatever name you want. There's uh, there's nuances there, but I actually think get up is the way people should be running the infrastructure, my virus in my personal, you know, it's something that we believe a lot in homicide as hard as you go towards immutable infrastructure, infrastructure, automation, we can get off plays a significant role. I think developers naturally gravitate towards it. And if you want to live in a world where development and operations are tightly linked, I think it after the huge role to play in that it's actually a big part of how we're planning to do things like yes, anywhere, for example, a significant player and that it would be a proton. I think get up will be a significant in the future of proton as well. So I think that's the other trend. If you wanted to pick a trend that people should pay attention. That's what I believe in a lot. >>Well you're an expert. So I want to get you a quick definition. What is get Ops, how would you define it? Because that's a big trend. What does it, what does that mean? >>Electricity will probably shoot me for getting this wrong. I tell you how I think about it. Which is, you know, in many cases, um, you when you're doing deployments are pushing a deployment getups is more of a full deployment. When you are pushing code to get depository, you have a system that knows that the event has happened and then pulls from there and triggers the thing as opposed to you telling it take I have this new piece of code now go deployed everywhere. So to me, the biggest changes that Two parts one is it's more for full mechanism where you're pulling because something has changed. So it needs systems like container orchestrators to keep them, you know, to keep them in sync. And the second part of the natural natural evolution of infrastructure score, which is basically everything is called the figures code. Infrastructure as code, code is code and everything is getting stored in that software repo and the software repo becomes your store of record and drives everything. Uh So for a glass of customers, that's going to be a pretty big deal. >>Yeah, when you're checking in code, that's again, it's like a compiler for the compiler, a container for the container, you've got things for each other. Automation is ultimately what we're talking about here. And that's to me where machine learning kicks in. So again, having this open source foundational fabric, as you said, forget out the muck or the undifferentiated heavy lifting. This is what we're talking about automation, isn't it? Deepak? >>Yes. I mean I said uh one thing where we hang our hat on is there's such good stuff out there in the world which we like to contribute to, but the thing we like to hang our hat on is how do you run this? How do you do it this in ways that you can uniquely bring capabilities to customers where there's things like nitro or things are nitro open stuff. Well, the fact that we have built up this operational infrastructure over the last in a decade plus or in the container space over the last seven years where we really really know how to run these things at scale and have made all the investments to make it easy to do. So that's that's where we have hanger hard keeping people safe, helping them only available applications, their new startup, that just completely takes off in over the weekend. For whatever reason, because, you know, you're the next hot thing on twitter and our goal is to support you whether you are, you know, uh enterprise that's moving from the main train or you are the next hot startup, that's you know, growing virally and uh, you know, we've done a lot to build systems help both sides and yeah, it's >>interesting if you sing about open source where it's come from, I mean I remember that base wouldn't open source wasn't open, I would be peddling software, there's a free copy of Linux, UNIX um in college and now it's all free. But I mean just what's changed now. It used to be just free software, download software. You got it now, it's a service. Service now can be monetized quickly. And what you guys are offering with AWS and cloud scale is you've done all these things as I don't have to have a developer. I get the benefits of the scale, I can bring my open source code to the table, make it a service integrated in with other services and be the next snowflake, be the next, you know, a company that could scale. And that is that's the that's the innovation, right? That's the this is a new phenomenon. So it also changes the business model. >>Yeah, actually you're you're quite right. Actually, I I like one more thing to it. But you look at how a lot of enterprises use containers today. Most of them are using something like this year, Symphony or GS to build an internal developer platform and internal developer portal. And then the question then becomes this hard to scale this modern and development practices to an entire organization. What is your big bank that's been around as thousands and thousands of ID stuff That may not all be experts are running communities running container is when you scale it out different systems that proton come into play. That was actually the inspiration is how do you help an organization where they're building these developer Portholes and developer infrastructure, developer platforms, How do you make it easy for them to build it? Be almost use it as a way to get these modern practices into the hands of all the business units, where they may not have the time to become experts at the modern ways of running infrastructure because they're busy doing other things. And I think you'll see the a lot more happening that space that's not happening in the open source community. There's proton, there's a bunch of interesting things happening here and be interesting to see how that evolves. >>And also, you know, the communal, communal aspect of not just writing code together, but succeeding, right, building something. I mean, that's when you start to see the commercial meets open kind of ethos of communal activity of working together and sharing a big part of this year's. Dakar Con is sharing not just running and shipping code but sharing. >>Yeah, I mean if you think about it uh Dockers original value was you build run and shit right? You use the same code to build it, you use the same code to ship it, the same sort of infrastructure interface and then you run it and that, you know, the fact that the doctor images such a wonderfully shareable entity uh that can run every girl is such a powerful and it's called the Ci Image. Now I still call him Dr images because it's just easier. But that to me like that is a big deal and I think it's becoming and become an even bigger deal over the years. I came from something before, Amazon has to work in The sciences and bioinformatics and you know, the ability to share codeshare dependencies, package all of that up in a container image is a big deal. It's what got me one of the reasons I got fascinated with container 78 years ago. So it will be interesting to see where all of systems. >>It's great, great stuff. Great success. And congratulations. Deepak, Great to always talk to you got a great finger on the pulse. You lead a really important organizations at AWS and you know, doctor has such a huge success with developers, even though the company has gone through kind of a uh change over and a pivot to what they're doing now. They're back to their open source roots, but they have millions and millions of developers use Docker and new developers are coming in dot net developers are coming in. Windows developers are coming in and and so it's no longer about Lennox anymore. It's about just coding. >>Yeah. And it's it's part of this big trend towards infrastructure, automation and and you know development and deployment practices that I think everyone is going to adopt faster than we think they will. But you know, companies like Doctor and opens those projects that they involved are critical in making that a lot easier for them. And then you know, folks like us get to build on top of that orbit them and make it even easier. >>Well, great testimony the doctor that you guys based your E C. S on Docker Doctor has a critical role in developing community. I run composed in their hub with dr desktop and we'll be watching amazon and and the community activity and see what kind of experiences you guys can bring to the table and continue that momentum. Thank you Deepak for coming on the >>cube. Thank you, john. That's always a pleasure. >>Okay. Mr cubes. Dr khan 2021 virtual coverage. I'm john for your host of the cube. Thanks for watching.

>>Individuals create developers, translate ideas to code, to create great applications and great applications. Touch everyone. A Docker. We know that collaboration is key to your innovation sharing ideas, working together. Launching the most secure applications. Docker is with you wherever your team innovates, whether it be robots or autonomous cars, we're doing research to save lives during a pandemic, revolutionizing, how to buy and sell goods online, or even going into the unknown frontiers of space. Docker is launching innovation everywhere. Join us on the journey to build, share, run the future. >>Hello and welcome to Docker con 2021. We're incredibly excited to have more than 80,000 of you join us today from all over the world. As it was last year, this year at DockerCon is 100% virtual and 100% free. So as to enable as many community members as possible to join us now, 100%. Virtual is also an acknowledgement of the continuing global pandemic in particular, the ongoing tragedies in India and Brazil, the Docker community is a global one. And on behalf of all Dr. Khan attendees, we are donating $10,000 to UNICEF support efforts to fight the virus in those countries. Now, even in those regions of the world where the pandemic is being brought under control, virtual first is the new normal. It's been a challenging transition. This includes our team here at Docker. And we know from talking with many of you that you and your developer teams are challenged by this as well. So to help application development teams better collaborate and ship faster, we've been working on some powerful new features and we thought it would be fun to start off with a demo of those. How about it? Want to have a look? All right. Then no further delay. I'd like to introduce Youi Cal and Ben, gosh, over to you and Ben >>Morning, Ben, thanks for jumping on real quick. >>Have you seen the email from Scott? The one about updates and the docs landing page Smith, the doc combat and more prominence. >>Yeah. I've got something working on my local machine. I haven't committed anything yet. I was thinking we could try, um, that new Docker dev environments feature. >>Yeah, that's cool. So if you hit the share button, what I should do is it will take all of your code and the dependencies and the image you're basing it on and wrap that up as one image for me. And I can then just monitor all my machines that have been one click, like, and then have it side by side, along with the changes I've been looking at as well, because I was also having a bit of a look and then I can really see how it differs to what I'm doing. Maybe I can combine it to do the best of both worlds. >>Sounds good. Uh, let me get that over to you, >>Wilson. Yeah. If you pay with the image name, I'll get that started up. >>All right. Sen send it over >>Cheesy. Okay, great. Let's have a quick look at what you he was doing then. So I've been messing around similar to do with the batter. I've got movie at the top here and I think it looks pretty cool. Let's just grab that image from you. Pick out that started on a dev environment. What this is doing. It's just going to grab the image down, which you can take all of the code, the dependencies only get brunches working on and I'll get that opened up in my idea. Ready to use. It's a here close. We can see our environment as my Molly image, just coming down there and I've got my new idea. >>We'll load this up and it'll just connect to my dev environment. There we go. It's connected to the container. So we're working all in the container here and now give it a moment. What we'll do is we'll see what changes you've been making as well on the code. So it's like she's been working on a landing page as well, and it looks like she's been changing the banner as well. So let's get this running. Let's see what she's actually doing and how it looks. We'll set up our checklist and then we'll see how that works. >>Great. So that's now rolling. So let's just have a look at what you use doing what changes she had made. Compare those to mine just jumped back into my dev container UI, see that I've got both of those running side by side with my changes and news changes. Okay. So she's put Molly up there rather than mobi or somebody had the same idea. So I think in a way I can make us both happy. So if we just jumped back into what we'll do, just add Molly and Moby and here I'll save that. And what we can see is, cause I'm just working within the container rather than having to do sort of rebuild of everything or serve, or just reload my content. No, that's straight the page. So what I can then do is I can come up with my browser here. Once that's all refreshed, refresh the page once hopefully, maybe twice, we should then be able to see your refresh it or should be able to see that we get Malia mobi come up. So there we go, got Molly mobi. So what we'll do now is we'll describe that state. It sends us our image and then we'll just create one of those to share with URI or share. And we'll get a link for that. I guess we'll send that back over to you. >>So I've had a look at what you were doing and I'm actually going to change. I think that might work for both of us. I wondered if you could take a look at it. If I send it over. >>Sounds good. Let me grab the link. >>Yeah, it's a dev environment link again. So if you just open that back in the doc dashboard, it should be able to open up the code that I've changed and then just run it in the same way you normally do. And that shouldn't interrupt what you're already working on because there'll be able to run side by side with your other brunch. You already got, >>Got it. Got it. Loading here. Well, that's great. It's Molly and movie together. I love it. I think we should ship it. >>Awesome. I guess it's chip it and get on with the rest of.com. Wasn't that cool. Thank you Joey. Thanks Ben. Everyone we'll have more of this later in the keynote. So stay tuned. Let's say earlier, we've all been challenged by this past year, whether the COVID pandemic, the complete evaporation of customer demand in many industries, unemployment or business bankruptcies, we all been touched in some way. And yet, even to miss these tragedies last year, we saw multiple sources of hope and inspiration. For example, in response to COVID we saw global communities, including the tech community rapidly innovate solutions for analyzing the spread of the virus, sequencing its genes and visualizing infection rates. In fact, if all in teams collaborating on solutions for COVID have created more than 1,400 publicly shareable images on Docker hub. As another example, we all witnessed the historic landing and exploration of Mars by the perseverance Rover and its ingenuity drone. >>Now what's common in these examples, these innovative and ambitious accomplishments were made possible not by any single individual, but by teams of individuals collaborating together. The power of teams is why we've made development teams central to Docker's mission to build tools and content development teams love to help them get their ideas from code to cloud as quickly as possible. One of the frictions we've seen that can slow down to them in teams is that the path from code to cloud can be a confusing one, riddle with multiple point products, tools, and images that need to be integrated and maintained an automated pipeline in order for teams to be productive. That's why a year and a half ago we refocused Docker on helping development teams make sense of all this specifically, our goal is to provide development teams with the trusted content, the sharing capabilities and the pipeline integrations with best of breed third-party tools to help teams ship faster in short, to provide a collaborative application development platform. >>Everything a team needs to build. Sharon run create applications. Now, as I noted earlier, it's been a challenging year for everyone on our planet and has been similar for us here at Docker. Our team had to adapt to working from home local lockdowns caused by the pandemic and other challenges. And despite all this together with our community and ecosystem partners, we accomplished many exciting milestones. For example, in open source together with the community and our partners, we open sourced or made major contributions to many projects, including OCI distribution and the composed plugins building on these open source projects. We had powerful new capabilities to the Docker product, both free and subscription. For example, support for WSL two and apple, Silicon and Docker, desktop and vulnerability scanning audit logs and image management and Docker hub. >>And finally delivering an easy to use well-integrated development experience with best of breed tools and content is only possible through close collaboration with our ecosystem partners. For example, this last year we had over 100 commercialized fees, join our Docker verified publisher program and over 200 open source projects, join our Docker sponsored open source program. As a result of these efforts, we've seen some exciting growth in the Docker community in the 12 months since last year's Docker con for example, the number of registered developers grew 80% to over 8 million. These developers created many new images increasing the total by 56% to almost 11 million. And the images in all these repositories were pulled by more than 13 million monthly active IP addresses totaling 13 billion pulls a month. Now while the growth is exciting by Docker, we're even more excited about the stories we hear from you and your development teams about how you're using Docker and its impact on your businesses. For example, cancer researchers and their bioinformatics development team at the Washington university school of medicine needed a way to quickly analyze their clinical trial results and then share the models, the data and the analysis with other researchers they use Docker because it gives them the ease of use choice of pipeline tools and speed of sharing so critical to their research. And most importantly to the lives of their patients stay tuned for another powerful customer story later in the keynote from Matt fall, VP of engineering at Oracle insights. >>So with this last year behind us, what's next for Docker, but challenge you this last year of force changes in how development teams work, but we felt for years to come. And what we've learned in our discussions with you will have long lasting impact on our product roadmap. One of the biggest takeaways from those discussions that you and your development team want to be quicker to adapt, to changes in your environment so you can ship faster. So what is DACA doing to help with this first trusted content to own the teams that can focus their energies on what is unique to their businesses and spend as little time as possible on undifferentiated work are able to adapt more quickly and ship faster in order to do so. They need to be able to trust other components that make up their app together with our partners. >>Docker is doubling down and providing development teams with trusted content and the tools they need to use it in their applications. Second, remote collaboration on a development team, asking a coworker to take a look at your code used to be as easy as swiveling their chair around, but given what's happened in the last year, that's no longer the case. So as you even been hinted in the demo at the beginning, you'll see us deliver more capabilities for remote collaboration within a development team. And we're enabling development team to quickly adapt to any team configuration all on prem hybrid, all work from home, helping them remain productive and focused on shipping third ecosystem integrations, those development teams that can quickly take advantage of innovations throughout the ecosystem. Instead of getting locked into a single monolithic pipeline, there'll be the ones able to deliver amps, which impact their businesses faster. >>So together with our ecosystem partners, we are investing in more integrations with best of breed tools, right? Integrated automated app pipelines. Furthermore, we'll be writing more public API APIs and SDKs to enable ecosystem partners and development teams to roll their own integrations. We'll be sharing more details about remote collaboration and ecosystem integrations. Later in the keynote, I'd like to take a moment to share with Docker and our partners are doing for trusted content, providing development teams, access to content. They can trust, allows them to focus their coding efforts on what's unique and differentiated to that end Docker and our partners are bringing more and more trusted content to Docker hub Docker official images are 160 images of popular upstream open source projects that serve as foundational building blocks for any application. These include operating systems, programming, languages, databases, and more. Furthermore, these are updated patch scan and certified frequently. So I said, no image is older than 30 days. >>Docker verified publisher images are published by more than 100 commercialized feeds. The image Rebos are explicitly designated verify. So the developers searching for components for their app know that the ISV is actively maintaining the image. Docker sponsored open source projects announced late last year features images for more than 200 open source communities. Docker sponsors these communities through providing free storage and networking resources and offering their community members unrestricted access repos for businesses allow businesses to update and share their apps privately within their organizations using role-based access control and user authentication. No, and finally, public repos for communities enable community projects to be freely shared with anonymous and authenticated users alike. >>And for all these different types of content, we provide services for both development teams and ISP, for example, vulnerability scanning and digital signing for enhanced security search and filtering for discoverability packaging and updating services and analytics about how these products are being used. All this trusted content, we make available to develop teams for them directly to discover poll and integrate into their applications. Our goal is to meet development teams where they live. So for those organizations that prefer to manage their internal distribution of trusted content, we've collaborated with