Hello and welcome back to Supercloud 2 where we examine the intersection of cloud and data in the 2020s. My name is Dave Vellante. Our Supercloud panel, our power panel is back. Maribel Lopez is the founder and principal analyst at Lopez Research. Sanjeev Mohan is former Gartner analyst and principal at Sanjeev Mohan. And Keith Townsend is the CTO advisor. Folks, welcome back and thanks for your participation today. Good to see you. >> Okay, great. >> Great to see you. >> Thanks. Let me start, Maribel, with you. Bob Muglia, we had a conversation as part of Supercloud the other day. And he said, "Dave, I like the work, you got to simplify this a little bit." So he said, quote, "A Supercloud is a platform." He said, "Think of it as a platform that provides programmatically consistent services hosted on heterogeneous cloud providers." And then Nelu Mihai said, "Well, wait a minute. This is just going to create more stove pipes. We need more standards in an architecture," which is kind of what Berkeley Sky Computing initiative is all about. So there's a sort of a debate going on. Is supercloud an architecture, a platform? Or maybe it's just another buzzword. Maribel, do you have a thought on this? >> Well, the easy answer would be to say it's just a buzzword. And then we could just kill the conversation and be done with it. But I think the term, it's more than that, right? The term actually isn't new. You can go back to at least 2016 and find references to supercloud in Cornell University or assist in other documents. So, having said this, I think we've been talking about Supercloud for a while, so I assume it's more than just a fancy buzzword. But I think it really speaks to that undeniable trend of moving towards an abstraction layer to deal with the chaos of what we consider managing multiple public and private clouds today, right? So one definition of the technology platform speaks to a set of services that allows companies to build and run that technology smoothly without worrying about the underlying infrastructure, which really gets back to something that Bob said. And some of the question is where that lives. And you could call that an abstraction layer. You could call it cross-cloud services, hybrid cloud management. So I see momentum there, like legitimate momentum with enterprise IT buyers that are trying to deal with the fact that they have multiple clouds now. So where I think we're moving is trying to define what are the specific attributes and frameworks of that that would make it so that it could be consistent across clouds. What is that layer? And maybe that's what the supercloud is. But one of the things I struggle with with supercloud is. What are we really trying to do here? Are we trying to create differentiated services in the supercloud layer? Is a supercloud just another variant of what AWS, GCP, or others do? You spoken to Walmart about its cloud native platform, and that's an example of somebody deciding to do it themselves because they need to deal with this today and not wait for some big standards thing to happen. So whatever it is, I do think it's something. I think we're trying to maybe create an architecture out of it would be a better way of saying it so that it does get to those set of principles, but it also needs to be edge aware. I think whenever we talk about supercloud, we're always talking about like the big centralized cloud. And I think we need to think about all the distributed clouds that we're looking at in edge as well. So that might be one of the ways that supercloud evolves. >> So thank you, Maribel. Keith, Brian Gracely, Gracely's law, things kind of repeat themselves. We've seen it all before. And so what Muglia brought to the forefront is this idea of a platform where the platform provider is really responsible for the architecture. Of course, the drawback is then you get a a bunch of stove pipes architectures. But practically speaking, that's kind of the way the industry has always evolved, right? >> So if we look at this from the practitioner's perspective and we talk about platforms, traditionally vendors have provided the platforms for us, whether it's distribution of lineage managed by or provided by Red Hat, Windows, servers, .NET, databases, Oracle. We think of those as platforms, things that are fundamental we can build on top. Supercloud isn't today that. It is a framework or idea, kind of a visionary goal to get to a point that we can have a platform or a framework. But what we're seeing repeated throughout the industry in customers, whether it's the Walmarts that's kind of supersized the idea of supercloud, or if it's regular end user organizations that are coming out with platform groups, groups who normalize cloud native infrastructure, AWS multi-cloud, VMware resources to look like one thing internally to their developers. We're seeing this trend that there's a desire for a platform that provides the capabilities of a supercloud. >> Thank you for that. Sanjeev, we often use Snowflake as a supercloud example, and now would presumably would be a platform with an architecture that's determined by the vendor. Maybe Databricks is pushing for a more open architecture, maybe more of that nirvana that we were talking about before to solve for supercloud. But regardless, the practitioner discussions show. At least currently, there's not a lot of cross-cloud data sharing. I think it could be a killer use case, egress charges or a barrier. But how do you see it? Will that change? Will we hide that underlying complexity and start sharing data across cloud? Is that something that you think Snowflake or others will be able to achieve? >> So I think we are already starting to see some of that happen. Snowflake is definitely one example that gets cited a lot. But even we don't talk about MongoDB in this like, but you could have a MongoDB cluster, for instance, with nodes sitting in different cloud providers. So there are companies that are starting to do it. The advantage that these companies have, let's take Snowflake as an example, it's a centralized proprietary platform. And they are building the capabilities that are needed for supercloud. So they're building things like you can push down your data transformations. They have the entire security and privacy suite. Data ops, they're adding those capabilities. And if I'm not mistaken, it'll be very soon, we will see them offer data observability. So it's all works great as long as you are in one platform. And if you want resilience, then Snowflake, Supercloud, great example. But if your primary goal is to choose the most cost-effective service irrespective of which cloud it sits in, then things start falling sideways. For example, I may be a very big Snowflake user. And I like Snowflake's resilience. I can move from one cloud to another cloud. Snowflake does it for me. But what if I want to train a very large model? Maybe Databricks is a better platform for that. So how do I do move my workload from one platform to another platform? That tooling does not exist. So we need server hybrid, cross-cloud, data ops platform. Walmart has done a great job, but they built it by themselves. Not every company is Walmart. Like Maribel and Keith said, we need standards, we need reference architectures, we need some sort of a cost control. I was just reading recently, Accenture has been public about their AWS bill. Every time they get the bill is tens of millions of lines, tens of millions 'cause there are over thousand teams using AWS. If we have not been able to corral a usage of a single cloud, now we're talking about supercloud, we've got multiple clouds, and hybrid, on-prem, and edge. So till we've got some cross-platform tooling in place, I think this will still take quite some time for it to take shape. >> It's interesting. Maribel, Walmart would tell you that their on-prem infrastructure is cheaper to run than the stuff in the cloud. but at the same time, they want the flexibility and the resiliency of their three-legged stool model. So the point as Sanjeev was making about hybrid. It's an interesting balance, isn't it, between getting your lowest cost and at the same time having best of breed and scale? >> It's basically what you're trying to optimize for, as you said, right? And by the way, to the earlier point, not everybody is at Walmart's scale, so it's not actually cheaper for everybody to have the purchasing power to make the cloud cheaper to have it on-prem. But I think what you see almost every company, large or small, moving towards is this concept of like, where do I find the agility? And is the agility in building the infrastructure for me? And typically, the thing that gives you outside advantage as an organization is not how you constructed your cloud computing infrastructure. It might be how you structured your data analytics as an example, which cloud is related to that. But how do you marry those two things? And getting back to sort of Sanjeev's point. We're in a real struggle now where one hand we want to have best of breed services and on the other hand we want it to be really easy to manage, secure, do data governance. And those two things are really at odds with each other right now. So if you want all the knobs and switches of a service like geospatial analytics and big query, you're going to have to use Google tools, right? Whereas if you want visibility across all the clouds for your application of state and understand the security and governance of that, you're kind of looking for something that's more cross-cloud tooling at that point. But whenever you talk to somebody about cross-cloud tooling, they look at you like that's not really possible. So it's a very interesting time in the market. Now, we're kind of layering this concept of supercloud on it. And some people think supercloud's about basically multi-cloud tooling, and some people think it's about a whole new architectural stack. So we're just not there yet. But it's not all about cost. I mean, cloud has not been about cost for a very, very long time. Cloud has been about how do you really make the most of your data. And this gets back to cross-cloud services like Snowflake. Why did they even exist? They existed because we had data everywhere, but we need to treat data as a unified object so that we can analyze it and get insight from it. And so that's where some of the benefit of these cross-cloud services are moving today. Still a long way to go, though, Dave. >> Keith, I reached out to my friends at ETR given the macro headwinds, And you're right, Maribel, cloud hasn't really been about just about cost savings. But I reached out to the ETR, guys, what's your data show in terms of how customers are dealing with the economic headwinds? And they said, by far, their number one strategy to cut cost is consolidating redundant vendors. And a distant second, but still notable was optimizing cloud costs. Maybe using reserve instances, or using more volume buying. Nowhere in there. And I asked them to, "Could you go look and see if you can find it?" Do we see repatriation? And you hear this a lot. You hear people whispering as analysts, "You better look into that repatriation trend." It's pretty big. You can't find it. But some of the Walmarts in the world, maybe even not repatriating, but they maybe have better cost structure on-prem. Keith, what are you seeing from the practitioners that you talk to in terms of how they're dealing with these headwinds? >> Yeah, I just got into a conversation about this just this morning with (indistinct) who is an analyst over at GigaHome. He's reading the same headlines. Repatriation is happening at large scale. I think this is kind of, we have these quiet terms now. We have quiet quitting, we have quiet hiring. I think we have quiet repatriation. Most people haven't done away with their data centers. They're still there. Whether they're completely on-premises data centers, and they own assets, or they're partnerships with QTX, Equinix, et cetera, they have these private cloud resources. What I'm seeing practically is a rebalancing of workloads. Do I really need to pay AWS for this instance of SAP that's on 24 hours a day versus just having it on-prem, moving it back to my data center? I've talked to quite a few customers who were early on to moving their static SAP workloads onto the public cloud, and they simply moved them back. Surprising, I was at VMware Explore. And we can talk about this a little bit later on. But our customers, net new, not a lot that were born in the cloud. And they get to this point where their workloads are static. And they look at something like a Kubernetes, or a OpenShift, or VMware Tanzu. And they ask the question, "Do I need the scalability of cloud?" I might consider being a net new VMware customer to deliver this base capability. So are we seeing repatriation as the number one reason? No, I think internal IT operations are just naturally come to this realization. Hey, I have these resources on premises. The private cloud technologies have moved far along enough that I can just simply move this workload back. I'm not calling it repatriation, I'm calling it rightsizing for the operating model that I have. >> Makes sense. Yeah. >> Go ahead. >> If I missed something, Dave, why we are on this topic of repatriation. I'm actually surprised that we are talking about repatriation as a very big thing. I think repatriation is happening, no doubt, but it's such a small percentage of cloud migration that to me it's a rounding error in my opinion. I think there's a bigger problem. The problem is that people don't know where the cost is. If they knew where the cost was being wasted in the cloud, they could do something about it. But if you don't know, then the easy answer is cloud costs a lot and moving it back to on-premises. I mean, take like Capital One as an example. They got rid of all the data centers. Where are they going to repatriate to? They're all in the cloud at this point. So I think my point is that data observability is one of the places that has seen a lot of traction is because of cost. Data observability, when it first came into existence, it was all about data quality. Then it was all about data pipeline reliability. And now, the number one killer use case is FinOps. >> Maribel, you had a comment? >> Yeah, I'm kind of in violent agreement with both Sanjeev and Keith. So what are we seeing here? So the first thing that we see is that many people wildly overspent in the big public cloud. They had stranded cloud credits, so to speak. The second thing is, some of them still had infrastructure that was useful. So why not use it if you find the right workloads to what Keith was talking about, if they were more static workloads, if it was already there? So there is a balancing that's going on. And then I think fundamentally, from a trend standpoint, these things aren't binary. Everybody, for a while, everything was going to go to the public cloud and then people are like, "Oh, it's kind of expensive." Then they're like, "Oh no, they're going to bring it all on-prem 'cause it's really expensive." And it's like, "Well, that doesn't necessarily get me some of the new features and functionalities I might want for some of my new workloads." So I'm going to put the workloads that have a certain set of characteristics that require cloud in the cloud. And if I have enough capability on-prem and enough IT resources to manage certain things on site, then I'm going to do that there 'cause that's a more cost-effective thing for me to do. It's not binary. That's why we went to hybrid. And then we went to multi just to describe the fact that people added multiple public clouds. And now we're talking about super, right? So I don't look at it as a one-size-fits-all for any of this. >> A a number of practitioners leading up to Supercloud2 have told us that they're solving their cloud complexity by going in monocloud. So they're putting on the blinders. Even though across the organization, there's other groups using other clouds. You're like, "In my group, we use AWS, or my group, we use Azure. And those guys over there, they use Google. We just kind of keep it separate." Are you guys hearing this in your view? Is that risky? Are they missing out on some potential to tap best of breed? What do you guys think about that? >> Everybody thinks they're monocloud. Is anybody really monocloud? It's like a group is monocloud, right? >> Right. >> This genie is out of the bottle. We're not putting the genie back in the bottle. You might think your monocloud and you go like three doors down and figure out the guy or gal is on a fundamentally different cloud, running some analytics workload that you didn't know about. So, to Sanjeev's earlier point, they don't even know where their cloud spend is. So I think the concept of monocloud, how that's actually really realized by practitioners is primary and then secondary sources. So they have a primary cloud that they run most of their stuff on, and that they try to optimize. And we still have forked workloads. Somebody decides, "Okay, this SAP runs really well on this, or these analytics workloads run really well on that cloud." And maybe that's how they parse it. But if you really looked at it, there's very few companies, if you really peaked under the hood and did an analysis that you could find an actual monocloud structure. They just want to pull it back in and make it more manageable. And I respect that. You want to do what you can to try to streamline the complexity of that. >> Yeah, we're- >> Sorry, go ahead, Keith. >> Yeah, we're doing this thing where we review AWS service every day. Just in your inbox, learn about a new AWS service cursory. There's 238 AWS products just on the AWS cloud itself. Some of them are redundant, but you get the idea. So the concept of monocloud, I'm in filing agreement with Maribel on this that, yes, a group might say I want a primary cloud. And that primary cloud may be the AWS. But have you tried the licensed Oracle database on AWS? It is really tempting to license Oracle on Oracle Cloud, Microsoft on Microsoft. And I can't get RDS anywhere but Amazon. So while I'm driven to desire the simplicity, the reality is whether be it M&A, licensing, data sovereignty. I am forced into a multi-cloud management style. But I do agree most people kind of do this one, this primary cloud, secondary cloud. And I guarantee you're going to have a third cloud or a fourth cloud whether you want to or not via shadow IT, latency, technical reasons, et cetera. >> Thank you. Sanjeev, you had a comment? >> Yeah, so I just wanted to mention, as an organization, I'm complete agreement, no organization is monocloud, at least if it's a large organization. Large organizations use all kinds of combinations of cloud providers. But when you talk about a single workload, that's where the program arises. As Keith said, the 238 services in AWS. How in the world am I going to be an expert in AWS, but then say let me bring GCP or Azure into a single workload? And that's where I think we probably will still see monocloud as being predominant because the team has developed its expertise on a particular cloud provider, and they just don't have the time of the day to go learn yet another stack. However, there are some interesting things that are happening. For example, if you look at a multi-cloud example where Oracle and Microsoft Azure have that interconnect, so that's a beautiful thing that they've done because now in the newest iteration, it's literally a few clicks. And then behind the scene, your .NET application and your Oracle database in OCI will be configured, the identities in active directory are federated. And you can just start using a database in one cloud, which is OCI, and an application, your .NET in Azure. So till we see this kind of a solution coming out of the providers, I think it's is unrealistic to expect the end users to be able to figure out multiple clouds. >> Well, I have to share with you. I can't remember if he said this on camera or if it was off camera so I'll hold off. I won't tell you who it is, but this individual was sort of complaining a little bit saying, "With AWS, I can take their best AI tools like SageMaker and I can run them on my Snowflake." He said, "I can't do that in Google. Google forces me to go to BigQuery if I want their excellent AI tools." So he was sort of pushing, kind of tweaking a little bit. Some of the vendor talked that, "Oh yeah, we're so customer-focused." Not to pick on Google, but I mean everybody will say that. And then you say, "If you're so customer-focused, why wouldn't you do a ABC?" So it's going to be interesting to see who leads that integration and how broadly it's applied. But I digress. Keith, at our first supercloud event, that was on August 9th. And it was only a few months after Broadcom announced the VMware acquisition. A lot of people, myself included said, "All right, cuts are coming." Generally, Tanzu is probably going to be under the radar, but it's Supercloud 22 and presumably VMware Explore, the company really... Well, certainly the US touted its Tanzu capabilities. I wasn't at VMware Explore Europe, but I bet you heard similar things. Hawk Tan has been blogging and very vocal about cross-cloud services and multi-cloud, which doesn't happen without Tanzu. So what did you hear, Keith, in Europe? What's your latest thinking on VMware's prospects in cross-cloud services/supercloud? >> So I think our friend and Cube, along host still be even more offended at this statement than he was when I sat in the Cube. This was maybe five years ago. There's no company better suited to help industries or companies, cross-cloud chasm than VMware. That's not a compliment. That's a reality of the industry. This is a very difficult, almost intractable problem. What I heard that VMware Europe were customers serious about this problem, even more so than the US data sovereignty is a real problem in the EU. Try being a company in Switzerland and having the Swiss data solvency issues. And there's no local cloud presence there large enough to accommodate your data needs. They had very serious questions about this. I talked to open source project leaders. Open source project leaders were asking me, why should I use the public cloud to host Kubernetes-based workloads, my projects that are building around Kubernetes, and the CNCF infrastructure? Why should I use AWS, Google, or even Azure to host these projects when that's undifferentiated? I know how to run Kubernetes, so why not run it on-premises? I don't want to deal with the hardware problems. So again, really great questions. And then there was always the specter of the problem, I think, we all had with the acquisition of VMware by Broadcom potentially. 