from the cube studios in palo alto in boston bringing you data driven insights from the cube and etr this is breaking analysis with dave vellante at our inaugural super cloud 22 event we further refined the concept of a super cloud iterating on the definition the salient attributes and some examples of what is and what is not a super cloud welcome to this week's wikibon cube insights powered by etr you know snowflake has always been what we feel is one of the strongest examples of a super cloud and in this breaking analysis from our studios in palo alto we unpack our interview with benoit de javille co-founder and president of products at snowflake and we test our super cloud definition on the company's data cloud platform and we're really looking forward to your feedback first let's examine how we defl find super cloudant very importantly one of the goals of super cloud 22 was to get the community's input on the definition and iterate on previous work super cloud is an emerging computing architecture that comprises a set of services which are abstracted from the underlying primitives of hyperscale clouds we're talking about services such as compute storage networking security and other native tooling like machine learning and developer tools to create a global system that spans more than one cloud super cloud as shown on this slide has five essential properties x number of deployment models and y number of service models we're looking for community input on x and y and on the first point as well so please weigh in and contribute now we've identified these five essential elements of a super cloud let's talk about these first the super cloud has to run its services on more than one cloud leveraging the cloud native tools offered by each of the cloud providers the builder of the super cloud platform is responsible for optimizing the underlying primitives of each cloud and optimizing for the specific needs be it cost or performance or latency or governance data sharing security etc but those primitives must be abstracted such that a common experience is delivered across the clouds for both users and developers the super cloud has a metadata intelligence layer that can maximize efficiency for the specific purpose of the super cloud i.e the purpose that the super cloud is intended for and it does so in a federated model and it includes what we call a super pass this is a prerequisite that is a purpose-built component and enables ecosystem partners to customize and monetize incremental services while at the same time ensuring that the common experiences exist across clouds now in terms of deployment models we'd really like to get more feedback on this piece but here's where we are so far based on the feedback we got at super cloud 22. we see three deployment models the first is one where a control plane may run on one cloud but supports data plane interactions with more than one other cloud the second model instantiates the super cloud services on each individual cloud and within regions and can support interactions across more than one cloud with a unified interface connecting those instantiations those instances to create a common experience and the third model superimposes its services as a layer or in the case of snowflake they call it a mesh on top of the cloud on top of the cloud providers region or regions with a single global instantiation a single global instantiation of those services which spans multiple cloud providers this is our understanding from a comfort the conversation with benoit dejaville as to how snowflake approaches its solutions and for now we're going to park the service models we need to more time to flesh that out and we'll propose something shortly for you to comment on now we peppered benoit dejaville at super cloud 22 to test how the snowflake data cloud aligns to our concepts and our definition let me also say that snowflake doesn't use the term data cloud they really want to respect and they want to denigrate the importance of their hyperscale partners nor do we but we do think the hyperscalers today anyway are building or not building what we call super clouds but they are but but people who bar are building super clouds are building on top of hyperscale clouds that is a prerequisite so here are the questions that we tested with snowflake first question how does snowflake architect its data cloud and what is its deployment model listen to deja ville talk about how snowflake has architected a single system play the clip there are several ways to do this you know uh super cloud as as you name them the way we we we picked is is to create you know one single system and that's very important right the the the um [Music] there are several ways right you can instantiate you know your solution uh in every region of a cloud and and you know potentially that region could be a ws that region could be gcp so you are indeed a multi-cloud solution but snowflake we did it differently we are really creating cloud regions which are superposed on top of the cloud provider you know region infrastructure region so we are building our regions but but where where it's very different is that each region of snowflake is not one in instantiation of our service our service is global by nature we can move data from one region to the other when you land in snowflake you land into one region but but you can grow from there and you can you know exist in multiple clouds at the same time and that's very important right it's not one single i mean different instantiation of a system is one single instantiation which covers many cloud regions and many cloud providers snowflake chose the most advanced level of our three deployment models dodgeville talked about too presumably so it could maintain maximum control and ensure that common experience like the iphone model next we probed about the technical enablers of the data cloud listen to deja ville talk about snow grid he uses the term mesh and then this can get confusing with the jamaicani's data mesh concept but listen to benoit's explanation well as i said you know first we start by building you know snowflake regions we have today furry region that spawn you know the world so it's a worldwide worldwide system with many regions but all these regions are connected together they are you know meshed together with our technology we name it snow grid and that makes it hard because you know regions you know azure region can talk to a ws region or gcp regions and and as a as a user of our cloud you you don't see really these regional differences that you know regions are in different you know potentially clown when you use snowflake you can exist your your presence as an organization can be in several regions several clouds if you want geographic and and and both geographic and cloud provider so i can share data irrespective of the the cloud and i'm in the snowflake data cloud is that correct i can do that today exactly and and that's very critical right what we wanted is to remove data silos and and when you instantiate a system in one single region and that system is locked in that region you cannot communicate with other parts of the world you are locking the data in one region right and we didn't want to do that we wanted you know data to be distributed the way customer wants it to be distributed across the world and potentially sharing data at world scale now maybe there are many ways to skin the other cat meaning perhaps if a platform does instantiate in multiple places there are ways to share data but this is how snowflake chose to approach the problem next question how do you deal with latency in this big global system this is really important to us because while snowflake has some really smart people working as engineers and and the like we don't think they've solved for the speed of light problem the best people working on it as we often joke listen to benoit deja ville's comments on this topic so yes and no the the way we do it it's very expensive to do that because generally if you want to join you know data which is in which are in different regions and different cloud it's going to be very expensive because you need to move you know data every time you join it so the way we do it is that you replicate the subset of data that you want to access from one region from other regions so you can create this data mesh but data is replicated to make it very cheap and very performant too and is the snow grid does that have the metadata intelligence yes to actually can you describe that a little bit yeah snow grid is both uh a way to to exchange you know metadata about so each region of snowflake knows about all the other regions of snowflake every time we create a new region diary you know the metadata is distributed over our data cloud not only you know region knows all the regions but knows you know every organization that exists in our clouds where this organization is where data can be replicated by this organization and then of course it's it's also used as a way to uh uh exchange data right so you can exchange you know beta by scale of data size and we just had i was just receiving an email from one of our customers who moved more than four petabytes of data cross-region cross you know cloud providers in you know few days and you know it's a lot of data so it takes you know some time to move but they were able to do that online completely online and and switch over you know to the diff to the other region which is failover is very important also so yes and no probably means typically no he says yes and no probably means no so it sounds like snowflake is selectively pulling small amounts of data and replicating it where necessary but you also heard him talk about the metadata layer which is one of the essential aspects of super cloud okay next we dug into security it's one of the most important issues and we think one of the hardest parts related to deploying super cloud so we've talked about how the cloud has become the first line of defense for the cso but now with multi-cloud you have multiple first lines of defense and that means multiple shared responsibility models and multiple tool sets from different cloud providers and an expanded threat surface so listen to benoit's explanation here please play the clip this is a great question uh security has always been the most important aspect of snowflake since day one right this is the question that every customer of ours has you know how you can you guarantee the security of my data and so we secure data really tightly in region we have several layers of security it starts by by encrypting it every data at rest and that's very important a lot of customers are not doing that right you hear these attacks for example on on cloud you know where someone left you know their buckets uh uh open and then you know you can access the data because it's a non-encrypted uh so we are encrypting everything at rest we are encrypting everything in transit so a region is very secure now you know you never from one region you never access data from another region in snowflake that's why also we replicate data now the replication of that data across region or the metadata for that matter is is really highly secure so snow grits ensure that everything is encrypted everything is you know we have multiple you know encryption keys and it's you know stored in hardware you know secure modules so we we we built you know snow grids such that it's secure and it allows very secure movement of data so when we heard this explanation we immediately went to the lowest common denominator question meaning when you think about how aws for instance deals with data in motion or data and rest it might be different from how another cloud provider deals with it so how does aws uh uh uh differences for example in the aws maturity model for various you know cloud capabilities you know let's say they've got a faster nitro or graviton does it do do you have to how does snowflake deal with that do they have to slow everything else down like imagine a caravan cruising you know across the desert so you know every truck can keep up let's listen it's a great question i mean of course our software is abstracting you know all the cloud providers you know infrastructure so that when you run in one region let's say aws or azure it doesn't make any difference as far as the applications are concerned and and this abstraction of course is a lot of work i mean really really a lot of work because it needs to be secure it needs to be performance and you know every cloud and it has you know to expose apis which are uniform and and you know cloud providers even though they have potentially the same concept let's say blob storage apis are completely different the way you know these systems are secure it's completely different the errors that you can get and and the retry you know mechanism is very different from one cloud to the other performance is also different we discovered that when we were starting to port our software and and and you know we had to completely rethink how to leverage blob storage in that cloud versus that cloud because just of performance too so we had you know for example to you know stripe data so all this work is work that's you know you don't need as an application because our vision really is that applications which are running in our data cloud can you know be abstracted of all this difference and and we provide all the services all the workload that this application need whether it's transactional access to data analytical access to data you know managing you know logs managing you know metrics all of these is abstracted too such that they are not you know tied to one you know particular service of one cloud and and distributing this application across you know many regions many cloud is very seamless so from that answer we know that snowflake takes care of everything but we really don't understand the performance implications in you know in that specific case but we feel pretty certain that the promises that snowflake makes around governance and security within their data sharing construct construct will be kept now another criterion that we've proposed for super cloud is a super pass layer to create a common developer experience and an enabler for ecosystem partners to monetize please play the clip let's listen we build it you know a custom build because because as you said you know what exists in one cloud might not exist in another cloud provider right so so we have to build you know on this all these this components that modern application mode and that application need and and and and that you know goes to machine learning as i say transactional uh analytical system and the entire thing so such that they can run in isolation basically and the objective is the developer experience will be identical across those clouds yes right the developers doesn't need to worry about cloud provider and actually our system we have we didn't talk about it but the marketplace that we have which allows actually to deliver we're getting there yeah okay now we're not going to go deep into ecosystem today we've talked about snowflakes strengths in this regard but snowflake they pretty much ticked all the boxes on our super cloud attributes and definition we asked benoit dejaville to confirm that this is all shipping and available today and he also gave us a glimpse of the future play the clip and we are still developing it you know the transactional you know unistore as we call it was announced in last summit so so they are still you know working properly but but but that's the vision right and and and that's important because we talk about the infrastructure right you mentioned a lot about storage and compute but it's not only that right when you think about application they need to use the transactional database they need to use an analytical system they need to use you know machine learning so you need to provide also all these services which are consistent across all the cloud providers so you can hear deja ville talking about expanding beyond taking advantage of the core infrastructure storage and networking et cetera and bringing intelligence to the data through machine learning and ai so of course there's more to come and there better be at this company's valuation despite the recent sharp pullback in a tightening fed environment okay so i know it's cliche but everyone's comparing snowflakes and data bricks databricks has been pretty vocal about its open source posture compared to snowflakes and it just so happens that we had aligotsy on at super cloud 22 as well he wasn't in studio he had to do remote because i guess he's presenting at an investor conference this week so we had to bring him in remotely now i didn't get to do this interview john furrier did but i listened to it and captured this clip about how data bricks sees super cloud and the importance of open source take a listen to goatzee yeah i mean let me start by saying we just we're big fans of open source we think that open source is a force in software that's going to continue for you know decades hundreds of years and it's going to slowly replace all proprietary code in its way we saw that you know it could do that with the most advanced technology windows you know proprietary operating system very complicated got replaced with linux so open source can pretty much do anything and what we're seeing with the data lake house is that slowly the open source community is building a replacement for the proprietary data warehouse you know data lake machine learning real-time stack in open source and we're excited to be part of it for us delta lake is a very important project that really helps you standardize how you lay out your data in the cloud and with it comes a really important protocol called delta sharing that enables you in an open way actually for the first time ever share large data sets between organizations but it uses an open protocol so the great thing about that is you don't need to be a database customer you don't even like databricks you just need to use this open source project and you can now securely share data sets between organizations across