leading container registry partners. We announced our partnership with J frog late last year. And today we're very pleased to announce our partnerships with Amazon and Miranda's for providing an integrated seamless experience for joint for our joint customers. Lastly, the container images themselves and this end to end flow are built on open industry standards, which provided all the teams with flexibility and choice trusted content enables development teams to rapidly build. >>As I let them focus on their unique differentiated features and use trusted building blocks for the rest. We'll be talking more about trusted content as well as remote collaboration and ecosystem integrations later in the keynote. Now ecosystem partners are not only integral to the Docker experience for development teams. They're also integral to a great DockerCon experience, but please join me in thanking our Dr. Kent on sponsors and checking out their talks throughout the day. I also want to thank some others first up Docker team. Like all of you this last year has been extremely challenging for us, but the Docker team rose to the challenge and worked together to continue shipping great product, the Docker community of captains, community leaders, and contributors with your welcoming newcomers, enthusiasm for Docker and open exchanges of best practices and ideas talker, wouldn't be Docker without you. And finally, our development team customers. >>You trust us to help you build apps. Your businesses rely on. We don't take that trust for granted. Thank you. In closing, we often hear about the tenant's developer capable of great individual feeds that can transform project. But I wonder if we, as an industry have perhaps gotten this wrong by putting so much emphasis on weight, on the individual as discussed at the beginning, great accomplishments like innovative responses to COVID-19 like landing on Mars are more often the results of individuals collaborating together as a team, which is why our mission here at Docker is delivered tools and content developers love to help their team succeed and become 10 X teams. Thanks again for joining us, we look forward to having a great DockerCon with you today, as well as a great year ahead of us. Thanks and be well. >>Hi, I'm Dana Lawson, VP of engineering here at get hub. And my job is to enable this rich interconnected community of builders and makers to build even more and hopefully have a great time doing it in order to enable the best platform for developers, which I know is something we are all passionate about. We need to partner across the ecosystem to ensure that developers can have a great experience across get hub and all the tools that they want to use. No matter what they are. My team works to build the tools and relationships to make that possible. I am so excited to join Scott on this virtual stage to talk about increasing developer velocity. So let's dive in now, I know this may be hard for some of you to believe, but as a former CIS admin, some 21 years ago, working on sense spark workstations, we've come such a long way for random scripts and desperate systems that we've stitched together to this whole inclusive developer workflow experience being a CIS admin. >>Then you were just one piece of the siloed experience, but I didn't want to just push code to production. So I created scripts that did it for me. I taught myself how to code. I was the model lazy CIS admin that got dangerous and having pushed a little too far. I realized that working in production and building features is really a team sport that we had the opportunity, all of us to be customer obsessed today. As developers, we can go beyond the traditional dev ops mindset. We can really focus on adding value to the customer experience by ensuring that we have work that contributes to increasing uptime via and SLS all while being agile and productive. We get there. When we move from a pass the Baton system to now having an interconnected developer workflow that increases velocity in every part of the cycle, we get to work better and smarter. >>And honestly, in a way that is so much more enjoyable because we automate away all the mundane and manual and boring tasks. So we get to focus on what really matters shipping, the things that humans get to use and love. Docker has been a big part of enabling this transformation. 10, 20 years ago, we had Tomcat containers, which are not Docker containers. And for y'all hearing this the first time go Google it. But that was the way we built our applications. We had to segment them on the server and give them resources. Today. We have Docker containers, these little mini Oasys and Docker images. You can do it multiple times in an orchestrated manner with the power of actions enabled and Docker. It's just so incredible what you can do. And by the way, I'm showing you actions in Docker, which I hope you use because both are great and free for open source. >>But the key takeaway is really the workflow and the automation, which you certainly can do with other tools. Okay, I'm going to show you just how easy this is, because believe me, if this is something I can learn and do anybody out there can, and in this demo, I'll show you about the basic components needed to create and use a package, Docker container actions. And like I said, you won't believe how awesome the combination of Docker and actions is because you can enable your workflow to do no matter what you're trying to do in this super baby example. We're so small. You could take like 10 seconds. Like I am here creating an action due to a simple task, like pushing a message to your logs. And the cool thing is you can use it on any the bit on this one. Like I said, we're going to use push. >>You can do, uh, even to order a pizza every time you roll into production, if you wanted, but at get hub, that'd be a lot of pizzas. And the funny thing is somebody out there is actually tried this and written that action. If you haven't used Docker and actions together, check out the docs on either get hub or Docker to get you started. And a huge shout out to all those doc writers out there. I built this demo today using those instructions. And if I can do it, I know you can too, but enough yapping let's get started to save some time. And since a lot of us are Docker and get hub nerds, I've already created a repo with a Docker file. So we're going to skip that step. Next. I'm going to create an action's Yammel file. And if you don't Yammer, you know, actions, the metadata defines my important log stuff to capture and the input and my time out per parameter to pass and puts to the Docker container, get up a build image from your Docker file and run the commands in a new container. >>Using the Sigma image. The cool thing is, is you can use any Docker image in any language for your actions. It doesn't matter if it's go or whatever in today's I'm going to use a shell script and an input variable to print my important log stuff to file. And like I said, you know me, I love me some. So let's see this action in a workflow. When an action is in a private repo, like the one I demonstrating today, the action can only be used in workflows in the same repository, but public actions can be used by workflows in any repository. So unfortunately you won't get access to the super awesome action, but don't worry in the Guild marketplace, there are over 8,000 actions available, especially the most important one, that pizza action. So go try it out. Now you can do this in a couple of ways, whether you're doing it in your preferred ID or for today's demo, I'm just going to use the gooey. I'm going to navigate to my actions tab as I've done here. And I'm going to in my workflow, select new work, hello, probably load some workflows to Claire to get you started, but I'm using the one I've copied. Like I said, the lazy developer I am in. I'm going to replace it with my action. >>That's it. So now we're going to go and we're going to start our commitment new file. Now, if we go over to our actions tab, we can see the workflow in progress in my repository. I just click the actions tab. And because they wrote the actions on push, we can watch the visualization under jobs and click the job to see the important stuff we're logging in the input stamp in the printed log. And we'll just wait for this to run. Hello, Mona and boom. Just like that. It runs automatically within our action. We told it to go run as soon as the files updated because we're doing it on push merge. That's right. Folks in just a few minutes, I built an action that writes an entry to a log file every time I push. So I don't have to do it manually. In essence, with automation, you can be kind to your future self and save time and effort to focus on what really matters. >>Imagine what I could do with even a little more time, probably order all y'all pieces. That is the power of the interconnected workflow. And it's amazing. And I hope you all go try it out, but why do we care about all of that? Just like in the demo, I took a manual task with both tape, which both takes time and it's easy to forget and automated it. So I don't have to think about it. And it's executed every time consistently. That means less time for me to worry about my human errors and mistakes, and more time to focus on actually building the cool stuff that people want. Obviously, automation, developer productivity, but what is even more important to me is the developer happiness tools like BS, code actions, Docker, Heroku, and many others reduce manual work, which allows us to focus on building things that are awesome. >>And to get into that wonderful state that we call flow. According to research by UC Irvine in Humboldt university in Germany, it takes an average of 23 minutes to enter optimal creative state. What we call the flow or to reenter it after distraction like your dog on your office store. So staying in flow is so critical to developer productivity and as a developer, it just feels good to be cranking away at something with deep focus. I certainly know that I love that feeling intuitive collaboration and automation features we built in to get hub help developer, Sam flow, allowing you and your team to do so much more, to bring the benefits of automation into perspective in our annual October's report by Dr. Nicole, Forsgren. One of my buddies here at get hub, took a look at the developer productivity in the stork year. You know what we found? >>We found that public GitHub repositories that use the Automational pull requests, merge those pull requests. 1.2 times faster. And the number of pooled merged pull requests increased by 1.3 times, that is 34% more poor requests merged. And other words, automation can con can dramatically increase, but the speed and quantity of work completed in any role, just like an open source development, you'll work more efficiently with greater impact when you invest the bulk of your time in the work that adds the most value and eliminate or outsource the rest because you don't need to do it, make the machines by elaborate by leveraging automation in their workflows teams, minimize manual work and reclaim that time for innovation and maintain that state of flow with development and collaboration. More importantly, their work is more enjoyable because they're not wasting the time doing the things that the machines or robots can do for them. >>And I remember what I said at the beginning. Many of us want to be efficient, heck even lazy. So why would I spend my time doing something I can automate? Now you can read more about this research behind the art behind this at October set, get hub.com, which also includes a lot of other cool info about the open source ecosystem and how it's evolving. Speaking of the open source ecosystem we at get hub are so honored to be the home of more than 65 million developers who build software together for everywhere across the globe. Today, we're seeing software development taking shape as the world's largest team sport, where development teams collaborate, build and ship products. It's no longer a solo effort like it was for me. You don't have to take my word for it. Check out this globe. This globe shows real data. Every speck of light you see here represents a contribution to an open source project, somewhere on earth. >>These arts reach across continents, cultures, and other divides. It's distributed collaboration at its finest. 20 years ago, we had no concept of dev ops, SecOps and lots, or the new ops that are going to be happening. But today's development and ops teams are connected like ever before. This is only going to continue to evolve at a rapid pace, especially as we continue to empower the next hundred million developers, automation helps us focus on what's important and to greatly accelerate innovation. Just this past year, we saw some of the most groundbreaking technological advancements and achievements I'll say ever, including critical COVID-19 vaccine trials, as well as the first power flight on Mars. This past month, these breakthroughs were only possible because of the interconnected collaborative open source communities on get hub and the amazing tools and workflows that empower us all to create and innovate. Let's continue building, integrating, and automating. So we collectively can give developers the experience. They deserve all of the automation and beautiful eye UIs that we can muster so they can continue to build the things that truly do change the world. Thank you again for having me today, Dr. Khan, it has been a pleasure to be here with all you nerds. >>Hello. I'm Justin. Komack lovely to see you here. Talking to developers, their world is getting much more complex. Developers are being asked to do everything security ops on goal data analysis, all being put on the rockers. Software's eating the world. Of course, and this all make sense in that view, but they need help. One team. I told you it's shifted all our.net apps to run on Linux from windows, but their developers found the complexity of Docker files based on the Linux shell scripts really difficult has helped make these things easier for your teams. Your ones collaborate more in a virtual world, but you've asked us to make this simpler and more lightweight. You, the developers have asked for a paved road experience. You want things to just work with a simple options to be there, but it's not just the paved road. You also want to be able to go off-road and do interesting and different things. >>Use different components, experiments, innovate as well. We'll always offer you both those choices at different times. Different developers want different things. It may shift for ones the other paved road or off road. Sometimes you want reliability, dependability in the zone for day to day work, but sometimes you have to do something new, incorporate new things in your pipeline, build applications for new places. Then you knew those off-road abilities too. So you can really get under the hood and go and build something weird and wonderful and amazing. That gives you new options. Talk as an independent choice. We don't own the roads. We're not pushing you into any technology choices because we own them. We're really supporting and driving open standards, such as ISEI working opensource with the CNCF. We want to help you get your applications from your laptops, the clouds, and beyond, even into space. >>Let's talk about the key focus areas, that frame, what DACA is doing going forward. These are simplicity, sharing, flexibility, trusted content and care supply chain compared to building where the underlying kernel primitives like namespaces and Seagraves the original Docker CLI was just amazing Docker engine. It's a magical experience for everyone. It really brought those innovations and put them in a world where anyone would use that, but that's not enough. We need to continue to innovate. And it was trying to get more done faster all the time. And there's a lot more we can do. We're here to take complexity away from deeply complicated underlying things and give developers tools that are just amazing and magical. One of the area we haven't done enough and make things magical enough that we're really planning around now is that, you know, Docker images, uh, they're the key parts of your application, but you know, how do I do something with an image? How do I, where do I attach volumes with this image? What's the API. Whereas the SDK for this image, how do I find an example or docs in an API driven world? Every bit of software should have an API and an API description. And our vision is that every container should have this API description and the ability for you to understand how to use it. And it's all a seamless thing from, you know, from your code to the cloud local and remote, you can, you can use containers in this amazing and exciting way. >>One thing I really noticed in the last year is that companies that started off remote fast have constant collaboration. They have zoom calls, apron all day terminals, shattering that always working together. Other teams are really trying to learn how to do this style because they didn't start like that. We used to walk around to other people's desks or share services on the local office network. And it's very difficult to do that anymore. You want sharing to be really simple, lightweight, and informal. Let me try your container or just maybe let's collaborate on this together. Um, you know, fast collaboration on the analysts, fast iteration, fast working together, and he wants to share more. You want to share how to develop environments, not just an image. And we all work by seeing something someone else in our team is doing saying, how can I do that too? I can, I want to make that sharing really, really easy. Ben's going to talk about this more in the interest of one minute. >>We know how you're excited by apple. Silicon and gravis are not excited because there's a new architecture, but excited because it's faster, cooler, cheaper, better, and offers new possibilities. The M one support was the most asked for thing on our public roadmap, EFA, and we listened and share that we see really exciting possibilities, usership arm applications, all the way from desktop to production. We know that you all use different clouds and different bases have deployed to, um, you know, we work with AWS and Azure and Google and more, um, and we want to help you ship on prime as well. And we know that you use huge number of languages and the containers help build applications that use different languages for different parts of the application or for different applications, right? You can choose the best tool. You have JavaScript hat or everywhere go. And re-ask Python for data and ML, perhaps getting excited about WebAssembly after hearing about a cube con, you know, there's all sorts of things. >>So we need to make that as easier. We've been running the whole month of Python on the blog, and we're doing a month of JavaScript because we had one specific support about how do I best put this language into production of that language into production. That detail is important for you. GPS have been difficult to use. We've added GPS suppose in desktop for windows, but we know there's a lot more to do to make the, how multi architecture, multi hardware, multi accelerator world work better and also securely. Um, so there's a lot more work to do to support you in all these things you want to do. >>How do we start building a tenor has applications, but it turns out we're using existing images as components. I couldn't assist survey earlier this year, almost half of container image usage was public images rather than private images. And this is growing rapidly. Almost all software has open source components and maybe 85% of the average application is open source code. And what you're doing is taking whole container images as modules in your application. And this was always the model with Docker compose. And it's a model that you're already et cetera, writing you trust Docker, official images. We know that they might go to 25% of poles on Docker hub and Docker hub provides you the widest choice and the best support that trusted content. We're talking to people about how to make this more helpful. We know, for example, that winter 69 four is just showing us as support, but the image doesn't yet tell you that we're working with canonical to improve messaging from specific images about left lifecycle and support. >>We know that you need more images, regularly updated free of vulnerabilities, easy to use and discover, and Donnie and Marie neuro, going to talk about that more this last year, the solar winds attack has been in the, in the news. A lot, the software you're using and trusting could be compromised and might be all over your organization. We need to reduce the risk of using vital open-source components. We're seeing more software supply chain attacks being targeted as the supply chain, because it's often an easier place to attack and production software. We need to be able to use this external code safely. We need to, everyone needs to start from trusted sources like photography images. They need to scan for known vulnerabilities using Docker scan that we built in partnership with sneak and lost DockerCon last year, we need just keep updating base images and dependencies, and we'll, we're going to help you have the control and understanding about your images that you need to do this. >>And there's more, we're also working on the nursery V2 project in the CNCF to revamp container signings, or you can tell way or software comes from we're working on tooling to make updates easier, and to help you understand and manage all the principals carrier you're using security is a growing concern for all of us. It's really important. And we're going to help you work with security. We can't achieve all our dreams, whether that's space travel or amazing developer products ever see without deep partnerships with our community to cloud is RA and the cloud providers aware most of you ship your occasion production and simple routes that take your work and deploy it easily. Reliably and securely are really important. Just get into production simply and easily and securely. And we've done a bunch of work on that. And, um, but we know there's more to do. >>The CNCF on the open source cloud native community are an amazing ecosystem of creators and lovely people creating an amazing strong community and supporting a huge amount of innovation has its roots in the container ecosystem and his dreams beyond that much of the innovation is focused around operate experience so far, but developer experience is really a growing concern in that community as well. And we're really excited to work on that. We also uses appraiser tool. Then we know you do, and we know that you want it to be easier to use in your environment. We just shifted Docker hub to work on, um, Kubernetes fully. And, um, we're also using many of the other projects are Argo from atheists. We're spending a lot