4.5 billion in increased profitability in three years is a unbelievable amount of money when you look at the size of the problem. So a lot of the conversation in Europe was about industry at large. How do we do what regulators are asking us to do in a practical way from a true technology sense? Is VMware cross-cloud great? >> Yeah. So, VMware, obviously, to your point. OpenStack is another way of it. Actually, OpenStack, uptake is still alive and well, especially in those regions where there may not be a public cloud, or there's public policy dictating that. Walmart's using OpenStack. As you know in IT, some things never die. Question for Sanjeev. And it relates to this new breed of data apps. And Bob Muglia and Tristan Handy from DBT Labs who are participating in this program really got us thinking about this. You got data that resides in different clouds, it maybe even on-prem. And the machine polls data from different systems. No humans involved, e-commerce, ERP, et cetera. It creates a plan, outcomes. No human involvement. Today, you're on a CRM system, you're inputting, you're doing forms, you're, you're automating processes. We're talking about a new breed of apps. What are your thoughts on this? Is it real? Is it just way off in the distance? How does machine intelligence fit in? And how does supercloud fit? >> So great point. In fact, the data apps that you're talking about, I call them data products. Data products first came into limelight in the last couple of years when Jamal Duggan started talking about data mesh. I am taking data products out of the data mesh concept because data mesh, whether data mesh happens or not is analogous to data products. Data products, basically, are taking a product management view of bringing data from different sources based on what the consumer needs. We were talking earlier today about maybe it's my vacation rentals, or it may be a retail data product, it may be an investment data product. So it's a pre-packaged extraction of data from different sources. But now I have a product that has a whole lifecycle. I can version it. I have new features that get added. And it's a very business data consumer centric. It uses machine learning. For instance, I may be able to tell whether this data product has stale data. Who is using that data? Based on the usage of the data, I may have a new data products that get allocated. I may even have the ability to take existing data products, mash them up into something that I need. So if I'm going to have that kind of power to create a data product, then having a common substrate underneath, it can be very useful. And that could be supercloud where I am making API calls. I don't care where the ERP, the CRM, the survey data, the pricing engine where they sit. For me, there's a logical abstraction. And then I'm building my data product on top of that. So I see a new breed of data products coming out. To answer your question, how early we are or is this even possible? My prediction is that in 2023, we will start seeing more of data products. And then it'll take maybe two to three years for data products to become mainstream. But it's starting this year. >> A subprime mortgages were a data product, definitely were humans involved. All right, let's talk about some of the supercloud, multi-cloud players and what their future looks like. You can kind of pick your favorites. VMware, Snowflake, Databricks, Red Hat, Cisco, Dell, HP, Hashi, IBM, CloudFlare. There's many others. cohesive rubric. Keith, I wanted to start with CloudFlare because they actually use the term supercloud. and just simplifying what they said. They look at it as taking serverless to the max. You write your code and then you can deploy it in seconds worldwide, of course, across the CloudFlare infrastructure. You don't have to spin up containers, you don't go to provision instances. CloudFlare worries about all that infrastructure. What are your thoughts on CloudFlare this approach and their chances to disrupt the current cloud landscape? >> As Larry Ellison said famously once before, the network is the computer, right? I thought that was Scott McNeley. >> It wasn't Scott McNeley. I knew it was on Oracle Align. >> Oracle owns that now, owns that line. >> By purpose or acquisition. >> They should have just called it cloud. >> Yeah, they should have just called it cloud. >> Easier. >> Get ahead. >> But if you think about the CloudFlare capability, CloudFlare in its own right is becoming a decent sized cloud provider. If you have compute out at the edge, when we talk about edge in the sense of CloudFlare and points of presence, literally across the globe, you have all of this excess computer, what do you do with it? First offering, let's disrupt data in the cloud. We can't start the conversation talking about data. When they say we're going to give you object-oriented or object storage in the cloud without egress charges, that's disruptive. That we can start to think about supercloud capability of having compute EC2 run in AWS, pushing and pulling data from CloudFlare. And now, I've disrupted this roach motel data structure, and that I'm freely giving away bandwidth, basically. Well, the next layer is not that much more difficult. And I think part of CloudFlare's serverless approach or supercloud approaches so that they don't have to commit to a certain type of compute. It is advantageous. It is a feature for me to be able to go to EC2 and pick a memory heavy model, or a compute heavy model, or a network heavy model, CloudFlare is taken away those knobs. and I'm just giving code and allowing that to run. CloudFlare has a massive network. If I can put the code closest using the CloudFlare workers, if I can put that code closest to where the data is at or residing, super compelling observation. The question is, does it scale? I don't get the 238 services. While Server List is great, I have to know what I'm going to build. I don't have a Cognito, or RDS, or all these other services that make AWS, GCP, and Azure appealing from a builder's perspective. So it is a very interesting nascent start. It's great because now they can hide compute. If they don't have the capacity, they can outsource that maybe at a cost to one of the other cloud providers, but kind of hiding the compute behind the surplus architecture is a really unique approach. >> Yeah. And they're dipping their toe in the water. And they've announced an object store and a database platform and more to come. We got to wrap. So I wonder, Sanjeev and Maribel, if you could maybe pick some of your favorites from a competitive standpoint. Sanjeev, I felt like just watching Snowflake, I said, okay, in my opinion, they had the right strategy, which was to run on all the clouds, and then try to create that abstraction layer and data sharing across clouds. Even though, let's face it, most of it might be happening across regions if it's happening, but certainly outside of an individual account. But I felt like just observing them that anybody who's traditional on-prem player moving into the clouds or anybody who's a cloud native, it just makes total sense to write to the various clouds. And to the extent that you can simplify that for users, it seems to be a logical strategy. Maybe as I said before, what multi-cloud should have been. But are there companies that you're watching that you think are ahead in the game , or ones that you think are a good model for the future? >> Yes, Snowflake, definitely. In fact, one of the things we have not touched upon very much, and Keith mentioned a little bit, was data sovereignty. Data residency rules can require that certain data should be written into certain region of a certain cloud. And if my cloud provider can abstract that or my database provider, then that's perfect for me. So right now, I see Snowflake is way ahead of this pack. I would not put MongoDB too far behind. They don't really talk about this thing. They are in a different space, but now they have a lakehouse, and they've got all of these other SQL access and new capabilities that they're announcing. So I think they would be quite good with that. Oracle is always a dark forest. Oracle seems to have revived its Cloud Mojo to some extent. And it's doing some interesting stuff. Databricks is the other one. I have not seen Databricks. They've been very focused on lakehouse, unity, data catalog, and some of those pieces. But they would be the obvious challenger. And if they come into this space of supercloud, then they may bring some open source technologies that others can rely on like Delta Lake as a table format. >> Yeah. One of these infrastructure players, Dell, HPE, Cisco, even IBM. I mean, I would be making my infrastructure as programmable and cloud friendly as possible. That seems like table stakes. But Maribel, any companies that stand out to you that we should be paying attention to? >> Well, we already mentioned a bunch of them, so maybe I'll go a slightly different route. I'm watching two companies pretty closely to see what kind of traction they get in their established companies. One we already talked about, which is VMware. And the thing that's interesting about VMware is they're everywhere. And they also have the benefit of having a foot in both camps. If you want to do it the old way, the way you've always done it with VMware, they got all that going on. If you want to try to do a more cross-cloud, multi-cloud native style thing, they're really trying to build tools for that. So I think they have really good access to buyers. And that's one of the reasons why I'm interested in them to see how they progress. The other thing, I think, could be a sleeping horse oddly enough is Google Cloud. They've spent a lot of work and time on Anthos. They really need to create a certain set of differentiators. Well, it's not necessarily in their best interest to be the best multi-cloud player. If they decide that they want to differentiate on a different layer of the stack, let's say they want to be like the person that is really transformative, they talk about transformation cloud with analytics workloads, then maybe they do spend a good deal of time trying to help people abstract all of the other underlying infrastructure and make sure that they get the sexiest, most meaningful workloads into their cloud. So those are two people that you might not have expected me to go with, but I think it's interesting to see not just on the things that might be considered, either startups or more established independent companies, but how some of the traditional providers are trying to reinvent themselves as well. >> I'm glad you brought that up because if you think about what Google's done with Kubernetes. I mean, would Google even be relevant in the cloud without Kubernetes? I could argue both sides of that. But it was quite a gift to the industry. And there's a motivation there to do something unique and different from maybe the other cloud providers. And I'd throw in Red Hat as well. They're obviously a key player and Kubernetes. And Hashi Corp seems to be becoming the standard for application deployment, and terraform, or cross-clouds, and there are many, many others. I know we're leaving lots out, but we're out of time. Folks, I got to thank you so much for your insights and your participation in Supercloud2. Really appreciate it. >> Thank you. >> Thank you. >> Thank you. >> This is Dave Vellante for John Furrier and the entire Cube community. Keep it right there for more content from Supercloud2.

>>Okay, we're back with the hybrid Cloud power panel. I'm Dave Ante and with me our Eric Lockhart, who's the corporate vice president of Microsoft Azure, Specialized Thomas Corny, the senior vice president of products at Nutanix, and Indu Care, who's the Senior Vice President of engineering, NCI and nnc two at Nutanix. Gentlemen, welcome to the cube. Thanks for coming on. >>It's to >>Be here. Have us, >>Eric, let's, let's start with you. We hear so much about cloud first. What's driving the need for hybrid cloud for organizations today? I mean, I wanna just ev put everything in the public cloud. >>Yeah, well, I mean, the public cloud has a bunch of inherent advantages, right? I mean, it's, it has effectively infinite capacity, the ability to, you know, innovate without a lot of upfront costs, you know, regions all over the world. So there is a, a trend towards public cloud, but you know, not everything can go to the cloud, especially right away. There's lots of reasons. Customers want to have assets on premise, you know, data gravity, sovereignty and so on. And so really hybrid is the way to achieve the best of both worlds, really to kind of leverage the assets and investments that customers have on premise, but also take advantage of, of the cloud for bursting or regionality or expansion, especially coming outta the pandemic. We saw a lot of this from work from home and, and video conferencing and so on, driving a lot of cloud adoption. So hybrid is really the way that we see customers achieving the best of both worlds. >>Yeah, makes sense. I wanna, Thomas, if you could talk a little bit, I don't wanna inundate people with the acronyms, but, but the Nutanix Cloud clusters on Azure, what is that? What problems does it solve? Give us some color there, please. >>That is, so, you know, cloud clusters on Azure, which we actually call NC two to make it simple. And so NC two on Azure is really our solutions for hybrid cloud, right? And you think about the hybrid cloud, highly desirable customers want it. They, they know this is the right way to do for them, given that they wanna have workloads on premises at the edge, any public clouds. But it's complicated. It's hard to do, right? And the first thing that you deal with is just silos, right? You have different infrastructure that you have to go and deal with. You have different teams, different technologies, different areas of expertise and dealing with different portals. Networkings get complicated, security gets complicated. And so you heard me say this already, you know, hybrid can be complex. And so what we've done, we then c to Azure is we make that simple, right? We allow teams to go and basically have a solution that allows you to go and take any application running on premises and move it as is to any Azure region where ncq is available. Once it's running there, you keep the same operating model, right? And that's something actually super valuable to actually go and do this in a simple fashion, do it faster, and basically do, do hybrid in a more cost effective fashion, know for all your applications. And that's really what's really special about NC Azure today. >>So Thomas, just a quick follow up on that. So you're, you're, if I understand you correctly, it's an identical experience. Did I get that right? >>This is, this is the key for us, right? Is when you think you're sending on premises, you are used to way of doing things of how you run your applications, how you operate, how you protect them. And what we do here is we extend the Nutanix operating model two workloads running in Azure using the same core stack that you're running on premises, right? So once you have a cluster deploying C to an Azure, it's gonna look like the same cluster that you might be running at the edge or in your own data center, using the same tools, using, using the same admin constructs to go protect the workloads, make them highly available with disaster recovery or secure them. All of that becomes the same, but now you are in Azure, and this is what we've spent a lot of time working with Americanist teams on, is you actually have access now to all of those suites of Azure services in from those workloads. So now you get the best of both world, you know, and we bridge them together and you get seamless access of those services between what you get from Nutanix, what you get from Azure. >>Yeah. And as you alluded to, this is traditionally been non-trivial and people have been looking forward to this for, for quite some time. So Indu, I want to understand from an engineering perspective, your team had to work with the Microsoft team, and I'm sure there was this, this is not just a press releases or a PowerPoint, you had to do some some engineering work. So what specific engineering work did you guys do and what's unique about this relative to other solutions in the marketplace? >>So let me start with what's unique about this, and I think Thomas and Eric both did a really good job of describing that the best way to think about what we are delivering jointly with Microsoft is that it speeds up the journey to the public cloud. You know, one way to think about this is moving to the public cloud is sort of like remodeling your house. And when you start remodeling your house, you know, you find that you start with something and before you know it, you're trying to remodel the entire house. And that's a little bit like what journey to the public cloud sort of starts to look like when you start to refactor applications. Because it wasn't, most of the applications out there today weren't designed for the public cloud to begin with. NC two allows you to flip that on its head and say that take your application as is and then lift and shift it to the public cloud, at which point you start the refactor journey. >>And one of the things that you have done really well with the NC two on Azure is that NC two is not something that sits by Azure side. It's fully integrated into the Azure fabric, especially the software defined network and SDN piece. What that means is that, you know, you don't have to worry about connecting your NC two cluster to Azure to some sort of a net worth pipe. You have direct access to the Azure services from the same application that's now running on an C2 cluster. And that makes your refactoring journey so much easier. Your management claim looks the same, your high performance notes let the NVMe notes, they look the same. And really, I mean, other than the facts that you're doing something in the public cloud, all the Nutanix goodness that you're used to continue to receive that, there is a lot of secret sauce that we have had to develop as part of this journey. >>But if we had to pick one that really stands out, it is how do we take the complexity, the network complexity, offer public cloud, in this case Azure, and make it as familiar to Nutanix's customers as the VPC construc, the virtual private cloud construct that allows them to really think of their on-prem networking and the public cloud networking in very similar terms. There's a lot more that's gone on behind the scenes. And by the way, I'll tell you a funny sort of anecdote. My dad used to say when I drew up that, you know, if you really want to grow up, you have to do two things. You have to like build a house and you have to marry your kid off to someone. And I would say our dad a third do a code development with the public cloud provider of the partner. This has been just an absolute amazing journey with Eric and the Microsoft team, and you're very grateful for their support. >>I need NC two for my house. I live in a house that was built and it's 1687 and we connect old to new and it's, it is a bolt on, but, but, but, and so, but the secret sauce, I mean there's, there's a lot there, but is it a PAs layer? You didn't just wrap it in a container and shove it into the public cloud, You've done more than that. I'm inferring, >>You know, the, it's actually an infrastructure layer offering on top of fid. You can obviously run various types of platform services. So for example, down the road, if you have a containerized application, you'll actually be able to tat it from OnPrem and run it on C two. But the NC two offer itself, the NCAA often itself is an infrastructure level offering. And the trick is that the storage that you're used to the high performance storage that you know, define Nutanix to begin with, the hypervisor that you're used to, the network constructs that you're used to light MI segmentation for security purposes, all of them are available to you on NC two in Azure, the same way that we're used to do on-prem. And furthermore, managing all of that through Prism, which is our management interface and management console also remains the same. That makes your security model easier, that makes your management challenge easier, that makes it much easier for an accusation person or the IT office to be able to report back to the board that they have started to execute on the cloud mandate and they have done that much faster than they'll be able to otherwise. >>Great. Thank you for helping us understand the plumbing. So now Thomas, maybe we can get to like the customers. What, what are you seeing, what are the use cases that are, that are gonna emerge for this solution? >>Yeah, I mean we've, you know, we've had a solution for a while and you know, this is now new on Azure is gonna extend the reach of the solution and get us closer to the type of use cases that are unique to Azure in terms of those solutions for analytics and so forth. But the kind of key use cases for us, the first one you know, talks about it is a migration. You know, we see customers on the cloud journey, they're looking to go and move applications wholesale from on premises to public cloud. You know, we make this very easy because in the end they take the same culture that are around the application and make them, we make them available Now in the Azure region, you can do this for any applications. There's no change to the application, no networking change. The same IP will work the same whether you're running on premises or in Azure. >>The app stays exactly the same, manage the same way, protected the same way. So that's a big one. And you know, the type of drivers point to politically or maybe I wanna go do something different or I wanna go and shut down education on premises, I need to do that with a given timeline. I can now move first and then take care of optimizing the application to take advantage of all that Azure has to offer. So migration and doing that in a simple fashion, in a very fast manner is, is a key use case. Another one, and this is classic for leveraging public cloud force, which are doing on premises IT disaster recovery and something that we refer to as elastic disaster recovery, being able to go and actually configure a secondary site to protect your on premises workloads, but I that site sitting in Azure as a small site, just enough to hold the data that you're replicating and then use the fact that you cannot get access to resources on demand in Azure to scale out the environment, feed over workloads, run them with performance, potentially feed them back to on premises and then shrink back the environment in Azure to again, optimize cost and take advantage of elasticity that you get from public cloud models. >>Then the last one, building on top of that is just the fact that you cannot get boosting use cases and maybe running a large environment, typically desktop, you know, VDI environments that we see running on premises and I have, you know, a seasonal requirement to go and actually enable more workers to go get access the same solution. You could do this by sizing for the large burst capacity on premises wasting resources during the rest of the year. What we see customers do is optimize what they're running on premises and get access to resources on demand in Azure and basically move the workload and now basically get combined desktops running on premises desktops running on NC two on Azure, same desktop images, same management, same services, and do that as a burst use case during, say you're a retailer that has to go and take care of your holiday season. You know, great use case that we see over and over again for our customers, right? And pretty much complimenting the notion of, look, I wanna go to desktop as a service, but right now I don't want to refactor the entire application stack. I just wanna be able to get access to resources on demand in the right place at the right time. >>Makes sense. I mean this is really all about supporting customers', digital transformations. We all talk about how that was accelerated during the pandemic and, but the cloud is a fundamental component of the digital transformation generic. You, you guys have obviously made a commitment between Microsoft and and Nutanix to simplify hybrid cloud and that journey to the cloud. How should customers, you know, measure that? What does success look like? What's the ultimate vision here? >>Well, the ultimate vision is really twofold. I think the one is to, you know, first is really to ease a customer's journey to the cloud to allow them to take advantage of all the benefits to the cloud, but to do so without having to rewrite their applications or retrain their, their administrators and or or to obviate their investment that they already have and platforms like, like Nutanix. And so the, the work that companies have done together here, you know, first and foremost is really to allow folks to come to the cloud in the way that they want to come to the cloud and take really the best of both worlds, right? Leverage, leverage their investment in the capabilities of the Nutanix platform, but do so in conjunction with the advantages and and capabilities of, of Azure. You know, Second is really to extend some of the cloud capabilities down onto the on-premise infrastructure. And so with investments that we've done together with Azure arc for example, we're really extending the Azure control plane down onto on premise Nutanix clusters and bringing the capabilities that that provides to the, the Nutanix customer as well as various Azure services like our data services and Azure SQL server. So it's really kind of coming at the problem from, from two directions. One is from kind of traditional on-premise up into the cloud and then the second is kind of from the cloud leveraging the investment customers have in in on-premise hci. >>Got it. Thank you. Okay, last question. Maybe each of you can just give us one key takeaway for our audience today. Maybe we start with with with with Thomas and then Indu and then Eric you can bring us home. >>Sure. So the key takeaway is, you know, Nutanix Cloud clusters on Azure is now ga you know, this is something that we've had tremendous demand from our customers, both from the Microsoft side and the Nutanix side going, going back years literally, right? People have been wanting to go and see this, this is now live GA open for business and you know, we're ready to go and engage and ready to scale, right? This is our first step in a long journey in a very key partnership for us at Nutanix. >>Great Indu >>In our Dave. In a prior life about seven or eight, eight years ago, I was a part of a team that took a popular cat's preparation software and moved it to the public cloud. And that was a journey that took us four years and probably several hundred million. And if we had had NC two then it would've saved us half the money, but more importantly would've gotten there in one third the time. And that's really the value of this. >>Okay. Eric, bring us home please. >>Yeah, I'll just point out like this is not something that's just both on or something. We, we, we started yesterday. This is something the teams, both companies have been working on together for, for years, really. And it's, it's a way of, of deeply integrating Nutanix into the Azure Cloud and with the ultimate goal of, of again, providing cloud capabilities to the Nutanix customer in a way that they can, you know, take advantage of the cloud and then compliment those applications over time with additional Azure services like storage, for example. So it really is a great on-ramp to the cloud for, for customers who have significant investments in, in Nutanix clusters on premise, >>Love the co-engineering and the ability to take advantage of those cloud native tools and capabilities, real customer value. Thanks gentlemen. Really appreciate your time. >>Thank >>You. Thank you. >>Okay. Keep it right there. You're watching Accelerate Hybrid Cloud, that journey with Nutanix and Microsoft technology on the cube. You're a leader in enterprise and emerging tech coverage.