clouds and it actually does so really efficiently just one copy of the data so you don't have to copy it if you're within the same cloud so the implication of ellie gotzi's comments is that databricks with delta sharing as john implied is playing a long game now i don't know if enough about the databricks architecture to comment in detail i got to do more research there so i reached out to my two analyst friends tony bear and sanji mohan to see what they thought because they cover these companies pretty closely here's what tony bear said quote i've viewed the divergent lake house strategies of data bricks and snowflake in the context of their roots prior to delta lake databrick's prime focus was the compute not the storage layer and more specifically they were a compute engine not a database snowflake approached from the opposite end of the pool as they originally fit the mold of the classic database company rather than a specific compute engine per se the lake house pushes both companies outside of their original comfort zones data bricks to storage snowflake to compute engine so it makes perfect sense for databricks to embrace the open source narrative at the storage layer and for snowflake to continue its walled garden approach but in the long run their strategies are already overlapping databricks is not a 100 open source company its practitioner experience has always been proprietary and now so is its sql query engine likewise snowflake has had to open up with the support of iceberg for open data lake format the question really becomes how serious snowflake will be in making iceberg a first-class citizen in its environment that is not necessarily officially branding a lake house but effectively is and likewise can databricks deliver the service levels associated with walled gardens through a more brute force approach that relies heavily on the query engine at the end of the day those are the key requirements that will matter to data bricks and snowflake customers end quote that was some deep thought by by tony thank you for that sanjay mohan added the following quote open source is a slippery slope people buy mobile phones based on open source android but it's not fully open similarly databricks delta lake was not originally fully open source and even today its photon execution engine is not we are always going to live in a hybrid world snowflake and databricks will support whatever model works best for them and their customers the big question is do customers care as deeply about which vendor has a higher degree of openness as we technology people do i believe customers evaluation criteria is far more nuanced than just to decipher each vendor's open source claims end quote okay so i had to ask dodgeville about their so-called wall garden approach and what their strategy is with apache iceberg here's what he said iceberg is is very important so just to to give some context iceberg is an open you know table format right which was you know first you know developed by netflix and netflix you know put it open source in the apache community so we embrace that's that open source standard because because it's widely used by by many um many you know companies and also many companies have you know really invested a lot of effort in building you know big data hadoop solution or data like solution and they want to use snowflake and they couldn't really use snowflake because all their data were in open you know formats so we are embracing icebergs to help these companies move through the cloud but why we have been relentless with direct access to data direct access to data is a little bit of a problem for us and and the reason is when you direct access to data now you have direct access to storage now you have to understand for example the specificity of one cloud versus the other so as soon as you start to have direct access to data you lose your you know your cloud diagnostic layer you don't access data with api when you have direct access to data it's very hard to secure data because you need to grant access direct access to tools which are not you know protected and you see a lot of you know hacking of of data you know because of that so so that was not you know direct access to data is not serving well our customers and that's why we have been relented to do that because it's it's cr it's it's not cloud diagnostic it's it's you you have to code that you have to you you you need a lot of intelligence while apis access so we want open apis that's that's i guess the way we embrace you know openness is is by open api versus you know you access directly data here's my take snowflake is hedging its bets because enough people care about open source that they have to have some open data format options and it's good optics and you heard benoit deja ville talk about the risks of directly accessing the data and the complexities it brings now is that maybe a little fud against databricks maybe but same can be said for ollie's comments maybe flooding the proprietaryness of snowflake but as both analysts pointed out open is a spectrum hey i remember unix used to equal open systems okay let's end with some etr spending data and why not compare snowflake and data bricks spending profiles this is an xy graph with net score or spending momentum on the y-axis and pervasiveness or overlap in the data set on the x-axis this is data from the january survey when snowflake was holding above 80 percent net score off the charts databricks was also very strong in the upper 60s now let's fast forward to this next chart and show you the july etr survey data and you can see snowflake has come back down to earth now remember anything above 40 net score is highly elevated so both companies are doing well but snowflake is well off its highs and data bricks has come down somewhat as well databricks is inching to the right snowflake rocketed to the right post its ipo and as we know databricks wasn't able to get to ipo during the covet bubble ali gotzi is at the morgan stanley ceo conference this week they got plenty of cash to withstand a long-term recession i'm told and they've started the message that they're a billion dollars in annualized revenue i'm not sure exactly what that means i've seen some numbers on their gross margins i'm not sure what that means i've seen some numbers on their net retention revenue or net revenue retention again i'll reserve judgment until we see an s1 but it's clear both of these companies have momentum and they're out competing in the market well as always be the ultimate arbiter different philosophies perhaps is it like democrats and republicans well it could be but they're both going after a solving data problem both companies are trying to help customers get more value out of their data and both companies are highly valued so they have to perform for their investors to paraphrase ralph nader the similarities may be greater than the differences okay that's it for today thanks to the team from palo alto for this awesome super cloud studio build alex myerson and ken shiffman are on production in the palo alto studios today kristin martin and sheryl knight get the word out to our community rob hoff is our editor-in-chief over at siliconangle thanks to all please check out etr.ai for all the survey data remember these episodes are all available as podcasts wherever you listen just search breaking analysis podcasts i publish each week on wikibon.com and siliconangle.com and you can email me at david.vellante at siliconangle.com or dm me at devellante or comment on my linkedin posts and please as i say etr has got some of the best survey data in the business we track it every quarter and really excited to be partners with them this is dave vellante for the cube insights powered by etr thanks for watching and we'll see you next time on breaking analysis [Music] you

(upbeat music) >> Announcer: TheCUBE presents KubeCon and CloudNativeCon Europe, 2022. Brought to you by Red Hat, the Cloud Native Computing Foundation and its ecosystem partners. >> Welcome to Valencia, Spain, a KubeCon, CloudNativeCon Europe, 2022. I'm your host, Keith Townsend alongside Paul Gillon, Senior Editor, Enterprise Architecture for SiliconANGLE. We are, I think at the half point way point this to be fair we've talked to a lot of folks in open source in general. What's the difference between open source communities and these closed source communities that we attend so so much? >> Well open source is just it's that it's open it's anybody can contribute. There are a set of rules that manage how your contributions are reflected in the code base. What has to be shared, what you can keep to yourself but the it's an entirely different vibe. You know, you go to a conventional conference where there's a lot of proprietary being sold and it's all about cash. It's all about money changing hands. It's all about doing the deal. And open source conferences I think are more, they're more transparent and yeah money changes hands, but it seems like the objective of the interaction is not to consummate a deal to the degree that it is at a more conventional computer conference. >> And I think that can create an uneven side effect. And we're going to talk about that a little bit with, honestly a friend of mine Alex Ellis, founder of OpenFaaS. Alex welcome back to the program. >> Thank you, good to see Keith. >> So how long you've been doing OpenFaaS? >> Well, I first had this idea that serverless and function should be run on your own hardware back in 2016. >> Wow and I remember seeing you at DockerCon EU, was that in 2017? >> Yeah, I think that's when we first met and Simon Foskett took us out to dinner and we got chatting. And I just remember you went back to your hotel room after the presentation. You just had your iPhone out and your headphones you were talking about how you tried to OpenWhisk and really struggled with it and OpenFaaS sort of got you where you needed to be to sort of get some value out of the solution. >> And I think that's the magic of these open source communities in open source conferences that you can try stuff, you can struggle with it, come to a conference either get some advice or go in another direction and try something like a OpenFaaS. But we're going to talk about the business perspective. >> Yeah. >> Give us some, like give us some hero numbers from the project. What types of organizations are using OpenFaaS and what are like the download and stars all those, the ways you guys measure project success. >> So there's a few ways that you hear this talked about at KubeCon specifically. And one of the metrics that you hear the most often is GitHub stars. Now a GitHub star means that somebody with their laptop like yourself has heard of a project or seen it on their phone and clicked a button that's it. There's not really an indication of adoption but of interest. And that might be fleeting and a blog post you might publish you might bump that up by 2000. And so OpenFaaS quite quickly got a lot of stars which encouraged me to go on and do more with it. And it's now just crossed 30,000 across the whole organization of about 40 different open source repositories. >> Wow that is a number. >> Now you are in ecosystem where Knative is also taken off. And can you distinguish your approach to serverless or FaaS to Knatives? >> Yes so, Knative isn't an approach to FaaS. That's simply put and if you listen to Aikas Ville from the Knative project, he was working inside Google and wished that Kubernetes would do a little bit more than what it did. And so he started an initiative with some others to start bringing more abstractions like Auto Scaling, revision management so he can have two versions of code and and shift traffic around. And that's really what they're trying to do is add onto Kubernetes and make it do some of the things that a platform might do. Now OpenFaaS started from a different angle and frankly, two years earlier. >> There was no Kubernetes when you started it. >> It kind of led in the space and and built out that ecosystem. So the idea was, I was working with Lambda and AWS Alexa skills. I wanted to run them on my own hardware and I couldn't. And so OpenFaaS from the beginning started from that developer experience of here's my code, run it for me. Knative is a set of extensions that may be a building block but you're still pretty much working with Kubernetes. We get calls come through. And actually recently I can't tell you who they are but there's a very large telecommunications provider in the US that was using OpenFaaS, like yourself heard of Knative and in the hype they switched. And then they switched back again recently to OpenFaaS and they've come to us for quite a large commercial deal. >> So did they find Knative to be more restrictive? >> No, it's the opposite. It's a lot less opinionated. It's more like building blocks and you are dealing with a lot more detail. It's a much bigger system to manage, but don't get me wrong. I mean the guys are very friendly. They have their sort of use cases that they pursue. Google's now donated the project to CNCF. And so they're running it that way. Now it doesn't mean that there aren't FaaS on top of it. Red Hat have a serverless product VMware have one. But OpenFaaS because it owns the whole stack can get you something that's always been very lean, simple to use to the point that Keith in his hotel room installed it and was product with it in an evening without having to be a Kubernetes expert. >> And that is and if you remember back that was very anti-Kubernetes. >> Yes. >> It was not a platform I thought that was. And for some of the very same reasons, I didn't think it was very user friendly. You know, I tried open with I'm thinking what enterprise is going to try this thing, especially without the handholding and the support needed to do that. And you know, something pretty interesting that happened as I shared this with you on Twitter, I was having a briefing by a big microprocessor company, one of the big two. And they were showing me some of the work they were doing in Cloud-native and the way that they stretch test the system to show me Auto Scaling. Is that they bought up a OpenFaaS what is it? The well text that just does a bunch of, >> The cows maybe. >> Yeah the cows. That does just a bunch of texts. And it just all, and I'm like one I was amazed at is super simple app. And the second one was the reason why they discovered it was because of that simplicity is just a thing that's in your store that you can just download and test. And it was open fast. And it was this big company that you had no idea that was using >> No >> OpenFaaS. >> No. >> How prevalent is that? That you're always running into like these surprises of who's using the solution. >> There are a lot of top tier companies, billion dollar companies that use software that I've worked on. And it's quite common. The main issue you have with open source is you don't have like the commercial software you talked about, the relationships. They don't tell you they're using it until it breaks. And then they may come in incognito with a personal email address asking for things. What they don't want to do often is lend their brands or support you. And so it is a big challenge. However, early on, when I met you, BT, live person the University of Washington, and a bunch of other companies had told us they were using it. We were having discussions with them took them to Kubecon and did talks with them. You can go and look at them in the video player. However, when I left my job in 2019 to work on this full time I went to them and I said, you know, use it in production it's useful for you. We've done a talk, we really understand the business value of how it saves you time. I haven't got a way to fund it and it won't exist unless you help they were like sucks to be you. >> Wow that's brutal. So, okay let me get this right. I remember the story 2019, you leave your job. You say I'm going to do OpenFaaS and support this project 100% of your time. If there's no one contributing to the project from a financial perspective how do you make money? I've always pitched open source because you're the first person that I've met that ran an open source project. And I always pitched them people like you who work on it on their side time. But they're not the Knatives of the world, the SDOs, they have full time developers. Sponsored by Google and Microsoft, etc. If you're not sponsored how do you make money off of open source? >> If this is the million dollar question, really? How do you make money from something that is completely free? Where all of the value has already been captured by a company and they have no incentive to support you build a relationship or send you money in any way. >> And no one has really figured it out. Arguably Red Hat is the only one that's pulled it off. >> Well, people do refer to Red Hat and they say the Red Hat model but I think that was a one off. And we quite, we can kind of agree about that in a business. However, I eventually accepted the fact that companies don't pay for something they can get for free. It took me a very long time to get around that because you know, with open source enthusiast built a huge community around this project, almost 400 people have contributed code to it over the years. And we have had full-time people working on it on and off. And there's some people who really support it in their working hours or at home on the weekends. But no, I had to really think, right, what am I going to offer? And to begin with it would support existing customers weren't interested. They're not really customers because they're consuming it as a project. So I needed to create a product because we understand we buy products. Initially I just couldn't find the right customers. And so many times I thought about giving up, leaving it behind, my family would've supported me with that as well. And they would've known exactly why even you would've done. And so what I started to do was offer my insights as a community leader, as a maintainer to companies like we've got here. So Casting one of my customers, CSIG one of my customers, Rancher R, DigitalOcean, a lot of the vendors you see here. And I was able to get a significant amount of money by lending my expertise and writing content that gave me enough buffer to give the doctors time to realize that maybe they do need support and go a bit further into production. And over the last 12 months, we've been signing six figure deals with existing users and new users alike in enterprise. >> For support >> For support, for licensing of new features that are close source and for consulting. >> So you have proprietary extensions. Also that are sort of enterprise class. Right and then also the consulting business, the support business which is a proven business model that has worked >> Is a proven business model. What it's not a proven business model is if you work hard enough, you deserve to be rewarded. >> Mmh. >> You have to go with the system. Winter comes after autumn. Summer comes after spring and you, it's no point saying why is it like that? That's the way it is. And if you go with it, you can benefit from it. And that's what the realization I had as much as I didn't want to do it. >> So you know this community, well you know there's other project founders out here thinking about making the leap. If you're giving advice to a project founder and they're thinking about making this leap, you know quitting their job and becoming the next Alex. And I think this is the perception that the misperception out there. >> Yes. >> You're, you're well known. There's a difference between being well known and well compensated. >> Yeah. >> What advice would you give those founders >> To be. >> Before they make the leap to say you know what I'm going to do my project full time. I'm going to lean on the generosity of the community. So there are some generous people in the community. You've done some really interesting things for individual like contributions etc but that's not enough. >> So look, I mean really you have to go back to the MBA mindset. What problem are you trying to solve? Who is your target customer? What do they care about? What do they eat and drink? When do they go to sleep? You really need to know who this is for. And then customize a journey for them so that they can come to you. And you need some way initially of funneling those people in qualifying them because not everybody that comes to a student or somebody doing a PhD is not your customer. >> Right, right. >> You need to understand sales. You need to understand a lot about business but you can work it out on your way. You know, I'm testament to that. And once you have people you then need something to sell them that might meet their needs and be prepared to tell them that what you've got isn't right for them. 