of time working with Microsoft, Amazon right now on getting natural UV to ready to ship in the next few. That's a really detailed piece of collaboration we've been working on for a long term. Long time is really important for our community as the scarcity of the container containers and, um, getting content for you, working together makes us stronger. Our community is made up of all of you have. Um, it's always amazing to be reminded of that as a huge open source community that we already proud to work with. It's an amazing amount of innovation that you're all creating and where perhaps it, what with you and share with you as well. Thank you very much. And thank you for being here. >>Really excited to talk to you today and share more about what Docker is doing to help make you faster, make your team faster and turn your application delivery into something that makes you a 10 X team. What we're hearing from you, the developers using Docker everyday fits across three common themes that we hear consistently over and over. We hear that your time is super important. It's critical, and you want to move faster. You want your tools to get out of your way, and instead to enable you to accelerate and focus on the things you want to be doing. And part of that is that finding great content, great application components that you can incorporate into your apps to move faster is really hard. It's hard to discover. It's hard to find high quality content that you can trust that, you know, passes your test and your configuration needs. >>And it's hard to create good content as well. And you're looking for more safety, more guardrails to help guide you along that way so that you can focus on creating value for your company. Secondly, you're telling us that it's a really far to collaborate effectively with your team and you want to do more, to work more effectively together to help your tools become more and more seamless to help you stay in sync, both with yourself across all of your development environments, as well as with your teammates so that you can more effectively collaborate together. Review each other's work, maintain things and keep them in sync. And finally, you want your applications to run consistently in every single environment, whether that's your local development environment, a cloud-based development environment, your CGI pipeline, or the cloud for production, and you want that micro service to provide that consistent experience everywhere you go so that you have similar tools, similar environments, and you don't need to worry about things getting in your way, but instead things make it easy for you to focus on what you wanna do and what Docker is doing to help solve all of these problems for you and your colleagues is creating a collaborative app dev platform. >>And this collaborative application development platform consists of multiple different pieces. I'm not going to walk through all of them today, but the overall view is that we're providing all the tooling you need from the development environment, to the container images, to the collaboration services, to the pipelines and integrations that enable you to focus on making your applications amazing and changing the world. If we start zooming on a one of those aspects, collaboration we hear from developers regularly is that they're challenged in synchronizing their own setups across environments. They want to be able to duplicate the setup of their teammates. Look, then they can easily get up and running with the same applications, the same tooling, the same version of the same libraries, the same frameworks. And they want to know if their applications are good before they're ready to share them in an official space. >>They want to collaborate on things before they're done, rather than feeling like they have to officially published something before they can effectively share it with others to work on it, to solve this. We're thrilled today to announce Docker, dev environments, Docker, dev environments, transform how your team collaborates. They make creating, sharing standardized development environments. As simple as a Docker poll, they make it easy to review your colleagues work without affecting your own work. And they increase the reproducibility of your own work and decreased production issues in doing so because you've got consistent environments all the way through. Now, I'm going to pass it off to our principal product manager, Ben Gotch to walk you through more detail on Docker dev environments. >>Hi, I'm Ben. I work as a principal program manager at DACA. One of the areas that doc has been looking at to see what's hard today for developers is sharing changes that you make from the inner loop where the inner loop is a better development, where you write code, test it, build it, run it, and ultimately get feedback on those changes before you merge them and try and actually ship them out to production. Most amount of us build this flow and get there still leaves a lot of challenges. People need to jump between branches to look at each other's work. Independence. Dependencies can be different when you're doing that and doing this in this new hybrid wall of work. Isn't any easier either the ability to just save someone, Hey, come and check this out. It's become much harder. People can't come and sit down at your desk or take your laptop away for 10 minutes to just grab and look at what you're doing. >>A lot of the reason that development is hard when you're remote, is that looking at changes and what's going on requires more than just code requires all the dependencies and everything you've got set up and that complete context of your development environment, to understand what you're doing and solving this in a remote first world is hard. We wanted to look at how we could make this better. Let's do that in a way that let you keep working the way you do today. Didn't want you to have to use a browser. We didn't want you to have to use a new idea. And we wanted to do this in a way that was application centric. We wanted to let you work with all the rest of the application already using C for all the services and all those dependencies you need as part of that. And with that, we're excited to talk more about docket developer environments, dev environments are new part of the Docker experience that makes it easier you to get started with your whole inner leap, working inside a container, then able to share and collaborate more than just the code. >>We want it to enable you to share your whole modern development environment, your whole setup from DACA, with your team on any operating system, we'll be launching a limited beta of dev environments in the coming month. And a GA dev environments will be ID agnostic and supporting composts. This means you'll be able to use an extend your existing composed files to create your own development environment in whatever idea, working in dev environments designed to be local. First, they work with Docker desktop and say your existing ID, and let you share that whole inner loop, that whole development context, all of your teammates in just one collect. This means if you want to get feedback on the working progress change or the PR it's as simple as opening another idea instance, and looking at what your team is working on because we're using compose. You can just extend your existing oppose file when you're already working with, to actually create this whole application and have it all working in the context of the rest of the services. >>So it's actually the whole environment you're working with module one service that doesn't really understand what it's doing alone. And with that, let's jump into a quick demo. So you can see here, two dev environments up and running. First one here is the same container dev environment. So if I want to go into that, let's see what's going on in the various code button here. If that one open, I can get straight into my application to start making changes inside that dev container. And I've got all my dependencies in here, so I can just run that straight in that second application I have here is one that's opened up in compose, and I can see that I've also got my backend, my front end and my database. So I've got all my services running here. So if I want, I can open one or more of these in a dev environment, meaning that that container has the context that dev environment has the context of the whole application. >>So I can get back into and connect to all the other services that I need to test this application properly, all of them, one unit. And then when I've made my changes and I'm ready to share, I can hit my share button type in the refund them on to share that too. And then give that image to someone to get going, pick that up and just start working with that code and all my dependencies, simple as putting an image, looking ahead, we're going to be expanding development environments, more of your dependencies for the whole developer worst space. We want to look at backing up and letting you share your volumes to make data science and database setups more repeatable and going. I'm still all of this under a single workspace for your team containing images, your dev environments, your volumes, and more we've really want to allow you to create a fully portable Linux development environment. >>So everyone you're working with on any operating system, as I said, our MVP we're coming next month. And that was for vs code using their dev container primitive and more support for other ideas. We'll follow to find out more about what's happening and what's coming up next in the future of this. And to actually get a bit of a deeper dive in the experience. Can we check out the talk I'm doing with Georgie and girl later on today? Thank you, Ben, amazing story about how Docker is helping to make developer teams more collaborative. Now I'd like to talk more about applications while the dev environment is like the workbench around what you're building. The application itself has all the different components, libraries, and frameworks, and other code that make up the application itself. And we hear developers saying all the time things like, how do they know if their images are good? >>How do they know if they're secure? How do they know if they're minimal? How do they make great images and great Docker files and how do they keep their images secure? And up-to-date on every one of those ties into how do I create more trust? How do I know that I'm building high quality applications to enable you to do this even more effectively than today? We are pleased to announce the DACA verified polisher program. This broadens trusted content by extending beyond Docker official images, to give you more and more trusted building blocks that you can incorporate into your applications. It gives you confidence that you're getting what you expect because Docker verifies every single one of these publishers to make sure they are who they say they are. This improves our secure supply chain story. And finally it simplifies your discovery of the best building blocks by making it easy for you to find things that you know, you can trust so that you can incorporate them into your applications and move on and on the right. You can see some examples of the publishers that are involved in Docker, official images and our Docker verified publisher program. Now I'm pleased to introduce you to marina. Kubicki our senior product manager who will walk you through more about what we're doing to create a better experience for you around trust. >>Thank you, Dani, >>Mario Andretti, who is a famous Italian sports car driver. One said that if everything feels under control, you're just not driving. You're not driving fast enough. Maya Andretti is not a software developer and a software developers. We know that no matter how fast we need to go in order to drive the innovation that we're working on, we can never allow our applications to spin out of control and a Docker. As we continue talking to our, to the developers, what we're realizing is that in order to reach that speed, the developers are the, the, the development community is looking for the building blocks and the tools that will, they will enable them to drive at the speed that they need to go and have the trust in those building blocks. And in those tools that they will be able to maintain control over their applications. So as we think about some of the things that we can do to, to address those concerns, uh, we're realizing that we can pursue them in a number of different venues, including creating reliable content, including creating partnerships that expands the options for the reliable content. >>Um, in order to, in a we're looking at creating integrations, no link security tools, talk about the reliable content. The first thing that comes to mind are the Docker official images, which is a program that we launched several years ago. And this is a set of curated, actively maintained, open source images that, uh, include, uh, operating systems and databases and programming languages. And it would become immensely popular for, for, for creating the base layers of, of the images of, of the different images, images, and applications. And would we realizing that, uh, many developers are, instead of creating something from scratch, basically start with one of the official images for their basis, and then build on top of that. And this program has become so popular that it now makes up a quarter of all of the, uh, Docker poles, which essentially ends up being several billion pulse every single month. >>As we look beyond what we can do for the open source. Uh, we're very ability on the open source, uh, spectrum. We are very excited to announce that we're launching the Docker verified publishers program, which is continuing providing the trust around the content, but now working with, uh, some of the industry leaders, uh, in multiple, in multiple verticals across the entire technology technical spec, it costs entire, uh, high tech in order to provide you with more options of the images that you can use for building your applications. And it still comes back to trust that when you are searching for content in Docker hub, and you see the verified publisher badge, you know, that this is, this is the content that, that is part of the, that comes from one of our partners. And you're not running the risk of pulling the malicious image from an employee master source. >>As we look beyond what we can do for, for providing the reliable content, we're also looking at some of the tools and the infrastructure that we can do, uh, to create a security around the content that you're creating. So last year at the last ad, the last year's DockerCon, we announced partnership with sneak. And later on last year, we launched our DACA, desktop and Docker hub vulnerability scans that allow you the options of writing scans in them along multiple points in your dev cycle. And in addition to providing you with information on the vulnerability on, on the vulnerabilities, in, in your code, uh, it also provides you with a guidance on how to re remediate those vulnerabilities. But as we look beyond the vulnerability scans, we're also looking at some of the other things that we can do, you know, to, to, to, uh, further ensure that the integrity and the security around your images, your images, and with that, uh, later on this year, we're looking to, uh, launch the scope, personal access tokens, and instead of talking about them, I will simply show you what they look like. >>So if you can see here, this is my page in Docker hub, where I've created a four, uh, tokens, uh, read-write delete, read, write, read only in public read in public creeper read only. So, uh, earlier today I went in and I, I logged in, uh, with my read only token. And when you see, when I'm going to pull an image, it's going to allow me to pull an image, not a problem success. And then when I do the next step, I'm going to ask to push an image into the same repo. Uh, would you see is that it's going to give me an error message saying that they access is denied, uh, because there is an additional authentication required. So these are the things that we're looking to add to our roadmap. As we continue thinking about the things that we can do to provide, um, to provide additional building blocks, content, building blocks, uh, and, and, and tools to build the trust so that our DACA developer and skinned code faster than Mario Andretti could ever imagine. Uh, thank you to >>Thank you, marina. It's amazing what you can do to improve the trusted content so that you can accelerate your development more and move more quickly, move more collaboratively and build upon the great work of others. Finally, we hear over and over as that developers are working on their applications that they're looking for, environments that are consistent, that are the same as production, and that they want their applications to really run anywhere, any environment, any architecture, any cloud one great example is the recent announcement of apple Silicon. We heard from developers on uproar that they needed Docker to be available for that architecture before they could add those to it and be successful. And we listened. And based on that, we are pleased to share with you Docker, desktop on apple Silicon. This enables you to run your apps consistently anywhere, whether that's developing on your team's latest dev hardware, deploying an ARM-based cloud environments and having a consistent architecture across your development and production or using multi-year architecture support, which enables your whole team to collaborate on its application, using private repositories on Docker hub, and thrilled to introduce you to Hughie cower, senior director for product management, who will walk you through more of what we're doing to create a great developer experience. >>Senior director of product management at Docker. And I'd like to jump straight into a demo. This is the Mac mini with the apple Silicon processor. And I want to show you how you can now do an end-to-end arm workflow from my M one Mac mini to raspberry PI. As you can see, we have vs code and Docker desktop installed on a, my, the Mac mini. I have a small example here, and I have a raspberry PI three with an led strip, and I want to turn those LEDs into a moving rainbow. This Dockerfile here, builds the application. We build the image with the Docker, build X command to make the image compatible for all raspberry pies with the arm. 64. Part of this build is built with the native power of the M one chip. I also add the push option to easily share the image with my team so they can give it a try to now Dr. >>Creates the local image with the application and uploads it to Docker hub after we've built and pushed the image. We can go to Docker hub and see the new image on Docker hub. You can also explore a variety of images that are compatible with arm processors. Now let's go to the raspberry PI. I have Docker already installed and it's running Ubuntu 64 bit with the Docker run command. I can run the application and let's see what will happen from there. You can see Docker is downloading the image automatically from Docker hub and when it's running, if it's works right, there are some nice colors. And with that, if we have an end-to-end workflow for arm, where continuing to invest into providing you a great developer experience, that's easy to install. Easy to get started with. As you saw in the demo, if you're interested in the new Mac, mini are interested in developing for our platforms in general, we've got you covered with the same experience you've come to expect from Docker with over 95,000 arm images on hub, including many Docker official images. >>We think you'll find what you're looking for. Thank you again to the community that helped us to test the tech previews. We're so delighted to hear when folks say that the new Docker desktop for apple Silicon, it just works for them, but that's not all we've been working on. As Dani mentioned, consistency of developer experience across environments is so important. We're introducing composed V2 that makes compose a first-class citizen in the Docker CLI you no longer need to install a separate composed biter in order to use composed, deploying to production is simpler than ever with the new compose integration that enables you to deploy directly to Amazon ECS or Azure ACI with the same methods you use to run your application locally. If you're interested in running slightly different services, when you're debugging versus testing or, um, just general development, you can manage that all in one place with the new composed service to hear more about what's new and Docker desktop, please join me in the three 15 breakout session this afternoon. >>And now I'd love to tell you a bit more about bill decks and convince you to try it. If you haven't already it's our next gen build command, and it's no longer experimental as shown in the demo with built X, you'll be able to do multi architecture builds, share those builds with your team and the community on Docker hub. With build X, you can speed up your build processes with remote caches or build all the targets in your composed file in parallel with build X bake. And there's so much more if you're using Docker, desktop or Docker, CE you can use build X checkout tonus is talk this afternoon at three 45 to learn more about build X. And with that, I hope everyone has a great Dr. Khan and back over to you, Donnie. >>Thank you UA. It's amazing to hear about what we're doing to create a better developer experience and make sure that Docker works everywhere you need to work. Finally, I'd like to wrap up by showing you everything that we've announced today and everything that we've done recently to make your lives better and give you more and more for the single price of your Docker subscription. We've announced the Docker verified publisher program we've announced scoped personal access tokens to make it easier for you to have a secure CCI pipeline. We've announced Docker dev environments to improve your collaboration with your team. Uh, we shared with you Docker, desktop and apple Silicon, to make sure that, you know, Docker runs everywhere. You need it to run. And we've announced Docker compose version two, finally making it a first-class citizen amongst all the other great Docker tools. And we've done so much more recently as well from audit logs to advanced image management, to compose service profiles, to improve where you can run Docker more easily. >>Finally, as we look forward, where we're headed in the upcoming year is continuing to invest in these themes of helping you build, share, and run modern apps more effectively. We're going to be doing more to help you create a secure supply chain with which only grows more and more important as time goes on. We're going to be optimizing your update experience to make sure that you can easily understand the current state of your application, all its components