foreign greetings from San Francisco thecube is live this is our second day of wall-to-wall coverage of VMware Explorer 2022. Lisa Martin and Dave Nicholson here we're going to be talking with some ladies from Rackspace next please welcome Adriana Bustamante VP of strategic alliances and Hannah Deuce director of strategic alliances from Rackspace it's great to have you on the program thank you so much for having us good afternoon good morning is it lunchtime already almost almost yes and it's great to be back in person we were just talking about the keynote yesterday that we were in and it was standing room only people are ready to be back they're ready to be hearing from VMware it's ecosystem its Partners it's Community yes talk to us Adriana about what Rackspace is doing with Dell and VMware particularly in the healthcare space sure no so for us Partnerships are a big foundation to how we operate as a company and um and I have the privilege of doing it for over over 16 years so we've been looking after the dell and VMware part partnership ourselves personally for the last three years but they've been long-standing partners for for us and and how do we go and drive more meaningful joint Solutions together so Rackspace you know been around since since 98 we've seen such an evolution of coming becoming more of this multi-cloud transformation agile Global partner and we have a lot of customers that fall in lots of different verticals from retail to public sector into Healthcare but we started noticing and what we're trying trying to drive as a company is how do we drive more specialized Solutions and because of the pandemic and because of post-pandemic and everyone really trying to to figure out what the new normal is addressing different clients we saw that need increasing and we wanted to Rally together with our most strategic alliances to do more Hannah talk about obviously the the pandemic created such problems for every industry but but Healthcare being front and center it still is talk about some of the challenges that Healthcare organizations are coming to Rackspace going help yeah common theme that we've heard from some of our large providers Healthcare Providers has been helped me do more with less which we're all trying to do as we navigate The New Normal but in that space we found the opportunity to really leverage some of our expertise long-term expertise and that the talent and the resource pool that we had to really help in a some of the challenges that are being faced at a resource shortage Talent shortage and so Rackspace is able to Leverage What what we've done for many many years and really tailor it to the outcomes that Health Care Providers are needing nowadays that more with less Mantra runs across the gamut but a lot of it's been helped me modernize helped me get to that next phase I can't I can't I don't have the resources to DIY it myself anymore I need to figure out a more robust business continuity program and so helping with business continuity Dr you know third copies of just all all this data that's growing so it's not just covered pandemic driven but it's that's definitely driving the the need and the requirement to modernize so much quicker it's interesting that you mentioned rackspace's history and expertise in doing things and moving that forward and leveraging that pivoting focusing on specific environments to create something net new we've seen a lot of that here if you go back 10 years I don't know if that's the perfect date to go back to but if you go back 10 years ago you think about VMware where would we have expected VMware to be in this era of cloud we may have thought of things very very differently differently Rackspace a Pioneer in creating off-premises hey we will do this for you didn't even really call it Cloud at the time right but it was Cloud yeah and so the ability for entities like Rackspace like VMware we had a NetApp talking to us about stuff they're doing in the cloud 10 years ago if you I would say no they'd be they'll be gone they'll be gone so it's really really cool to see Rackspace making this transition and uh you know being aware of everything that's going on and focusing on the best value proposition moving forward I mean am I am I you know do I sound like somebody who would who would fit into the Rackspace culture right now or do I not get it yes you sound like a rocker we'll make you an honorary record that's what we call a Rackspace employees yes you know what we've noticed too and is budgets are moving those decision makers are moving so again 10 years ago just like you said you would be talking to sometimes a completely different Persona than we do than we do today and we've seen a shift more towards that business value we have a really unique ability to bring business and Technical conversations together I did a lot of work in the past of working with a lot of CMO and and digital transformation companies and so helping bring it and business seeing the same and how healthcare because budgets are living in different places and even across the board with Rackspace people are trying to drive more business outcomes business driven Solutions so the technical becomes the back end and really the ingredients to make all of that all of that happen and that's what we're helping to solve and it's a lot it's very fast paced everyone wants to be agile now and so they're leaning on us more and more to drive more services so if you've seen Rackspace evolve we're driving more of that advisement and those transformation service type discussions where where our original history was DNA was very much always embedded in driving a great experience now they're just wanting more from us more services help us how help us figure out the how Adriana comment on the outcomes that you're helping Healthcare organizations achieve as as we as we it's such a relatable tangible topic Healthcare is Right everybody's everybody's got somebody who's sick or you've been sick or whatnot what are some of those outcomes that we can ex that customers can expect to achieve with Rackspace and VMware oh great great question so very much I can't mentioned earlier it's how do I modernize how do I optimize how do I take the biggest advantage of the budgets and the landscape that I have I want to get to the Cloud we need to help our patients and get access to that data is this ready to go into the cloud is this not ready to go into the cloud you know how do we how do we help make sure we're taking care of our patients we're keeping things secure and accessible you know what else do you think is coming up yeah and one specific one uh sequencing genetic sequencing and so we've had this come up from a few different types of providers whether it's medical devices that they may provide to their end clients and an outcome that they're looking for is how do we get how do we leverage um here's rip here's what we do but now we have so many more people we need to give this access to we need them to be able to have access to the sequencing that all of this is doing all of these different entities are doing and the outcome that they're trying to get to to is more collaboration so so that way we can speed up in the face of a pandemic we can speed up those resolutions we could speed up to you know whether it's a vaccine needed or something that's going to address the next thing that might be coming you know um so that's a specific one I've heard that from a handful of different different um clients that that we work with and so trying to give them a Consolidated not trying to we are able to deliver them a Consolidated place that their application and tooling can run in and then all of these other entities can safely and securely access this data to do what they're going to do in their own spaces and then hopefully it helps the betterment of of of us globally like as humans in the healthcare space we all benefit from this so leveraging the technology to really drive a valuable outcome helps us all so so and by the way I like trying to because it conveys the proper level of humility that we all need to bring to this because it's complicated and anybody who looks you in the eye it pretends like they know exactly how to do it you need to run from those people no it is and and look that's where our partners become so significant we we know we're Best in Class for specific things but we rely on our Partnerships with Dell and VMware to bring their expertise to bring their tried and true technology to help us all together collectively deliver something good technology for good technology for good it is inherently good and it's nice when it's used for goodness it's nice when it's yeah yeah talk about security for a second you know we've seen the threat landscape change dramatically obviously nobody wants to be the next breach ransomware becoming a household term it's now a matter of when we get a head not F where has security gone in terms of conversations with customers going help us ensure that what we're doing is delivering data access to the right folks that need it at the right time in real time in a secure fashion no uh that's another good question in hot and burning so you know I think if we think about past conversations it was that nice Insurance offering that seemed like it came at a high cost if you really need it I've never been breached before um I'll get it when I when I need it but exactly to your point it's the win and not the if so what we're finding and also working with a nice ecosystem of Partners as well from anywhere from Akamai to cloudflare to BT it's how do we help ensure that there is the security as Hannah mentioned that we're delivering the right data access to the right people and permissions you know we're able to help meet multitude of compliance and regulations obviously health care and other regulated space as well we look to make sure that from our side of the house from the infrastructure that we have the right building blocks to help them Reach those compliance needs obviously it's a mutual partnership in maintaining that compliance and that we're able to provide guidance and best practices on to make sure that the data is living in a secure place that the people that need access to it get it when they when they need it and monitor those permissions and back to your complexity comment so more and more complex as we are a global global provider so when you start to talk to our teams in the UK and our our you know clients there specializing um kind of that Sovereign Cloud mentality of hey we need to have um we need to have a cloud that is built for the specific needs that reside within Healthcare by region so it's not just even I mean you know we're we're homegrown out of San Antonio Texas so like we know the U.S and have spent time here but we've been Global for many years so we just get down into the into the nitty-gritty to customize what's needed within each region well Hannah is that part of the Rackspace value proposition at large moving forward because frankly look if I if I want if I want something generic I can I can swipe credit card and and fire up some Services sure um moving forward this is something that is going to more characterize the Rackspace experience and I and I understand that the hesitancy to say hey it's complicated it's like I don't want to hear that I want to hear that it's easy it's like well okay we'll make it easy for you yes but it's still complicated is that okay that's the honest that's that's the honest yeah that's why you need help right that's why we need to talk about that because people people have a legitimate question why Rackspace yep and we don't I don't want to put you on the spot but no yeah but why why Rackspace you've talked a little bit about it already but kind of encapsulate it oh gosh so good good question why Rackspace it's because you can stand up [Laughter] well you can you do it there's many different options out there um and if I had a PowerPoint slide I'd show you this like lovely web of options of directions that you could go and what is Rackspace value it's that we come in and simplify it because we've had experience with this this same use case whatever somebody is bringing forward to us is typically something we've dealt with at numerous times and so we're repeating and speeding up the ability to simplify the complex and to deliver something more simplified well it may be complex within us and we're like working to get it done the outcome that we're delivering is is faster it's less expensive than dedicating all the resources yourself to do it and go invest in all of that that we've already built up and then we're able to deliver it in a more simplified manner it's like the duck analogy the feet below the water yes exactly and a lot of expertise as well yes a lot talk a little bit about the solution that that Dell VMware Rackspace are delivering to customers sure so when we think about um Healthcare clouds or Cloud specific to the healthcare industry you know there's some major players within that space that you think epic we'll just use them as an example this can play out with others but we are building out a custom or we have a custom clouds able to host epic and then provide services up through the Epic help application through partnership so that is broadening the the market for us in the sense that we can tailor what the what that end and with that healthcare provider needs uh do they do they have the expertise to manage the application okay you do that and then we will build out a custom fit Cloud for that application oh and you need all the adjacent things that come with it too so then we have reference architecture you know built out already to to tailor to whatever all those other 40 80 90 hundreds of applications that need to come with that and then and then you start to think about Imaging platforms so we have Imaging platforms available for those specific needs whether it's MRIs and things like that and then the long-term retention that's needed with that so all of these pieces that build out a healthcare ecosystem and those needs we've built those we've built those out and provide those two to our clients yesterday VMware was talking about Cloud chaos yes and and it's true you talk about the complexity and Dave talks about it too like acknowledging yes this is a very complex thing to do yeah there's just so many moving parts so many Dynamics so many people involved or lack thereof people they they then talked about kind of this this the goal of getting customers from cloud chaos to Cloud smart how does that message resonate with Rackspace and how are you helping customers get from simplifying the chaos to eventually get to that cloud smart goal so a lot of it I I believe is with the power of our alliances and I was talking about this earlier we really believe in creating those powerful ecosystems and Jay McBain former for Forester analyst talks about you know the people are going to come ahead really are serve as that orchestration layer of bringing everybody together so if you look at all of that cloud chaos and all of the different logos and the webs and which decisions to make you know the ones that can help simplify that bring it all together like we're going to need a little bit of this like baking a cake in some ways we're going to need a little bit of sugar we'll need this technology this technology and whoever is able to put it together in a clean and seamless way and as Hannah said you know we have specific use cases in different verticals Healthcare specifically and talking from the Imaging and the Epic helping them get hospitals and different you know smaller clinics get to the edge so we have all of the building blocks to get them what they need and we can't do that without Partners but we help simplify those outcomes for those customers yep so there's where they're Cloud smart so then they're like I want I want to be agile I want to work on my cost I want to be able to leverage a multi-cloud fashion because some things may may inherently need to be on Azure some things we inherently need to be on VMware how do we make them feel like they still have that modernized platform and Technology but still give the secure and access that they need right yeah we like to think of it as are you multi-cloud by accident or multi-cloud by Design and help you get to that multi-cloud by Design and leveraging the right yeah the right tools the right places and Dell was talking about that just that at Dell Technologies world just a couple months ago that most most organizations are multi-cloud by default not designed are you seeing any customers that are are able or how are you able to help customers go from that we're here by default for whatever reason acquisition growth.oit line of business and go from that default to a more strategic multi-cloud approach yes it takes planning and commitment you know you really need the business leaders and the technical leaders bought in and saying this is what I'm gonna do because it is a journey because exactly right M A is like inherited four different tools you have databases that kind of look similar but they're a little bit different but they serve four different things so at Rackspace we're able to help assess and we sit down with their teams we have very amazing rock star expertise that will come in and sit with the customers and say what are we trying to drive for it let's get a good assessment of the landscape and let's figure out what are you trying to get towards in your journey and looking at what's the best fit for that application from where it is now to where it is where it wants to be because we saw a lot of customers move to the cloud very quickly you know they went Cloud native very fast some of it made sense retailers who had the spikiness that completely made sense we had some customers though that we've seen move certain workloads they've been in the public Cloud now for a couple years but it was a static website it doesn't make as much sense anymore for certain things so we're able to help navigate all of those choices for them so it's interesting you just you just said something sort of offhand about having experts having them come in so if I am a customer and I have some outcome I want to achieve yes the people that I'm going to be talking to from Rackspace or from Rackspace and the people from Rackspace who are going to be working with the actual people who are deploying infrastructure are also Rackspace people so the interesting contrast there between other circumstances oftentimes is you may have a Global Systems integrator with smart people representing what a cloud provider is doing the perception if they try to make people perceive that okay everybody is working in lockstep but often there are disconnects between what the real capabilities are and what's being advertised so is that I mean I I know it's like a leading question it's like softball get your bats out but I mean isn't that an advantage you've got a single you know the saying used to be uh one throat to show now it's one back to pack because it's kind of Contour friendly yeah yeah but talk about that is that a real Advantage it does it really helps us because again this is our our this is our expertise this is where we where we live we're really close to the infrastructure we're great at the advisement on it we can help with those ongoing and day two management and Opera in operations and what it feels like to grow and scale so we lay this out cleanly and and clearly as possible if this is where we're really good we can we can help you in these areas but we do work with system integrators as well and part of our partner Community because they're working on sometimes the bigger overall Transformations and then we're staying look we understand this multi-cloud but it helps us because in the end we're doing that end to end for for them customer knows this is Rackspace and on hand and we we really strive to be very transparent in what it is that we want to drive and outcomes so sometimes at the time where it's like we're gonna talk about a certain new technology Dell might bring some of their Architects to the table we will say here is Dell with us we're doing that actively in the healthcare space today and it's all coming together but you know at the end of the day this is what Rackspace is going to drive and deliver from an end to end and we tap those people when needed so you don't have to worry about picking up the phone to call Dell or VMware so if I had worded the hard-hitting journalist question the right way it would have elicited the same responses that yeah yeah it drives accountability at the end of the day because what we advised on what we said now we got to go deliver yeah and it's it's all the same the same organization driving accountability so from a customer perspective they're engaging Rackspace who will then bring in dell and VMware as needed as we find the solution exactly we have all of the certification I mean the team the team is great on getting all of the certs because we're getting to handling all of the level one level two level three business they know who to call they have their dedicated account teams they have engagement managers that help them Drive what those bigger conversations are and they don't have to worry about the experts because we either have it on hand or we'll pull them in as needed if it's the bat phone we need to call awesome ladies thank you so much for joining Dave and me today talking about what Rackspace is up to in the partner ecosystem space and specifically what you're doing to help Healthcare organizations transform and modernize we appreciate your insights and your thoughts yeah thank you for having us thank you pleasure for our guests and Dave Nicholson I'm Lisa Martin you're watching thecube live from VMware Explorer 2022 we'll be back after a short break foreign [Music]

(upbeat techno music) >> Welcome to theCube's coverage of VMworld 2021. I'm Lisa Martin. Another Cube alum joining me on the program next, Sanjay Uppal is here, the SVP and GM of Service Provider and Edge Business at VMware. Sanjay, it's great to see you. Thanks for coming back on the program. >> Oh yeah. Thank you. Thanks Lisa. And thank you to theCube. >> It's great that we're covering VMworld. I can't wait til they're back in person. This is another event that is virtual for obvious reasons. But I wanted to dig into your role and have you really kind of unpack that for us. Your role is the senior vice president and general manager of the Service Provider and Edge Business. Talk to me about that. >> Yeah, it's a bit of a mouthful, but really what we're doing here is recognizing that the world is shifting and a lot of the workloads are moving to the edge. So that's the edge part of my responsibility. And the other part is the service providers. Service provider of course, is the name for facilities based telecom operators, as they used to be called in the past, but simply called service providers today. So putting those two things together because service provider, 5G and the edge all go together. So I'm running that as a business for VMware. >> Got it. Let's get VMware's definition of the edge. I always like to do that because some companies have a slightly different spin on it. What is it to VMware? >> Yeah, so to VMware, the edge is distributed digital infrastructure. Digital infrastructure of course, is the software stack that you need to run the applications on top, and it's for running workloads. Now, the important part here that we're defining is that the workloads can be in what's known as the underlay, which you can think of as the infrastructure that is needed to run 5G and fiber. But the workloads can also be in the overlay, which is where you find software defined RAN, secure access service edge. And the workloads can be at the edge application layer. These are the new class of applications that we'll talk about. So it's for running workloads. And the other important part of it is, it's across a number of locations. This is not just about being in a few handful of data centers. This is about being in hundreds of thousands, sometimes millions of locations, which has its own quirks in terms of how that infrastructure should work. And the important point is that the edge is placed close to where the end points are either producing or consuming data. So that's what the edge is, as we define it at VMware. >> Got it. Talk to me about the strategy and the vision that VMware has for edge. >> That's, you know, we're at a very important inflection point in the industry, as far as the edge is concerned. And I just always link it back into what's happening, as an example, in music. So one of my favorite songs from Aerosmith is, "Living on the Edge," and that's literally where we are right now. We're living on the edge and what Aerosmith says is, "We're looking at the world in a different way because things are changing all the way around." Of course, I'm paraphrasing a little bit, but our strategy at VMware is to take this living at the edge, which is happening across the board, and to capture it into infrastructure that we're building, come up with a common software stack that will support workloads that are running in the underlay, in the overlay or at the application layer, and support this entirely new class of applications that are coming in. And these applications, to contrast it with what has been happening before, these applications are being built for experiences. And I'll dig into this in a little bit, but really essentially VMware strategy is to come up with that common software stack that is going to be placed at all of these edge locations, sometimes millions of them, for different types of workloads, but the commonality of the stack is important because that is what the service providers and the enterprises use to derive the benefits. >> Being designed for experiences. It's so interesting, because that's what we expect in our personal lives, in our business lives. We want to have good experiences, whether we're ordering something on Amazon or we're trying to collaborate via Slack or something like that. Experience matters. It sounds silly to say, but it's absolutely true. Talk to me about some of the things, the edge being core to customer's future in any industry. >> Yeah. So, you know, from an industry standpoint, we always used to talk about, what are the features of your product and what are the benefits for customers? And then we started seeing an evolution from benefits into, what are the outcomes that the customers want? But now we are getting from outcomes to experiences. And you take, just an example of a retail chain that we're working with, what they want to do is not just simply sell a product to a customer, walks into the store. They want that person to have an excellent experience. And in order to get to that experience, as an example of what would happen is, this