'cause sometimes that's the one thing that will build integrity. >> That's very hard for community leaders. It's very hard for community leaders to say, no >> Absolutely so how do you help them over that hump? I think of what you've done. >> So you have to set some boundaries because as an open source developer and maintainer you want to help everybody that's there regardless. And I think for me it was taking some of the open source features that companies used not releasing them anymore in the open source edition, putting them into the paid developing new features based on what feedback we'd had, offering support as well but also understanding what is support. What do you need to offer? You may think you need a one hour SLA for a fix probably turns out that you could sell a three day response time or one day response time. And some people would want that and see value in it. But you're not going to know until you talk to your customers. >> I want to ask you, because this has been a particular interest of mine. It seems like managed services have been kind of the lifeline for pure open source companies. Enabling these companies to maintain their open source roots, but still have a revenue stream of delivering as a service. Is that a business model option you've looked at? >> There's three business models perhaps that are prevalent. One is OpenCore, which is roughly what I'm following. >> Right. >> Then there is SaaS, which is what you understand and then there's support on pure open source. So that's more like what Rancher does. Now if you think of a company like Buoyant that produces Linkerd they do a bit of both. So they don't have any close source pieces yet but they can host it for you or you can host it and they'll support you. And so I think if there's a way that you can put your product into a SaaS that makes it easier for them to run then you know go for it. However, we've OpenFaaS, remember what is the core problem we are solving, portability So why lock into my cloud? >> Take that option off the table, go ahead. >> It's been a long journey and I've been a fan since your start. I've seen the bumps and bruises and the scars get made. If you're open source leader and you're thinking about becoming as famous as Alex, hey you can do that, you can put in all the work become famous but if you want to make a living, solve a problem, understand what people are willing to pay for that problem and go out and sell it. Valuable lessons here on theCUBE. From Valencia, Spain I'm Keith Townsend along with Paul Gillon and you're watching theCUBE the leader in high-tech coverage. (Upbeat music)

>>From the cube studios in Palo Alto, in Boston, bringing you data-driven insights from the cube and ETR. This is breaking analysis with Dave Vellante >>UI path has always been an unconventional company. You know, it started with humble beginnings. It was essentially a software development shop. And then it caught lightning in a bottle with its computer vision technology. And it's really it's simplification mantra. And it created a very easy to deploy software robot system for bespoke departments. So they could automate mundane tasks. You know, you know, the story, the company grew rapidly was able to go public early this year. Now consistent with its out of the ordinary approach. While other firms are shutting down travel and physical events, UI path is moving ahead with forward for its annual user conference next week with a live audience there at the Bellagio in Las Vegas, it's also fast-forwarding as a company determined to lead the charge beyond RPA and execute on a more all encompassing enterprise automation agenda. Hello everyone. And welcome to this week's Wiki bond Cuban sites powered by ETR in this breaking analysis and a head of forward four we'll update you in the RPA market. >>The progress that UI path has made since its IPO and bringing some ETR customer survey data to contextualize the company's position in the overall market and relative to the competition. Here's a quick rundown of today's agenda. First, I want to tell you the cube is going to be at forward for, at the Bellagio next week, UI paths. This is their big customer event. It's live. It's a physical event. It's primarily outdoors. You have to be vaccinated to attend. Now it's not completely out of the ordinary John furrier and the cube. We're at AWS public sector this past week. And we were at mobile world Congress and one of the first big hybrid events of the year at Barcelona. And we thought that event would kick off the fall event season live event in earnest, but the COVID crisis has caused many tech firms. Most tech firms actually to hit the pause button, not UI path. >>They're moving ahead, they're going forward. And we see a growing trend for smaller VIP events with a virtual component topic, maybe for another day. Now we've talked extensively about the productivity challenges and the automation mandate. The pandemic has thrust upon us. Now we've seen pretty dramatic productivity improvements as remote work kicked in, but it's brought new stresses. For example, according to Qualtrics, 32% of working moms said their mental health has declined since the pandemic hit. 15% of working dads said the same by the way. So one has to question the sustainability of this perpetual Workday, and we're seeing a continuum of automation solutions emerging. And we'll talk about that today. We're seeing tons of MNA, M and a as well, but now in that continuum on the left side of the spectrum, there's Microsoft who in some ways they stand alone and that Azure is becoming ubiquitous as a SAS cloud collaboration and productivity platform. >>Microsoft is everywhere and in virtually every market with their video conferencing security database, cloud CRM, analytics, you name it, Microsoft is pretty much there. And RPA is no different with the acquisition of soft emotive. Last year, Microsoft entered the RTA market in earnest and is penetrating very deeply into the space, particularly as it pertains to personal approach, personal productivity building on its software state. Now in the middle of that spectrum, if you will, we're seeing more M and a, and that's defined really by the big software giants. Think of this domain as integrated software plays SAP, they acquired contexture, uh, uh, they also acquired a company called process insight service now acquired Intella bought Salesforce service trace. We see in for entering the fray. And I, I would put even Pega Pega systems in this camp, software companies focused on integrating RPA into their broader workflows into their software platforms. >>And this is important because these platforms are entrenched. They're walled gardens of sorts and complicated with lots of touchpoints and integration points. And frankly, they're much harder to automate because of their entrenched legacy. Now on the far side of that, spectrum are the horizontal automation players and that's being led by UI path with automate automation anywhere as the number two player in this domain. And I didn't even put blue prism prism in there more M and a recently announced, uh, that Vista is going to acquire them. Vista also owns TIBCO. They're going to merge those two companies, you know, tip goes kind of an integration play. And so again, I'm, I might, I would put them in that, you know, horizontal piece of the spectrum. So with that as background, we're going to look at how UI path has performed since we last covered them at IPO. >>And then we'll bring in some ETR survey data to get the spending view from customers. And then we'll wrap up now just to emphasize the importance of, of automation and the automation mandate mandate. We talk about it all the time in this program, we use this ETR chart. It's a two dimensional view with net score, which is a measure of spending momentum on the vertical axis and market share, which is a proxy for pervasiveness in the dataset. That's on the horizontal axis. Now note that red dotted line at signifies companies with an elevated position on the net score, vertical axis, anything over that is considered pretty good, very good. Now this shows every spending segment within the ETR taxonomy and the four spending categories with the greatest velocity are AI cloud containers and RPA. And they've topped the charts for quite a while. Now they're the only four categories which have sustained above that 40% line consistently throughout the pandemic. >>And even before now, the impressive thing about cloud of course, is it has a spending has both spending momentum on the vertical axis at a very large share of the, of the market share of presence in the dataset. The point is RPA is nascent still. It has an affinity with AI as a means of more intelligently identifying and streamlining process improvements. And so we expect those to, to remain elevated and grow to the right together, UI path pegs it's Tam, total available market at 60 billion. And the reality is that could be understated. Okay. As we reported from the UI path S one analysis, we did pre IPO. The company at that time had an AR annual recurring revenue of $580 million and was growing at 65% annually at nearly 8,000 customers at the time, a thousand of which had an ARR in excess of a hundred K and a net revenue retention, the company had with 145%. >>So let's take a look at the picture six months forward. We mentioned the $60 billion Tam ARR now up over 725 million on its way to a billion ARR holding pretty steady at 60% growth as is an RR net revenue retention, and more than a thousand new customers in 200 more with over a hundred thousand in ARR and a small operating profit, which by the way, exceeded the consensus pretty substantially. Profitability is not shown here and no one seems to care anyway, these days it's all about growing into that Tam. Well, that's a pretty good looking picture. Isn't it? The company had a beat and a raise for the quarter early this month. So looking good, right? Well, you ask how come the stock's not doing better. That's an interesting question. So let's first look at the stocks performance on a relative basis. Here, we show you I pass performance against Pega systems and blue prism. >>The other two publicly traded automation, pure plays, you know, sort of in the case of Pega. So UI path outperformed post its IPO, but since the early summer Pega has been the big winner. Well, UI path slowly decelerated, you see blue prism was the laggard until it was announced. It was in an acquisition talks with a couple of PE firms and the prospects of a bidding war sent that yellow line up. As you can see UI path, as you can see on the inset has a much higher valuation than Pega and way higher than blue prison. Pega. Interestingly is growing revenues nicely at around 40%. And I think what's happening is the street simply wants more, even though UI path beat and raised wall street, still getting comfortable with which is new to the public market game. And the company just needs to demonstrate a track record and build trust. >>There's also some education around billings and multi-year contracts that the company addressed on its last earnings call, but the street was concerned about ARR from new logos. It appears to be slowing down sequentially in a notable decline in billings momentum, which UI pass CEO, CFO addressed on the earnings call saying, look, they don't need to trade margin for prepaid multi-year deals, given the strong cash position while I give anything up. And even though I said, nobody cares about profitability. Well, I guess that's true until you guide for an operating loss. When you've been showing a small profit in recent recent quarters, which you AIPAC did, then all of a sudden people care. So UI path, isn't a bit of an unknown territory to the street and it has a valuation that's pretty rich, very rich, actually at 30 times, a revenue multiple greater than 30 times revenue, multiple. >>So that's why in, in my view, investors are being cautious, but I want to address a dynamic that we've seen with these high growth rocket ship companies, something we talked about with snowflake. And I think you're seeing some of that here with UI paths, different model in the sense that snowflake is pure cloud, but I'm talking about concerns around ARR from new logos and in that growth on a sequential basis. And here's what's happening in my view with UI path, you have a company that started within departments with a small average contract size in ACV, maybe 25,000, maybe 50,000, but not deep six figure deals that wasn't UI paths play it because the company focused so heavily on simplicity and made it really easy to adopt customer saw really fast ROI. I mean breakeven in months. So you very quickly saw expansion into other departments. >>So when ACV started to rise and installations expanded within each customer UI path realized it had to move beyond being a point product. And it started thinking about a platform and making acquisitions like process gold and others, and this marked a much deeper expansion into the customer base. And you can see that here in this UI path, a chart that they shared at their investor deck customers that bought in 2016 and 2017 expanded their they've expanded their spend 15, 13, 15, 18 20 X. So the LTV, the lifetime value of the customer is growing dramatically. And because UI path has focused on simplicity, it has a very facile freemium model, much easier to try before you buy than its competitors. It's CAC, it's customer acquisition costs are likely much lower than some of its peers. And that's a key dynamic. So don't get freaked out by some of those concerns that we raised earlier, because just like snowflake what's happening is the company for sure is gaining new customers. >>Maybe just not at the same rate, but don't miss the forest through the trees. I E they're getting more money from their existing customers, which means retention, loyalty and growth. Speaking of forests, this chart is the dynamic I'm talking about. It's an ETR graphic that shows the components of net score or against spending momentum net score breaks down into five areas that lime green at the top is new additions. Okay? So that's only 11% of the customer mentions by the way, we're talking about more than 125 responses for UI path. So it's meaningful. It's, it's actually larger in this survey, uh, or certainly comparable to Microsoft. So that says something right there. The next bar is the forest green forest. Green is where I want you to focus. That's customer spending 6% or more in the second half of the year, relative to the first half. >>The gray is flat spending, which is quite large, the pink or light red that's spending customer spending 6% or worse. That's a 4% number, but look at the bottom bar. There is no bar that's churn. 