and keep them all current without worrying about breaking everything as you're doing. So we're going to make it easier for you to synchronize your work. Using cloud sync features. We're going to improve collaboration through dev environments and beyond, and we're going to do make it easy for you to run your microservice in your environments without worrying about things like architecture or differences between those environments. Thank you so much. I'm thrilled about what we're able to do to help make your lives better. And now you're going to be hearing from one of our customers about what they're doing to launch their business with Docker >>I'm Matt Falk, I'm the head of engineering and orbital insight. And today I want to talk to you a little bit about data from space. So who am I like many of you, I'm a software developer and a software developer about seven companies so far, and now I'm a head of engineering. So I spend most of my time doing meetings, but occasionally I'll still spend time doing design discussions, doing code reviews. And in my free time, I still like to dabble on things like project oiler. So who's Oberlin site. What do we do? Portal insight is a large data supplier and analytics provider where we take data geospatial data anywhere on the planet, any overhead sensor, and translate that into insights for the end customer. So specifically we have a suite of high performance, artificial intelligence and machine learning analytics that run on this geospatial data. >>And we build them to specifically determine natural and human service level activity anywhere on the planet. What that really means is we take any type of data associated with a latitude and longitude and we identify patterns so that we can, so we can detect anomalies. And that's everything that we do is all about identifying those patterns to detect anomalies. So more specifically, what type of problems do we solve? So supply chain intelligence, this is one of the use cases that we we'd like to talk about a lot. It's one of our main primary verticals that we go after right now. And as Scott mentioned earlier, this had a huge impact last year when COVID hit. So specifically supply chain intelligence is all about identifying movement patterns to and from operating facilities to identify changes in those supply chains. How do we do this? So for us, we can do things where we track the movement of trucks. >>So identifying trucks, moving from one location to another in aggregate, same thing we can do with foot traffic. We can do the same thing for looking at aggregate groups of people moving from one location to another and analyzing their patterns of life. We can look at two different locations to determine how people are moving from one location to another, or going back and forth. All of this is extremely valuable for detecting how a supply chain operates and then identifying the changes to that supply chain. As I said last year with COVID, everything changed in particular supply chains changed incredibly, and it was hugely important for customers to know where their goods or their products are coming from and where they were going, where there were disruptions in their supply chain and how that's affecting their overall supply and demand. So to use our platform, our suite of tools, you can start to gain a much better picture of where your suppliers or your distributors are going from coming from or going to. >>So what's our team look like? So my team is currently about 50 engineers. Um, we're spread into four different teams and the teams are structured like this. So the first team that we have is infrastructure engineering and this team largely deals with deploying our Dockers using Kubernetes. So this team is all about taking Dockers, built by other teams, sometimes building the Dockers themselves and putting them into our production system, our platform engineering team, they produce these microservices. So they produce microservice, Docker images. They develop and test with them locally. Their entire environments are dockerized. They produce these doctors, hand them over to him for infrastructure engineering to be deployed. Similarly, our product engineering team does the same thing. They develop and test with Dr. Locally. They also produce a suite of Docker images that the infrastructure team can then deploy. And lastly, we have our R and D team, and this team specifically produces machine learning algorithms using Nvidia Docker collectively, we've actually built 381 Docker repositories and 14 million. >>We've had 14 million Docker pools over the lifetime of the company, just a few stats about us. Um, but what I'm really getting to here is you can see actually doctors becoming almost a form of communication between these teams. So one of the paradigms in software engineering that you're probably familiar with encapsulation, it's really helpful for a lot of software engineering problems to break the problem down, isolate the different pieces of it and start building interfaces between the code. This allows you to scale different pieces of the platform or different pieces of your code in different ways that allows you to scale up certain pieces and keep others at a smaller level so that you can meet customer demands. And for us, one of the things that we can largely do now is use Dockers as that interface. So instead of having an entire platform where all teams are talking to each other, and everything's kind of, mishmashed in a monolithic application, we can now say this team is only able to talk to this team by passing over a particular Docker image that defines the interface of what needs to be built before it passes to the team and really allows us to scalp our development and be much more efficient. >>Also, I'd like to say we are hiring. Um, so we have a number of open roles. We have about 30 open roles in our engineering team that we're looking to fill by the end of this year. So if any of this sounds really interesting to you, please reach out after the presentation. >>So what does our platform do? Really? Our platform allows you to answer any geospatial question, and we do this at three different inputs. So first off, where do you want to look? So we did this as what we call an AOI or an area of interest larger. You can think of this as a polygon drawn on the map. So we have a curated data set of almost 4 million AOIs, which you can go and you can search and use for your analysis, but you're also free to build your own. Second question is what you want to look for. We do this with the more interesting part of our platform of our machine learning and AI capabilities. So we have a suite of algorithms that automatically allow you to identify trucks, buildings, hundreds of different types of aircraft, different types of land use, how many people are moving from one location to another different locations that people in a particular area are moving to or coming from all of these different analyses or all these different analytics are available at the click of a button, and then determine what you want to look for. >>Lastly, you determine when you want to find what you're looking for. So that's just, uh, you know, do you want to look for the next three hours? Do you want to look for the last week? Do you want to look every month for the past two, whatever the time cadence is, you decide that you hit go and out pops a time series, and that time series tells you specifically where you want it to look what you want it to look for and how many, or what percentage of the thing you're looking for appears in that area. Again, we do all of this to work towards patterns. So we use all this data to produce a time series from there. We can look at it, determine the patterns, and then specifically identify the anomalies. As I mentioned with supply chain, this is extremely valuable to identify where things change. So we can answer these questions, looking at a particular operating facility, looking at particular, what is happening with the level of activity is at that operating facility where people are coming from, where they're going to, after visiting that particular facility and identify when and where that changes here, you can just see it's a picture of our platform. It's actually showing all the devices in Manhattan, um, over a period of time. And it's more of a heat map view. So you can actually see the hotspots in the area. >>So really the, and this is the heart of the talk, but what happened in 2020? So for men, you know, like many of you, 2020 was a difficult year COVID hit. And that changed a lot of what we're doing, not from an engineering perspective, but also from an entire company perspective for us, the motivation really became to make sure that we were lowering our costs and increasing innovation simultaneously. Now those two things often compete with each other. A lot of times you want to increase innovation, that's going to increase your costs, but the challenge last year was how to do both simultaneously. So here's a few stats for you from our team. In Q1 of last year, we were spending almost $600,000 per month on compute costs prior to COVID happening. That wasn't hugely a concern for us. It was a lot of money, but it wasn't as critical as it was last year when we really needed to be much more efficient. >>Second one is flexibility for us. We were deployed on a single cloud environment while we were cloud thought ready, and that was great. We want it to be more flexible. We want it to be on more cloud environments so that we could reach more customers. And also eventually get onto class side networks, extending the base of our customers as well from a custom analytics perspective. This is where we get into our traction. So last year, over the entire year, we computed 54,000 custom analytics for different users. We wanted to make sure that this number was steadily increasing despite us trying to lower our costs. So we didn't want the lowering cost to come as the sacrifice of our user base. Lastly, of particular percentage here that I'll say definitely needs to be improved is 75% of our projects never fail. So this is where we start to get into a bit of stability of our platform. >>Now I'm not saying that 25% of our projects fail the way we measure this is if you have a particular project or computation that runs every day and any one of those runs sale account, that is a failure because from an end-user perspective, that's an issue. So this is something that we know we needed to improve on and we needed to grow and make our platform more stable. I'm going to something that we really focused on last year. So where are we now? So now coming out of the COVID valley, we are starting to soar again. Um, we had, uh, back in April of last year, we had the entire engineering team. We actually paused all development for about four weeks. You had everyone focused on reducing our compute costs in the cloud. We got it down to 200 K over the period of a few months. >>And for the next 12 months, we hit that number every month. This is huge for us. This is extremely important. Like I said, in the COVID time period where costs and operating efficiency was everything. So for us to do that, that was a huge accomplishment last year and something we'll keep going forward. One thing I would actually like to really highlight here, two is what allowed us to do that. So first off, being in the cloud, being able to migrate things like that, that was one thing. And we were able to use there's different cloud services in a more particular, in a more efficient way. We had a very detailed tracking of how we were spending things. We increased our data retention policies. We optimized our processing. However, one additional piece was switching to new technologies on, in particular, we migrated to get lab CICB. >>Um, and this is something that the costs we use Docker was extremely, extremely easy. We didn't have to go build new new code containers or repositories or change our code in order to do this. We were simply able to migrate the containers over and start using a new CIC so much. In fact, that we were able to do that migration with three engineers in just two weeks from a cloud environment and flexibility standpoint, we're now operating in two different clouds. We were able to last night, I've over the last nine months to operate in the second cloud environment. And again, this is something that Docker helped with incredibly. Um, we didn't have to go and build all new interfaces to all new, different services or all different tools in the next cloud provider. All we had to do was build a base cloud infrastructure that ups agnostic the way, all the different details of the cloud provider. >>And then our doctors just worked. We can move them to another environment up and running, and our platform was ready to go from a traction perspective. We're about a third of the way through the year. At this point, we've already exceeded the amount of customer analytics we produce last year. And this is thanks to a ton more albums, that whole suite of new analytics that we've been able to build over the past 12 months and we'll continue to build going forward. So this is really, really great outcome for us because we were able to show that our costs are staying down, but our analytics and our customer traction, honestly, from a stability perspective, we improved from 75% to 86%, not quite yet 99 or three nines or four nines, but we are getting there. Um, and this is actually thanks to really containerizing and modularizing different pieces of our platform so that we could scale up in different areas. This allowed us to increase that stability. This piece of the code works over here, toxin an interface to the rest of the system. We can scale this piece up separately from the rest of the system, and that allows us much more easily identify issues in the system, fix those and then correct the system overall. So basically this is a summary of where we were last year, where we are now and how much more successful we are now because of the issues that we went through last year and largely brought on by COVID. >>But that this is just a screenshot of the, our, our solution actually working on supply chain. So this is in particular, it is showing traceability of a distribution warehouse in salt lake city. It's right in the center of the screen here. You can see the nice kind of orange red center. That's a distribution warehouse and all the lines outside of that, all the dots outside of that are showing where people are, where trucks are moving from that location. So this is really helpful for supply chain companies because they can start to identify where their suppliers are, are coming from or where their distributors are going to. So with that, I want to say, thanks again for following along and enjoy the rest of DockerCon.

>>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 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 BTC company. We're live today really live TV, which is the heritage of the Cuban. 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 Fribourg 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. Yes. As you said, the Bio 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 in 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 five years ago. It >>was announced at the end of 2016, and we actually started operations in 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 off his building and MP labs. And very quickly we had something running about from anything. 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, um, very 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 road, 150,000 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 a testing system that will serve those departments. So then we decided that it was unnecessary to keep going with testing in the other biopsy that would shut down, >>right? Thank you for that. Now, Now, Philip, you What you do is mind melting. You basically helped keep the world safe. Maybe you describe a little bit more about silver side 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 a port 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 can do things like but 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 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. >>You do both Zito shares. 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 outside 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 up 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 in stem, we need mawr underrepresented women, minorities, etcetera. We were just talking to John her stock and integrate Grayson 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, you know, diverse base and 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 funnels 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 fruits 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 our engineering programs that sort of baked into the DNA and also are a big public school. And we have about 50% of the students are under the poverty line, and we should I mean, 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 and or the program and be successful, >>that's phenomenal. 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 ah 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 then would have been done previous technologies. Mhm. 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, uh, 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 there 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 forced march to digital. Thanks to cove it I think that's just gonna continue. Thio grow Raphael one. If you could describe the process that you used 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 teachers in the body. Um, and then it has the set of platforms. Um, mind is one of them by engineering that are all technology. Read it. 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 scientists on. We have a genomics platform. That is all about sequencing DNA in our DNA. Um, and then an advanced microscopy. It's all about developing technologies, uh, to look at things with advanced microscopes and the little technologies to marry computation on microscope. So, um, the scientists said 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. I 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, and it's being used to purify all these different important proteins in the cove. It virus the SARS cov to virus on Dwyer, 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. 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, God s o mat. I mean, you gotta be listening to this in thinking about, Okay? Some. 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 that just have I 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 that 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 do 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 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 Hammond Barker. The greatest minds of my generation are trying to figure out how to get people to click on ads. E. I think we're really generally generationally finally, at the point where you know young students and engineering and really you know it 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. 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. Um, 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 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 remembers, what they are, the person left and now nobody knows which version is the right one m s 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 personal account 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. >>Rafael, 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 were they 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 serving 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, their 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, Phillip. What's your experience been? Maybe you could take us through your journey with on 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 and 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 will have the speed of technology progression. I was explaining to some young guns the other day how e used to have a daytime er and that was my life. And if I lost that day, timer, I was dead. And I don't know how we weigh existed without, you know, Google Maps. Eso did we get anywhere? I don't know, but, uh, but so So, Matt, you know, it's interesting to think about, um, 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 It's 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 in, um, 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 shoot 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 the cat. And there's so much about it, E >>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 or Rafael anything. Your 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 there's a dream for kids Thio to be able to do this. And, um, yeah, there's so many other technologies coming on, like Arduino and 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 Way >>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 and support world right ahead, which was cool, but also a 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. It's an 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 gonna 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. And I think he 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, and 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 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 a modern era. And so that's, you know, 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 it 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 a PTC s that worked with us. Really well, so I'm not complaining. There. You there? >>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. Um, 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. >>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 comics necessities that regenerating the document takes a little longer than I would like to. It's not a serious issue, but anyway, 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 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 a helping address the challenge, But I'm gonna ask you the big, chewy question now, then would 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 can be applied to some of the the problems that that you all are passionate about? Big question. But 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 stem 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 they had? >>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 doing ableto pull together instead of pulling, pulling separately and to be able to spur the idea is onwards. So that's where I think the education side is really exciting. What Matt is doing and 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 shaped and 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. Andi, that'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 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 so super important, I think, for any of these efforts to improve, um, some of the hardest part was in the world from 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, that 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. Uh, 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 can. 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. What 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, uh, 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. 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 products 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 are 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 air going to result in, uh 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 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. You're 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