person walks into a store. They recognize who that person is, what they had purchased before, they look at what are the likelihood that they want to buy something today? Do I have that thing in my inventory? If I don't, can I manufacture it with my third generation printer that I have over here? The 3D printer that is sitting in the back room. And then, once that is produced in the next few minutes, can they have an experienced in playing a game with the sportsmen of their choice, on this massive screen that's in there? That's experience. That's not just walking into a store, buying a product and walking out. Another experience would be, when you look at healthcare, what's going on right now that when you have a symptom, you go to your doctor to get checked out. But what if your body tells you that there's something that you need to get done? So this entire new class of applications are coming in with sensors that have artificial intelligence in them that are metricating what is happening. And these sensors with that intelligence then get fed into the edge infrastructure, because this is voluminous amount of information. As you can imagine, the amount of metrics that your body needs to track, all this voluminous information needs to get correlated. And then you may need to make an inference about it. Again, that's an experience because you're completely changing the nature of health as this is going about. So in every vertical industry, we have these examples of experiences and what this requires is computation, networking and storage to be pushed all the way into the edge. It requires a network to get this done. It requires connectivity. And it requires, as I've spoken about before, this common software stack that VMware is bringing. >> So talk to me about what's being announced and unveiled at VMworld. >> So what we are announcing very simply is the VMware Edge. And what that VMware Edge is, it comprises three common software stacks at different layers of the stack. So the first thing that we're saying is that we are announcing the VMware Edge compute stack. So this is software that companies can use, ISV's can use, to develop Edge native applications. These are applications that are born at the edge. They're not applications that are necessarily being refactored from somewhere else. And this is stack that is available in very small form factors, all the way to large form factors, and it'S stack that's connected together. As I mentioned before, the numbers of locations are very important. So we are packaging this, we're making it available across the board next week. This is the first part of the announcement. The second part of the announcement is the expansion of our secure access service edge offering. And that expansion includes going from software defined RAN, which was the first and highly successful service to include secure access, cloud web security, and then to follow that on in a multi-services approach and add more services as we go along. And the third piece is to take our Telco cloud platform, we are announcing that that platform is being co-opted to now run at the edge. Now, one very important development in that part, is that we've had our ESXI product, which is very successful in running in the data center, we have an edge ready version for this product. We've made a 10X improvement in the overhead and latency of ESXI. So now it can be deployed in edge locations in very small form factors, and it is absolutely equivalent to bare metal overhead. So now when companies are looking at, is there overhead associated with the ESXI hypervisor? We're saying, no. It's equivalent to bare metal. And all the benefits that you get with deploying ESXI, will now accrue to benefits that you would have at the edge. >> Talk to me about how the events of the past 18 months, we've seen massive acceleration in digital transformation. We've seen, you mentioned the retailer, the retailer is having to be able to massively shift curbside delivery, e-commerce. How have the events of the last 18 months influenced or catalyzed VMware Edge? >> Absolutely. So if you take a step back and think what has happened due to the pandemic, all of us are working from locations that are not, we're not going to some centralized location to our offices. We're actually working from our home edges. We are literally living at the edge when we were working from home. And also when you go to do curbside pickup, you're making a decision right there. You're going to where that edge location is for that retail store. So really to me, what has happened with the pandemic, is emphasized the need for moving computation all the way to the edge. Now you take one use case, work from home itself. Work from home has gone up by, in some cases, 5X to 8X compared to what it was before. And we've seen the network come under tremendous strain because of work from home. We've seen that the user experience, if it's not good, then of course your productivity gets hampered. So work from home is one of those use cases that has been focused on, because of the pandemic, and we've come up with the solution that will help people when they're sitting in their home environment, the kids can do homework, someone can be watching, streaming movie, but the business users still continues to function with full productivity. So it's really emphasizing the need for moving computation all the way out to the edge. >> Yeah. The edge exploded in the last year and a half. I'm going to now rethink, instead of working from home or living at work, living on the edge. So thank you for giving me that idea. That definitely changes how I feel about this room right here. Talk to me about some of the customers, customer examples, customers in terms of their feedback, as VMware has been developing this. I know you're very much a customer centric organization, but what were some of the directions on the influences from the field? >> I think, as far as customers go, they're an integral part of our development process. It's not like we develop a product and then we go sell it to the customer. What we do is, we get the customer to be a part of that process. We figured out what are the issues that the customers are facing in their own business. As an example, when the pandemic hit, in the healthcare space we had one acute care hospital that came to us and said, "well, we can't get enough of the telemedicine done because the radiologists and all are not able to come into the office." Well, we came up with a solution So that radiologist sitting at home can still look at very high definition images as they're talking to their patients. Now, once we develop the first part of the solution, we actually brought the customer in, gave them a prototype. And then I tell my team that when the customer gives feedback, it's like they're handing us a flashlight and that flashlight illuminates the path ahead for us. And so we follow that path that the customer has set based on the technology that we've produced. Our responsibility is to iterate on that technology in a very fast cycle, so that as we get the flashlights, we illuminate the path and that gets to building the product. And then we get the product built and then we have a happy, successful customer with good outcomes and experiences. And in the end, VMware has done something positive, not just in terms of our business, but for the world at large. >> Right. I love that. Handing the customer a flashlight. Another one I'm going to steal from you, Sanjay. Thank you. You've given me two good ones today. And also a different look at Aerosmith, which I probably now won't be able to get that song out of my head. Some of the trends that we've seen, trends over the last 18 months, what are some of the things that you think we've had a lot of acceleration, but there's a lot of positivity that's come from that, that I don't think gets enough coverage. All of the capabilities that we now have. If you take even just the work from home use case that you mentioned, that's going to be persisting for quite some time, some amount of it's going to be permanent. But what are some of the trends that you're seeing now that you think are really going to help facilitate the edge and the compute and the network and customers being able to take advantage of that even faster? >> Yeah. I think that one of the really important changes that has come because of the pandemic is giving customers choice. And as a part of it, VMware is really focused on multicloud. So, the cloud has come in, we had a movement of workloads from the private data center into the public cloud, but now what customers are saying is, we want choice. We want to make sure that this infrastructure is always available to us. So we are focusing from a VMware standpoint on multicloud. Now, what does that mean? It means that it gives customers choice. They can go to different cloud providers, including the private data center and run their applications on top. And this, we think, is here to stay. This is a trend that we think is as important as what's happening in the future of work. Because previously it used to be, we used to think of work as a destination. It's not. It's a workspace right now. People could essentially be working from anywhere. And one of the things that we've learned in the pandemic is that, that actually does happen. Human beings, we are flexible enough that we can accommodate to these changes that are coming in. So the future of work is going to be distributed. It's going to be workspaces and not workplaces. And then multicloud and marrying those two things together is what we are focusing on at VMware. >> What are some of the tracks or sessions at VMware where folks can go to learn more about that use case in particular, as well as the VMware Edge and what you're announcing? >> Yeah, so we have some excellent tracks. We have a track about, of course, the distributed edge. We have a track about what's going on with cross-cloud services that we have come up with. We have tracks in terms of what's happening with networking and security, because security obviously goes hand in hand with everything. Zero trust is becoming fundamental in everything that we do. I was talking to one of my customers who owns gas stations, and he was saying, "Sanjay, I have gas stations in places that I would never visit. But there are people who would sit at these gas stations. I still need for them to come into the network, but I can't trust the devices that they're coming in on." So these would be a few of the tracks that I would recommend that people would go and watch. >> Excellent. Yeah. Speaking of zero trust and just the massive changes in the threat landscape in the last year and a half, the things that we've seen with massive rise in ransomware and DDoS attacks and attacks like this becoming a when, not if, kind of a scenario. So everybody needed to ensure that they have, they can trust the people and the devices on the network. Sanjay, thank you so much for joining me, talking to us about VMware Edge. You gave us some great analogies there that I'm going to take forward with me. And I look forward to seeing you, hopefully next year at VMworld, in person. Fingers crossed. >> In-person would be awesome. Thank you so much, Lisa. And thank you to theCube. >> Our pleasure. Sunjay Uppal. I'm Lisa Martin. You're watching theCube's coverage of VMworld 2021. (upbeat techno music)

>>Please >>welcome back to HPD discovered 2021. The cubes virtual coverage, continuous coverage of H P. S H. P. S. Annual customer event. My name is Dave Volonte and we're going to dive into the intersection of high performance computing data and AI with DR Eng limb go who is the senior vice president and CTO for AI Hewlett Packard enterprise Doctor go great to see you again. Welcome back to the cube. >>Hello Dave, Great to talk to you again. >>You might remember last year we talked a lot about swarm intelligence and how AI is evolving. Of course you hosted the day two keynotes here at discover and you talked about thriving in the age of insights and how to craft a data centric strategy. And you addressed you know some of the biggest problems I think organizations face with data that's You got a data is plentiful but insights they're harder to come by. And you really dug into some great examples in retail banking and medicine and health care and media. But stepping back a little bit with zoom out on discovered 21, what do you make of the events so far? And some of your big takeaways? >>Mm Well you started with the insightful question, Right? Yeah, data is everywhere then. But we like the insight. Right? That's also part of the reason why that's the main reason why you know Antonio on day one focused and talked about that. The fact that we are now in the age of insight, right? Uh and uh and and how to thrive thrive in that in this new age. What I then did on the day to kino following Antonio is to talk about the challenges that we need to overcome in order in order to thrive in this new asia. >>So maybe we could talk a little bit about some of the things that you took away in terms I'm specifically interested in some of the barriers to achieving insights when customers are drowning in data. What do you hear from customers? What we take away from some of the ones you talked about today? >>Oh, very pertinent question. Dave You know the two challenges I spoke about right now that we need to overcome in order to thrive in this new age. The first one is is the current challenge and that current challenge is uh you know stated is no barriers to insight. You know when we are awash with data. So that's a statement. Right? How to overcome those barriers. What are the barriers of these two insight when we are awash in data? Um I in the data keynote I spoke about three main things. Three main areas that received from customers. The first one, the first barrier is in many with many of our customers. A data is siloed. All right. You know, like in a big corporation you've got data siloed by sales, finance, engineering, manufacturing, and so on, uh supply chain and so on. And uh there's a major effort ongoing in many corporations to build a federation layer above all those silos so that when you build applications above they can be more intelligent. They can have access to all the different silos of data to get better intelligence and more intelligent applications built. So that was the that was the first barrier. We spoke about barriers to incite when we are washed with data. The second barrier is uh that we see amongst our customers is that uh data is raw and dispersed when they are stored and and uh and you know, it's tough to get tough to to get value out of them. Right? And I in that case I I used the example of uh you know the May 6 2010 event where the stock market dropped a trillion dollars in in tens of minutes. You know, we we all know those who are financially attuned with know about this uh incident, But this is not the only incident. There are many of them out there and for for that particular May six event, uh you know, it took a long time to get insight months. Yeah, before we for months we had no insight as to what happened, why it happened, right. Um, and and there were many other incidences like this and the regulators were looking for that one rule that could, that could mitigate many of these incidences. Um, one of our customers decided to take the hard road to go with the tough data right? Because data is rolling dispersed. So they went into all the different feeds of financial transaction information, took the took the tough took the tough road and analyze that data took a long time to assemble. And they discovered that there was quote stuffing right? That uh people were sending a lot of traits in and then cancelling them almost immediately. You have to manipulate the market. Um And why why why didn't we see it immediately? Well, the reason is the process reports that everybody sees the rule in there that says all trades, less than 100 shares don't need to report in there. And so what people did was sending a lot of less than 103 100 100 shares trades uh to fly under the radar to do this manipulation. So here is here the second barrier right? Data could be raw and dispersed. Um Sometimes you just have to take the hard road and um and to get insight And this is 1 1 great example. And then the last barrier is uh is has to do with sometimes when you start a project to to get insight to get uh to get answers and insight. You you realize that all the datas around you but you don't you don't seem to find the right ones to get what you need. You don't you don't seem to get the right ones. Yeah. Um here we have three quick examples of customers. 111 was it was a great example right? Where uh they were trying to build a language translator, a machine language translator between two languages. Right? By not do that. They need to get hundreds of millions of word pairs, you know, of one language compared uh with a corresponding other hundreds of millions of them. They say, well I'm going to get all these word pairs. Someone creative thought of a willing source. And you thought it was the United Nations, you see. So sometimes you think you don't have the right data with you, but there might be another source. And the willing one that could give you that data Right? The 2nd 1 has to do with uh there was uh the uh sometimes you you may just have to generate that data, interesting one. We had an autonomous car customer that collects all these data from their cars, right? Massive amounts of data, loss of sensors, collect loss of data. And uh, you know, but sometimes they don't have the data they need even after collection. For example, they may have collected the data with a car uh in in um in fine weather and collected the car driving on this highway in rain and also in stone, but never had the opportunity to collect the car in hill because that's a rare occurrence. So instead of waiting for a time where the car can dr inhale, they build a simulation you by having the car collector in snow and simulated him. So, these are some of the examples where we have customers working to overcome barriers, right? You have barriers that is associated the fact that data silo the Federated it various associated with data. That's tough to get that. They just took the hard road, right? And, and sometimes, thirdly, you just have to be creative to get the right data. You need, >>wow, I I'll tell you, I have about 100 questions based on what you just said. Uh, there's a great example, the flash crash. In fact, Michael Lewis wrote about this in his book The Flash Boys and essentially right. It was high frequency traders trying to front run the market and sending in small block trades trying to get on the front end it. So that's and they, and they chalked it up to a glitch like you said, for months. Nobody really knew what it was. So technology got us into this problem. I guess my question is, can technology help us get out of the problem? And that maybe is where AI fits in. >>Yes, yes. Uh, in fact, a lot of analytics, we went in to go back to the raw data that is highly dispersed from different sources, right, assemble them to see if you can find a material trend, right? You can see lots of trends, right? Like, uh, you know, we if if humans look at things right, we tend to see patterns in clouds, right? So sometimes you need to apply statistical analysis, um math to to be sure that what the model is seeing is is real. Right? And and that required work. That's one area. The second area is uh you know, when um uh there are times when you you just need to to go through that uh that tough approach to to find the answer. Now, the issue comes to mind now is is that humans put in the rules to decide what goes into a report that everybody sees. And in this case uh before the change in the rules. Right? But by the way, after the discovery, uh authorities change the rules and all all shares, all traits of different any sizes. It has to be reported. No. Yeah. Right. But the rule was applied uh you know, to say earlier that shares under 100 trades under 100 shares need not be reported. So sometimes you just have to understand that reports were decided by humans and and under for understandable reasons. I mean they probably didn't want that for various reasons not to put everything in there so that people could still read it uh in a reasonable amount of time. But uh we need to understand that rules were being put in by humans for the reports we read. And as such there are times you just need to go back to the raw data. >>I want to ask, >>it's gonna be tough. >>Yeah. So I want to ask a question about AI is obviously it's in your title and it's something you know a lot about but and I want to make a statement, you tell me if it's on point or off point. So it seems that most of the Ai going on in the enterprise is modeling data science applied to troves of data but but there's also a lot of ai going on in consumer whether it's you know, fingerprint technology or facial recognition or natural language processing will a two part question will the consumer market as has so often in the enterprise sort of inform us uh the first part and then will there be a shift from sort of modeling if you will to more you mentioned autonomous vehicles more ai influencing in real time. Especially with the edge you can help us understand that better. >>Yeah, it's a great question. Right. Uh there are three stages to just simplify, I mean, you know, it's probably more sophisticated than that but let's simplify three stages. All right. To to building an Ai system that ultimately can predict, make a prediction right or to to assist you in decision making, have an outcome. So you start with the data massive amounts of data that you have to decide what to feed the machine with. So you feed the machine with this massive chunk of data and the machine uh starts to evolve a model based on all the data is seeing. It starts to evolve right to the point that using a test set of data that you have separately kept a site that you know the answer for. Then you test the model uh you know after you trained it with all that data to see whether it's prediction accuracy is high enough and once you are satisfied with it, you you then deploy the model to make the decision and that's the influence. Right? So a lot of times depend on what what we are focusing on. We we um in data science are we working hard on assembling the right data to feed the machine with, That's the data preparation organization work. And then after which you build your models, you have to pick the right models for the decisions and prediction you wanted to make. You pick the right models and then you start feeding the data with it. Sometimes you you pick one model and the prediction isn't that robust, it is good but then it is not consistent right now. What you do is uh you try another model so sometimes it's just keep trying different models until you get the right kind. Yeah, that gives you a good robust decision making and prediction after which It is tested well Q eight. You would then take that model and deploy it at the edge. Yeah. And then at the edges is essentially just looking at new data, applying it to the model that you have trained and then that model will give you a prediction decision. Right? So uh it is these three stages. Yeah, but more and more uh your question reminds me that more and more people are thinking as the edge become more and more powerful. Can you also do learning at the edge? Right. That's the reason why we spoke about swarm learning the last time, learning at the edge as a swamp, right? Because maybe individually they may not have enough power to do so. But as a swamp they made >>is that learning from the edge? You're learning at the edge? In other words? >>Yes. >>Yeah, I understand the question. Yeah. >>That's a great question. That's a great question. Right? So uh the quick answer is learning at the edge, right? Uh and and also from the edge, but the main goal, right? The goal is to learn at the edge so that you don't have to move the data that the edge sees first back to the cloud or the core to do the learning because that would be the reason. One of the main reasons why you want to learn at the edge, right? Uh So so that you don't need to have to send all that data back and assemble it back from all the different Edge devices, assemble it back to the cloud side to to do the learning right. With someone you can learn it and keep the data at the edge and learn at that point. >>And then maybe only selectively send the autonomous vehicle example you gave us great because maybe there, you know, there may be only persisting, they're not persisting data that is inclement weather or when a deer runs across the front. And then maybe they they do that and then they send that smaller data set back and maybe that's where it's modelling done. But the rest can be done at the edges. It's a new world that's coming down. Let me ask you a question, is there a limit to what data should be collected and how it should be collected? >>That's a great question again, you know uh wow today, full of these uh insightful questions that actually touches on the second challenge. Right? How do we uh in order to thrive in this new age of insight? The second challenge is are you know the is our future challenge, right? What do we do for our future? And and in there is uh the statement we make is we have to focus on collecting data strategically for the future of our enterprise. And within that I talk about what to collect right? When to organize it when you collect and where will your data be, you know, going forward that you are collecting from? So what, when and where for the what data for the what data to collect? That? That was the question you ask. Um it's it's a question that different industries have to ask themselves because it will vary, right? Um Let me give you the, you use the autonomous car example, let me use that. And We have this customer collecting massive amounts of data. You know, we're talking about 10 petabytes a day from the fleet of their cars. And these are not production autonomous cars, right? These are training autonomous cars, collecting data so they can train and eventually deploy commercial cars. Right? Um, so this data collection cars they collect as a fleet of them collect 10 petabytes a day and when it came to us uh building a storage system yeah, to store all of that data, they realized they don't want to afford to store all of it. Now here comes the dilemma, right? Should what should I after I spent so much effort building all these cars and sensors and collecting data, I've now decide what to delete. That's a dilemma right now in working with them on this process of trimming down what they collected. You know, I'm constantly reminded of the sixties and seventies, right? To remind myself 16 seventies we call a large part of our D. N. A