0% of the respondents in the survey are churning and churn is the silent killer of SAS companies, 0% defections. So you've got 46% spending, more nobody leaving. That's the dynamic that is powering UI path right now. And I would take this picture any day over a larger lime green and a smaller forest green and a bigger churn number. Okay. So it's pretty good. It's not snowflake good, but it's solid. So how does this picture compare to UI pass peers? Well, let's take a look at that. So this is ETR data, same data showing the granularity net score for Microsoft power, automate UI path automation, anywhere blue prism and Pega. >>So as we said before, Microsoft is ubiquitous. What can we say about that? But UI path is right there with a more robust platform, not to overlook Microsoft. You can't, but UI path, it'll tell you that they don't compete head to head for enterprise automation deals with Microsoft. Now, maybe they will over time. They do however, compete head to head with automation anywhere. And their picture is quite strong. As you can see here, it has this blue Prism's picture and even Pega, although blue prism, automation, anywhere UI path and power automate all have net scores on this chart. As you can see the table in the upper right over 40% Pega does not. But again, we don't see Pega as a pure play RPA vendor. It's a little bit of sort of apples and oranges there, but they do sell RPA and ETR captures in their taxonomy. >>So why not include them also note that UI path has, as I said before, more mentions in the survey than power automate, which is actually quite interesting, given the ubiquity of Microsoft. Now, one other notable notable note is the bright red that's defections and only UI path is showing zero defections. Everybody else has at least even of the slim, some defections. Okay. So take that as you will, but it's another data 0.1. That's powerful, not only for UI path, but really for the entire sector. Now, the last ETR data point that we want to share is our famous two dimensional view. Like the sector chart we showed earlier, this graphic shows net score on the vertical axis. That's against spending velocity and market share or pervasiveness on the horizontal axis. So as we said earlier, UI path actually has greater presence in the survey than the ever-present Microsoft. >>Remember, this is the July survey. We don't have full results from the September, October survey yet. And we can't release them until ETR is out of its quiet period. But I expect the entire sector, like everything is going to be slightly down because as we reported last week, tech spending is moderated slightly in the second half of this year, but we don't expect the picture to change dramatically. UI path and power automate, we think are going to lead and market presence in those two plus automation anywhere are going to show strength and spending momentum as well. Most of the sector. And we'll see who comes in above the 40% line. Okay. What to watch at forward four. So in summary, I'll be looking for a few things. One UI path has hinted toward a big platform announcement that will deepen its capabilities to go beyond being an RPA point tool into much more of an enterprise automation platform rewriting a lot of the code Linux cloud, better automation of the UI. >>You're going to hear all kinds of new product announcements that are coming. So I'll be listening for those details. I want to hear more from customers to further confirm what I've been hearing from them over the last couple of years and get more data, especially on that ROI on that land and expand. I want to understand that dynamic and that true enterprise automation. It's going to be good to get an update face to face and test some of our assumptions here and see where the gaps are and where UI path can improve. Third. I want to talk to ecosystem players to see where they are in participating in the value chain here. What kind of partner has UI path become since it's IPO? Are they investing more in the ecosystem? How to partners fit into that flywheel fourth, I want to hear from UI path management, Daniel DNAs, and other UI path leaders, they're exiting toddler Ville and coming into an adolescent phase or early adulthood. >>And what does that progression look like? How does it feel? What's the vibe at the show. And finally, I'm very excited to participate in a live in-person event to see what's working, see how a hybrid events are evolving. We got a good glimpse at mobile world Congress and this week, and, uh, in DC and public sector summit, here's, you know, the cube has been doing hybrid events for years, and we intend to continue to lead in this regard and bring you the best, real time information as possible. Okay. That's it for today. Remember, these episodes are all available as podcasts, wherever you listen. All you do is search braking analysis podcast. We publish each week on Wiki bond.com and siliconangle.com. And you can always connect on twitter@devolanteoremailmeatdaviddotvolanteatsiliconangle.com. Appreciate the comments on LinkedIn. And don't forget to check out E T r.plus for all the survey data. This is Dave Volante for the cube insights powered by ETR be well, and we'll see you next time.

from the silicon angle media office in Boston Massachusetts it's the queue now here's your host David on tape all right buddy welcome to this cute conversation my name is Dave Ville on time or the co-host of the cube and we're gonna have a conversation to really try to explore does infrastructure matter you hear a lot today I've ever since I've been in this business I've heard Oh infrastructure is dead hardware is dead but we're gonna explore that premise and with me is Randy Arsenault and Steve Kenaston they're both global market development execs at IBM guys thanks for coming in and let's riff thanks for having us Dave so here's one do I want to start with the data we were just recently at the MIT chief data officer event 10 years ago that role didn't even exist now data is everything so I want to start off with you here this bro my data is the new oil and we've said you know what data actually is more valuable than oil oil I can put in my car I can put in my house but I can't put it in both data is it doesn't follow the laws of scarcity I can use the same data multiple times and I can copy it and I can find new value I can cut cost I can raise revenue so data in some respects is more valuable what do you think right yeah I would agree and I think it's also to your point kind of a renewable resource right so so data has the ability to be reused regularly to be repurposed so I would take it even further we've been talking a lot lately about this whole concept that data is really evolving into its own tier so if you think about a traditional infrastructure model where you've got sort of compute and network and applications and workloads and on the edge you've got various consumers and producers of that data the data itself has those pieces have evolved the data has been evolving as well it's becoming more complicated it's becoming certainly larger and more voluminous it's better instrumented it carries much more metadata it's typically more proximal with code and compute so the data itself is evolving into its own tier in a sense so we we believe that we want to treat data as a tier we want to manage it to wrap the services around it that enable it to reach its maximum potential in a sense so guys let's we want to make this interactive in a way and I'd love to give you my opinions as well as links are okay with that but but so I want to make an observation Steve if you take a look at the top five companies in terms of market cap in the US of Apple Google Facebook Amazon and of course Microsoft which is now over a trillion dollars they're all data companies they've surpassed the bank's the insurance companies the the Exxon Mobil's of the world as the most valuable companies in the world what are your thoughts on that why is that I think it's interesting but I think it goes back to your original statement about data being the new oil the and unlike oil Ray's said you can you can put it in house what you can't put it in your car you also when it's burnt it's gone right but with data you you have it around you generate more of it you keep using it and the more you use it and the more value you get out of it the more value the company gets out of it and so as those the reason why they continue to grow in value is because they continue to collect data they continue to leverage that data for intelligent purposes to make user experiences better their business better to be able to go faster to be able to new new things faster it's all part of part of this growth so data is one of the superpowers the other superpower of course is machine intelligence or what everybody talks about as AI you know it used to be that processing power doubling every 18 months was what drove innovation in the industry today it's a combination of data which we have a lot of it's AI and cloud for scaling we're going to talk about cloud but I want to spend a minute talking about AI when I first came into this business AI was all the rage but we didn't have the amount of data that we had today we don't we didn't have the processing power it was too expensive to store all this data that's all changed so now we have this emerging machine intelligence layer being used for a lot of different inks but it's sort of sitting on top of all these workloads that's being injected into databases and applications it's being used to detect fraud to sell us more stuff you know in real time to save lives and I'm going to talk about that but it's one of these superpowers that really needs new hardware architectures so I want to explore machine intelligence a little bit it really is a game changers it really is and and and tying back to the first point about sort of the the evolution of data and the importance of data things like machine learning and adaptive infrastructure and cognitive infrastructure have driven to your point are a hard requirement to adapt and improve the infrastructure upon which that lives and runs and operates and moves and breathes so we always had Hardware evolution or development or improvements and networks and the basic you know components of the infrastructure being driven again by advances in material science and silicon etc well now what's happening is the growth and importance and and Dynamis city of data is far outpacing the ability of the physical sciences to keep pace right that's a reality that we live in so therefore things like you know cognitive computing machine learning AI are kind of bridging the gap almost between the limitations we're bumping up against in physical infrastructure and the immense unlocked potential of data so that intermediary is really where this phenomenon of AI and machine learning and deep learning is happening and you're also correct in pointing out that it's it's everywhere I mean it's imbuing every single workload it's transforming every industry and a fairly blistering pace IBM's been front and center around artificial intelligence in cognitive computing since the beginning we have a really interesting perspective on it and I think we bring that to a lot of the solutions that we offer as well Ginni Rometty a couple years ago actually use the term incumbent disruptors and when I think of that I think about artificial intelligence and I think about companies like the ones I mentioned before that are very valuable they have data at their core most incumbents don't they have data all over the place you know they might have a bottling plant at the core of the manufacturing plant or some human process at the core so to close that gap artificial intelligence from the incumbents the appointees they're gonna buy that from companies like IBM they're gonna you know procure Watson or other AI tools and you know or maybe you know use open-source AI tools but they're gonna then figure out how to apply those to their business to do whatever fraud detection or recommendation engines or maybe even improve security and we're going to talk about this in detail but Steve this there's got to be new infrastructure behind that we can't run these new workloads on infrastructure that was designed 30 40 years ago exactly I mean I think I am truly fascinated by with this growth of data it's now getting more exponential and why we think about why is it getting more exponential it's getting more exponential because the ease at which you can actually now take advantage of that data it's going beyond the big financial services companies the big healthcare companies right we're moving further and further and further towards the edge where people like you and I and Randi and I have talked about the maker economy right I want to be able to go in and build something on my own and then deliver it to either as a service as a person a new application or as a service to my infrastructure team to go then turn it on and make something out of that that infrastructure it's got to come down in cost but all the things that you said before performance reliability speed to get there intelligence about data movement how do we get smarter about those things all of the underlying ways we used to think about how we managed protect secure that it all has evolved and it's continuing to evolve everybody talks about the journey the journey to cloud why does that matter it's not just the cloud it's also the the componentry underneath and it's gonna go much broader much bigger much faster well and I would just add just amplify what Steve said about this whole maker movement one of the other pressures that that's putting on corporate IT is it's driving essentially driving product development and innovation out to the end to the very edge to the end user level so you have all these very smart people who are developing these amazing new services and applications and workloads when it gets to the point where they believe it can add value to the business they then hand it off to IT who is tasked with figuring out how to implement it scale it protect it secured debt cetera that's really where I believe I um plays a key role or where we can play a key role add a lot of values we understand that process of taking that from inception to scale and implementation in a secure enterprise way and I want to come back to that so we talked about data as one of the superpowers an AI and the third one is cloud so again it used to be processor speed now it's data plus AI and cloud why is cloud important because cloud enables scale there's so much innovation going on in cloud but I want to talk about you know cloud one dot o versus cloud two dot o IBM talks about you know the new era of cloud so what was cloud one dot o it was largely lift and shift it was taking a lot of crap locations and putting him in the public cloud it was a lot of tests in dev a lot of startups who said hey I don't need to you know have IT I guess like the cube we have no ID so it's great for small companies a great way to experiment and fail fast and pay for you know buy the drink that was one dot o cloud to dot all to datos is emerging is different it's hybrid it's multi cloud it's massively distributed systems distributed data on Prem in many many clouds and it's a whole new way of looking at infrastructure and systems design so as Steve as you and I have talked about it's programmable so it's the API economy very low latency we're gonna talk more about what that means but that concept of shipping code to data wherever it lives and making that cloud experience across the entire infrastructure no matter whether it's on Prem or in cloud a B or C it's a complicated problem it really is and when you think about the fact that you know the big the big challenge we started to run into when we were talking about cloud one always shadow IT right so folks really wanted to be able to move faster and they were taking data and they were actually copying it to these different locations to be able to use it for them simply and easily well once you broke that mold you started getting away from the security and the corporate furnance that was required to make sure that the business was safe right it but it but it but following the rules slowed business down so this is why they continued to do it in cloud 2.0 I like the way you position this right is the fact that I no longer want to move data around moving data it within the infrastructure is the most expensive thing to do in the data center so if I can move code to where I need to be able to work on it to get my answers to do my AI to do my intelligent learning that all of a sudden brings a lot more value and a lot more speed and speed as time as money rate if I can get it done faster I get more valuable and then just you know people often talk about moving data but you're right on you the last thing you want to do is move data in just think about how long it takes to back up the first time you ever backed up your iPhone how long it took well and that's relatively small compared to all the data in a data center there's another subtext here from a standpoint of cloud 2.0 and it involves the edge the edge is a new thing and we have a belief inside of wiki bond and the cube that we talk about all the time that a lot of the inference is going to be done at the edge what does that mean it means you're going to have factory devices autonomous vehicles a medical device equipment that's going to have intelligence in there with new types of processors and we'll talk about that but a lot of the the inference is that conclusions were made real-time and and by the way these machines will be able to talk to each other so you'll have a machine to machine communication no humans need to be involved to actually make a decision as to where should I turn or you know what should be the next move on the factory floor so again a lot of the data is gonna stay in place now what does that mean for IBM you still have an opportunity to have data hubs that collect that data analyze it maybe push it up to the cloud develop models iterate and push it back down but the edge is a fundamentally new type of approach that we've really not seen before and it brings in a whole ton of new data yeah that's a great point and it's a market phenomenon that has moved and is very rapidly moving from smartphones to the enterprise right so right so your point is well-taken if you look in the fact is we talked earlier that compute is now proximal to the data as opposed to the other way around and the emergence of things like mesh networking and you know high bandwidth local communications peer-to-peer communications it's it's not only changing the physical infrastructure model and the and the best practices around how to implement that infrastructure it's also fundamentally changing the way you buy them the way you consume them the way you charge