>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel and AWS. Yeah, welcome back to the Cubes. Live coverage of AWS reinvent 2020. It's virtual this year over three weeks. Next three weeks we're here on the ground, covering all the live action. Hundreds of videos Walter Wall coverage were virtual not in person this year. So we're bringing all the interviews remote. We have Deepak Singh, vice president of Compute Services. A range of things within Amazon's world. He's the container guy. He knows all what's going on with open source. Deepak, great to see you again. Sorry, we can't be in person, but that's the best we could do. Thanks for coming on. And big keynote news all year all over the keynote. Your DNA is everywhere in the keynote. Thanks for coming on. >>Yeah. Now, no thanks for having me again. It's always great to be on the Cube. Unfortunately, not sitting in the middle of the floral arrangement, which I kind of miss. I know, but it waas great morning for us. We had a number of announcements in the container space and sort of adjacent to that in the developer and operator experience space about making it easy for people to adopt things like containers and serverless. So we're pretty excited about. And his keynote today and the rest agreement. >>It's interesting, You know, I've been following Amazon. Now start a three invent. I've been using Amazon since easy to started telling that garment that story. But you look like the mainstream market right now. This is a wake up call for Cloud. Um, mainly because the pandemic has been forced upon everybody. I talked to Andy about that he brought up in the keynote, but you start to get into the meat on the bone here. When you're saying OK, what does it really mean? The containers, the server Lis, Uh, the machine learning all kind of tied together with computers getting faster. So you see an absolute focus of infrastructures of service, which has been the bread and butter for Amazon web services. But now that kinda you know, connective tissue between where the machine learning kicks in. This is where I see containers and lambda and serve Earless really kicking ass and and really fill in the hole there because that's really been the innovation story and containers air all through that and the eks anywhere was to me the big announcement because it shows Amazon's wow vision of taking Amazon to the edge to the data center. This is a big important announcement. Could you explain E. K s anywhere? Because I think this is at the heart of where customers are looking to go to its where the puck is going. You're skating to where the puck is. Explain the importance of eks anywhere. >>Yeah, I'll actually step back. And I talked about a couple of things here on I think some of the other announcements you heard today like the smaller outposts, uh, you know, the one you and do you outpost skills are also part of that story. So I mean, if you look at it, AWS started thinking about what will it take for us to be successful in customers data centers a few years ago? Because customers still have data centers, they're still running there On our first step towards that Waas AWS in many ways benefits a lot from the way we build hardware. How what we do with nitro all the way to see C two instance types that we have. What we have a GPS on our post waas. Can we bring some of the core fundamental properties that AWS has into a customer data center, which then allowed PCs any KS and other AWS services to be run on output? Because that's how we run today. But what we started hearing from customers waas That was not enough for two reasons. One, not all of them have big data centers. They may want to run things on, you know, in a much smaller location. I like to think about things like oil rates of point of sale places, for they may have existing hardware that they still plan to use and intend to use for a very long time with the foundational building blocks easy to EBS. Those get difficult when we go on to hardware. That is not a W s hardware because be very much depend on that. But it containers we know it's possible. So we started thinking about what will it take for us to bring the best of AWS toe help customers run containers in their own data center, so I'll start with kubernetes, so with que binaries. People very often pick Kubernetes because they start continue rising inside their own data centers. And the best solution for them is Cuban Aires. So they learn it very well. They understand it, their organizations are built around it. But then they come to AWS and run any chaos. And while communities is communities, if you're running upstream, something that runs on Prem will run on AWS. They end up in two places in sort of two situations. One, they want to work with AWS. They want to get our support. They want to get our expertise second, most of them once they start running. Eks realized that we have a really nice operational posture of a D. K s. It's very reliable. It scales. They want to bring that same operational posture on Prem. So with the ts anywhere what we decided to do Waas start with the bits underlying eks. The eks destroyed that we announced today it's an open source communities distribution with some additional pieces that that we had some of the items that we use that can be run anywhere. They're not dependent on AWS. You don't even have be connected to a W s to use eks destro, but we will Patrick. We will updated. It's an open source project on get help. So that's a starting point that's available today. No, Over the next several months, what will add is all of the operational to link that we have from chaos, we will make available on premises so that people can operate the Cuban and these clusters on Prem just the way they do on AWS. And then we also announced the U. K s dashboard today which gives you visibility into our communities clusters on AWS, and we'll extend that so that any communities clusters you're running will end up on the dashboard to get a single view into what's going on. And that's the vision for eks anywhere, which is if you're running communities. We have our operational approach to running it. We have a set of tools that we're gonna that we have built. We want everybody to have access to the same tools and then moving from wherever you are to aws becomes super easy cause using the same tooling. We did something similar with the C s as well the DCs anywhere. But we did it a little bit differently. Where in the CSU was centralized control plane and all we want for you is to bring a CPU and memory. The demo for that actually runs in a bunch of raspberry PiS. So as long as you can install the C s agent and connect to an AWS region, you're good to go. So same problem. Different, slightly different solutions. But then we are customers fall into both buckets. So that's that's the general idea is when we say anywhere it means anywhere and we'll meet you there >>and then data centers running the case in the data center and cloud all good stuff. The other thing that came out I want you to explain is the importance of what Andy was getting to around this notion of the monolith versus Micro Services at one slightly put up. And that's where he was talking about Lambda and Containers for smaller compute loads. What does it mean? What was he talking about there? Explain what he means by that >>that Z kind of subtle and quite honestly, it's not unique to London containers. That's the way the world was going, except that with containers and with several functions with panda. You got this new small building blocks that allow you to do it that much better. So you know you can break your application off. In the smaller and smaller pieces, you can have teams that own each of those individual pieces each other pieces. Each of these services can be built using architecture that you secret, some of them makes sense. Purely service, land and media gateway. Other things you may want to run on the C s and target. Ah, third component. You may have be depending on open source ecosystem of applications. And there you may want to run in communities. So what you're doing is taking up what used to be one giant down, breaking up into a number of constituent pieces, each of which is built somewhat independently or at least can be. The problem now is how do you build the infrastructure where the platform teams of visibility in tow, what all the services are they being run properly? And also, how do you scale this within an organization, you can't train an entire organ. Communities overnight takes time similar with similarly with server list eso. That's kind of what I was talking about. That's where the world is going. And then to address that specific problem we announced AWS proton, uh, AWS program is essentially a service that allows you to bring all of these best practices together, allows the centralized team, for example, to decide what are the architectures they want to support. What are the tools that they want to support infrastructure escort, continuous delivery, observe ability. You know all the buzzwords, but that's where the world's going and then give them a single framework where they can deploy these and then the developers can come into self service. It's like I want to build a service using Lambda. I don't even learn how toe put it all together. I'm just gonna put my coat and pointed at this stock that might centralized team has built for me. All I need to do is put a couple of parameters, um, and I'm off to the races and not scale it to end, and it gives you the ability to manage also, So >>it's really kind of the building blocks pushing that out to the customer. I gotta ask you real quick on the proton. That's a fully managed service created best. Could you explain what that means for the developer customer? What's the bottom line? What's the benefit to >>them? So the biggest benefit of developers if they don't need to become an expert at every single technology out there, they can focus on writing application court, not have to learn how to crawl into structure and how pipelines are built and what are the best practices they could choose to do. So the developers, you know, modern and companies Sometimes developers wear two hats and the building off, the sort of underlying scaffolding and the and the build applications for application development. Now all you have to do is in writing an application code and then just go into a proton and say, This is architecture, that I'm going to choose your self, service it and then you're off to the races. If there's any underlying component that's changing, or any updates are coming on, put on it automatically take care off updates for you or give you a signal that says, Hey, the stock has to be updated first time to redeploy accord so you can do all of that in a very automated fashion. That's why everything is done. Infrastructures Gold. It's like a key, uh, infrastructure and told us, and continuous delivery of sort of key foundational principles off put on. And what they basically do is doing something that every company that we talked oh wants to do. But only a handful have the teams and the skill set to do that. It takes a lot of work and it takes ah lot of retraining. And now most companies don't need to do that. Or at least not in that here. So I think this is where the automation and manageability that brings makes life a lot easier. >>Yeah, a lot of drugs. No docker containers. They're very familiar with it. They want to use that. Whatever. Workflow. Quickly explain again to me so I can understand fully the benefit of the lamb container dynamic. Because what was the use case there? What's the problem that you solve? And what does it mean for the developer? What specifically is going on there? What's the What's the benefit? Why would I care? >>Yeah, eso I'll actually talked about one of the services that my team runs called it of your stature. AWS batch has a front time that's completely serverless. It's Lambda and FBI did play its back in the PCs running on the city right? That's the better the back end services run on their customers. Jobs in the running. Our customers are just like that. You know, we have many customers out there that are building services that are either completely service, but they fit that pattern. They are triggered by events. They're taking an event from something and then triggering a bunch of services or their triggering an action which is doing some data processing. And then they have these long running services, which almost universally in our running on containment. How do you bring all of this together into a single framework, as opposed to some people being experts on Lambda and some people being experts and containers? That's not how the real world works. So trying to put all of this because these teams do work together into a single framework was our goal, because that's what we see our customers doing, and I think they'll they'll do it. More related to that is the fact that Lambda now supports Dr Images containing images as a packaging format because a lot of companies have invested in tooling, toe build container images and our land. I can benefit from that as well. While customers get all the, you know, magic, The Lambda brings you >>a couple of years ago on this on the Cube. I shared this tweet out earlier in the week. Andy, we pressed and even services launches like, would you launch build Amazon on Lamb? Day says we probably would. And then he announced to me And he also I think you mentioned the keynote that half of Amazon's new APS are built on lambda. >>Yeah, that's good. This >>is a new generation of developers. >>Oh, absolutely. I mean, you should talk to the Lambda today also, but even like even in the container side, almost half of the new container customers that we have on AWS in 2020 have chosen target, which is serverless containers. They're not picking E c s or E. T. S and running at least two. They're running it on target the vast majority of those two PCs, but we see that trend on the container side as well, and actually it's accelerating. More and more and more new customers will pick target, then running containers on the city. >>Deepak, great to chat with you. I know you gotta go. Thanks for coming on our program. Breaking down the keynote analysis. You've got a great, um, focus area is only going to get hotter and grow faster and a lot more controversy and goodness coming at the same time. So congratulations. >>Thank you. And always good to be here. >>Thanks for coming on. This is the Cube Virtual. We are the Cube. Virtual. I'm John for your host. Thanks for watching.

>>Well, welcome everybody to our last session of the day. I want to introduce you to Sean O'Meara. Orfield Cto. Hey, Sean. >>Hey, Nick. Good afternoon. It's been a crazy day. It has. It's been a busy run up to today in a busy day with a lot of great things going on. You know, we've heard from Adrian on his strategy this morning. The great way the Marantz is moving forward. We announced our new product line. You know, we spoke about the new doctor Enterprise Container Cloud line, New future for Mirant. Us. We had a great lineup of customers share their story. We introduced lanes following on the lanes launch a couple of weeks ago. Andi, we're introducing new great projects like our mosque project. New way to deliver open stack going into the future on then in parallel sel. This We ran a great tutorial tracker teachers you all about how to use these new products, and hopefully you'll go and everyone had opportunity to go and look through guys. Yeah. What's next? What is next? Yeah, lots going on. A lot of new things that we're thinking about for the future. Obviously, a lot of work to do on what we have right now. A lot of great things coming. But, you know, we've had this opportunity to talk about all these cool things that are coming down the road. And everybody these days seems to be talking about topics like edge computing or hybrid cloud. Or, you know, hyper scale data centers, even things like disaster recovery is a service. Andi, you know, we talk a lot about things like hyper converged, but frankly, it's boring. It's one thing a little. Good morning. Uh, you know, you and I have been talking about these topics for a while now, and I think it's about time when we spoke about some of the cool things that we're thinking about for the future, not necessarily looking out for the road map, but ideas for the future. Things that may could have an impact on the way we do business going to. So today we're gonna talk a little bit about things like pervasive computing. A nick, what is pervasive computing. >>Well, basically pervasive computing is when everything that you interact with, for the most part, is computerized. So in some ways, we're already there in that You know your phone is a computer. Your refrigerator may have a computer in it. Um, your smart watch your car has a computer in it. And the the most obvious sign of that is this whole Internet of things where, you know your vacuum is, uh is connected to your phone and all of that. And so pervasive computing is this, uh is this sense of you don't even really think about it. You just kind of assume that everything is computerized. >>So how is that different from ubiquitous computing? >>Oh, God. You hit, You hit my hot button. Okay, so if you look, there are a lot of places that will say that pervasive computing and ubiquitous computing are the same thing, but not the same thing. Don't use them interchangeably. They're not the same thing. You big. What is computing is where you can do your computing virtually anywhere. So, for example, you know, I've got, uh I've got a document. I started it on my laptop. I can then go and finish it sitting on the beach on my phone. Or, you know, I can go and do it in a coffee shop or a library. or wherever. So the idea of ubiquitous computing is similar in that, yes, there's computing everywhere, but it's more about your data being universally accessible. So essentially it is cloud computing. That is what this whole ubiquitous computing thing is about. >>Okay on that then differs from pervasive computing in the fact that pervasive is the devices that we have all around us versus the access to those devices. >>Exactly. It's it's really it's more about the data. So ubiquitous computing is more about My data is stored in some central place, and I could hit it from anywhere. There is a device, whereas pervasive computing is there is a device almost everywhere. Okay, so yeah, >>So why Why do we as Moran takes care about the vice of computing? >>Well, pervasive computing brings up a whole lot of new issues, and it's coming up really fast. I mean, you last night I was watching, you know, commercial where you know, somebody a woman's coming out and starting her car with her phone. Um, which sounds really cool. Um, but you know what they say Anything that you can access, you know, with your computer is hackable. So, you know, there are security issues that need to be considered when it comes to all of this, but that's that's the downside. But there's just this huge upside on pervasive computing that it's so exciting when you think about this. I mean, think about a world where remember I said your refrigerator might be attached to the network. Well, what if you could rent out space on your refrigerator to somebody someplace else in a secure way? Of course. You know what? If you could define your personal network as all of these devices that you own and it doesn't matter where your workloads run or, you know, you could define all of this stuff in such a way that the connectivity between objects is really huge. Um, so you know, I mean, you look at things like, you know, I f t t you know, it's like get a notification when the International space station passes over your house. Okay? I don't know why I would need that. Um, but it's the kind of thing that people >>would have a nine year old. You can run him outside and show Z. Oh, >>there you go. There you go. So I mean, that kind of level of connectivity between objects is really really it gives us this new level off. Uh, this new level of functionality that we would never even considered even 10 years ago. Um, it also extends the life of objects that we already have. So, you know, maybe you've got that, uh, that computerized vacuum cleaner, and you don't like the way that it you don't like the pattern that uses in your house. So you re program it or, uh Or I watched. I watched a guy decide that he didn't want to buy multiple vacuums for his house. So he programmed his programa will act Hume to fly between floors. It was actually pretty funny. Um, I it's some people just have too much time. >>It's driving the whole world of programmable at all levels. Really? Like the projects coming out of the car industry of creating a programmable car would fit into that category. Then, I >>suppose absolutely, absolutely needs developer tool kits. Um, that make it possible for anybody to re program these devices that you never would have thought of reprogramming before. So it's important. So do >>we want to talk about the questions. We would love people to give us some feedback on at this stage. >>I would love to talk about these questions. So what we did is we put together, uh, we put together a place for you to answer questions. If you're not watching this live. If you're watching this live, please go ahead. Drop your ideas in the chat. We would love to discuss them, you know. Do you want to see more of this? Or does it? Conversely, Does it scare you, Sean? You What? >>What do you >>think about these questions? >>Well, I mean, for me, the idea of the connected world at one level, the engineering me loves the idea. Another level. It comes to these questions of privacy. Vegas questions off. How do I control this going into the future? What prevents somebody from taking over my flying vacuum cleaner? I'm using it, you know? So it's an interesting question. I think there's a lot of cool, cool ideas. Yeah, and a lot of work to be done. I really want to hear other people's ideas as well and see how we can take this into the future. >>Definitely, definitely. I mean, look I mean, we're joking about it, but, you know, when somebody hacks into your grandmother's insulin pump, maybe not so