junk DNA. Today we realize that a large part of that what we call john has function as valuable function. They are not jeans, but they regulate the function of jeans, you know? So, so what's jumped in the yesterday could be valuable today or what's junk today could be valuable tomorrow. Right? So, so there's this tension going on right between you decided not wanting to afford to store everything that you can get your hands on. But on the other hand, you you know, you worry you you you ignore the wrong ones, right? You can see this tension in our customers, right? And it depends on industry here. Right? In health care, they say I have no choice. I I want it. All right. One very insightful point brought up by one health care provider that really touched me was, you know, we are not we don't only care. Of course we care a lot. We care a lot about the people we are caring for, right? But you also care for the people were not caring for. How do we find them? Mhm. Right. And that therefore they did not just need to collect data that is uh that they have with from their patients. They also need to reach out right to outside data so that they can figure out who they are not caring for. Right? So they want it all. So I tell us them. So what do you do with funding if you want it all? They say they have no choice but to figure out a way to fund it and perhaps monetization of what they have now is the way to come around and find out. Of course they also come back to us rightfully that, you know, we have to then work out a way to help them build that system, you know, so that health care, right? And and if you go to other industries like banking, they say they can't afford to keep them on, but they are regulated. Seems like healthcare, they are regulated as to uh privacy and such. Like so many examples different industries having different needs but different approaches to how what they collect. But there is this constant tension between um you perhaps deciding not wanting to fund all of that uh all that you can stall right on the other hand, you know, if you if you kind of don't want to afford it and decide not to store some uh if he does some become highly valuable in the future right? Don't worry. >>We can make some assumptions about the future, can't we? I mean, we know there's gonna be a lot more data than than we've ever seen before. We know that we know. Well notwithstanding supply constraints on things like nand, we know the prices of storage is gonna continue to decline. We also know and not a lot of people are really talking about this but the processing power but he says moore's law is dead. Okay, it's waning. But the processing power when you combine the Cpus and N. P. U. S. And Gpus and accelerators and and so forth actually is is increasing. And so when you think about these use cases at the edge, you're going to have much more processing power, you're going to have cheaper storage and it's going to be less expensive processing. And so as an ai practitioner, what can you do with that? >>So the amount of data that's gonna come in, it's gonna we exceed right? Our drop in storage costs are increasing computer power. Right? So what's the answer? Right? So so the the answer must be knowing that we don't and and even the drop in price and increase in bandwidth, it will overwhelm the increased five G will overwhelm five G. Right? Given amount 55 billion of them collecting. Right? So the answer must be that there might need to be a balance between you needing to bring all that data from the 55 billion devices data back to a central as a bunch of central. Cause because you may not be able to afford to do that firstly band with even with five G. M and and SD when you'll still be too expensive given the number of devices out there, Were you given storage costs dropping? You'll still be too expensive to try and store them all. So the answer must be to start at least to mitigate the problem to some leave both a lot of the data out there. Right? And only send back the pertinent ones as you said before. But then if you did that, then how are we gonna do machine learning at the core and the cloud side? If you don't have all the data, you want rich data to train with. Right? Some sometimes you wanna mix of the uh positive type data and the negative type data so you can train the machine in a more balanced way. So the answer must be eventually right. As we move forward with these huge number of devices out of the edge to do machine learning at the edge today, we don't have enough power. Right? The edge typically is characterized by a lower uh energy capability and therefore lower compute power. But soon, you know, even with lower energy they can do more with compute power, improving in energy efficiency, Right? Uh So learning at the edge today we do influence at the edge. So we data model deploy and you do in France at the age, that's what we do today. But more and more I believe given a massive amount of data at the edge, you, you have to have to start doing machine learning at the edge and, and if when you don't have enough power then you aggregate multiple devices, compute power into a swamp and learn as a swan. >>Oh, interesting. So now of course, if, if I were sitting and fly, fly on the wall in hp board meeting, I said okay. HB is as a leading provider of compute how do you take advantage of that? I mean we're going, we're, I know its future, but you must be thinking about that and participating in those markets. I know today you are, you have, you know, edge line and other products. But there's, it seems to me that it's, it's not the general purpose that we've known in the past. It's a new type of specialized computing. How are you thinking about participating in that >>opportunity for the customers? The world will have to have a balance right? Where today the default? Well, the more common mode is to collect the data from the edge and train at uh at some centralized location or a number of centralized location um going forward. Given the proliferation of the edge devices, we'll need a balance. We need both. We need capability at the cloud side. Right? And it has to be hybrid and then we need capability on the edge side. Yeah. That they want to build systems that that on one hand, uh is uh edge adapted, right? Meaning the environmentally adapted because the edge different. They are on a lot of times. On the outside. Uh They need to be packaging adapted and also power adapted, right? Because typically many of these devices are battery power. Right? Um, so you have to build systems that adapt to it. But at the same time they must not be custom. That's my belief. They must be using standard processes and standard operating system so that they can run a rich set of applications. So yes. Um that's that's also the insightful for that Antonio announced in 2018 Uh the next four years from 2018, right $4 billion dollars invested to strengthen our edge portfolio. Edge product lines, Right. Edge solutions. >>I can doctor go, I could go on for hours with you. You're you're just such a great guest. Let's close. What are you most excited about in the future? Of of of it. Certainly H. P. E. But the industry in general. >>Yeah. I think the excitement is uh the customers, right? The diversity of customers and and the diversity in a way they have approached their different problems with data strategy. So the excitement is around data strategy, right? Just like you know uh you know, the the statement made was was so was profound, right? Um And Antonio said we are in the age of insight powered by data. That's the first line, right. Uh The line that comes after that is as such were becoming more and more data centric with data, the currency. Now the next step is even more profound. That is um You know, we are going as far as saying that you know um data should not be treated as cost anymore. No. Right. But instead as an investment in a new asset class called data with value on our balance sheet, this is a this is a step change right? In thinking that is going to change the way we look at data, the way we value it. So that's a statement that this is the exciting thing because because for for me, a city of Ai right uh machine is only as intelligent as the data you feed it with data is a source of the machine learning to be intelligent. So, so that's that's why when when people start to value data, right? And and and say that it is an investment when we collect it, it is very positive for AI because an AI system gets intelligent, get more intelligence because it has a huge amounts of data and the diversity of data. So it would be great if the community values values data. Well, >>you certainly see it in the valuations of many companies these days. Um and I think increasingly you see it on the income statement, you know, data products and people monetizing data services and maybe eventually you'll see it in the in the balance. You know, Doug Laney, when he was a gardener group wrote a book about this and a lot of people are thinking about it. That's a big change, isn't it? Dr >>yeah. Question is is the process and methods evaluation right. But I believe we'll get there, we need to get started and then we'll get there. Believe >>doctor goes on >>pleasure. And yeah. And then the Yeah, I will well benefit greatly from it. >>Oh yeah, no doubt people will better understand how to align you know, some of these technology investments, Doctor goes great to see you again. Thanks so much for coming back in the cube. It's been a real pleasure. >>Yes. A system. It's only as smart as the data you feed it with. >>Excellent. We'll leave it there, thank you for spending some time with us and keep it right there for more great interviews from HP discover 21 this is Dave Volonte for the cube. The leader in enterprise tech coverage right back

>>Welcome >>back to HP discover 2021. My name is Dave Volonte and you're watching the cubes virtual coverage of discover 21 we're excited to welcome back our wa Kadoura, She's the vice president and worldwide go to market leader for HP. Es smoking hot. Green Lake Cloud services are welcome back to the cube. Good to see you again. >>Thank you for having me to be with you. >>So talk about how your products and services are supporting customer transformations. I'm interested in the experience that everybody has been dreaming about describe how you're giving your customer that competitive advantage. If you've got any examples, that would be awesome. >>Yeah, you got it. Um, I think as we heard Antonio say the cloud is an experience, not a destination, right? And what we're doing with Green Lake is bringing those cloud capabilities and the cloud experience to our customers. You know, we like to say co locations, data center and edge of course. So this is the cloud on prem. And so rather than forcing customers to only have to go up to cloud to get modern cloud capabilities or the benefits of things like, you know, pay as you go for consumption, et cetera. You know, cloud native capabilities like containers, leveraging, kubernetes. We now bring all of that to Green Lake and to our customers. Edge locations and co locations and data centers. We've been able to dramatically transform many of our customers businesses. Right? And you'll probably see it discover some of those examples come to life. For example, Care Stream, who is, you know, in the electronic medical imaging world, Right? They have all of the X ray equipment that capture x rays and different sort of diagnostics for patients. Um and we worked with them to not only craft a ml solution to better read and diagnose these images, um but also all of the underlying infrastructure with the HP Green Lake Ml ops platform that allows them to instantly leverage the capabilities of machine learning and the infrastructure to go with it. >>And so tell me, so, how is it resonating with customers? What you're out there, talking to customers all the time? What are they >>telling you? You know, I think what our customers appreciate about HP Green Lake is it's not sort of look, it's either all on prem in my data center and I have to fully manage it, build it, implement it, take care of it or it's fully public cloud. I have little control and basically I get whatever the public cloud gives me right. Hp Green leg gives our customers the flexibility and control that they require. Right. And so you can think of many use cases where customers have a need to have the compute storage sort of processing need to happen closer to where their data and apps live. Um and so for that exact reason our customers love the flexibility, right? Cloud one, Dato was public cloud. Cloud to Dato I think is the cloud that comes to our customers at their convenience. And to me, you know what I tell C I O S and C T O S and sort of other lines of business leaders when I meet with them is you shouldn't be forced to have to take your data and apps elsewhere to get the transformation that you need. We want to be able to bring that directly to our customers. >>Of course, a lot of the transformation is around data. We love talking about data on the cube and it's funny, I mean we talked about big data last decade. We don't use that term much anymore. Uh It was kind of overhyped but as as often times as the case may be in the early days it's overhyped but then it's under hyped when it actually starts to kick in. And I feel like we're entering a new age of data. And insights with the ascendancy of machine learning and ai what does this mean from H. P. S. Perspective and what our customers telling you that it means for them. >>Yeah no data. I think we often hear data is the new currency writes the new gold. Um You know we've heard uh Antonio even say things like look data could even become something that maybe over time companies start to put some kind of value on their balance sheet. Behind right the same way that maybe brands represented this value on a balance sheet. Um effectively what's happened with data is a lot of people have a lot of data but there's not been a lot of ability to extract insights from data. Right? And I think this is the new revolution that we're all undergoing is we finally have the modern analytics tools to actually turn the data into insights and what we bring to the table from an HPD perspective is the fact that we have the best infrastructure. We obviously now have the cloud capabilities mixed in with our data fabric or container platform, our machine learning operations platform to then be able to process that data again, integrated with many of the great I SV partners that we have on the data side allow our customers to turn that into real insights for their business. And effectively data is becoming a huge competitive advantage. Right? I think many of us are you know, leveraging some, you know, pretty interesting tools or gadgets these days, right? Like I wear one of those, you know, sleep brings, you can imagine a company like that in the future that's able to collect so much data from the folks that purchase their products. Then being able to give us insights about, you know, where is the best zip code that, you know, people get the most amount of sleep in or you know, which zip codes are the healthiest and you know, the United States or countries, et cetera. Um but data really is becoming um you know, a competitive advantage. And one of the things that we care most about at HP is also using it as a force for good and making sure that there is a sort of ethical ai capability. >>That's a great message and very important one. And and it's interesting you're saying about data and the value how well it's clearly it's clearly being valued in terms of companies market caps. I mean it's it's it's you know, maybe it's not the balance yet, but it's on the income statement in terms of data products and data services that that's happening. So we'll see if Antonio's right in the next, you know, several years. But so let's talk more about the specific data challenges that you're solving for your customers. They talk about silos, they talk about they haven't got as much value out of their data initiatives as they wanted to. What are they telling you? Are there challenges and how are you approaching it? >>Yeah, I think, you know, um data's everywhere right. The ability for customers to store the right amount of data is a huge challenge because obviously there's, you know, a huge cost associated with collecting, keeping cleansing processing, you know, all the way to sort of analyzing your data. There tends to be a ton of data silos, right? So customers are looking for a common data fabric that they can then process their data sources across and then be able to sort of tap into that data from an analytics perspective. So much of the technology again that we're focused on is be able to store the data right, Our data fabric layer with his moral right being able to process that data capture that data and then allow the analytics tools to then harness the power of that data and turn that into real business insights for our customers. Um Every customer that I have spoken to, you know whether their financial services, you know, you can imagine the big financial services. I mean they've got you know, just bazillions of pockets of data everywhere and you know, the real sort of a challenge for them is how do I build a common data platform that allows me to tap into that data in effective ways for my business users? >>You talk a little bit about how you're changing the way you're providing solutions? Maybe maybe you could contrast it with the way HP has done in the past, because I think that's important when you, when you think about, you talk a lot about green lake and as a service, but if the products are still, you know, kind of boxes and Luns and, and gigahertz and ports, then, you know, that's that's a dis continuity. So what's changed from the past and how are you feeding into the way customers are transforming their business and supporting their outcomes? >>That's exactly right. You know, at some point in time, right. If you think maybe 10 or 20 years back, it used to be very much about the infrastructure for hp. What's exciting about what we're doing differently for our customers is look, we have the best infrastructure in the business, right. Hp has been doing this you no longer than anyone has probably almost 60 years now. Um but being able to vertically integrate right, move up in that value change so that our customers can get more complete solutions is the more interesting part for our customers. Our customers love our technology, Yes, the gigahertz and the speeds and feeds all of that do matter because they, you know, make for some very powerful infrastructure. However, what makes it easier is the fact that we are building platform stacks on top of that hardware, um that help abstract away the complexity of that infrastructure and the ability to use it far more seamlessly. Um and then if you think about it, we of course have also one of the most advanced services organizations. So being able to leverage our services capabilities, our platform capabilities on top of that hardware, again, deliver it back to our customers In a consumption model, which they've become two X, which they've come to expect from a cloud model. Um and then surrounded by a very rich ecosystem of partners. And we're talking about system Integrators that now have capabilities on helping our customers run their Green Lake environments. We're talking about I. S. V. S. Right? So software stacks and platforms that fully integrate with the Green Lake platform for completely seamless solutions. Um as well as channel Partners and global distributors. So I think that's where we can truly deliver the ultimate end to end solution. It's not just the hardware, right? But it's being complemented with the right services being complemented with the right platform capabilities, the software integrations to deliver that workload that the customer expects. >>And partners, they gotta they gotta place bets, they gonna put resources time money in a line, their resources with with their their partners and their suppliers like HP. So when they ask you, hey, okay. Hp. Tell me or well, what's your overall strategy? Why is it compelling and why do you give me competitive advantage relative to some of your peers in the industry? >>Yeah, I think what, you know, partners are going to be most excited about is the openness of the platform, right? Being able to allow our partners to leverage Green Lake Central with open API so that they can integrate some of their own technologies into our platform. Uh the ability to allow them to also layer in their own um managed services on top of the platform is key. Um And of course being able to build sort of these win win solutions with the system Integrators, right. The system Integrators have some fantastic capabilities all the way from an application development, all the way down to the infrastructure management and data center delivery centers that they have. And so leveraging HP Green Lake um really helps them have access to core technologies that they need to deliver these solutions. >>I wonder if I could take a little sort of side road here and ask you because so many changes going on HP itself is transforming your customers are transforming the pandemic has accelerated all these transformations. Can you talk a little bit about how you've transformed go to market specifically in the context of of as a service? I mean that had to be quite a change for you guys. >>Yeah, no, go to market transformations in support of sort of moving from traditional go to markets right to call, go to markets or significant. Um They required us to really think through what does delivering as a service solutions mean for our direct sales force? What does it mean for our partners and their transformations and being able to support as a service solutions? Um for HP specifically, it also means um thinking about our customer outcomes, not just our ability to ship them, you know, the requisite hardware and say, look, once it's left our dog, our job is done right. It really takes our obligation all the way to the customer using the technology on a day by day basis, as well as supporting them in making sure that everything from implementation to set up to the ongoing monitoring operations of the technology is working for them in the way that they expect in an as a service way, right? We don't expect them to operate it. We don't expect them to, you know, do anything more than pick up the phone and call us if something doesn't go as planned. >>And how about your sellers and your partners? How did they respond? I mean you just wake up one day is okay guys, here we go, new compensation scheme, new way to sell new way to market that that took some thought in some time. And where are you in that journey? >>That's right. And I always say, you know, if you expect people to wake up one day and be transformed, right? You're kidding yourself. Um So everything from sort of the way that we think about our customers use cases, right? And empowering our sellers to understand the outcomes that our customers expect and demand from us to things like compensation too. You know, the partner rebate program that we leverage through the channel partners in order to give them the right incentives to also allow them to make the right investments to support Green Lake. Um, you know, we've all, you know, HP has a fairly significant field sales and solution team and so not thinking about this only as a single person that represents Green Lake, but looking at our capabilities across the board, right. We have fantastic advisory consultants on the ground with phds and data science. We have folks that understand, you know, high performance computing, so making sure that we're embedding the expertise in all of the right personas that support our customers, not just from a calm perspective, but also from an understanding of the end to end solutions that we're bringing to those markets. >>So what gets you stoked in the morning, you get out of bed and you're like, okay, I'm gonna go attack the world. What are you most excited about for H P E and his future? >>You know, it's, there's so much happening right now in this sort of cloud world. Right? Um to me the most exciting portion is the fact that given that we've now introduced on prem cloud to the world, our ability to ship new services and new capabilities, um, but also do that via a very rich partner ecosystem honestly is what probably has me most excited. This is no longer the age of go at it alone, Right. So not only are engineering and product teams hard at work in the engine room producing, you know, capabilities at sort of lightening fast speeds, but it's also our ability to partner, uh you know, whether it's with platform providers, you know, software providers or, you know, system Integrators and services providers, that ecosystem is starting to come together to deliver highly meaningful solutions to our customers and all in a very open way. Um, the number one thing that I personally care about is that our customers never feel like they are being locked in or that they are sort of being forced to have to give up certain levels of capabilities. We want to give them the best of what's out there and allow them to then have that flexibility in their solution. >>And one of the challenges, of course with virtual events is you don't have the hallway track. You know, somebody can't say, hey, have you seen that IOT zone? It's amazing. They got all these robots going around. But so what, what would you say that people should be focused on the discovery maybe things that you want to call out specific highlights or segments that you think are relevant? >>Yeah, there's gonna be a ton of fantastic stuff I think, um you know, really looking for that edge to cloud strategy, um that we're gonna be spending a lot of time talking about um looking at some of our vertical workload solutions, right. We're gonna be talking about quite a few from electronic health care records to payment solutions. Um and many more I think depending on what folks are interested in, there's gonna be something for everyone. Um Project Aurora, which now starts to announce our new security capabilities. Um, you know, the zero trust capabilities that we're delivering um is probably interesting to a lot of our customers, so lots of exciting things coming and I'm excited for our customers to check this out. >>No doubt that's a hot topic. Especially given what's been happening the news these past several months. All right, well, thanks so much for coming back in. The cube is great to see you hopefully face to face next time. >>I sure hope so. Thanks so much for having me. >>It's our pleasure. And thank you for watching and thank you for being with us and our ongoing coverage of HPD discovered 2021. This is Dave Volonte. You're watching the cube, The leader and digital tech coverage. >>Yeah.