for them so it's it's that shift is changing and having a ripple effect across our industry in every sense whether it's from the financial perspective the operational perspective the time to market perspective it's also and we talked a lot about industry transformation and disruptors that show up you know in an industry who work being the most obvious example and just got an industry from the from the bare metal and recreate it they are able to do that because they've mastered this new environment where the data is king how you exploit that data cost-effectively repeatably efficiently is what differentiates you from the pack and allows you to create a brand new business model that that didn't exist prior so that's really where every other industry is going you talking about those those those big five companies in North America that are that are the top top companies now because of data I often think about rewind you know 25 years do you think Amazon when they built Amazon really thought they were going to be in the food service business that the video surveillance business the drone business all these other book business right maybe the book business right but but their architecture had to scale and change and evolve with where that's going all around the data because then they can use these data components and all these other places to get smarter bigger and grow faster and that's that's why they're one of the top five this is a really important point especially for the young people in the audience so it used to be that if you were in an industry if you were in health care or you were in financial services or you were in manufacturing you were in that business for life every industry had its own stack the sales the marketing the R&D everything was wired to that industry and that industry domain expertise was really not portable across businesses because of data and because of digital transformations companies like Amazon can get into content they can get into music they can get it to financial services they can get into healthcare they can get into grocery it's all about that data model being portable across those industries it's a very powerful concept that you and I mean IBM owns the weather company right so I mean there's a million examples of traditional businesses that have developed ways to either enter new markets or expand their footprint in existing markets by leveraging new sources of data so you think about a retailer or a wholesale distributor they have to very accurately or as accurately as possible forecast demand for goods and make sure logistically the goods are in the right place at the right time well there are million factors that go into that there's whether there's population density there's local cultural phenomena there's all sorts of things that have to be taken into consideration previously that would be near impossible to do now you can sit down again as an individual maker I can sit down at my desk and I can craft a model that consumes data from five readily available public api's or data sets to enhance my forecast and I can then create that model execute it and give it to two of my IT guy to go scale-out okay so I want to start getting into the infrastructure conversation again remember the premise of this conversation it doesn't read for structure matter we want to we want to explore that oh I start at the high level with with with cloud multi-cloud specifically we said cloud 2.0 is about hybrid multi cloud I'm gonna make a statements of you guys chime in my my assertion is that multi cloud has largely been a symptom of multi-vendor shadow IT different developers different workloads different lines of business saying hey we want to we want to do stuff in the cloud this happened so many times in the IT business all and then I was gonna govern it how is this gonna be secure who's got access control on and on and on what about compliance what about security then they throw it over to IT and they say hey help us fix this and so itea said look we need a strategy around multi cloud it's horses for courses maybe we go for cloud a for our collaboration software cloud B for the cognitive stuff cloud C for the you know cheap and deep storage different workloads for different clouds but there's got to be a strategy around that so I think that's kind of point number one and I T is being asked to kind of clean up this stuff but the future today the clouds are loosely coupled there may be a network that connects them but there's there's not a really good way to take data or rather to take code ship it to data wherever it lives and have it be a consistent well you were talking about an enterprise data plane that's emerging and that's kind of really where the opportunity is and then you maybe move into the control plane and the management piece of it and then bring in the edge but envision this mesh of clouds if you will whether it's on pram or in the public cloud or some kind of hybrid where you can take metadata and code ship it to wherever the data is leave it there much smaller you know ship five megabytes of code to a petabyte of data as opposed to waiting three months to try to ship you know petabytes to over the network it's not going to work so that's kind of the the spectrum of multi cloud loosely coupled today going to this you know tightly coupled mesh your guys thoughts on that yeah that's that's a great point and and I would add to it or expand that even further to say that it's also driving behavioral fundamental behavioral and organizational challenges within a lot of organizations and large enterprises cloud and this multi cloud proliferation that you spoke about one of the other things that's done that we talked about but probably not enough is it's almost created this inversion situation where in the past you'd have the business saying to IT I need this I need this supply chain application I need this vendor relationship database I need this order processing system now with the emergence of this cloud and and how easy it is to consume and how cost-effective it is now you've got the IT guys and the engineers and the designers and the architects and the data scientists pushing ideas to the business hey we can expand our footprint and our reach dramatically if we do this so you've get this much more bi-directional conversation happening now which frankly a lot of traditional companies are still working their way through which is why you don't see you know 100% cloud adoption but it drives those very productive full-duplex conversations at a level that we've never seen before I mean we encounter clients every day who are having these discussions are sitting down across the table and IT is not just doesn't just have a seat at the table they are often driving the go-to-market strategy so that's a really interesting transformation that we see as well in addition to the technology so there are some amazing things happening Steve underneath the covers and the plumbing and infrastructure and look at we think infrastructure matters that's kind of why we're here we're infrastructure guys but I want to make a point so for decades this industry is marked to the cadence of Moore's law the idea that you can double processing speeds every 18 months disk drive processors disk drives you know they followed that curve you could plot it out the last ten years that started to attenuate so what happened is chip companies would start putting more cores on to the real estate well they're running out of real estate now so now what's happening is we've seen this emergence of alternative processors largely came from mobile now you have arm doing a lot of offload processing a lot of the storage processing that's getting offloaded those are ARM processors in video with GPUs powering a lot of a lot of a is yours even seeing FPGAs they're simple they're easy them to spin up Asics you know making a big comeback so you've seen these alternative processes processors powering things underneath where the x86 is and and of course they're still running applications on x86 so that's one sort of big thing big change in infrastructure to support this distributed systems the other is flash we saw flash basically take out spinning disk for all high-speed applications we're seeing the elimination of scuzzy which is a protocol that sits in between the the the disk you know and the rest of the network that's that's going away you're hearing things like nvme and rocky and PCIe basically allowing stores to directly talk to the so now a vision envision this multi-cloud system where you want to ship metadata and code anywhere these high speed capabilities interconnects low latency protocols are what sets that up so there's technology underneath this and obviously IBM is you know an inventor of a lot of this stuff that is really gonna power this next generation of workloads your comments yeah I think I think all that 100% true and I think the one component that we're fading a little bit about it even in the infrastructure is the infrastructure software right there's hardware we talked a lot talked about a lot of hardware component that are definitely evolving to get us better stronger faster more secure more reliable and that sort of thing and then there's also infrastructure software so not just the application databases or that sort of thing but but software to manage all this and I think in a hybrid multi cloud world you know you've got these multiple clauses for all practical purposes there's no way around it right marketing gets more value out of the Google analytic tools and Google's cloud and developers get more value out of using the tools in AWS they're gonna continue to use that at the end of the day I as a business though need to be able to extract the value from all of those things in order to make different business decisions to be able to move faster and surface my clients better there's hardware that's gonna help me accomplish that and then there are software things about managing that whole consetta component tree so that I can maximize the value across that entire stack and that stack is multiple clouds plus the internal clouds external clouds everything yeah so it's great point and you're seeing clear examples of companies investing in custom hardware you see you know Google has its own ship Amazon its own ship IBM's got you know power 9 on and on but none of this stuff works if you can't manage it so we talked before about programmable infrastructure we talked about the data plane and the control plane that software that's going to allow us to actually manage these multiple clouds as at least a quasi single entity you know something like a logical entity certainly within workload classes and in Nirvana across the entire you know network well and and the principal or the principle drivers of that evolution of course is containerization right so the containerization phenomenon and and you know obviously with our acquisition of red hat we're now very keenly aware and acutely plugged into the whole containerization phenomenon which is great we're you're seeing that becoming almost the I can't think of us a good metaphor but you're seeing containerization become the vernacular that's being spoken in multiple different types of reference architectures and use case environments that are vastly different in their characteristics whether they're high throughput low latency whether they're large volume whether they're edge specific whether they're more you know consolidated or hub-and-spoke models containerization is becoming the standard by which those architectures are being developed and with which they're being deployed so we think we're very well-positioned working with that emerging trend and that rapidly developing trend to instrument it in a way that makes it easier to deploy easier to instrument easier to develop so that's key and I want to sort of focus now on the relevance of IBM one side one thing that we understand because that that whole container is Asian think back to your original point Dave about moving data being very expensive and the fact that the fact that you want to move code out to the data now with containers microservices all of that stuff gets a lot easier development becomes a lot faster and you're actually pushing the speed of business faster well and the other key point is we talked about moving code you know to the data as you move the code to the data and run applications anywhere wherever the data is using containers the kubernetes etc you don't have to test it it's gonna run you know assuming you have the standard infrastructure in place to do that and the software to manage it that's huge because that means business agility it means better quality and speed alright let's talk about IBM the world is complex this stuff is not trivial the the more clouds we have the more edge we have the more data we have the more complex against IBM happens to be very good at complex three components of the innovation cocktail data AI and cloud IBM your customers have a lot of data you guys are good with data it's very strong analytics business artificial intelligence machine intelligence you've invested a lot in Watson that's a key component business and cloud you have a cloud it's not designed to compete not knock heads and the race to zero with with the cheap and deep you know storage clouds it's designed to really run workloads and applications but you've got all three ingredients as well you're going hard after the multi cloud world for you guys you've got infrastructure underneath you got hardware and software to manage that infrastructure all the modern stuff that we've talked about that's what's going to power the customers digital transformations and we'll talk about that in a moment but maybe you could expand on that in terms of IBM's relevance sure so so again using the kind of maker the maker economy metaphor bridging from that you know individual level of innovation and creativity and development to a broadly distributed you know globally available work loader or information source of some kind the process of that bridge is about scale and reach how do you scale it so that it runs effectively optimally is easily managed Hall looks and feels the same falls under the common umbrella of services and then how do you get it to as many endpoints as possible whether it's individuals or entities or agencies or whatever scale and reach iBM is all about scale and reach I mean that's kind of our stock and trade we we are able to take solutions from small kind of departmental level or kind of skunkworks level and make them large secure repeatable easily managed services and and make them as turnkey as possible our services organizations been doing it for decades exceptionally well our product portfolio supports that you talk about Watson and kind of the cognitive computing story we've been a thought leader in this space for decades I mean we didn't just arrive on the scene two years ago when machine learning and deep learning and IO ste started to become prominent and say this sounds interesting we're gonna plant our flag here we've been there we've been there for a long time so you know I kind of from an infrastructure perspective I kind of like to use the analogy that you know we are technology ethos is built on AI it's built on cognitive computing and and sort of adaptive computing every one of our portfolio products is imbued with that same capability so we use it internally we're kind of built from AI for AI so maybe that's the answer to this question of it so what do you say that somebody says well you know I want to buy you know my flash storage from pure AI one of my bi database from Oracle I want to buy my you know Intel servers from Dell you know whatever I want to I want to I want control and and and I gotta go build it myself why should I work with IBM do you do you get that a lot and how do you respond to that Steve I think I think this whole new data economy has opened up a lot of places for data to be stored anywhere I think at the end of the day it really comes down to management and one of the things that I was thinking about as you guys were we're conversing is the enterprise class or Enterprise need for things like security and protection that sort of thing that rounds out the software stack in our portfolio one of the things we can bring to the table is sure you can go by piece parts and component reform from different people that you want right and in that whole notion around fail-fast sure you can get some new things that might be a little bit faster that might be might be here first but one of the things that IBM takes a lot of pride was a lot of qual a lot of pride into is is the quality of their their delivery of both hardware and software right so so to me even though the infrastructure does matter quite a bit the question is is is how much into what degree so when you look at our core clients the global 2,000 right they want to fail fast they want to fail fast securely they want to fail fast and make sure they're protected they want to fail fast and make sure they're not accidentally giving away the keys to the kingdom at the end of the day a lot of the large vendor a lot of the large clients that we have need to be able to protect their are their IP their brain trust there but also need the flexibility to be creative and create new applications that gain new customer bases so the way I the way I look at it and when I talk to clients and when I talk to folks is is we want to give you them that while also making sure they're they're protected you know that said I would just add that that and 100% accurate depiction the data economy is really changing the way not only infrastructure is deployed and designed but the way it can be I mean it's opening up possibilities that didn't exist and there's new ones cropping up every day to your point if you want to go kind of best to breed or you want to have a solution that includes multi vendor solutions that's okay I mean the whole idea of using again for instance containerization thinking about kubernetes and docker for instance as a as a protocol standard or a platform standard across heterogeneous