funny. >>Yeah, a very real risk. >>A very real risk. A very real risk. But yeah, I mean, we'd love Thio. We'd love to hear how you'd like to see this used. So that's that's my That's kind of what I've been thinking about thes days. Um, but, you know, Sean, uh, now, you I know you are really concerned about this whole issue of developers and how they feel about infrastructure. So I would love to hear what you've got to say on that. >>Yeah, I'd like to sex, but a bit about that. You know, we we've done a lot of work over the last few years looking at how developing our history has been very focused on operations, but without big drive towards supporting developers providing better infrastructure for developers. One of the interesting things that keeps coming up to the four on Do you know, the way the world is changing is that big question is, do developers actually give a damn about infrastructure in any way, shape or form? Um, you know, ultimately more and more development languages and tools abstract that underlying infrastructure. What communities does is basically abstract. The infrastructure away, Um, mawr and more options. They're coming to market, which you can quite literally creating application without out of a writing a line of code. Um, so this morning, way Dio, we're doing it all the time, sometimes without even realizing it on. I think the definition of what a developer is is also changing to a certain extent. So you know the big question, which I have on which I'd like to understand Maureen, from talking to low developers is due. Developers care about infra What is it that you expect from infrastructure? What do they want going into the future? How are they going to interact with that infrastructure? I My personal opinion is that they don't really care about infrastructure, that they're going to find more ways to completely abstract away from that. And they just want to focus on delivering applications faster and getting value to market. But I might be wrong, and I'd really like to hear people's impact ideas and thoughts on that >>on. And that's exactly and that's why we're asking this question. Developers out there. Do you care? Or do you just want the whole thing completely abstracted away from you >>on? If you do care why, If you don't, what would you like to see? Another. It's a couple of questions to ask, but really like to hear those opinions on bond. You know, Do you just want the operations guys to live with it? You never want to hear about it again, just fine. It's actually good to say that we'll work it out. >>Yes, and that there's nothing. There's nothing wrong with pushing that up stack >>pretty much what we're trying to do here. >>Well, it is what we're trying to do. But at the same time, we want to do what's good for developers. And if you developers or like No, don't don't do that. Well, we want to know because, you know, we don't wanna work away here and some ivory tower and wind up with something that's not good for >>you after school. So cool. So, yeah, there are some other interesting things we're talking about. >>I know, I know. This is This is one of my favorites. This is one of my favorites. >>Zoo this? Yes. While >>we're on the subject of not getting involved with the infrastructure. Go ahead, Sean. Tell us about it. >>Thing is a pet topic of mine and something that that we've spoken about a lot. And thanks something that we we have spent many nights talking about. The idea is AI ops using artificial intelligence to drive operations within our infrastructure. And so a lot of people ask me, You know why? Um, essentially, What the hell is a I out on? I have answered this question many times, and it does often seem that we all take this AI ops thing for granted or look at it in a different way. To me, it is essentially, it's it's automation on steroids. That's what it boils down Thio. It's using intelligence systems that to replace the human cerebellum. I mean, let's just be blunt about this. We're trying to replace humans. Onda reason for that is we humans less meat sacks are airplane. We make mistakes all the time and compared to computers were incredibly slow. Um, you know, that's really the simplest point with the scale of modern infrastructure that we're dealing with the sheer volume. I mean, we've gone from, you know, thousands to tens of thousands of the EMS to now hundreds and thousands of containers spread across multiple time zones. Multiple places. We need to come up with better ways of managing this on the old fashioned stick through mechanism of automation. It's just too limited for that. Right >>when we say we want to replace meat sacks, we mean in a good way. >>We mean in a good way. I know it's a bit of a harsh way of putting it. Um, ultimately, humans have ability for creativity that machines just don't have. But machines can do other things, and they could do analysis of data a lot faster than we can. Quite often, we have to present that data to humans to have invalidate that information. But, you know, one of the options for us is to use artificial intelligence, quantified data, um, correlated, you know, look for root cause and then provide that information to us in such a way that we can make valid decisions based on that information a lot faster than we could otherwise, >>right? So what are the what are the implications? What are the practical implications of doing this so >>practically we can analyze massive amounts of data a lot faster than a single human. Could we even just a normal type system that's searching? We We have the tools to learn by looking at data and have machines do it a lot faster than we can. We can take action faster based on that data, because we get the data foster. We can take action and much more complex action that involves maybe many different layers of tasking much, much faster. Um, on we could start to do maintenance operations and maintenance tasks without having to wait for human beings to wake up or get to an office. But more importantly, we could start making tasks happen very complex tasks in a very specific orders, with much less potential for error. And those are the kinds of areas we're looking at. >>That's that's true. So how do you kind of see this moving forward? I mean, obviously, we're not gonna go from nothing to Skynet, and hopefully we never get to Skynet. Well, >>depends if you are in control of Skynet or not. Ultimately, Dionysus little computer. Um, practically speaking, we have a few things Thio hoops to jump through our suppose before we can look at where else is going to be really effective on the first one is a trust issue. We have to learn to trust it. And to do that, we have to put in a position where it can learn and start providing us that data analysis on that inference and then having humans validated. That's practically the very first step. No, it's a trust issue. You know, we've seen been watching sci fi for the last 30 years. Class on. Do you know the computers take over? Well, ultimately, is that real or not? Um, if we look at how we gonna get there? Probably midterm. Adaptive maintenance, maybe infrastructure orchestration. Smart allocation of resource is across cloud services. Well, >>we can talk for a minute About what that would would actually look like. So, I mean, we could talk about, you know, abs, midterms. I mean, in a practical sense, how would that actually work? >>Yeah, Okay. It's a great question. So, practically speaking, the first thing we're gonna do is we're going to start to collect all this data. We're gonna find all this data. I mean, the modern computer systems that we have infrastructure systems. We are producing many hundreds of gigabytes, sometimes terabytes of logging data every day. The majority of it gives far 13. I mean, we throw the majority of their logging information away or if it's not thrown away, it's stored some way for security purposes and never analyzed. So let's start by taking their data and actually analyzing it. To do that, we have laid and correlated, >>so we >>gotta put it all together. We've got a match it and we've got to start building patents. We're going to start looking for the patterns. This is where I is particularly good at starting to help us. Bold patterns start to look for those patterns. Initially, humans will have to do some training. Um, once we have that patent, once we've got that working, we can now start having the AI systems start to do some affairs. E, here's the recalls. So we the system can tell us based on the data based on the patterns we've been learning. We know from the past debt. If those three network links get full bad example, we're gonna have a failure in Region X, right. So start telling us while those network links of filling up tell us before they fall rather than after their full always they're falling up as we see trending information now seems like a simple I could do trending information with just normal monitoring systems. But if I can start to correlate that with greater users in, you know, Beijing Office versus Users in California office filling up those links and different times of the day, I can now start to make much more clever decisions, which is a human on its own, to try and correlate that information, which is be insane once you've done that way to go to the next stage, which is not to have the system act do actions for us. Based on that information right now, we're starting to get close to the scan it. Speaking of this doesn't have to be a big, complex pile of change. Smart ai solution. I have data on that AI solution is talking to my existing automation solutions to action. That change. That's how I see this moving forward, >>right? So essentially you, instead of saying, you know, deploy this too. Uh, this workload to AWS, you would say deploy this. Yeah, And then the system would look and go. Okay, It's this kind of workload. At this time of day at this size, it's gonna interact with this and this and this. And so it's gonna be best off in this region of this cloud provider on then. Uh, you know, two days from now, when the prices drop, we're gonna put it over there, >>even taking a different different. Spoken exactly that it could be. The Beijing office is coming online. Let's move the majority of the workload to a cloud that's closer to them. Reducing the network bandwidth. Yeah, and inference. Andi Also reducing the impact on international lines as Beijing winds down for the day, I can just move the majority of the workload into California on board Europe. In between, it's very simple examples, but have humans do that would be very complex and very time consuming >>exactly. And end. Just having humans notice those patterns would be difficult. But once you have the system noticing those patterns, then the humans could start to think, How can I take advantage of this, you know, So as you are talking about much longer term in the actual applicant patients themselves. So you know, everything can be optimized that way so >>everybody may optimized way can optimize down to the way we even potentially write applications in the future. Humans were still deciding the base logic. Humans were still deciding the creative components of that. Right as we as we build things, we can start to optimize them, breaking down into smaller and smaller units that are much more specific. But the complexity goes up. When we do that right. I want to use AI and AI solutions to start to manage that complexity across multiple spaces. Multiple time zones, etcetera. >>Exactly. Exactly. So. So that's the question, you know. What do you guys think? You know, we really want to know >>on Dhere again. You know, we mentioned this around the beginning, but do you think you could trust in a iob sedition? What would it take for you to trust in our absolution? And where do you practically see it being used in the short term? >>Yeah, that's that's the big question is where do you see it being used? Where would you like it to be used, you know? Is there something that you don't think would be possible, but you would like to see it, you know. But the main thing is, on a practical matter, what would you like to see? >>Let me ask. The question is like a different way. Do you have a problem that we could solve within a isolation today? E, They're really well >>right. A re a world problem. And And assuming that, you know, we are not gonna, you know, take over the world. >>Yeah. Important. My evil plan is to take over the world with >>man. I'm so sorry. First >>had to let that draw. >>I did. I did. I'm so sorry. Okay, Alright. So that's so That's a I ops. And we like I said, if you're watching this live, throw in the chat. We want to hear your ideas. If your, um if you're doing this, if you're watching this on the replay, go to the survey because we way, we really want to hear your ideas and your opinions. All right, So moving right along. All right. What the heck are you know, kernels? >>Uh, lovely questions. So, you know, the whole world is talking about containers today way we're talking about containers today. But containers like VMS or just one way to handle compute Andi. They're more and more ideas that are out there today, and people have been trying different ways off, shrinking the size of the compute environment. COMPUTER Paxil Another cool way of looking at this and saying That's been around for a little while. But it's getting your attraction to learn to sing called unique kernels, and what they are is they're basically highly optimized. Execute a bles that include the operating system, Um, there on OS settle libraries, um, and some very simplified application code all mixed into a very, very tiny package. Easiest way to describe them. They're super simplified. And I were talking about in the eye ops discussion this idea off taking everything into smaller and smaller individual functions but creating a certain level of complexity. Well, if we look at uni kernels, those are those smaller and smaller bundles and functions. They interact directly with the hardware or through a hyper visor. Um, so actually, no overhead. I mean the overhead If you just look at what a modern you clinics operating system is made up of these days, there are so many different parts and components. Even just the colonel has got anything from, you know, 5 to 7 different parts to it. Plus, of course, drivers and a boot loader. Then we look at the system libraries that set on top of that, you know? And then they're demons and utilities and shells and scream components and, you know, additional colonel stacks that go on top of that for hyper visors. What we're trying to say is, what, This text of space, I'm >>getting tired. Just listening, >>Thio. I'm tired talking about it. You know that the unique colonel, really, it just takes over their complexity. It puts the application the OS on the basic libraries necessary. That application in tow, one really tiny package. Um, yeah. Give you an idea what we're talking about here. We're talking about memory footprints or time package footprints in the kilobytes. You know, a small container is considered 100 make plus, we're talking kilobytes. We're talking memory utilization in the kilobyte two megabytes space because there's no no fact, no fluff, no unnecessary components. And then only the CPU that it needs. >>So Bill Gates was right 6. 40 k is all anybody will ever need >>Potentially. Yeah, right. E, there was there was an IBM CEO who said even less at some point. So we'll see >>how that go. What goes around comes around. >>But one of the really interesting things about this small size, which is really critical, is how fast they can boot. Yeah, we're talking boot times measured in 30 seconds. Wow, We're talking the ability to spin up specific functions only when you need them. Now, if we look at the knock on effect of that, we're looking at power saving. Who knew? Run the app when I need it because there's no Leighton. See to start it up. The app is tiny so I can pack a lot mawr into a lot less space game power seconds. But when I start looking at where you were talking about earlier, which the basic compute idea in the world all of a sudden that tiny little arm chips it in my raspberry pi that's running my fridge, My raspberry pi equivalent that's running my fridge no longer has a fact operating system around it. I can run tens thousands, potentially off these very tiny specific devices when I need them. Wow, I'm kind of excited about it. I'm excited by the idea. You >>can hear that >>I'm a hardware geek from from many, many moons ago on DSO. I kind of like the idea of being able to better utilize along this very low powered hardware that we have lying around and really take it into the future. Well, that's good. Yeah. So I'm not going to kill, not going to kill containers. But it is a parallel technology that I'm very interested in >>that that is true. Now what does it I mean in terms of, like, attack surface. That means it's got a much smaller attack surface, though, right? >>Yeah. Great. Great point. I mean, there's no there's no fluff. There's no extra components in the system. Therefore, the attack surface is very, very small. Um, you know, and because they're so small and can be distributed much, much faster and much more easily updating and upgrading them as much easier way can we can upgrade a 60 k b file across a GPRS connection on which I certainly can't do with 600 make, uh, four gig VM 600 made container. You know, just unrealistic. Um, e >>I was just going to say so. So now these. You know, kernels, they're they're so small. And they have on Lee what they absolutely need. Now, how do you access the hardware? >>So the hardware is accessed via hyper visor. So you have to have some kind of hyper visor running on top of the hard way. But because Because we need very little from their type adviser, we don't actually need to interact with that very much. It could be a very cut down operating system. Very, very simplified operating system. We're also not trying to run another layer on top of that. We're not We're not ending up with multiple potential VMS or something underneath it were completely removed. That layer, um, the the drivers, the necessary drivers are built into that particular colonel device. >>Oh, okay. That makes sense. >>Tiny footprint easily distributed, um, and once again, very specialized, >>right? Right. Well, that makes sense. Okay. So, yeah, I mean, I guess so. These these individual stacks, you know, comparing virtual machines to containers to unit colonels, there just a completely different architecture. But I can see how that would How That would work where you have the hi perverse. A little hyper buys are on top of rented teeth. OK, so moving right along certain. Where do we see these being used? >>Um, it's early days, although there are some very good practical applications out there. There's a big, big ecosystem of people trying different ways for this I o ts off the obvious immediate place. I i o t s a quick, easy place for something very specialized. Um, what's interesting to me? And you mentioned this earlier. You know, we're talking about medical devices. We're talking about potentially disposable medical devices. Now, if I can keep those devices to run on really low power very, very cheap, um, CPUs and all of a sudden I've got a device that is available to a lot more people. I don't need a massive, powerful CPU. I just need saying that runs a very specific function really fast, A very small scale. I could do well disposable devices. I can build medical devices that are so small we can potentially swallow them and other areas which are really interesting. And I spoke a little bit about it, but it's energy efficiency. Where We need to be very, very energy efficient. No. And that can also impact on massively scalable systems where I want to deal with tens of thousands of potential transactions from users going into a system. I can spin them up only when I need them. I don't need to keep them running all the time again. It comes back to that low latency on then. Anyway, that an incredibly fast food time is valuable. Um, a car, you know, Think about it. If if my if my electric car is constantly draining that battery when it's parked in the garage and I'm traveling or if it takes 20 minutes from my car to boot up its clinics. Colonel, when I wanted, I'm going to get very irritated. Well, >>that and if you have a specific function, you know, like, identify that thing, Yeah, it would be good if you haven't smashed into it before. Identified it as a baby carriage e dark today. Yes. >>So, Nick, you know, these is all really interesting topics. Um, yeah. We spoke about air ops. We spoke about the impact is gonna have on humans. Um, all of these changes to the world that we're living in from computer systems, the impact it's having on our lives biggest. An interesting question about the ethics of all of this >>ethics of all of this. Yes, because let's be let's be realistic. There are actual riel concerns when it comes to privacy, when it comes to how corporations operate, when it comes to how governments operate. Um, there are areas of the world's where, how all of this has has moved, it's absolutely I'll be honest, absolutely terrifying the economic disparity. Um, but when you really come right down to it, um, it's all about the human control over the technology because all of these ethical issues are are in our hands. Okay, we could joke about Sky Net. We can joke about things like that, but this is one place that technology can't help us. We have to do this. We have to be aware of what's going on. We have to be aware. Are they using facial recognition? Uh, you know, when you go to X y Z, are they using recidivism algorithms in sentencing? And how is that? How is that going? Is it? Are those algorithms fair? Certain groups get longer sentences because historical data, uh, is skewed. Be educated. Know how this works? Don't be afraid of any of this. None of this is, uh, none of this is rocket science. Really? Come right down to it. I mean, it's it's not simple, but you can learn this. You can do it. >>Ask good questions. Be interested to be part of the part of the discussion. Not just a passive bystander. >>Exactly. Don't just complain about what you think is going on. Learn about what is actually going on and be active, where you see something that needs to be fixed. So that's what that's what we can do about it. We need to be aware that there's an issue or potential issues, and we need to step in and fix it. So that z myself box, I'll step down zone >>important topic. And it's one that we all can have influence on on bits one. Those who are us who are actually involved in building these systems for the future. We can help make sure that the rules are there. That's right. Systems are built correctly on that. We have open dialogues and discussions around these points and topics and on going away, was she? I think we're coming to the end of the time on hopefully we've kept everybody interested in some of the things that we think are cool for the future. And we're putting our efforts into E O. But I think we need to wrap this up now. So, Nick, great chatting to you is always >>always, always a pleasure, Sean. >>It's been an amazing week. Um, been amazing. Couple of weeks, everybody leading up to this event on bond. No, thank you, everybody for listening to us. Please go and download and try. Dr. Enterprise, Uh, the container card is available. Will post the links here to better understand what we've been doing. Go and have a look through the tutorial track. You'll hear my voice. I'm sure you'll hear next voice and make other people's voices through those tutorials. Hopefully, we keep you all interested and then going download and try lens, Please. Finally, we want your feedback. We're interested to hear what you think would be the great ideas. Good, Bad. Otherwise let us know what you think about products. We are striving to make them better all the time. >>Absolutely. And we want your involvement. Was it all right? Thank you all. Bye bye. Yeah,