>>Welcome back to HPD discovered 2021 the cubes virtual coverage, continuous coverage of H P. S H. P. S. Annual customer event. My name is Dave Volonte and we're going to dive into the intersection of high performance computing data and AI with DR Eng limb go who is the senior vice president and CTO for AI at Hewlett Packard enterprise Doctor go great to see you again. Welcome back to the cube. >>Hello Dave, Great to talk to you again. >>You might remember last year we talked a lot about swarm intelligence and how AI is evolving. Of course you hosted the day two keynotes here at discover you talked about thriving in the age of insights and how to craft a data centric strategy and you addressed you know some of the biggest problems I think organizations face with data that's You got a data is plentiful but insights they're harder to come by. And you really dug into some great examples in retail banking and medicine and health care and media. But stepping back a little bit with zoom out on discovered 21, what do you make of the events so far? And some of your big takeaways? >>Mm Well you started with the insightful question, right? Yeah. Data is everywhere then. But we like the insight. Right? That's also part of the reason why that's the main reason why you know Antonio on day one focused and talked about that. The fact that we are now in the age of insight. Right? Uh and and uh and and how to thrive thrive in that in this new age. What I then did on the day to kino following Antonio is to talk about the challenges that we need to overcome in order in order to thrive in this new age. >>So maybe we could talk a little bit about some of the things that you took away in terms I'm specifically interested in some of the barriers to achieving insights when you know customers are drowning in data. What do you hear from customers? What we take away from some of the ones you talked about today? >>Oh, very pertinent question. Dave you know the two challenges I spoke about right now that we need to overcome in order to thrive in this new age. The first one is is the current challenge and that current challenge is uh you know stated is you know, barriers to insight, you know when we are awash with data. So that's a statement right? How to overcome those barriers. What are the barriers of these two insight when we are awash in data? Um I in the data keynote I spoke about three main things. Three main areas that received from customers. The first one, the first barrier is in many with many of our customers. A data is siloed. All right. You know, like in a big corporation you've got data siloed by sales, finance, engineering, manufacturing, and so on, uh supply chain and so on. And uh, there's a major effort ongoing in many corporations to build a federation layer above all those silos so that when you build applications above they can be more intelligent. They can have access to all the different silos of data to get better intelligence and more intelligent applications built. So that was the that was the first barrier we spoke about barriers to incite when we are washed with data. The second barrier is uh, that we see amongst our customers is that uh data is raw and dispersed when they are stored and and uh and you know, it's tough to get tough to to get value out of them. Right? And I in that case I I used the example of uh you know the May 6 2010 event where the stock market dropped a trillion dollars in in tens of ministerial. We we all know those who are financially attuned with know about this uh incident But this is not the only incident. There are many of them out there and for for that particular May six event uh you know, it took a long time to get insight months. Yeah before we for months we had no insight as to what happened, why it happened, right. Um and and there were many other incidences like this. And the regulators were looking for that one rule that could, that could mitigate many of these incidences. Um one of our customers decided to take the hard road go with the tough data right? Because data is rolling dispersed. So they went into all the different feeds of financial transaction information. Uh took the took the tough uh took the tough road and analyze that data took a long time to assemble and they discovered that there was court stuffing right? That uh people were sending a lot of traits in and then cancelling them almost immediately. You have to manipulate the market. Um And why why why didn't we see it immediately? Well the reason is the process reports that everybody sees uh rule in there that says all trades. Less than 100 shares don't need to report in there. And so what people did was sending a lot of less than 103 100 100 shares trades uh to fly under the radar to do this manipulation. So here is here the second barrier right? Data could be raw and dispersed. Um Sometimes you just have to take the hard road and um and to get insight And this is 1 1 great example. And then the last barrier is uh is has to do with sometimes when you start a project to to get insight to get uh to get answers and insight. You you realize that all the datas around you but you don't you don't seem to find the right ones To get what you need. You don't you don't seem to get the right ones. Yeah. Um here we have three quick examples of customers. 111 was it was a great example right? Where uh they were trying to build a language translator, a machine language translator between two languages. Right? But not do that. They need to get hundreds of millions of word pairs, you know, of one language compared uh with the corresponding other hundreds of millions of them. They say we are going to get all these word pairs. Someone creative thought of a willing source and a huge, so it was a United Nations you see. So sometimes you think you don't have the right data with you, but there might be another source and a willing one that could give you that data right. The second one has to do with uh there was uh the uh sometimes you you may just have to generate that data, interesting one. We had an autonomous car customer that collects all these data from their cars, right, massive amounts of data, loss of senses, collect loss of data. And uh you know, but sometimes they don't have the data they need even after collection. For example, they may have collected the data with a car uh in in um in fine weather and collected the car driving on this highway in rain and also in stone, but never had the opportunity to collect the car in hale because that's a rare occurrence. So instead of waiting for a time where the car can dr inhale, they build a simulation you by having the car collector in snow and simulated him. So these are some of the examples where we have customers working to overcome barriers, right? You have barriers that is associated the fact that data is silo Federated, it various associated with data. That's tough to get that. They just took the hard road, right? And sometimes, thirdly, you just have to be creative to get the right data you need, >>wow, I tell you, I have about 100 questions based on what you just said. Uh, there's a great example, the flash crash. In fact, Michael Lewis wrote about this in his book, The Flash Boys and essentially right. It was high frequency traders trying to front run the market and sending in small block trades trying to get on the front end it. So that's and they, and they chalked it up to a glitch like you said, for months, nobody really knew what it was. So technology got us into this problem. I guess my question is, can technology help us get out of the problem? And that maybe is where AI fits in. >>Yes, yes. Uh, in fact, a lot of analytics, we went in, uh, to go back to the raw data that is highly dispersed from different sources, right, assemble them to see if you can find a material trend, right? You can see lots of trends right? Like, uh, you know, we, if if humans look at things right, we tend to see patterns in clouds, right? So sometimes you need to apply statistical analysis, um math to be sure that what the model is seeing is is real. Right? And and that required work. That's one area. The second area is uh you know, when um uh there are times when you you just need to to go through that uh that tough approach to to find the answer. Now, the issue comes to mind now is is that humans put in the rules to decide what goes into a report that everybody sees in this case uh before the change in the rules. Right? But by the way, after the discovery, the authorities change the rules and all all shares, all traits of different any sizes. It has to be reported. No. Yeah. Right. But the rule was applied uh you know, to say earlier that shares under 100 trades under 100 shares need not be reported. So sometimes you just have to understand that reports were decided by humans and and under for understandable reasons. I mean they probably didn't want that for various reasons not to put everything in there so that people could still read it uh in a reasonable amount of time. But uh we need to understand that rules were being put in by humans for the reports we read. And as such, there are times you just need to go back to the raw data. >>I want to ask, >>albeit that it's gonna be tough. >>Yeah. So I want to ask a question about AI is obviously it's in your title and it's something you know a lot about but and I want to make a statement, you tell me if it's on point or off point. So it seems that most of the Ai going on in the enterprise is modeling data science applied to troves of data >>but >>but there's also a lot of ai going on in consumer whether it's you know, fingerprint technology or facial recognition or natural language processing. Will a two part question will the consumer market has so often in the enterprise sort of inform us uh the first part and then will there be a shift from sort of modeling if you will to more you mentioned autonomous vehicles more ai influencing in real time. Especially with the edge. She can help us understand that better. >>Yeah, it's a great question. Right. Uh there are three stages to just simplify, I mean, you know, it's probably more sophisticated than that but let's simplify three stages. All right. To to building an Ai system that ultimately can predict, make a prediction right or to to assist you in decision making, have an outcome. So you start with the data massive amounts data that you have to decide what to feed the machine with. So you feed the machine with this massive chunk of data and the machine uh starts to evolve a model based on all the data is seeing. It starts to evolve right to the point that using a test set of data that you have separately campus site that you know the answer for. Then you test the model uh you know after you trained it with all that data to see whether it's prediction accuracy is high enough and once you are satisfied with it, you you then deploy the model to make the decision and that's the influence. Right? So a lot of times depend on what what we are focusing on. We we um in data science are we working hard on assembling the right data to feed the machine with, That's the data preparation organization work. And then after which you build your models, you have to pick the right models for the decisions and prediction you wanted to make. You pick the right models and then you start feeding the data with it. Sometimes you you pick one model and the prediction isn't that robust, it is good but then it is not consistent right now what you do is uh you try another model so sometimes it's just keep trying different models until you get the right kind. Yeah, that gives you a good robust decision making and prediction after which It is tested well Q eight. You would then take that model and deploy it at the edge. Yeah. And then at the edges is essentially just looking at new data, applying it to the model, you're you're trained and then that model will give you a prediction decision. Right? So uh it is these three stages. Yeah, but more and more uh you know, your question reminds me that more and more people are thinking as the edge become more and more powerful. Can you also do learning at the edge? Right. That's the reason why we spoke about swarm learning the last time, learning at the edge as a swamp, right? Because maybe individually they may not have enough power to do so. But as a swampy me, >>is that learning from the edge or learning at the edge? In other words? Yes. Yeah. Question Yeah. >>That's a great question. That's a great question. Right? So uh the quick answer is learning at the edge, right? Uh and also from the edge, but the main goal, right? The goal is to learn at the edge so that you don't have to move the data that the Edge sees first back to the cloud or the core to do the learning because that would be the reason. One of the main reasons why you want to learn at the edge, right? Uh So so that you don't need to have to send all that data back and assemble it back from all the different edge devices, assemble it back to the cloud side to to do the learning right? With swampland. You can learn it and keep the data at the edge and learn at that point. >>And then maybe only selectively send the autonomous vehicle example you gave us. Great because maybe there, you know, there may be only persisting, they're not persisting data that is inclement weather or when a deer runs across the front and then maybe they they do that and then they send that smaller data set back and maybe that's where it's modelling done. But the rest can be done at the edges. It's a new world that's coming down. Let me ask you a question, is there a limit to what data should be collected and how it should be collected? >>That's a great question again. You know uh wow today, full of these uh insightful questions that actually touches on the second challenge. Right? How do we uh in order to thrive in this new age of inside? The second challenge is are you know the is our future challenge, right? What do we do for our future? And and in there is uh the statement we make is we have to focus on collecting data strategically for the future of our enterprise. And within that I talk about what to collect right? When to organize it when you collect and then where will your data be, you know going forward that you are collecting from? So what, when and where for the what data for the what data to collect? That? That was the question you ask. Um it's it's a question that different industries have to ask themselves because it will vary, right? Um let me give you the you use the autonomous car example, let me use that. And you have this customer collecting massive amounts of data. You know, we're talking about 10 petabytes a day from the fleet of their cars. And these are not production autonomous cars, right? These are training autonomous cars collecting data so they can train and eventually deploy commercial cars, right? Um so this data collection cars they collect as a fleet of them collect temporal bikes a day. And when it came to us building a storage system to store all of that data, they realized they don't want to afford to store all of it. Now, here comes the dilemma, right? What should I after I spent so much effort building all these cars and sensors and collecting data, I've now decide what to delete. That's a dilemma right now in working with them on this process of trimming down what they collected. You know, I'm constantly reminded of the sixties and seventies, right? To remind myself 60 and seventies, we call a large part of our D. N. A junk DNA. Today. We realize that a large part of that what we call john has function as valuable function. They are not jeans, but they regulate the function of jeans, you know, So, so what's jump in the yesterday could be valuable today or what's junk today could be valuable tomorrow, Right? So, so there's this tension going on right between you decided not wanting to afford to store everything that you can get your hands on. But on the other hand, you you know, you worry you you you ignore the wrong ones, right? You can see this tension in our customers, right? And it depends on industry here, right? In health care, they say I have no choice. I I want it. All right. One very insightful point brought up by one health care provider that really touched me was, you know, we are not we don't only care. Of course we care a lot. We care a lot about the people we are caring for, right? But you also care for the people were not caring for. How do we find them? Mhm. Right. And that therefore, they did not just need to collect data. That is that they have with from their patients. They also need to reach out right to outside data so that they can figure out who they are not caring for, right? So they want it all. So I tell us them, so what do you do with funding if you want it all? They say they have no choice but to figure out a way to fund it and perhaps monetization of what they have now is the way to come around and find that. Of course they also come back to us rightfully that you know, we have to then work out a way to help them build that system, you know? So that's health care, right? And and if you go to other industries like banking, they say they can't afford to keep them off, but they are regulated, seems like healthcare, they are regulated as to uh privacy and such. Like so many examples different industries having different needs, but different approaches to how what they collect. But there is this constant tension between um you perhaps deciding not wanting to fund all of that uh all that you can store, right? But on the other hand, you know, if you if you kind of don't want to afford it and decide not to store some uh if he does some become highly valuable in the future, right? Yeah. >>We can make some assumptions about the future, can't we? I mean, we know there's gonna be a lot more data than than we've ever seen before. We know that we know well notwithstanding supply constraints on things like nand. We know the prices of storage is going to continue to decline. We also know, and not a lot of people are really talking about this but the processing power but he says moore's law is dead okay. It's waning. But the processing power when you combine the Cpus and NP US and GPUS and accelerators and and so forth actually is is increasing. And so when you think about these use cases at the edge, you're going to have much more processing power, you're gonna have cheaper storage and it's going to be less expensive processing And so as an ai practitioner, what can you do with that? >>Yeah, it's highly again, another insightful questions that we touched on our keynote and that that goes up to the why I do the where? Right, When will your data be? Right. We have one estimate that says that by next year there will be 55 billion connected devices out there. Right. 55 billion. Right. What's the population of the world? Of the other? Of 10 billion? But this thing is 55 billion. Right? Uh and many of them, most of them can collect data. So what do you what do you do? Right. Um So the amount of data that's gonna come in, it's gonna weigh exceed right? Our drop in storage costs are increasing computer power. Right? So what's the answer? Right. So, so the the answer must be knowing that we don't and and even the drop in price and increase in bandwidth, it will overwhelm the increased five G will overwhelm five G. Right? Given amount 55 billion of them collecting. Right? So, the answer must be that there might need to be a balance between you needing to bring all that data from the 55 billion devices of data back to a central as a bunch of central Cause because you may not be able to afford to do that firstly band with even with five G. M and and SD when you'll still be too expensive given the number of devices out there. Were you given storage cause dropping will still be too expensive to try and store them all. So the answer must be to start at least to mitigate the problem to some leave both a lot of the data out there. Right? And only send back the pertinent ones as you said before. But then if you did that, then how are we gonna do machine learning at the core and the cloud side? If you don't have all the data you want rich data to train with. Right? Some sometimes you want a mix of the uh positive type data and the negative type data so you can train the machine in a more balanced way. So the answer must be eventually right. As we move forward with these huge number of devices out of the edge to do machine learning at the edge. Today, we don't have enough power. Right? The edge typically is characterized by a lower uh, energy capability and therefore lower compute power. But soon, you know, even with lower energy, they can do more with compute power improving in energy efficiency, Right? Uh, so learning at the edge today, we do influence at the edge. So we data model deploy and you do influence at the age, that's what we do today. But more and more, I believe, given a massive amount of data at the edge, you you have to have to start doing machine learning at the edge. And and if when you don't have enough power, then you aggregate multiple devices, compute power into a swamp and learn as a swan, >>interesting. So now, of course, if I were sitting and fly on the wall in HP board meeting, I said, okay, HP is as a leading provider of compute, how do you take advantage of that? I mean, we're going, I know it's future, but you must be thinking about that and participating in those markets. I know today you are you have, you know, edge line and other products. But there's it seems to me that it's it's not the general purpose that we've known in the past. It's a new type of specialized computing. How are you thinking about participating in that >>opportunity for your customers? Uh the world will have to have a balance right? Where today the default, Well, the more common mode is to collect the data from the edge and train at uh at some centralized location or a number of centralized location um going forward. Given the proliferation of the edge devices, we'll need a balance. We need both. We need capability at the cloud side. Right. And it has to be hybrid. And then we need capability on the edge side. Yeah. That they want to build systems that that on one hand, uh is uh edge adapted, right? Meaning the environmentally adapted because the edge different they are on a lot of times on the outside. Uh They need to be packaging adapted and also power adapted, right? Because typically many of these devices are battery powered. Right? Um so you have to build systems that adapt to it, but at the same time they must not be custom. That's my belief. They must be using standard processes and standard operating system so that they can run rich a set of applications. So yes. Um that's that's also the insightful for that Antonio announced in 2018, Uh the next four years from 2018, right, $4 billion dollars invested to strengthen our edge portfolio, edge product lines, right Edge solutions. >>I get a doctor go. I could go on for hours with you. You're you're just such a great guest. Let's close what are you most excited about in the future of of of it? Certainly H. P. E. But the industry in general. >>Yeah I think the excitement is uh the customers right? The diversity of customers and and the diversity in a way they have approached their different problems with data strategy. So the excitement is around data strategy right? Just like you know uh you know the the statement made was was so was profound. Right? Um And Antonio said we are in the age of insight powered by data. That's the first line right? The line that comes after that is as such were becoming more and more data centric with data the currency. Now the next step is even more profound. That is um you know we are going as far as saying that you know um data should not be treated as cost anymore. No right. But instead as an investment in a new asset class called data with value on our balance sheet, this is a this is a step change right in thinking that is going to change the way we look at data the way we value it. So that's a statement that this is the exciting thing because because for for me a city of AI right uh machine is only as intelligent as the data you feed it with. Data is a source of the machine learning to be intelligent. So so that's that's why when when people start to value data right? And and and say that it is an investment when we collect it. It is very positive for ai because an Ai system gets intelligent, more intelligence because it has a huge amounts of data and the diversity of data. So it'd be great if the community values values data. Well >>you certainly see it in the valuations of many companies these days. Um and I think increasingly you see it on the income statement, you know data products and people monetizing data services and maybe eventually you'll see it in the in the balance. You know Doug Laney when he was a gardener group wrote a book about this and a lot of people are thinking about it. That's a big change isn't it? Dr >>yeah. Question is is the process and methods evaluation. Right. But uh I believe we'll get there, we need to get started then we'll get their belief >>doctor goes on and >>pleasure. And yeah and then the yeah I will will will will benefit greatly from it. >>Oh yeah, no doubt people will better understand how to align you know, some of these technology investments, Doctor goes great to see you again. Thanks so much for coming back in the cube. It's been a real pleasure. >>Yes. A system. It's only as smart as the data you feed it with. >>Excellent. We'll leave it there. Thank you for spending some time with us and keep it right there for more great interviews from HP discover 21. This is dave a lot for the cube. The leader in enterprise tech coverage right back.