hardware that's fine like like we will still support that environment we believe there are significant additive advantages to to looking at IBM as a full solution or a full stack solution provider and our largest you know most mission critical application clients are doing that so we think we can tell a pretty compelling story and I would just finally add that we also often see situations where in the journey from the kind of maker to the largely deployed enterprise class workload there's a lot of pitfalls along the way and there's companies that will occasionally you know bump into one of them and come back six months later and say ok we encountered some scalability issues some security issues let's talk about how we can develop a new architecture that solves those problems without sacrificing any of our advanced capabilities all right let's talk about what this means for customers so everybody talks about digital transformation and digital business so what's the difference in a business in the digital business it's how they use data in order to leverage data to become one of those incumbent disruptors using Ginny's term you've got to have a modern infrastructure if you want to build this multi cloud you know connection point enterprise data pipeline to use your term Randy you've got to have modern infrastructure to do that that's low latency that allows me to ship data to code that allows me to run applet anywhere leave the data in place including the edge and really close that gap between those top five data you know value companies and yourselves now the other piece of that is you don't want to waste a lot of time and money managing infrastructure you've got to have intelligence infrastructure you've got to use modern infrastructure and you've got to redeploy those labor assets toward a higher value more productive for the company activities so we all know IT labor is a chop point and we spend more on IT labor managing Leung's provisioning servers tuning databases all that stuff that's gotta change in order for you to fund digital transformations so that to me is the big takeaway as to what it means for customer and we talked about that sorry what we talked about that all the time and specifically in the context of the enterprise data pipeline and within that pipeline kind of the newer generation machine learning deep learning cognitive workload phases the data scientists who are involved at various stages along the process are obviously kind of scarce resources they're very expensive so you can't afford for them to be burning cycles and managing environments you know spinning up VMs and moving data around and creating working sets and enriching metadata that they that's not the best use of their time so we've developed a portfolio of solutions specifically designed to optimize them as a resource as a very valuable resource so I would vehemently agree with your premise we talked about the rise of the infrastructure developer right so at the end of the day I'm glad you brought this topic up because it's not just customers it's personas Pete IBM talks to different personas within our client base or our prospect base about why is this infrastructure important to to them and one of the core components is skill if you have when we talk about this rise of the infrastructure developer what we mean is I need to be able to build composable intelligent programmatic infrastructure that I as IT can set up not have to worry about a lot of risk about it break have to do in a lot of troubleshooting but turn the keys over to the users now let them use the infrastructure in such a way that helps them get their job done better faster stronger but still keeps the business protected so don't make copies into production and screw stuff up there but if I want to make a copy of the data feel free go ahead and put it in a place that's safe and secure and it won't it won't get stolen and it also won't bring down the enterprise's is trying to do its business very key key components - we talked about I infused data protection and I infused storage at the end of the day it's what is an AI infused data center right it needs to be an intelligent data center and I don't have to spend a lot of time doing it the new IT person doesn't want to be troubleshooting all day long they want to be in looking at things like arm and vme what's that going to do for my business to make me more competitive that's where IT wants to be focused yeah and it's also we just to kind of again build on this this whole idea we haven't talked a lot about it but there's obviously a cost element to all this right I mean you know the enterprise's are still very cost-conscious and they're still trying to manage budgets and and they don't have an unlimited amount of capital resources so things like the ability to do fractional consumption so by you know pay paper drink right buy small bits of infrastructure and deploy them as you need and also to Steve's point and this is really Steve's kind of area of expertise and where he's a leader is kind of data efficiency you you also can't afford to have copy sprawl excessive data movement poor production schemes slow recovery times and recall times you've got a as especially as data volumes are ramping you know geometrically the efficiency piece and the cost piece is absolutely relevant and that's another one of the things that often gets lost in translation between kind of the maker level and the deployment level so I wanted to do a little thought exercise for those of you think that this is all you know bromide and des cloud 2.0 is also about we're moving from a world of cloud services to one where you have this mesh which is ubiquitous of of digital services you talked about intelligence Steve you know the intelligent data center so all these all these digital services what am I talking about AI blockchain 3d printing autonomous vehicles edge computing quantum RPA and all the other things on the Gartner hype cycle you'll be able to procure these as services they're part of this mesh so here's the thought exercise when do you think that owning and driving your own vehicle is no longer gonna be the norm right interesting thesis question like why do you ask the question well because these are some of the disruptions so the questions are designed to get you thinking about the potential disruptions you know is it possible that our children's children aren't gonna be driving their own car it's because it's a it's a cultural change when I was 16 year olds like I couldn't wait but you started to see a shifted quasi autonomous vehicles it's all sort of the rage personally I don't think they're quite ready yet but it's on the horizon okay I'll give you another one when will machines be able to make better diagnosis than doctors actually both of those are so so let's let's hit on autonomous and self-driving vehicles first I agree they're not there yet I will say that we have a pretty thriving business practice and competency around working with a das providers and and there's an interesting perception that a das autonomous driving projects are like there's okay there's ten of them around the world right maybe there's ten metal level hey das projects around the world what people often don't see is there is a gigantic ecosystem building around a das all the data sourcing all the telemetry all the hardware all the network support all the services I mean building around this is phenomenal it's growing at a had a ridiculous rate so we're very hooked into that we see tremendous growth opportunities there if I had to guess I would say within 10 to 12 years there will be functionally capable viable autonomous vehicles not everywhere but they will be you will be able as a consumer to purchase one yeah that's good okay and so that's good I agree that's a the time line is not you know within the next three to five years all right how about retail stores will well retail stores largely disappeared we're we're rainy I was just someplace the other day and I said there used to be a brick-and-mortar there and we were walking through the Cambridge Tseng Galleria and now the third floor there's no more stores right there's gonna be all offices they've shrunken down to just two floors of stores and I highly believe that it's because you know the brick you know the the retailers online are doing so well I mean think about it used to be tricky and how do you get in and and and I need the Walmart minute I go cuz I go get with Amazon and that became very difficult look at places like bombas or Casper or all the luggage plate all this little individual boutique selling online selling quickly never having to have to open up a store speed of deployment speed of product I mean it's it's it's phenomenal yeah and and frankly if if Amazon could and and they're investing billions of dollars and they're trying to solve the last mile problem if Amazon could figure out a way to deliver ninety five percent of their product catalog Prime within four to six hours brick-and-mortar stores would literally disappear within a month and I think that's a factual statement okay give me another one will banks lose control traditional banks lose control of the payment systems you can Moselle you see that banks are smart they're buying up you know fin tech companies but right these are entrenched yeah that's another one that's another one with an interesting philosophical element to it because people and some of its generational right like our parents generation would be horrified by the thought of taking a picture of a check or using blockchain or some kind of a FinTech coin or any kind of yeah exactly so Bitcoin might I do my dad ask you're not according I do I don't bit going to so we're gonna we're waiting it out though it's fine by the way I just wanted to mention that we don't hang out in the mall that's actually right across from our office I want to just add that to the previous comment so there is a philosophical piece of it they're like our generation we're fairly comfortable now because we've grown up in a sense with these technologies being adopted our children the concept of going to a bank for them will be foreign I mean it will make it all have no context for the content for the the the process of going to speak face to face to another human it just say it won't exist well will will automation whether its robotic process automation and other automation 3d printing will that begin to swing the pendulum back to onshore manufacturing maybe tariffs will help to but again the idea that machine intelligence increasingly will disrupt businesses there's no industry that's safe from disruption because of the data context that we talked about before Randy and I put together a you know IBM loves to use were big words of transformation agile and as a sales rep you're in the field and you're trying to think about okay what does that mean what does that mean for me to explain to my customer so he put together this whole thing about what his transformation mean to one of them was the taxi service right in the another one was retail so and not almost was fencers I mean you're hitting on on all the core things right but this transformation I mean it goes so deep and so wide when you think about exactly what Randy said before about uber just transforming just the taxi business retailers and taxis now and hotel chains and that's where the thing that know your customer they're getting all of that from data data that I'm putting it not that they're doing work to extract out of me that I'm putting in so that autonomous vehicle comes to pick up Steve Kenaston it knows that Steve likes iced coffee on his way to work gives me a coupon on a screen I hit the button it automatically stops at Starbucks for me and it pre-ordered it for me you're talking about that whole ecosystem wrapped around just autonomous vehicles and data now it's it's unbeliev we're not far off from the Minority Report era of like Anthem fuck advertising targeted at an individual in real time I mean that's gonna happen it's almost there now I mean you just use point you will get if I walk into Starbucks my phone says hey why don't you use some points while you're here Randy you know so so that's happening at facial recognition I mean that's all it's all coming together so and again underneath all this is infrastructure so infrastructure clearly matters if you don't have the infrastructure to power these new workloads you're drugged yeah and I would just add and I think we're all in agreement on that and and from from my perspective from an IBM perspective through my eyes I would say we're increasingly being viewed as kind of an arms dealer and that's a probably a horrible analogy but we're being used we're being viewed as a supplier to the providers of those services right so we provide the raw materials and the machinery and the tooling that enables those innovators to create those new services and do it quickly securely reliably repeatably at a at a reasonable cost right so it's it's a step back from direct engagement with consumer with with customers and clients and and architects but that's where our whole industry is going right we are increasingly more abstracted from the end consumer we're dealing with the sort of assembly we're dealing with the assemblers you know they take the pieces and assemble them and deliver the services so we're not as often doing the assembly as we are providing the raw materials guys great conversation I think we set a record tends to be like that so thank you very much for no problem yeah this is great thank you so much for watching everybody we'll see you next time you're watching the cube

live from San Francisco it's the cube covering Google cloud next 19 taught to you by Google cloud and its ecosystem partners hello everyone welcome back to the cubes live coverage here in San Francisco the Moscone Center for the Google clouds conference is called Google next 2019 I'm Chevrolet my costume in omim de Ville ante is also here doing interviews our next guest is probably Bob who's the VP of product and design for server lists at Google probably great to see you thanks for coming on thank you for having me so you'd be a you're the VP of Product you got the keys to the kingdom on the roadmap you're seeing all the announcements obviously server lists cloud run was announced cloud code was mentioned on stage that's going to come out tomorrow so code build run this is DevOps this is actually happening yeah you know what super exciting is that we've we're finally solving the problem for customers and taking a customer centric view of this I'll start off with a little bit of the journey we took to get here right as we were talking to customers they kept coming back to three things that they wanted from us the first thing they wanted was agility they understand that you know cloud could give them great cost savings but they also wanted to be able to move faster and innovate right the second bit they wanted was having the flexibility to be hybrid and multi-cloud super important especially to our largest customers and then the third piece was they've really struggled with his journey to cloud and they wanted our partnership to make it a much more seamless and non-deceptive journey so as we talk to them about these three things right we came back to the drawing board and said hey what are the products that we can build to make their journey to be more cloud native and more agile much more seamless and future-proofed that much better right so we came back to the drawing board and came up with three products that you talked about this now the first was we looked at developers and their journeys and we said look they're building in traditional ideas like IntelliJ or vs code optimized for local development right and they're not writing a lick of Yama they're right for kubernetes and we said okay how can we take those environments and help those development teams build cloud native apps really really easily so really just turbocharging their cloud native development so bill cloud code which extends their local ids and lets them deploy to remote clusters so they can get full debugging full deployment building its integrated in the cloud build and they get the full kubernetes a development environment right in place so cloud build was released earlier you got enhancements of that so news the hard news here is enhancements to cloud build cloud code as new announce here yeah cloud run announced today that's right so this is the new this is the new hard news that's right so bottom line what does it mean for a developer so like I didn't enterprise so I'm a cio I'm a site C so I'm gonna be putting all my eggs in the cloud basket I've still gonna run the on Prem day is gonna be critical to my strategy it's this early day set up time or are you guys thinking it's more about the setup or more the life cycle of CI CD pipelining all the way to application deployment a great question John so I think where we are in this journey is that enterprises have started off with something that's the most basic cloud ready workloads that have been lifted and shifted we now see the next wave of workloads this is the 80% of workloads that are still on premise we see them start to get cloud ready and cloud native and the way that their enterprises are gonna do that is by building on top of the standards we've created like kubernetes and sto and key native and what cloud cold and build and run and of course Anthes that we talked off this morning as well these are great managed solutions from Google fully managed solutions from Google that let you get cloud native fast all right Polly wonder if you can help us you know spin through I see a disconnect in the market so you know Google showed great leadership in the container space and of course kubernetes we came out of Google and when I look at like cloud run okay it's helping to connect that and Kay native to kubernetes in service when I talk to a lot of the developers and service it's not the infrastructure moving up the stack it's they didn't want to even think about it it's right built in the cloud that's right I focus on the application I don't even