>> Narrator: From around the globe, it's theCUBE with digital coverage of AWS Public Sector Online. Brought to you by Amazon Web Services. >> Welcome back to the coverage of AWS Public Sector Summit virtual. I'm John for host of theCUBE. We're here in theCUBE studios, quarantine crew here talking to all the guests remotely as part of our virtual coverage of AWS Public Sector. So I've got a great guest here talking about data science, weather predictions, accurate climate modeling, really digging into how cloud is helping science. Dr. Chelle Gentemann, who is a senior scientist at Farallon Institute is my guest. Chelle, thank you for joining me. >> Thank you. >> So tell us a little about your research. It's fascinating how, I've always joked in a lot of my interviews, 10, 15, 20 years ago, you need super computers to do all these calculations. But now with cloud computing, it opens up so much more on the research side and the impact is significant. You're at an awesome Institute, the Farallon Institute, doing a lot of stuff in the sea and the ocean and a lot of your things. What's your focus? >> I study the ocean from space, and about 71% was covered by ocean. 40% of our population in the globe actually lives within 100 kilometers of the coast. The ocean influences our weather, it influences climate, but it also provides fisheries and recreational opportunities for people. So it's a really important part of the earth system. And I've been focused on using satellites. So from space, trying to understand how the ocean influences weather and climate >> And how new is this in terms of just state of the art? Fairly new, been around for a while? What's some of the progress for the state of the art we're involved in. >> I started working on satellite data in the 90s during school, and I liked the satellite data cause it's the interface of sort of applied math, computer science and physics. The state of the art is that we've really had remote sensing around for about 20, 30 years. But things are changing because right now we're having more sensors and different types of instruments up there and trying to combine that data is really challenging. To use it, our brain is really good in two and three dimensions, but once you get past that, it's really difficult for the human brain to try and interpret the data. And that's what scientists do. Is they try and take all these multidimensional data sets and try to build some understanding of the physics of what's going on. And what's really interesting is how cloud computing is impacting that. >> It sounds so exciting. The confluence of multiple disciplines kind of all right there, kind of geek out big time. So I've got to ask you, in the past you had the public data set program. Are you involved in that? Do you take advantage that research? How is some of the things that AWS is doing help you and is that public data set part of it? >> It's a big part of it now. I've helped to deploy some of the ocean temperature data sets on the cloud. And the way that AWS public data sets as sort of has potential to transform science is the way that we've been doing science, the way that I was trained in science was that you would go and download the data. And most of these big institutions that do research, you start to create these dark repositories where the institutions or someone in your group has downloaded data sets. And then you're trying to do science with these data, but you're not sure if it's the most recent version. It makes it really hard to do reproducible science, because if you want to share your code, somebody also has to access that data and download it. And these are really big data sets. So downloading it could take quite a long time. It's not very transparent, it's not very open. So when you move to a public data set program like AWS, you just take all of that download out of the equation. And instantly when I share my code now, people can run the code and just build on it and go right from there, or they can add to it or suggest changes. That's a really big advantage for trying to do open science. >> I had a dinner with Teresa Carlson who is awesome. She runs the Public Sector Summit for AWS. And I remember this was years ago and we were dreaming about a future where we would have national parks in the cloud or this concept of a Yosemite-like beautiful treasure. Physical place you could go there. And we were kind of dreaming that, wouldn't it be great to have like these data sets or supercomputer public commons. It sounds like that's kind of the vibe here where it's shareable and it's almost like a digital national park or something. Is that it's a shared resource. Is that kind of happening? First of all, what do you react to that? And what's your thoughts around that dream? And does this kind of tie to that? >> Yeah, I think it ties directly to that. When I think about how science is still being done and has been done for the past sort of 20 years, we had a real change about 20 years ago when a lot of the government agencies started requiring their data to be public. And that was a big change. So then we got, we actually had public data sets to work with. So more people started getting involved in science. Now I see it as sort of this fortress of data that in some ways have prevented scientists from really moving rapidly forward. But with moving onto the cloud and bringing your ideas and your compute to the data set, it opens up this entire Pandora's box, this beautiful world of how you can do science. You're no longer restricted to what you have downloaded or what you're able to do because you have this unlimited compute. You don't have to be at a big institution with massive supercomputers. I've been running hundreds of workers analyzing in my realm. Over two or 300 gigabytes of data on a $36 Raspberry Pi that I was playing around with my kids. That's transformative. That allows anyone to access data. >> And if you think about what it would have to do to do that in the old days, stack and spike servers. Call, first of all, you'll get the cash, buy servers, rack them and stack them, connect to a download of nightmare. So I got to ask you now with all this capability, first of all, you're talking to someone who loves the cloud. So I'm pretty biased. What are you doing now with the cloud that you couldn't do before? So certainly the old way from a provisioning standpoint, check, done. Innovation, bars raised. Now you're creative, you're looking at solutions, you're building enabling device like a Raspberry Pi, almost like a switch or an initiation point. How has the creativity changed? What can you do now? What are some of the things that are possible that you're doing? >> I think that you can point to within some of the data sets that have already gone on the cloud are being used in these really new, different ways. Again, it points to this, when you don't have access to the data, just simply because you have to download it. So that downloading the data and figuring out how to use it and figuring out how to store it is a big barrier for people. But when things like the HF Radar data set went online. Within a couple of months, there was a paper where people were using it to monitor bird migration in ways that they'd never been able to do before, because they simply hadn't been able to get the data. There's other research being done, where they've put whale recordings on the cloud and they're using AI to actually identify different whales. It's using one data set, but it's also the ability to combine all these different data sets and have access to them at the same time and not be limited by your computer anymore. Which for a lot of science, we've been limited by our access to compute. And that when you take away that, it opens all these new doors into doing different types of research with new types of data, >> You could probably correlate the whale sounds with the temperature and probably say, hey, it's cold. >> Chelle: Exactly. >> I'm making that up. But that's the kind of thing that wouldn't be possible before because you'd have to get the data set, do some math. I mean, this is cool stuff with the ocean. I mean, can you just take a minute to share some, give people an insight in some of the cool projects that are being either thought up or dreamed up or initiated or done or in process or in flight, because actually there's so much data in the ocean. So much things to do, it's very dynamic. There's a lot of data obviously. Share, for the folks that might not have a knowledge of what goes on. What are you guys thinking about? >> A lot of what we're thinking about is how to have societal impact. So as a scientist, you want your work to be relevant. And one of the things that we found is that the ocean really impacts weather at scales that we simply can't measure right now. So we're really trying to push forward with space instrumentation so that we can monitor the ocean in new ways at new resolutions. And the reason that we want to do that is because the ocean impacts longterm predictability in the weather forecast. So a lot of weather forecasts now, if you look out, you can go on to Weather Underground or whatever weather site you want. And you'll see the forecast goes out 10 days and that's because there's not a lot of accuracy after that. So a lot of research is going into how do we extend into seasonal forecast? I'm from Santa Rosa, California. We've been massively impacted by wildfires. And being able to understand how to prepare for the coming season is incredibly important. And surprisingly, I think to a lot of people, the ocean plays a big role in that. The ocean can impact how much storm systems, how they grow, how they evolve, how much water they actually got. Moisture they pick up from the ocean and then transport over land. So if you want to talk about, it's really interesting to talk about how the ocean impacts our weather and our seasonal weather. So that's an area where people are doing a lot of research. And again, you're talking about different data sets and being able to work together in a collaborative environment on the cloud is really what's starting to transform how people are working together, how they're communicating and how they're sharing their science. >> I just hope it opens up someone's possibilities. I want to get your vision of what you think the breakthroughs might be possible with cloud for research and computing. Because you have kind of old school and new school. Amazon CEO, Andy Jassy calls it old guard, new guard. The new guard is really more looking for self provisioning, auto-scaling, all that. Super computer on demand, all that stuff at your fingertips. Great, love that. But is there any opportunity for institutional change within the scientific community? What's your vision around the impact? It's not just scientific. It also can go to government for societal impact. So you start to see this modernization trend. What's your vision on the impact of the scientific community with cloud? >> I think that the way the scientific community has been organized for a long time is that scientists that are at an institute. And a lot of the research has been siloed. And it's siloed in part because of the way the funding mechanism works. But that inhibits creativity and inhibits collaboration. And it inhibits the advancement of science. Because if you hold onto data, you hold on to code. You're not allowing other people to work on it and to build on what you do. The traditional way that scientists have moved forward is you make a discovery, you write up a paper, you describe it in a journal article, and then you publish that. Then if someone wants to build on your research, they get your journal article, they read it. Then they try to understand what you did. They maybe recode all of your analysis. So they're redoing the work that you did, which is simply not efficient. Then they have to download the data sets that you access. This slows down all of science. And it also inhibits bringing in new data sets again because you don't have access to them. So one of the things I'm really excited about with cloud computing is that by bringing our scientific ideas and our compute to the data, it allows us to break out of these silos and collaborate with people outside of our institution, outside of our country, and bring new ideas and new voices and elevate everyone's ideas to another level. >> It brings the talent and the ideas together. And now you have digital and virtual worlds, cause we've been virtualized with COVID-19. You can create content as a community building capability or your work can create a network effect with other peers. And is a flash mobbing effect of potential collaboration. So work, work forces, workplaces, work loads, work flows, kind of are interesting or kind of being changed in real time. You were just talking about speed, agility. These are technical concepts being applied to kind of real world scenarios. I mean your thoughts on that. >> I now work with people like right now, I'm working with students in Denmark, Oman, India, France, and the US. That just wasn't possible 10 years ago. And we're able to bring all these different voices together, which it really frees up science and it frees up who can participate in science, which is really fun. I mean, I'm a scientist. I do it because it's really, really fun. And I love working with other people. So this new ability that I've gained in the last couple of years by moving onto the cloud has really accelerated all the different types of collaborations I'm involved with. And hopefully accelerating science as a whole. >> I love this topic. It's one of my passion areas where it's an issue I've been scratching for over a decade too. Is that content and your work is an enabler for community engagement because you don't need to publish it to a journal. It's like waterfall mentality. It's like you do it. But if you can publish something or create something and show it, demo it or illustrate it, that's better than a paper. If you're on video, you can talk about it. It's going to attract other people, like-minded peers can come together. That's going to create more collaboration data. That's going to create more solidarity around topics and accelerate the breakthroughs. >> For our last paper, we actually published all the software with it. We got a digital firewall for the software, published the software and then containerized it so that when you read our paper, at the bottom of the paper, you get a link. You go to that link, you click on a button and you're instantly in our compute environment, you can reproduce all of our results. Do the error propagation analysis that we did. And then if you don't like something, go ahead and change it or add onto it or ask us some questions. That's just magical. >> Yeah, it really is. And Amazon has been a real investor and I got to give props to Teresa Carlson and her team and Andy Jassy, the CEO, because they've been investing in credits and collaborating with groups like Jet Propulsion Lab, you guys, everyone else. Just space has been a big part of that. I see Bezos love space. So they've been investing in that and bringing that resource to the table. So you've got to give Amazon some props for that. But great work that you're doing. I'm fascinated. I think it's one of those examples where it's a moonshot, but it's doable. It's like you can get there. >> Yeah, and it's just so exciting. I'm the lead on a proposal for a new science mission to NASA. And we are going all in with the cloud computing. So we're going to do all the processing on the cloud. We want to do the entire science team on the cloud and create a science data platform where we're all working together. That's just never happened before. And I think that by doing this, we multiply the benefits of all of our analysis. We make it faster and we make it better and we make it more collaborative. So everyone wins. >> Sure, you're an inspiration to many. I'm so excited to do this interview with you. I love what you said earlier at the beginning about your focus of being in computer science, physics, space. That confluence is multiple disciplines. Not everyone can have that. Some people just get a computer science degree. Some people get, I'm premed, or I'm going to do biology. I'm going to do this. This notion of multiple disciplines coming together is really what society needs now. Is we're converging or virtualizing or becoming a global society. And that brings up my final question. Is something I know that you're passionate about creating a more inclusive scientific community because you don't have to be the, just the computer science major. Now, if you have all three, it's a multi-tool when you're a multiple skill player. But you don't have to be something to get into this new world. Because if you have certain disciplines, whether it's math, maybe you don't have computer science but it's quick to learn. There's frameworks out there, no code, low code. So cloud computing supports this. What's your vision and what's your opinion of how more inclusivity can come into the scientific community? >> I think that, when you're at an institution or at a commercial company or a nonprofit, if you're at some sort of organized institution, you have access to things that not everyone has access to. And in a lot of the world, there's trouble with internet connectivity. There is trouble downloading data. They simply don't have the ability to download large data sets. So I'm passionate about inclusivity because I think that, until we include global voices in science, we're not going to see these global results that we need to. We need to be more interdisciplinary. And that means working with different scientists in different fields. And if we can all work together on the same platform that really helps explode interdisciplinary science and what can be done. A lot of science has been quite siloed because you work at an institution. So you talked to the people one door down, or two doors down or on the same floor. But when you start working in this international community and people don't have to be online all the time, they can write code and then just jump on and upload it. You don't need to have these big, powerful resources or institutions behind you. And that gives a platform for all types of scientists, that all types of levels to start working with everyone. >> This is why I love the idea of the content and the community being horizontally scalable. Because if you're stuck around a physical institution or space, you kind of like have group think, or maybe you have the same kind of ideas being talked about. But here, when you pull back the remote work with COVID-19, as an example, it highlights it. The remote scientist could be anywhere. So that's going to increase access. What can we do to accept those voices? Is there a way or an idea or formula you see that people could, assuming there's access, which I would say, yes. What do we do? What do you do? >> I think you have to be open and you have to listen. Because, if I ask a question into the room where my colleagues work, we're going to come up with an answer. But we're going to come up with an answer that's informed by how we were trained in science and what fields we know. So when you open up this box and you allow other voices to participate in science, you're going to get new and different answers. And as a scientist, you need to be open to allowing those voices to be heard and to acting on them and including them in your research results and thinking about how they may change what you think and bring you to new conclusions. >> Machine learning has been a part. I know your work in the past, obviously cloud you're a big fan, obviously can tell. Proponent of it. Machine learning and AI can be a big part of this too, both on not only sourcing new voices and identifying what's contextually relevant at any given time, but also on the science-side machine learning. Because if we can take a minute to give your thoughts on the and relevance of machine learning and AI, because you still got the humans and you got machines augmenting each other, that relationship is going to be a constant conversation point going forward. Is there data about the data and what's the machines doing? What's your thoughts on all of these? Machine learning and AI as an impact. >> It's funny you say impact. So I work with this NASA IMPACT project, which is this interdisciplinary team that tries to advance science, and it's really into machine learning and AI. One of the difficulties when you start to do science is you have an idea like, okay, I want to study tropical storms. And then you have to go and wade through all these different types of data to identify when events happened and then gather all the data from those different events and start to try and do some analysis. They're working and they've been really successful in using AI to actually do this sort of event identification. So what's interesting and how can we use AI and machine learning to identify those interesting events and gathering everything together for scientists to then try and bring for analysis? So AI is being used in a lot of different ways in science. It's being used to look at these multi-dimensional problems that are just a little bit too big for our brains to try and understand. But if we can use AI and machine learning to gather insights into certain aspects of them, it starts to lead to new conclusions and it starts to allow us to see new connections. AI and machine learning has this potential to transform how we do science. Cloud computing is part of that because we have access to so much more data now. >> It's a real enabling technology. And when you have enabling technology, the power is in the hands of the creative minds. And it's really what you can think up and what you can dream up and that's going to come from people. Phenomenal. Final question for you, to kind of end on a light note. Dr. Chelle Gentemann here, senior scientist at the Farallon Institute. You're doing a lot of work on the ocean, space, ocean interaction. What's the coolest thing you're working on right now? Or you you've worked on that you think would be worth sharing. >> There's a couple of things. I have to think about what's the most fun. Right now, I'm working on doing some analysis with data. We had a big, huge international field campaign this winter off of Barbados, there were research festival, rustles and aircraft. There were sail drones involved, which are these autonomous robotic vehicles that go along the ocean surface and measure air-sea interactions. Right now we're working on analyzing that data. So we have all of this ground truth data. We're bringing in all the satellite observations to see how we can better understand the earth system in that region with a specific focus on air-sea interactions over the ocean where when it rains, you get the salinity stratification. When there's strong solar, you get diurnal stratification. So you have upper ocean stratification and heat and salinity. And how those impact the fluxes and how the ocean impacts the heat and moisture transport into the atmosphere, which then affects weather. So again, this is this multidimensional data set with all these different types of both ground truth data, satellite data that we're trying to bring together and it's really exciting. >> It could shape policy, it could shape society. Maybe have a real input into global warming. Our behaviors in the world, sounds awesome. Plus, I love the ground truth and the observational data. It sounds like our media business algorithm, we got to get the observation, get the truth, report it. Sounds like there's something in there that we could learn from. (both giggling) >> Yeah, it's very interesting cause you often find what you see from a distance is not quite true up close. >> I can tell you that we as in media as we do a lot of investigative journalism. So we appreciate that. Dr. Chelle Gentemann, senior scientist at the Farallon Institute, here as part of AWS Public Sector Summit. Thank you so much for time. What a great story. We'll keep in touch. Love the sails drone. Great innovation. And continue the good work, I'm looking forward to checking in later. Thanks for joining. >> Thanks so much. It was nice talking to you. >> I'm John Furrier with theCUBE. We're here in our studios covering the Amazon Web Services Public Sector Summit virtual. This is theCUBE virtual bringing you all the coverage with Amazon and theCUBE. Thanks for watching. (upbeat music)