>>Welcome >>back to HP discover 2021. My name is Dave Volonte and you're watching the cubes virtual coverage of discover 21 we're excited to welcome back our wa Kadoura, She's the vice president and worldwide go to market leader for HP. Es smoking hot. Green Lake Cloud services are welcome back to the cube. Good to see you again. >>Thank you for having me to be with you. >>So talk about how your products and services are supporting customer transformations. I'm interested in the experience that everybody has been dreaming about describe how you're giving your customer that competitive advantage. If you've got any examples, that would be awesome. >>Yeah, you got it. Um, I think as we heard Antonio say the cloud is an experience, not a destination, right? And what we're doing with Green Lake is bringing those cloud capabilities and the cloud experience to our customers. You know, we like to say co locations, data center and edge of course. So this is the cloud on prem. And so rather than forcing customers to only have to go up to cloud to get modern cloud capabilities or the benefits of things like, you know, pay as you go for consumption, et cetera. You know, cloud native capabilities like containers, leveraging, kubernetes. We now bring all of that to Green Lake and to our customers. Edge locations and co locations and data centers. We've been able to dramatically transform many of our customers businesses. Right? And you'll probably see it discover some of those examples come to life. For example, Care Stream, who is, you know, in the electronic medical imaging world, Right? They have all of the X ray equipment that capture x rays and different sort of diagnostics for patients. Um and we worked with them to not only craft a ml solution to better read and diagnose these images, um but also all of the underlying infrastructure with the HP Green Lake Ml ops platform that allows them to instantly leverage the capabilities of machine learning and the infrastructure to go with it. >>And so tell me, so, how is it resonating with customers? What you're out there, talking to customers all the time? What are they >>telling you? You know, I think what our customers appreciate about HP Green Lake is it's not sort of look, it's either all on prem in my data center and I have to fully manage it, build it, implement it, take care of it or it's fully public cloud. I have little control and basically I get whatever the public cloud gives me right. Hp Green leg gives our customers the flexibility and control that they require. Right. And so you can think of many use cases where customers have a need to have the compute storage sort of processing need to happen closer to where their data and apps live. Um and so for that exact reason our customers love the flexibility, right? Cloud one, Dato was public cloud. Cloud to Dato I think is the cloud that comes to our customers at their convenience. And to me, you know what I tell C I O S and C T O S and sort of other lines of business leaders when I meet with them is you shouldn't be forced to have to take your data and apps elsewhere to get the transformation that you need. We want to be able to bring that directly to our customers. >>Of course, a lot of the transformation is around data. We love talking about data on the cube and it's funny, I mean we talked about big data last decade. We don't use that term much anymore. Uh It was kind of overhyped but as as often times as the case may be in the early days it's overhyped but then it's under hyped when it actually starts to kick in. And I feel like we're entering a new age of data. And insights with the ascendancy of machine learning and ai what does this mean from H. P. S. Perspective and what our customers telling you that it means for them. >>Yeah no data. I think we often hear data is the new currency writes the new gold. Um You know we've heard uh Antonio even say things like look data could even become something that maybe over time companies start to put some kind of value on their balance sheet. Behind right the same way that maybe brands represented this value on a balance sheet. Um effectively what's happened with data is a lot of people have a lot of data but there's not been a lot of ability to extract insights from data. Right? And I think this is the new revolution that we're all undergoing is we finally have the modern analytics tools to actually turn the data into insights and what we bring to the table from an HPD perspective is the fact that we have the best infrastructure. We obviously now have the cloud capabilities mixed in with our data fabric or container platform, our machine learning operations platform to then be able to process that data again, integrated with many of the great I SV partners that we have on the data side allow our customers to turn that into real insights for their business. And effectively data is becoming a huge competitive advantage. Right? I think many of us are you know, leveraging some, you know, pretty interesting tools or gadgets these days, right? Like I wear one of those, you know, sleep brings, you can imagine a company like that in the future that's able to collect so much data from the folks that purchase their products. Then being able to give us insights about, you know, where is the best zip code that, you know, people get the most amount of sleep in or you know, which zip codes are the healthiest and you know, the United States or countries, et cetera. Um but data really is becoming um you know, a competitive advantage. And one of the things that we care most about at HP is also using it as a force for good and making sure that there is a sort of ethical ai capability. >>That's a great message and very important one. And and it's interesting you're saying about data and the value how well it's clearly it's clearly being valued in terms of companies market caps. I mean it's it's it's you know, maybe it's not the balance yet, but it's on the income statement in terms of data products and data services that that's happening. So we'll see if Antonio's right in the next, you know, several years. But so let's talk more about the specific data challenges that you're solving for your customers. They talk about silos, they talk about they haven't got as much value out of their data initiatives as they wanted to. What are they telling you? Are there challenges and how are you approaching it? >>Yeah, I think, you know, um data's everywhere right. The ability for customers to store the right amount of data is a huge challenge because obviously there's, you know, a huge cost associated with collecting, keeping cleansing processing, you know, all the way to sort of analyzing your data. There tends to be a ton of data silos, right? So customers are looking for a common data fabric that they can then process their data sources across and then be able to sort of tap into that data from an analytics perspective. So much of the technology again that we're focused on is be able to store the data right, Our data fabric layer with his moral right being able to process that data capture that data and then allow the analytics tools to then harness the power of that data and turn that into real business insights for our customers. Um Every customer that I have spoken to, you know whether their financial services, you know, you can imagine the big financial services. I mean they've got you know, just bazillions of pockets of data everywhere and you know, the real sort of a challenge for them is how do I build a common data platform that allows me to tap into that data in effective ways for my business users? >>You talk a little bit about how you're changing the way you're providing solutions? Maybe maybe you could contrast it with the way HP has done in the past, because I think that's important when you, when you think about, you talk a lot about green lake and as a service, but if the products are still, you know, kind of boxes and Luns and, and gigahertz and ports, then, you know, that's that's a dis continuity. So what's changed from the past and how are you feeding into the way customers are transforming their business and supporting their outcomes? >>That's exactly right. You know, at some point in time, right. If you think maybe 10 or 20 years back, it used to be very much about the infrastructure for hp. What's exciting about what we're doing differently for our customers is look, we have the best infrastructure in the business, right. Hp has been doing this you no longer than anyone has probably almost 60 years now. Um but being able to vertically integrate right, move up in that value change so that our customers can get more complete solutions is the more interesting part for our customers. Our customers love our technology, Yes, the gigahertz and the speeds and feeds all of that do matter because they, you know, make for some very powerful infrastructure. However, what makes it easier is the fact that we are building platform stacks on top of that hardware, um that help abstract away the complexity of that infrastructure and the ability to use it far more seamlessly. Um and then if you think about it, we of course have also one of the most advanced services organizations. So being able to leverage our services capabilities, our platform capabilities on top of that hardware, again, deliver it back to our customers In a consumption model, which they've become two X, which they've come to expect from a cloud model. Um and then surrounded by a very rich ecosystem of partners. And we're talking about system Integrators that now have capabilities on helping our customers run their Green Lake environments. We're talking about I. S. V. S. Right? So software stacks and platforms that fully integrate with the Green Lake platform for completely seamless solutions. Um as well as channel Partners and global distributors. So I think that's where we can truly deliver the ultimate end to end solution. It's not just the hardware, right? But it's being complemented with the right services being complemented with the right platform capabilities, the software integrations to deliver that workload that the customer expects. >>And partners, they gotta they gotta place bets, they gonna put resources time money in a line, their resources with with their their partners and their suppliers like HP. So when they ask you, hey, okay. Hp. Tell me or well, what's your overall strategy? Why is it compelling and why do you give me competitive advantage relative to some of your peers in the industry? >>Yeah, I think what, you know, partners are going to be most excited about is the openness of the platform, right? Being able to allow our partners to leverage Green Lake Central with open API so that they can integrate some of their own technologies into our platform. Uh the ability to allow them to also layer in their own um managed services on top of the platform is key. Um And of course being able to build sort of these win win solutions with the system Integrators, right. The system Integrators have some fantastic capabilities all the way from an application development, all the way down to the infrastructure management and data center delivery centers that they have. And so leveraging HP Green Lake um really helps them have access to core technologies that they need to deliver these solutions. >>I wonder if I could take a little sort of side road here and ask you because so many changes going on HP itself is transforming your customers are transforming the pandemic has accelerated all these transformations. Can you talk a little bit about how you've transformed go to market specifically in the context of of as a service? I mean that had to be quite a change for you guys. >>Yeah, no, go to market transformations in support of sort of moving from traditional go to markets right to call, go to markets or significant. Um They required us to really think through what does delivering as a service solutions mean for our direct sales force? What does it mean for our partners and their transformations and being able to support as a service solutions? Um for HP specifically, it also means um thinking about our customer outcomes, not just our ability to ship them, you know, the requisite hardware and say, look, once it's left our dog, our job is done right. It really takes our obligation all the way to the customer using the technology on a day by day basis, as well as supporting them in making sure that everything from implementation to set up to the ongoing monitoring operations of the technology is working for them in the way that they expect in an as a service way, right? We don't expect them to operate it. We don't expect them to, you know, do anything more than pick up the phone and call us if something doesn't go as planned. >>And how about your sellers and your partners? How did they respond? I mean you just wake up one day is okay guys, here we go, new compensation scheme, new way to sell new way to market that that took some thought in some time. And where are you in that journey? >>That's right. And I always say, you know, if you expect people to wake up one day and be transformed, right? You're kidding yourself. Um So everything from sort of the way that we think about our customers use cases, right? And empowering our sellers to understand the outcomes that our customers expect and demand from us to things like compensation too. You know, the partner rebate program that we leverage through the channel partners in order to give them the right incentives to also allow them to make the right investments to support Green Lake. Um, you know, we've all, you know, HP has a fairly significant field sales and solution team and so not thinking about this only as a single person that represents Green Lake, but looking at our capabilities across the board, right. We have fantastic advisory consultants on the ground with phds and data science. We have folks that understand, you know, high performance computing, so making sure that we're embedding the expertise in all of the right personas that support our customers, not just from a calm perspective, but also from an understanding of the end to end solutions that we're bringing to those markets. >>So what gets you stoked in the morning, you get out of bed and you're like, okay, I'm gonna go attack the world. What are you most excited about for H P E and his future? >>You know, it's, there's so much happening right now in this sort of cloud world. Right? Um to me the most exciting portion is the fact that given that we've now introduced on prem cloud to the world, our ability to ship new services and new capabilities, um, but also do that via a very rich partner ecosystem honestly is what probably has me most excited. This is no longer the age of go at it alone, Right. So not only are engineering and product teams hard at work in the engine room producing, you know, capabilities at sort of lightening fast speeds, but it's also our ability to partner, uh you know, whether it's with platform providers, you know, software providers or, you know, system Integrators and services providers, that ecosystem is starting to come together to deliver highly meaningful solutions to our customers and all in a very open way. Um, the number one thing that I personally care about is that our customers never feel like they are being locked in or that they are sort of being forced to have to give up certain levels of capabilities. We want to give them the best of what's out there and allow them to then have that flexibility in their solution. >>And one of the challenges, of course with virtual events is you don't have the hallway track. You know, somebody can't say, hey, have you seen that IOT zone? It's amazing. They got all these robots going around. But so what, what would you say that people should be focused on the discovery maybe things that you want to call out specific highlights or segments that you think are relevant? >>Yeah, there's gonna be a ton of fantastic stuff I think, um you know, really looking for that edge to cloud strategy, um that we're gonna be spending a lot of time talking about um looking at some of our vertical workload solutions, right. We're gonna be talking about quite a few from electronic health care records to payment solutions. Um and many more I think depending on what folks are interested in, there's gonna be something for everyone. Um Project Aurora, which now starts to announce our new security capabilities. Um, you know, the zero trust capabilities that we're delivering um is probably interesting to a lot of our customers, so lots of exciting things coming and I'm excited for our customers to check this out. >>No doubt that's a hot topic. Especially given what's been happening the news these past several months. All right, well, thanks so much for coming back in. The cube is great to see you hopefully face to face next time. >>I sure hope so. Thanks so much for having me. >>It's our pleasure. And thank you for watching and thank you for being with us and our ongoing coverage of HPD discovered 2021. This is Dave Volonte. You're watching the cube, The leader and digital tech coverage. >>Yeah.