think about that so I've got this big gap as to you know on premises forget it I don't never want to touch it or think about it and you know the one of the reasons you know there's the term server list would put it to the side but now if I need one is this environment I don't want to think about it and we know hybrid is a reality but there's this big disconnect as to what kind of developer are you or you a DevOps person that came from an infrastructure background or are you just building apps today yeah yeah yeah we're definitely seeing that from our customers right so one thing that we hear all the time is developers don't want to just not think about infrastructure they actually want the managed service and the platform they're building on to think about the infrastructure and optimize it for them so it's not this program will infrastructure it it's cloud run programming the infrastructure for you so you don't have to do it and I think increasingly you're gonna see products like cloud run and anthos and cloud code let developers focus just on code because that's what they want to do right I don't ever seen a developer say I really want to write a Yama file or I want to set up more configuration parameters right so I think we're gonna get to the place where you have developers being able to focus on cold and all of the rest of this being taken care of by platforms like code and run and anthos automation becomes key I mean Jennifer Lynn's demo I thought was very game-changing because she made the comment developers can focus on their code and agility not access permissions and all the configuration management that goes on under the you guys gonna provide that in an automatic programmable way we're gonna believe he is and she kind of teased out service missions so service missions kind of point in the future which is app developers are gonna still need to be aware of maybe not aware of what cloud run how to manage those sirs as they come stand up and get pulled down dynamically yeah how do you view that because this has become a gonna become complex is that gonna be automated is that where cloud run comes in you expand on this whole impact of service meshes because that's the next level that's right that's right so if you think about key native it's built on kubernetes and it forms the kind of triad with sto as well right and what a product like cloud run does is it lets you not have to think about that because at the end of the day we don't want developers to have to think about K native what cloud run is it takes care of the K native portability and compatibility for you and all you do is focus on the code itself right so ultimately we want developers to focus on their applications but I will say this right we do care about another important constituent which is all of those folks who've already got an apps built out there can those workloads be serviced as well and that's part of the problem we're trying to solve it that's an operational thing all right so let's take a step back here so server list actually fanfare has been great we're seeing a lot of traction people are enamored by it because functions as a service has been very compelling whether it's retail managing you know that spiked loads and becomes we see some some use cases where it's like you know really an amazing thing where is it limiting what is the next level growth for server list where do you see you mention workloads and we see people deploying functions and being happy with it are there limitations with serverless how does it go to the next level can you take a minute to describe the current state of server lists and what's coming around the corner now so great question the first thing I'll say is that there's a ton of developers who come up to us every day and tell us cloud functions is awesome right and they really like functions as a service they like the event-driven approach to it they like the service full approach but several is provides love the programming model that's great but there's an another large contingent of developers who tell us look this is super constraining for what I want to do I don't get to choose the libraries I want you're forcing me into a particular programming model can you give me more flexibility and what they see every day is the flexibility that containers provide especially on kubernetes right and what we've tried to do with cloud run is try to bridge those worlds where you get all of the flexibility that you want right that you get with containers but then combine it with what what you really want with the operational model which is service right so you pay only for what you use and of course you get the agility of service as well now one thing that we've noticed heard some great stories about this is a customer of ours Veolia which is one of the early adopters of cloud run and they've been partnering with us we thank them for it they are running a complex workload you talked about retail what Veolia does is they're large French multinational they do energy water and environmental services these are things that need to be highly reliable very complex and these are workloads that have existed for ages right and what viola is doing is using cloud run to run that complex workload but in a service in a service full way running in a service fashion all right take a minute explain what's a complex workload for your definition what is a simple workload because guys again we love functions Stu and I always talk about how great it is but what's that what's the D mark line when when does something become complex by your standards where you guys are addressing they could think describe the characteristics of a complex workload so the first thing is does the workload require flexibility right meaning are their custom workloads sometimes even legacies C++ or C applications do they need to pull that functionality in as well right do they need to pull random artifacts from across the enterprise to combine it and sometimes these are things that have been built over 20 years ago they're really critical mission critical pieces of software that need to be able to trigger and run right and can we actually take that flexibility but also combine in with a highly reliable environment right so were close like New Orleans there is no downtime right they need to be up 24 by 7 for 365 days of the year right so that flexibility plus that level of reliability is what we look at when we look at complexes so you're getting into complex systems where you got some code may be written in a mainframe COBOL in C++ we mentioned that was my jamm what kind of old dating myself but that was state-of-the-art back in the 90s so I'm running an agile job maybe of standing up cloud native but I need a use software and data from a system that's where is that where the container piece comes that ku burning it on either kubernetes but cloud run also supports docker so let's say you're running it in a docker container all you need is a docker container image and we can host that workload on program yeah Polly help us understand where where Google kind of what what's the same one what's different compared to the other service offerings out there just what I've heard feedback the last year or two is you know the great thing about server list is it's really easy to get started I've talked to marketing people that have no coding background that you know can get off and running it but doing complex mission-critical stuff yeah like we understand you know there is no magic wand NIT no silver bullet to make it easy but you know what do you see as Google's role in in this broader marketplace and you know where does open-source fit into that too yeah yeah so first I'll start off by saying there's a whole host of functions that are running on cloud functions which are relatively lightweight simple targeted event-driven functions those work great where we see us really making a difference for our customers is in two ways the first is get these more complex workloads that are currently running in a container whether it's a docker container our and or on gke for that matter and bring the agility of service to those workloads so it's the first thing it's something that we think is very unique because combining containers with serverless the second bit really is the open approach we've taken right built on top of K native key native as you know has a number of partners so one of the cool demos that you'll see during during Google Cloud next is you'll see a workload being shifted from cloud run on gke to the IBM cloud IBM is one of our partners 4k native without a single line of code and that flexibility is something that I think customers really decided talk about the business pen and some of the benefits at the business level in a developer level at the operations level can you hit those three points yeah of serverless silikal server less on those three sectors what's the benefits yep so we talked about the benefits for developers for developers it's simply about agility focus on your own code don't worry about Gamal don't worry about ki native you don't have to worry about any of that we'll take care of it for you the second benefit that I'll talk about is again this is just a benefit for the CIO which is hey we're gonna give you the flexibility and the openness so you can have portability of your workloads across whatever and why are you environment you want whether it's on tram or in a cloud whether it's Google or another cloud that's the second benefit the third bit is all of the operational benefits of service one of the things you'll see us do and continue to commit to do is we'll bill you to the hundredth of a millisecond right and so you'll continue to get that with all of the resiliency you expect of Google infrastructure security also pretty much baked in as well security is big then there's a fully managed offering from Google and so you'll get security compliance policies all Big Data of course we watched the keynote and we watch every word from Koreans giving Diane green a little tip of the hat which was nice signal a lot of class a great respect for that but jennifer lynn said something i want to get your reaction to she was kind of talking about her thing doing a great demo he changing and when she said this would allow you to negotiate better contracts okay that might have been a slip of the tongue your reaction that that implied to me I took that and say whoa that means leverage shifts to the customer your thoughts and that kind of maybe a slip of the tongue but if you're saying that I couldn't have options and choice yes Janice pardon this is what customers want and at Google what we're focused on is giving customers what they want and one of the things that customers are worried about today is lock-in and especially in the server this area because the current offerings are so proprietary customers are worried about it because they want server lists for all the benefits offers that we talked about here but they do want that flexibility and that's what we negotiate actually we know Oracle is very strict on their cloud this is going to give customers the choice is the saying that's whoa you want a license renewal yeah that's what you're getting out here so Polly you talked about choice and flexibility you know kubernetes gives some of that concern with serverless is if I look at a sure if I look at AWS if I look at Kay native you know those three aren't the same I talked there there's a small start-up called trigger mesh that's getting Kay native to work with AWS lambda but do you see a future is there you know I've talked to the CMC F I've looked at some of the various pieces that you know serverless isn't just something that I'm baked into a cloud yeah look I think we've seen extraordinary momentum around Kay native it's very similar to what we had seen when in the early days of kubernetes this huge amount of ecosystem interest and so we'll see continued innovation where you'll see work load portability come to service and I'm confident in that because of all of the momentum we were seeing around Canada so we're committed at Google to K native and its success so you'll see us continue to innovate yeah talk about open source open source becomes a very strategic part you can Shin kubernetes which you guys were the that have the DNA the founding fathers of kubernetes now teams on the team went to vmware someone have Microsoft some stay within Google containers certainly we see what you guys have done when four against four J but open source still this fear of open source I mean I don't mean it in a way that it's going to be inhibited and primitive but support making sure s LA's work latency microservice is going to be involved you mentioned k- yeah so as open source accelerates the time then value for the code that also triggers this op side of the serviceability and reliability and support what's your thoughts on that how are you guys how do you see the industry supporting that that critical piece of the puzzle yeah could not be more critical right for customers to be able to adopt this because the number one thing that we need to do for customers is give them a managed offering that lets them not have to worry about security lets them not have to worry about compliance lets them not have to worry about policies or identity etc right bake all of that into the managed service and then the second operational bit is which is as important this goes to what Thomas talked about at the very end of his keynote which is the open source announcement is we want to make it simple for customers to adopt it will be supported by Google and the partner you'll get unified billing unified support and one person to call when you have a problem yeah Polly we're at an interesting point in open source today because they're they want to get your opinion as a product person and your relationship with open source because you know there's a certain cloud out there it's they're gonna give you open source as a managed service but you have some of the companies that are making like open source databases changing their policies to try to fight against just being you know taken over by somehow the big players how does Google react to that yeah for us the approach is all about partnership because we think together we can better serve customers needs and best serve them and so our approach has always been about partnership so whether it's kubernetes or key native or the larger manage store manager open source offerings that we talked about earlier in the keynote we want to bring all of these together so we can serve customers so you're gonna see us continue to like support the open source equals because we believe that innovation is absolutely critical to helping our customers really start innovated in be agile final question I know we're tight on time I want to get this in because you know I see a lot of positive I've come out of the show there's been some critical analysis around you've got to build up salespeople and all the field stuff which is you guys are well aware of but one of the things that was kind of teased out in the open source announcement was the role of Google having their own ecosystem Asli the C & C has been a big tailwind for Google you guys been a big part of that ecosystem as a cloud commercial provider and with these kinds of server list you're going to have an ecosystem starting to develop kind of a thousand flowers blooming pun intended so how do you see that in your area because this is going to be super important partnering ecosystem support yeah which is you know developer traction distribution of software integration opportunities that's why in monetization all kind of come together your thoughts huge hugely critical for us and that's something that we've been focused on we have a rich ecosystem of partners for service we're gonna continue to build it out across all of the different pieces you need one of the things we didn't talk much about was our entire operational stack monitoring logging all of those pieces right we need to bring all of those together along with all of our partners we have a big partnership with the likes of data dog right number of others so we're gonna continue to partner with the entire ecosystem so we can go solve the problems that they have are you guys gonna show them the white space where they can play is gonna be part of the strategy yeah so it's gonna be across the board you'll see us continue to support the key native ecosystem tremendously and like lean into that and we're already excited to see all the different offerings that are exist on key native same thing with kubernetes we're gonna continue to like press hard we've got on the operational side we've got an offering called open census it's got lots of traction again just open monitoring of applications so we're gonna continue to do that across the board yeah probably great to have you on vice president of product and design got the keys to the kingdom right here he's the who's running the show for the server list really the key part of how kubernetes really intersects old and new to create the next generation applications thanks for joining us and sharing the insight I'm Jeff forest do many men here live coverage Google next more coverage after this short break