>> Announcer: Live from San Diego, California, it's theCUBE, covering Kubecon and CloudNativeCon, brought to you by RedHat, a CloudNative computing foundation and it's ecosystem partners. >> Hi and welcome back to Kubecon, CloudNativeCon 2019 here in San Diego. I'm Stu Miniman and my cohost for three days of coverage is John Troyer, and happy to welcome back to the program, was on the keynote stage earlier at the conference, Derek Collison is the founder and CEO of Synadia. >> Yes, welcome. >> Stu: Showing the logo, thanks so much for joining us, Derek. >> Oh, thank you, I really appreciate it, it's been a while. >> Yeah, it has, so you know, we've known you for many years, had you on the program, you look at us, you've got one of those VIP logos 'cause you've been on the show a few times, and you've seen a couple of these waves. Latest thing, of course, you're talking a lot about NATS, but of course Cloud Foundry you built that, so you've seen a lot of these waves, but I want to start with something you said that I thought was really thought-provoking and interesting. A lot of people, we talk about the Cloud economy, talk about the data economy... You talk about the connective economy, so, explain to our audience a little bit what that means. >> So, the general gist of it is, hey, where's the innovation and where's the value coming out of information technology, IT, infrastructure and things like that, and for a long time, we were swept up in the Cloud economy, which was how you move from CapEx into OpEx, and things like that, and then of course it was all about data. And it still is about data, but if you notice, it's not the data moving to where you're trying to process things, now it's all of a sudden being distributed, and so you take that, and you take MicroServices, and you take all these things, and at least from my perspective, I see the value driving out of these systems now is in, how are they connected? How are you observing them, how are you securing them and trusting them? And I believe that's where the value in the next wave of innovation's going to come from. >> Yeah, it's funny, I hear sometimes we talk about the pendulum of technology, and I look in the ten years we've been doing this, really we're talking about the journey along the distributed architecture we've been trying to build, and it's not moving back and forth, but it's kind of... >> Derek: Circling. >> It's kind of circling, and some of the themes are repeating, but it's growing that along the way, so, give us NATS and messaging, how this plays into helping to solve that communication issue, it's the kind of thing, we read about in the Google papers as to, global distributed architectures. >> Yeah, so, the general gist is that NATS was built to power Cloud Foundry, right, and that was the deployment mechanism for applications and such like that. And NATS, just like a lot of the other technologies, was built for an itch I needed to scratch. And it was a silo technology. So about two years ago, we had the opportunity to actually think about if we wanted to make a business out of NATS, right? And any time you say open source and commercial entity, there's challenges, and I don't think anyone has all of the answers. But the answer we came up with internally as a team was, we need to build something that's value is greater than the sum of its parts. I personally, again, and a lot of people won't agree with me and that's okay, I don't believe in the open core model. I don't believe in the fact that you make certain enterprise features and certain open source features. However, what I do believe is that if we could take a communication technology and make it a true utility, like the global cellular now, or the Internet, and connect everything, we'd have these opportunities that no one could foresee, for example, with the web, or even with the global cellular network and what people think is about to happen with the 5G. So we took NATS, which is a very mature technology, made it multi-tinted, made it very, very forward-looking secure, made it run in any Cloud, Edge, IoT, with the hope that we could encourage people to connect everything, start isolated, but have the ability to say, hey, we want to start sharing data securely in an audited way, that it's drop-dead simple to do. It's not a, let's plan a six-month project to integrate your systems with these systems and things like that, and so that's the gist of what we're trying to do, and we believe that running this thing as a server as such that it's a utility, it's not just something for you or for you or for me, it's that we're all using the same thing and we're all connected if we want to be, we think there's value there. >> Derek, maybe let's go in a little bit on NATS, and the service you're running too, but maybe educate us a little bit on the landscape here. We've already talked about IoT, Cloud data, VAP messaging, and I think people understand, to a certain extent, what a messaging system is, sometimes it gets conflated with a streaming system, maybe you could talk about what NATS does really well, we've talked about security, we've talked about a few other things, you've teased already here, but how should we be thinking about NATS? >> Well, I think, outside of NATS, just in general, any type of way of communications, we need to think secure by default, right? We can't do what happened with the Internet, where we go, ooh, it'd be really nice to do these kind of things, but we need security. And we have to wait, as a group of excited individuals, probably 15 years to get that, we can't do that in this generation with IoT and things. But when you look at NATS, or any technology, there's essentially two types of patterns that anybody wants to support. A service-based pattern, where I ask you a question, you give me an answer, ninety-plus percent of distributed systems today, that's their main architectural pattern. So I'm coordinating and asking a lot of questions of these services, micro-services, you know, has become popular. Streaming is now becoming popular with things like Kafka and stuff like that, it's been around for a while, but that's the second, other pattern. So it's like, I'm emitting events or data streams or things like that, and they could be persisted or not, but essentially if you want to make it simple, it's services and streams, and for us, we wanted technology that did equally well in both of them, right, you didn't have to pick one technology for one pattern and another one for a different one. >> All right, let's talk a little bit about your business. So you talked a little bit about kind of the business model, so explain the business model, what you're doing, how that actually goes together? >> Yeah, and for the viewers, this is our take on it, which means it's advice, you get what you pay for, it's free, type of stuff, but, you know... Been around the block a little bit. So, when we started out, what we didn't want to do is ignore the old models. I don't think a long-term business model is the old models, meaning recurring support, consulting, NRE work type of stuff, but I've also seen startups that ignore that and say, "no, we're not going to do that at all." And I did a little bit of that with my prior company, so we embrace that, but we know long-term that's not going to be it. So we deploy a global network, we have a global network, it's available with a single URL, secure by default, runs in every Cloud, every major GO, and more importantly, you can extend it on your own, on your own servers, with the RN off to do that. And we believe that Saas model, that utility model where, again, its value is greater than the sum of its parts, allows us to keep everything open-source, but there's a value in being connected to this network. Multi-Cloud, Cloud to Edge, all that kind of stuff. And what we want is we want customers to slowly transition to that. I've been telling people there's basic cable, which is like, just the dial tone, then there's going to be premium channels on that, that you can pay for, like storage, DR, secrets, zero-trust mechanisms, anomaly detection around communication patterns. People might opt in and say, "ooh, we want to pay for those things 'cause they're interesting to us." And then the last piece of that pie is, there may be people who are running against the global utility, running their own servers, and they go, "that service right there inside of that system, we love it, we want it on premise, can we actually license it from you?" So it's a combination of softwares and service, license revenue, and recurring support. >> Okay, and so, are you enabling partners to deliver those services, is that Synadia does that themselves, where do those premium services come from? >> So, we're going to seed the market, but yeah, we want it to be an open marketplace, and what we will provide is things like billing and such like that, almost, not exactly, but almost like the app store, the Apple app store, where someone who just wants to write a simple service, and if people like it, they don't have to do much, they just have it run and it's receiving stuff and they just get paid. So we do think that's a federated model. Believe it or not, we also feel running the network on a global scale is also federated. So we've designed it such that we don't have to be the only operators. Matter of fact, if we're successful, we're the smallest operator going forward. But, the system is always interconnected, right, so if John's trying to connect in and he's connecting to a Google server, I can connect to that server also, even though Synadia might have actually granted me the rights to access the system. And so we're working on that, we're thinking about that, but Cloud providers are really good at running infrastructure and running services on that infrastructure. We want to embrace that, we just want to make sure that any user of the system, it's like a SIM card that's unlocked, essentially, right? You could go to any provider that you want and it works, that's what we want to make sure we set up for. >> Right, it seems like a great example of this next wave of companies that's being built on top of the existing Cloud infrastructure. You don't have to be a hoster yourself, you could take advantage of and partner with all the other infrastructure providers and interconnect them in several different ways. Maybe, Derek, could you give us an example of an app, what an app might look like that's globally distributed and what kind of messages would be being passed back and forth? >> Sure, so, we're about to release something on Synadia where we truly believe, at the base of everything, it's just sending messages. And so, most people think of NATS as a communication mechanism, and it is, but when we say storage or state storage, they kind of say, "oh, NATS doesn't do that." But we can send a message to a KV service that says KV.set, and I could send a message that says KV get and get it back. Now, what's interesting is, we can make that zero trust, meaning, it leaves your app totally encrypted, so none of our servers, none of Google, Amazon, or Azure's servers, actually even understand what the heck it is, but what's interesting is, you could connect to any of our servers worldwide, or even run your own servers, and connect to those, and it works, all the time. We have another one that's just a usage server, meaning it tells you how much usage you've been racking up, let's say, over the month, kind of like a cell bill. And the way we built it was, there's multiple servers that are running, collecting this data, totally independent, there's no consensus. Everyone has the same subject, NGS.usage, you send a request saying, "what's my usage for the last hour?" Yet the backend service, guaranteed secure, trusted, it receives a request that it knows it's John, knows it's Stu, knows it's Derek, and so it can say, "oh, I'm trying to get John's usage, I'm trying to get Stu's usage." Yet the user experience is, everyone does the same thing, which we think is extremely powerful. And you don't have to do anything unnatural to get that with a system like NATS, right, where we tried to put security first and really think hard about what it meant, and that wasn't fun, it wasn't easy, but we think it's important. >> Yeah. So, Derek, I want to kind of step up-level a second here, 'cause you've got some great viewpoints on things, so, there's some people that look at a show like this or look at the industry and say, "Ah, there's all this hype around multi-Cloud, but there's a lot of challenges." Does it become least common denominator? How do these things work together? My definition that I've been saying for a while, I'll use a phrase you've used a couple of times. If, for multi-Cloud to be real, the value that I get out of it has to be greater than the sum of its parts. You live through the PaaS and the post-PaaS era, you've done a number of environments here, so where are we today, where do we need to go as an industry, as a whole, to reach that value statement that we talk about? >> Yeah, that's a great question. Even from day one in Cloud Foundry, I've believed in multi-Cloud, but I've watched how the markets have actually reacted and what they are doing, and the first wave in my perspective was, posturing for better pricing. To be honest with you, it was Netflix go, "hey we're going to move to Google unless you give us a better price." And I've seen that time and time again. Where it becomes real, though, is, when there's a class of service in a given Cloud provider, that is extremely attractive. Amazon, just in terms of the breadth, Azure a lot for some of the big data stuff, Google a lot for some of the AI stuff they have. Where an organization has a legitimate use to say "we really need best of breed in AI," best of breed in, let's say, big data, and they want to run an app in Azure and an app in Google, and that's kind of the realest situation I've seen. The notion of running something that's truly oblivious and can run anywhere, it's possible, but your lowest common denominators compute and simple storage, and a lot of times, that's not actually distinguishing. So I still see a lot of pricing pressure, you know, posturing, around multi-Cloud, just as a negotiation tactic. Where I see it being real is, this class of app, we want to run it in this Cloud provider to access these services that are differentiating. >> Derek, you have been around for a few generations of Stack wars, PaaS wars, I don't know that they need a name. Any advice to application architects and technologists who are choosing technologies here? I mean, here at this conference, Kubernetes is kind of a common assumption for a lot of what people are doing, not everybody, but there's a lot of other parts that plug into it, and a lot of other decisions to be made about architectures, and about, everything from messaging, to security, to networking, to storage, and I can go on and on and on and on. So, I mean how... Again, you've seen this happen a couple times, people having to pick and make choices, worried about lock-in, whatever they're worried about, I don't know. What are your thoughts on what's the, what are the right ways to do this so you actually succeed? >> Yeah, you know, it's a great question. And yeah, I have seen the pendulum swing back and forth quite a bit, but I think for the viewers, I can simplify it, at least from my perspective. It goes between choice and simplicity. So if you look in even the PaaS wars versus IaS versus all that stuff, PaaS was a swing towards simplicity, get stuff done, you know what I mean? And then there was like, "oh, I can get stuff done, but I don't have enough choice." So we saw this swing back, and I think Kubernetes hit at the absolute perfect time to take advantage of, "hey, we need choice at these base layers," right? And the way Kubernetes was architected was to give you that full choice. So if a startup's coming along and saying, okay, given the fact that the pendulum's over here, knowing it's going to be swinging back, and at least in my opinion, we're swinging back for simplicity, concentrate on, how do you simplify what people are struggling with today? So at this conference, there's a tremendous amount of people, you can get a lot of insight into what's going on, ask 'em where it hurts, you know what I mean? What are you struggling with? How long have you been struggling with it? And then solve those problems, especially when the pendulum you know is starting to swing back around. Hey, can we do this in a more simplified way, why does it have to be so hard? Those are the big opportunities right now. But again, it'll swing this way, and it'll swing back, eventually it'll get to the middle, and then we'll pick a whole other class of problems to, you know, swing back and forth from. >> Well, you know, it actually, it's not surprising to me that you're actually echoing a comment that Steve Harrod made on the program yesterday, saying when he goes and talks to all the companies here, it's, tell me how you make my life better as a company, and that's what we need to focus on. That wave toward simplicity absolutely is something we see, it's something we've been driving toward from Kubernetes, but an area that you're spending some time in talking about at the keynote, Edge computing. And absolutely, we need simplicity for that to be able to come there. What are you seeing in the Edge space, what's real, customers you're talking to, give us a little bit of forward-looking as where you see that whole space going. >> Yeah, so, I mean, for me, Edge and IoT, you can define it a lot of different ways, but even for enterprise companies that are here, it's, hey, do you deploy a piece of software out into the field, or a hardware/software combination? So, Bose headsets, Peloton bikes, whatever, that's kind of an industrial IoT type of thing. I see a lot of people wanting to drag what they think works in Cloud out to the Edge. Kubernetes works here, we're going to drag it out here. We're just going to slim it up a little bit and package it. I don't know if that's the right answer. What I think we need to think about is how do we get data and compute, compute meaning processing of that data, securely in a trusted fashion out to the Edge, however that works? It doesn't necessarily mean we have to have all the same pieces, but you have to say, I want to push an update and I want it to go over the air so to speak to the Edge, I want to be able to trust that it's doing the right thing. And so I think there's a massive amount of opportunity around that, and in how do you move all those pieces around. And what we're trying to do at Synadia is encompassing both, right? So we started with the secure by default, trusting in the beginning, and then if we say, hey, it's just messages, and in the keynote, I talked a little bit about our excitement around web assembly. But where we get excited about it is, we give you a drop-dead easy system and say, I want to digitally sign that web assembly for use in this certain situation at the Edge. And then that shovels it out there, and the system looks at it, verifies that it was signed by John, and says, yep, I can run this now. And so we're looking very heavily at those types of opportunities. We don't care how the things are deployed per se, but I would say that I think as you get further out, I think you're going to see more common denominators around web assembly, secure and signed web assemblies, than on how we actually deploy them. So you're going to see lighter weight things, not to say that Kubernetes might not have relevance out there, but I don't think it's needed to get to where we want. We need that trust factor, ubiquitous, communications to really kind of light that field up. The other one at least that we feel we need to meet the customer where they're at, is most of the IoT type devices are MQTT. And so we talked also that in Q1, we're going to allow native MQTT apps to connect directly into a NATS server and the NGS ecosystem, meaning you get the best of both worlds as well. Then an Edge router's running a NATS server, could be a raspberry pie, thousands of devices all connecting in, we think that connectivity and trust will light up a lot of opportunities. >> All right, well, Derek, always a pleasure to catch up with you, thanks so much for the updates. >> Thank you guys, I really appreciate it. >> All right. John Troyer, I'm Stu Miniman, back with lots more coverage here at Kubecon CloudNativeCon, thanks for watching theCUBE.