live from Washington DC if the queue covering in forum DC 2018 brought to you by in for and welcome back here on the cube inform 2018 we're live in Washington DC continuing our day to coverage here on the cube along with de Ville on tape I'm John Wallace it's now a pleasure as well to welcome Eric Noren to the cube is the managing director of the CFO and enterprise value consulting at Accenture good morning Eric Harry a good morning to see you guys glad to have you with us we appreciate the time yeah let's talk about first the relationship assurance your and in for I know you've had you've been elsewhere right doing some other things with other folks and have kind of migrated back into the in four fold what led to that and what kind of successes are you having well so we're very excited about the partnership with with in for this is kind of like the really the second year for us right now as we go into the second year the first year was really driven from the partnership and the work that we do at Koch Industries and that that client experience kind of led us into a variety of different paths of partnership with with in for we've been doing work with with in for products for many years but we just our alliances just kind of blossomed in this past year into a variety of different areas focusing on the cloud suite financials focusing on GT Nexus in the supply chain space and now we're getting more and more excited about bursts and we're also getting very excited about the the whole the way the infor OS platform is just blossoming and and being tailored to a variety different industries and you've got you've got three offerings right if I remember right that you're taking out that you're taking to your client base as we speak once you give us a rundown of what you're up to well in our practice we have in our CFO and enterprise value practice we have an offering that's all around digital finance that's one of our biggest areas and that's really all just about the intersection of platform technology and how it enables the next generation of the finance function for the CFO so that we cloud that could also include things like you know automation and artificial intelligence applied to the finance function we see in our recent research here that CFO role as pivoting really not to be not really as focused on the books and records and being the controllers right but the CFOs role is now becoming more focused on being the digital steward the value architect of the enterprise and so the core of Finance is being digitized so that the transaction handling can be done more in an automated and efficient way and then freeing up the talent to focus on analytics and value-add and that really allows the CFO to focus more on driving insights into the business driving growth and what we call enterprise value so I totally agree the role of the CFO is transforming quite dramatically you know long gone in my view anyway are the days of CFO equals bean-counter this is a little there's a controller for that and no bean counter by the way is not a pejorative I run a business and I'm happy when people are counting those beans but it's not the CFO's role they're really transforming you see some Rockstar CFOs certainly in the tech industry like Scarpelli Tom sweet to just name a couple right reporting still matters compliance still matters but the CFO is taking a much more strategic role I'm really interested in this this this digitization of finance double-click on that yeah what does that specifically mean maybe you could give us some examples well I think that a couple things one is cloud right also I would say one thing is how transaction handling is moving from paper into all aspects of touchless transaction handling one is that harnessing the data to for transaction so it's touchless between vendors and customers and how that just flows through the system in a more digital way less paper more digital more touchless integration more automation right and then with that platform enabling things like artificial intelligence or machine learning being applied to these patterns of transaction handling so it can do the compliance checking in the reconciliation and so that the accountants right are enabling these algorithms to check things and don't have to do it themselves right but then there's also this whole context of of digital sort of process automation that that yields new ways of working you know new ways of looking at efficiency in terms of how and where the work is done right there was a view of like shared services and how we enable a digital operating model where there is there's work that can be done you know in with business unit intimacy and then there's work that can be done from other locations but then enabled by digital technology that's common and standardized right in a common platform that's also scalable and flexible and so putting all those things together is what we call digital finance I love this conversation and Accenture is like the best of the best you guys gets deep industry expertise and domain expertise I'm interested in Eric and in what the organizational structure looks like because when we talk about digital you're talking about data yeah and when you talking about data you're talking about monetization in some way shape or form not people I think got confused in the early days of big data so we can sell our data and more importantly as how data contributes to the monetization of the company sure and and how you can harness that and invest in that and that's really where the CFO comes in but he or she is not an expert at at digital not an X not a chief data officer or chief digital officer but they are an enabler they got to understand the strategy they got to pay for the strategy and maybe help course-correct it so what are you seeing is the right organizational regime to take advantage of digital well I think it first off it's integrated and it's and it's and it's focused on integration and collaboration for sure I think that there's a role where finance has the the business acumen and the insights to find out where the the story of enterprise value where it is now where it could be relative to the drivers of the business and but what's going on in the industry or the adjacent industries they can take advantage of so it's really all about you know a partnership between you know let's say finance right and let's say bringing in new talent and skills like data scientists and all those kind of you know digital skills and integrating it into finance so that it could be more accessible and then and then translate it into opportunities for for the business units so so a couple examples could be just one just getting a when we say monetization I think there's two things one is cost reduction where could you just use data to just understand the business in all aspects of where costs and how they're behaving and just being farm Warp know precise about where there are opportunities to reduce costs increase your bottom line right and that that in of those is value then there's the other side on you know revenue up left where there could be optimization of pricing optimization of your discounting strategy all those things that get into maintaining and improving your revenue without any additional cost of goods sold correct cost of sales right exactly that's a great example rights right your your operating structures it stays the same they're getting more leverage out of that that's writing and then there's other things where there's adjacent opportunities in to just gain market share right just to say well where there's opportunities with and really what we want to say is that by applying all this intelligence it's focused on really the theme is focused on customer experiences like what are the customer experiences that could be enabled with digital digital technologies in a seamless touchless way that are just differentiating the company you know in the market customers are and I think the world is changing its disrupting so the ways in which customers are interacting with businesses are expecting these kind of digital experiences very much inspired by a lot of the digital native companies they're out there in the market so the traditional companies that don't have those experience need to catch up and invest in these kind of customer experiences give me an example I mean how about expectations and and so let's say for example if you're a telco alright and you've got experiences that are about paying your bill or experiences have to do with services that you need by going to a call center all right now maybe you can have you know the traditional route of talking to someone or maybe there's a way you can go between the information and the channels that you have between your telephone your the mobile app between the website being able to talk to someone and having chat bots and the mix and how you coordinate all those different experiences so that that the customer can come in and get their questions answered in a very efficient way in some cases the the chat BOTS and the kind of sophistication that they can have to to to address the customers question right on the spot in a very timely way helps them just say I got my question solved and I'm happy with that experience right same thing with having information about I'm getting a you know service supply to my home how do I know that I'm having that same certainty of the service supply to the home much like the certainty that consumers are experiencing kind of like when they get an uber and they're like hey I know that the car is only five minutes away and it's coming and I have that certainty of an experience now that's being applied to other kind of customer experience it's a lot of situation I'm there at three things so first was saved money you know example RP a jerk something to help you drop money to the bottom line just cutting out mundane tasks yeah the top the top line operating leverage and that's around analytics may be optimizing pricing was the example you gave now the third I'll call Tam expansion which is which is really gaining share you leveraging your digital strategy to maybe try to be an incumbent disruptor just disrupt before you get disrupted now that last one has more risk associated with it because there are there are additional cost you've got other cost of goods sold you go to market cost but the reward could be you know huge these are the conversations is a great great proxy for the conversations that are going on with your clients yeah absolutely and I think that look you know there's the the market is going through changes constant disruption is coming in different forms whether it be through technology or other kind of industry integrations and you know they're different in the different we I specialize and more the communications me in technology industry alright and so those those are where I spend most of my time and and what's going on in communications right now and what's going on with communications and media is a quite interesting time on how content and distribution of content is changing and the way that the next generation of consumers are going to think about you know consuming media and how advertising is distributed we're going through a tremendous transformation in that space and all the companies are kind of racing to to be have that advantage of how they connect with the consumers at scale in a seamless connected way so that they have that that that ability to continue to serve them in new and innovative ways so let's talk about them so you said comms and media are we talking telecoms yeah okay and then tech industry is in IT technical yeah I mean tech suppliers tech suppliers yes girls just go and and companies like novo those kind of companies that are in that those guys are pretty forward-thinking in terms of technology adoption oh absolutely okay the telco business is really interesting right now though absolutely hardened infrastructures they get over the top suppliers coming in the cost per per bit is going down but they can't charge more you know this you know very well yeah they're going through some really radical transformation at the same time they have a huge opportunity with content yes you see and people make some moves yes absolutely about what's going on in that business a little bit more well you know there was the recent you know Comcast just an acquisition of sky is quite Norway we got 18 t going through the Time Warner thing and then you have so that's a Content play that I think is just frees up some opportunities for for companies like Comcast and AT&T you know to start really servicing their customers and a new profound way you know to be able to say it could be you know content that is suited to different demographics and to get those consumers at scale not only to keep them you know comfortable with the and and very delighted if you will with the kind of wireless service and flexibility they have with that but then to be able to see all the range of content that it could be consuming all of which is coming back to those companies as data as the consumers are watching all this content and having better control visibility of all the different patterns that they're seeing in the use of this content so they can then in turn shape different kinds of programming and shape different kinds of advertising programs that are tailored to those demographics and there's an it there's an underlying infrastructure transformation that's going on so it's something as basic as you know things like network function virtualization not to get too geeky out here but I'm trying to to make their their infrastructure more agile so they can compete with the OTT suppliers and they're trying to vertically integrate as content yes Rogers absolutely in this whole next wave of 5g is is a huge thing that's gonna come to us and that's that's a big disruption that's just starting and will happen in the next three to five years that will level be coming due so everybody's trying to get digital right yeah yeah yo that you talk to but do you do you when you go beneath that to the organization it's harder to get people you know to actually move do you get do you see a sense of complacency of people saying well you know not we're doing pretty well in our industry or I'll be retired before this all happens I mean how do you compel well I think that I mean that does exist in certain industries and certain types of companies you know I think that's the whole point about talent right and I think when we come back and look at talent is really when we think about change not only is the technology changing but the the talent that's available not only in the finance function but in all parts of an enterprise the the the the next generation of folks that are going into the workforce are just coming from a different place in terms of how they use technology in their lifestyle but how they want to apply to their as a customer but then how they want to do it as an employee and so for when we have that conversation about well what is the future going to look like a lot of it will come down to well what does digital mean as an experience for your consumer and your customer but also what does it mean for the talent and and we believe that look talent is a critical asset in every and every company it's the biggest asset that we have in a center right so how do we inspire and have folks have been enabled to use digital technologies to have that entrepreneurial you know sort of platform to use these digitally native tools that's really the key and I think that any kind of you know CFO that's like thinking about betting on the future that talent is very much a part of that stories it's definitely about technology is very important it's an enabler it's a platform however it's the talent that will be using the platform to take those info sites and drive growth in the wild card is data all right that's the new oh yeah absolutely I mean when a variable in the equation yeah this data putting data at the sort of score of your organization and having the talent that knows how they'll exploit your day that's right and I think it's like when I think about talent there's I mean there's different specializations right but I think the talent is really about the collaboration you see people who are able to work with other different cross functions and say well how do we how do we build and find this together how do we discover where the opportunity the insight is together right and you know there's you know there's differences between you know stuff which I said like the you know things that are known and we just optimized what we have and then there's going into the new areas right that I haven't been discovered yet and I think that the thing about the the the talent that's curious you know we like the way to think about like okay curious about what could be or what's out there and using data not as a as a hurdle but harnessing the power of data to go into these areas and start exploring and using all those different tools to explore where could we go and one of the things it's doing is it's not about you know we talked about analytics and some of the tools that are out there it's not about necessarily precision in this moment it's about direction of where you can go and exploring and continuing to find the facts that support investment it's your point I mean the the tools and the tech aren't the hard part it's the it's the unknown it's the people right you know the processes around that right getting everybody on the same page to collaborate it's like old dogs new tricks I mean I mean so yeah never simplifying but you you are trying to bring new tricks yeah to folks and there's a generational awareness that you're the difference between the people they have coming up and where they said that's right and we think that look you know by bringing the fresh new talent in to the organization that and of itself has has the team operating and working differently because not only they have new tools but there's new a new way of talent being integrated you know new talent and experienced talent you know seeing how these things come together to wither with a mandate again on superior business outcomes like let's go after these prizes it's worth it to get this right to make these investments because if we get it right there's an opportunity to grow revenue to grow to grow profitably to gain market share right so there's a there's a it's hard okay there's culture change and change this is normal okay digital transformation is not an easy thing to do all companies go through you know different things but it's worth it in the end yeah and it enforced talked a lot at this show about new new ways to work what I call new ways to and I think there's some substance there yeah absolutely Eric thank you and for the record we are always open to new tricks we do like new tricks okay good it'd be good to have you with us okay my pleasure guys Norman ceinture back with more on the key we're live here in Washington DC [Music]