>> Narrator: From around the globe, it's theCUBE, with digital coverage of IBM Think 2021 brought to you by IBM. >> Welcome to theCUBEs coverage of IBM Think 2021. I'm Lisa Martin. Exciting conversation coming up about in vaccine cloud management. I've got two guests with me, Tim Elcott is here, the sales and delivery director of IBM services for Salesforce and Fran Thompson joins us as well, the CEO of the Health Service Executive in Ireland. Gentlemen, welcome to the program. >> Hi, there. >> Hi. >> Good to be here. >> So we're very socially distance, Northern California, UK. Glad to have you guys here. We're going to talk about what the Health Service Executive or HSE in Ireland has done with IBM and Salesforce to facilitate vaccine management. But Fran, let's go ahead and start with you, talk to us a little bit about HSE. >> Well, the HSE provides public health and social services to everyone living in Ireland, okay. We got Acute hospitals, community services nationally. We directly employ about 80,000 people and we formed a farther about 40,000 people. And our annual budget is slightly North of 21.6 billion a year. We are the largest employer in the state and the largest organizations in the state. And, you know, we provide a huge range of services right across the whole spectrum. And we also formed other organizations who provide those services as well. So we would fund some voluntary and charity organizations and we would also buy services from the likes of say GP and other organizations as well. >> So talk to me about a year or so ago when the pandemic hit what were some of the challenges that HSE faced? And then when it came time to, we have a vaccine, we have multiple vaccines that rollout capability what were some of the challenges that you faced initially? >> So from an organizational perspective, there were huge challenges in that we were like every other health service worldwide facing an enormous pandemic that was impacting on people. And this is all about people, it's all about people's lives at the end of the day. People can talk about numbers and they can talk about costs and they can talk about other elements but at the end of the day this is about individual, people's lives, their families and their communities. And for the HSE, our challenge was really about how do we manage to protect the totality of the population in Ireland, as much as we can from the ravages of the virus. And the initial challenge we had was around contact tracing and managing that before a vaccine became available. And once the vaccine became available it was then how do we stand up a national vaccine solution that we would be able to deliver and record vaccines to the totality of the population who were getting a vaccine. >> Yeah, so there was no preexisting vaccination program of course, probably in most places you needed to get healthcare workers vaccinated ASAP and it's also needed to be a national program. So what did you do next after determining all right, we need to work with some partners to be able to build technology to facilitate equitable efficient rollout of the vaccine? >> So we did have regional vaccine systems and we do have a number of vaccine programs out there that were managing flu vaccine, Hep C vaccine, but we didn't have a national program and we needed to vaccinate people immediately. And we also wanted to make sure that vaccine program was not dependent on the HSE infrastructure, because we want to be able to vaccinate people in non HSE sites, and we wanted non HSE staff to be able to vaccinate. And we didn't want a huge pre-dependence on our existing infrastructure. So the first thing we did, we looked at a number of vendors and we chose IBM as our partner with Salesforce. And that partnership is really a strategic partnership and it's a partnership that we worked to all the bumps and all the lumps through the program together and there have been challenges but like it's still working with Tim and his team and to our team that we've overcome some of those challenges. And like, when we started off I remember the very first conversation I had with Tim he said, "Look, we need to vaccinate healthcare workers now, okay? And you've got two weeks to start and we need to configure a system, get it up and running and to be able to roll it out to the hospitals and very quickly then to all of our nursing care homes now" and that was the challenge. >> And let's bring Tim in, and this is a radically quick project from MPV to roll out in two weeks. Tim talk to us first about the IBM partnership with Salesforce and what you're building together. >> Absolutely, it's great and Fran it's interesting to hear you speaking about the running into this, 'cause from my perspective a week before we all started this we had a simple conversation called into the Health Service Executive they're talking about some vaccination program how can we help? And then within a week, we've gone from zero to having how many calls with Fran and team just to understand and with the Salesforce team to really understand how the three parties can bring the best of IBM, the best of Salesforce and the best of HSE in terms of the adaptability and what we need to get done to get those vaccinations up and running for the healthcare workers now. When Fran said to me, "We need something in two weeks." There was absolutely clarity, if you can't do it in two weeks there's the door, right? So we knew exactly the challenge and that's the kind of thing right before Christmas that we were so fortunate to really bring in the team, like everyone you think about this, everyone has probably the 14th of December was thinking of winding down, thinking of having their Christmas holidays and vacation time. And everybody from the Irish team and from the English team said, "No, we will cancel Christmas, we will cancel everything." So is it really Christmas came early and Christmas was canceled all at once. So, and the key bit here, the strategic partnership is IBM and Salesforce have been working together for years and years and years growing out a partnership. We know their products really well, we've got huge capability in that space. But actually with the new health cloud part of it the vaccine management parts are quite new to Salesforce as well only launched back in sort of the August, September time. So it's quite new. So we had to go in together as a sort of a partnership there to say, "Did you get this done?" So we had the best people from Salesforce who know the product, the best people from IBM all turning up on the 14th of December and saying, "Right, we've got to get this done by the 29th, with Christmas holidays in the way, the vacation time in the way." I think we had 36 hours of time off to eat turkey and fill ourselves before getting back to the wheel and really getting this done. And to get I think it was four acute hospitals we went into as of the 29th to start the vaccination program. So trying to do that, understanding everything is a compromise at that point. Yeah, but it has to be secure, you know this is personal data going into these systems. So you can't forget about all the aspects it's got as minimum, but minimum with those kinds of constraints as a health system. So it needs to be secure, it needs to also be that national platform going forwards as well. So basing on a great platform like Salesforce, you know you can scale out, you know you've got those options to grow in the future, but yeah, not without a lot of challenge and then working out what's now getting to know each other, but if we only talked about twice before we ever know each other pretty well now. But just trying to work out how we then structure what's going to happen every two weeks afterwards, how's that going to move forward? We're going live every two weeks and we have done that now for the last three months, so, good fun. >> So, yeah, good fun. But so much work to get done and accord a huge coordinated effort in a very short time period during a very challenging time. Talk to me a little bit about Fran but you launched this Vaccine Cloud Management in January, 2021. And to date, I think you told me 1 million people have been vaccinated so far. Talk to me about what the IBM, Salesforce solution enables you to deliver to the HSE and to the Irish citizens. >> So we have delivered a million vaccines, okay in two stages. The dose one, the dose two for most people in Ireland. And there's about 720,000 people got their dose one and the balance have got the dose two. That's about sort of just about one in five of the population that has to be vaccinated. And one of things we were very conscious of is that as an organization like that we need to take a risk based approach to this. So we need to look at the most vulnerable groups there were lots of people who were dying from this. And a lot of people were elderly groups, and people who were vulnerable with pre medical conditions. So our challenge was how do we vaccinate those people quickly and effectively and also vaccinate healthcare workers who are going to care for these people. And that's where we prioritize the work. So we have to go into 50 acute sites about 600 or so care homes, we set up a lot of what we call pop-up clinics literally a tent in a location, or we took over a sports hall or whatever we did. We rolled it out to the GP so about two and a half thousand GP sites. And all of that was being done while we were building the system. So we were building the system and designing a system on two week sprints. We have to be agile, we have to be quick, we had to make huge compromises and we know that. Though I hate to admit it everyone wants a perfect system, which will make the compromise and look into what do you need to do now to keep the program running? And how you manage that with about 3,000 users all to be set up fairly quickly or a little over half thousand users. So you have to manage all that as you're going through everything. >> I think agile is the name of the game here. Tim, talk to us about how you're delivering the agility in such a tenuous time. >> Well, we're all virtual, which is added to the mix. But the funny thing with that agility we've got a span of people across all the countries and everywhere that we can bring in to that party. And yeah, we're running what I would call a normal agile project, except normally it would take two, three months to really get that team working effectively, getting to know each other and we just not had time to do that. So there's been a core team here and we're bringing in the experts around it but really just everything is working with Fran, worked very hand in glove trying just to work out, what we need to do here, to look at the next sprint to look at the next go live, to look at the compromise. How do we compromise for two weeks? What can we live with for two weeks? What's in the backlog for now and Fran and I have many conversations. What do we need to do this week and then what's next week? And that's level of fluidity and that's in part because of the way the pandemics and the response of pandemic is mapping out. As we saw the vaccines are changing, availability is changing, the rollout plan is changing. None of us have worked through a pandemic before. So agility is the name of the game at the highest level. I think we're all now very used to being, sorry there's a problem something's changed, can we adapt the system too, you know, and normally in a sprint I'll be thinking, I've got some fixed requirements for two weeks, I'll build that and then do the next two weeks. Everything is up for grabs and we're just having to maintain quality at the pace, the responsiveness and balancing it all as an IBM team and you think. And whilst we're also doing that on a platform that it takes time to configure and build these things as well. So it's some of it is you're going to have to wait a few days. So we're sorry, you know, a few days is really the probably sometimes the maximum amount of time that can be you can defer, but as Fran and everyone in the HSE and the National Immunization Office, everyone's pragmatic about realizing we're all in this together and it's really just being one single team, one unit working out and very open and transparent about the odds that are possible. >> And when doing something... Go ahead, Fran. >> We had a phrase there like there was a pieces we just had, "Just do it now." And we did a lot of that, okay? You know, where there were things that were prioritized were in the middle of a sprint, there were changes in the program or there were changes in how the vaccination was going to be delivered. And we couldn't waste the week just wasn't available. So we have the thing just got to do it now. And Tim and the team they'll drop what they were doing you know, made the changes, we tested them fast and we pulled them in and then gave us an extra time to actually then deliver the rest of the sprint. We have to do that several occasions, several very, very late night delivers. >> And I imagine that's still going on, but to wrap here guys, an amazing work that you've done together so far with the Salesforce Vaccine Club Management rolling out across the HSE you said 1 million vaccinations delivered many hundreds of thousands in the queue. I'm sure more iterative work and sleepless nights but what you're doing for the country of Ireland is literally as Fran said in the beginning, lifesaving. Gentlemen, thank you so much for joining me today on the program. >> You're welcome, thank you. >> You're very welcome. Thank you. >> From Tim and Fran I'm Lisa Martin. You're watching theCUBEs coverage of IBM Think 2021. (upbeat music)

(Upbeat music) >> Okay, welcome back everyone, to theCUBE's Coverage of Red Hat Summit 2021 virtual I'm John Furrier, your host of theCUBE got two great guests from Deloitte Consulting Dave Knight who manages the Red Hat Relationship, Lee he's the lead there, and Mike Bourgeois who's the Public Sector Managing Director both from Deloitte Consulting LLP official name. Guys, great to come on, and we were just talking before camera about all the stories. Great to have you on theCUBE, thanks for coming on. >> Yeah, thanks for having me. >> Like I said we were just talking about all the stories from the transition from pre-COVID, COVID. Now we've got a view into post-COVID. I want to dig into that 'cause there's a lot of things happening. You guys have been in the trenches, front lines bringing solutions, but before we get into that, can you guys just introduce yourself share your roles at Deloitte and give us a quick overview of what you work on. >> Yeah, so again, thanks for having us John Dave Knight I'm a solution architect and Global Red Hat Alliance Manager for Deloitte. I've got responsibility for making sure that play nicely in the sandbox together or we've got a joint customer and solutions to deliver to those customers. >> Hi everyone, thanks for having us John, I'm a Managing Director Mike Bushwa out of Boston Texas. I am coming up on year 20 and Public Sector Consulting. My area of expertise is large state government systems that serve the needs of millions of citizens and thousands of state workers, good to be here. >> Yeah. Great to have you. And I wanted to chime in with you right away because Mike you are living in probably one of the hottest markets Public Sector. I've been following that for many, many years, generations actually from the early computer industry GSA contracts, all these contracts you've got all the Public Sector, they move very slowly but now the pandemic, there was no place to hide. Everything got pulled back, disruption, you can't just shut down critical infrastructure and critical services. People had to move fast. What was your experience and how is it now give us a taste of some of the challenges and the landscape. >> You bet John, so we talked a little bit before we started this, but my 20 year consulting career, I can't think of anything really in close to this, other than maybe Y2K and as Dave mentioned the Affordable Care Act Legislation in 2009, though that was a much smaller scale as it turned out to be. So I would be remiss not to share examples of extraordinary challenges our clients have had related to the pandemic. Department of Labor and Health and Human Service Agencies for example, responded to the pandemic in rapid timeframe that were rarely seen in government. Citizens that were used to coming in appealed offices, We're now required to do most things virtually. Deloitte has been privileged to assist clients with digital solutions across the country in response to this unprecedented event. And so I'd like to share just a couple of examples. The first is for Department of Labor, the pandemic contributed to millions of layoffs throughout the country Department of Labor workers found called volumes increasing by a 1000% in some cases, the amount of increased volume required agencies across the country hire temporary workers to help out. Millions of new unemployment claims needed to be filed in benefits rapidly provided to citizens of name. So the big challenge was the agency had to figure out how to rapidly file claims into the unemployment system, rather than requiring new citizens to use an external web application they were really unfamiliar, the agency needed more efficient approach. The approach we used was to create an internal web application that enabled workers to file unemployment insurance claims on behalf of citizens. Workers collected the necessary data from citizens and claims were filed into the system. The application enabled workers to focus on filing claims rather than sort of a technical support role showing how to people use an external web application. More citizen were served in much less time, claims are filed efficiently by train workers which resulted in benefits being received in a much more timely fashion. And so a second example is, with Department of Human Services. So one stay as mentioned Citizens were used to going into field offices but suddenly they were told you can't come into the field office. So once they provided a 100% virtual application and the important part here is certification solution for the Disaster Supplemental Nutrition Assistance Program or DSNAP for short. this application was stood up in two weeks, families who needed food assistance can now apply and be certified for benefits remotely. Today over 50,000 cases have certified and citizens receiving food nutrition assistance. Back to you John. >> So, I mean obviously there's some great use cases you got, basically I got to work at home, new architecture there you got to have a new workflows. I mean, this poses some real challenges. How did you guys put it together? I mean, Dave take us through where this all fits in with the Red Hat, because obviously now it's new deployment new capabilities have to be deployed for the pandemic. How does this bring together the partnership with Red Hat? >> Yeah, so great question and it really plays to the strength of both Deloitte and Red Hat, right? The success stories that Mike has illustrated show how we can quickly pivot as a firm to delivering these types of solutions and help our customers think through innovative ways to solve the problems. So, I mean the prime example that Mike just gave, everything used to be done in offices. Now it's all done remotely cause you can't go to the office even if you want to. And that is very much aligned with the innovation we get with our partnership with Red Hat, right? They've led the way in open source and some of the technologies that we've leveraged that our solutions include, answerable for automation, some of the middleware products, and I would say one of the cornerstones is the OpenShift Platform. Now that allows us to greatly accelerate the development and delivery of those solutions to our customers. Sort of again, aligning our innovative thinking with Red Hats Innovative Technologies. >> What would you say if someone said, "what's the partnership strengths and what needs specifically are you addressing with customers and customer needs?" >> So I, again, I think our lean towards innovation is a common thread across both firms and where we have our greatest strength. We like to take our customers on a journey but it's not our journey, it's their journey, right? So we help them figure out where they want to go and how they want to get there in a way that aligns with their business goals, their budgets all the sort of factors that drive those things and Red Hat is very open to that approach. They sort of invented the crowdsourcing of open source they made it into a business model. They've developed that from literally nothing. And that aligns very nicely with us. That's one of the key strengths. We also are firm believers in open source again to the degree that our customers like the leverage that to drive their journeys. And we're seeing that, especially in the Public Sector Space as being a key driver of the technologies they employ. >> Mike, I want to come back to you on this open ma component open question, open source, open to technology open innovation out in the open as Red Hat calls it. How does Red Hat open source software, address the needs for your customers for security and on-premise considerations. >> I'll talk a little bit about open source principles in general still the open source principles of transparency meritocracy community problem solving and collaboration. These are on its of both software innovation as well as organizational transformation. One of the highest demand transformation needs that I'm seeing in the market is the desire to adopt innovative technology, and most importantly, moving workloads to the cloud. It's no longer a thought, it is an imperative moving workloads to the cloud, on new deals hosted in the cloud, on an existing, is it large systems let Deloitte help us get to the cloud. So I believe the key to success embracing the cloud is recognizing first the need for change in people, processes and technology. The vehicle for this transformation is DevSecOps and innovative open source platforms, such as the OpenShift platform that Dave mentioned. OpenShift focuses on people, processes and technology and the security conversation becomes even easier. I mean, I see Linux was around for years, and we've always used Linux on our Java based workloads now we can have the conversation about saying, Hey, well that se Linux operating system we've been using for years now, there's this really cool Container Management Platform that we can solve real problems like auto scaling, in my Health and Human Services career, I can remember every year when open enrollment comes around systems engineers are teed up, and ready to manually add those to a BMR cluster or something like that. Well, now we don't have to do these things. We can rely on Kubernetes so auto scale, and then and get rid of those instances when workload demands seven resolved. So it's a really cool technology kind of behind the scenes. It's not the dog and pony show sometimes but in the end it helps the clients and Deloitte remain consistent with those service level agreements. >> That's a great example about the open enrollment illustrates the fact that, you got to provision more stuff to take that load on it. It's always hard in Public Sector you might not have the speed. So I got to follow up and ask you, you guys have had wins in the Public Sector lately with Red Hat, you guys Deloitte and Red Hat working together and get some wins under your belt, on around cloud and cloud and technology obviously with the pandemic has needs there. Are you guys seeing any particular sector challenges specifically around Public Sector as it goes this next level a lot of modernization happening we're seeing that, but any challenges that you're seeing, can you give some examples of how these challenges are being addressed? First talk about the challenges and then give some examples of how they're overcoming them. >> So I can jump in here with this one then, and Mike I think you probably have some maybe Public Sector specific examples, but one of the things that I think is common across all industries is resource constraints, right? And particularly as we look for human resources and not in the HR sense, but developers, CIS admins those types of resources as Mike said, the cloud is here to stay, right? And it's not something that people are thinking about it's de facto part of the conversation. And that's great, but it leads to silos of skills which puts further sort of strain on a limited pool of resources within most sites IT organization. So something like an OpenShift, something like an Ansible solves problems related to resource constraints, because they're skills that are portable across cloud environments, right? If you can manage OpenShift you can manage OpenShift on-prem, you can manage it recently released AWS version of that ROSA on the Azure version of that. So it's no matter where you're running it you've got a common set of skills and access sort of a force multiplier, same thing with Ansible automation, right? If you can write scripts, with an Ansible you can do those repeatable tasks in a much more efficient fashion. And again sort of multiplying the capacity of your existing workforce. >> So you've got an operating leverage there. I mean, this is what you're getting at is that, Public Sector and other commercial areas they kind of got to get used to this fact that, you get some leverage here, you get some operating leverage. >> More or less has always been a thing in IT. And it's not relenting that's for sure. >> It's been more at the more, with less has always been kind of a tagline for budget cuts, right? You can squeeze more out of the investment. Here it's kind of like do more with less than the sense of there's more net new things happening with leverage. So, I mean, do you agree with that? What's your take on that? >> Yeah, I think that's exactly right. It's more with less from a resource perspective, right? Typically it was budget, but no money is just another resource. Now we're getting into the personnel side of it. The other thing I would say is, something like an OpenShift Platform allows the Mike's point around DevOps, it allows the developers to develop, right? I have an article in wired.com about this, where developers are saddled with meetings and they have to become concerned with infrastructure and they have traditionally and security. And I am I doing all these things that aren't related to development. If you have a good DevOps Platform in place the security folks can build guard rails into the platform and the developers can just go develop which is what they want to do in the first place. Yeah exactly, that's another riff on the more, with less, again in a resource, the human resource way versus the budget way. >> Yeah, and that really is where OpenShift ties in. Mike what's your take on this? Because with this kind of program ability infrastructure as code DevSecOps kind of modern developers, Public Sector loves that, because they just want to build the new apps. They got to modernize. So change the infrastructure once. And then a lot of ma many benefits on top of it. It's almost like, it sounds like an operating system to me. >> Yeah, lots of thoughts going around my head right now but I'll say the more with less to me when I'm having client conversations is imagine a world of higher innovation, more technology at lower costs, right? I mean, so CIO is light up when I explained to them the orders of magnitude cost savings on top of the innovation introduced to their environment. So when moving workloads to the cloud is not as easy as just packaging up a binary and dropping in on a name, your cloud provider, right? There's an entire, a blueprinting strategy. There's a Cloud Native Architecture, modernization discussion, so we do those sorts of things, at Deloitte and we work with clients very closely to do that. I want to say teaming with Red Hat allows us to be proactive with our design and reference architecture validation. The Collaborative Partnership in Relationship allows us to connect senior engineers from Deloitte and Red Hat. So we have low level strategic discussions, we validate our assumptions and optimize to use a Red Hat technology. What we're doing in Public Sector is separating the monolithic application into layers. And whenever it comes to technologies like Ansible, like OpenShift, like Jenkins, all of these things that any application needs and Public Sector, we're saying out to the account teams across the country, look this is a slower layer DevOps Platform. And by the way, you can run any .Net or Java based workload on it. So we're trying to make opinionated reference architecture so that regardless of the solution, we can just go to market with that platform that tried and true production application. So I'll give a quick example John, if now's a convenient time regarding, well, one of the things that we've done for particular state client. >> Definitely yeah, give the use cases we love those. >> Yes so one of the impactful modernization that struck my mind was the State of Washington. They've mentioned the affordable care act earlier, there are two major things that came out of that. One was the eligibility and enrollment systems had to be modified across all 50 states. But the second thing and the primary driver behind the affordable care act was health insurance exchange. A way for millions of citizens to have access to healthcare using Subsidized Health Insurance Plans. So in Washington and health benefits exchange is that health insurance exchange, State of Washington has been a client of Deloitte since 2012. The solution was originally designed using closed source proprietary products. There are three drivers for change. The first is the API gateway was end of life and needed to be replaced. Number two was the client wanted it to move health benefit exchange to the cloud from an on-premise hosting arrangement. And third is reducing cost of those solution with innovative products. So the agency was looking for a platform that provided flexibility, auto-scaling and performance and lower cost of ownership. So we worked with the agency and we evaluated a variety of API Management and Integration Platforms after reviewing the outcomes for each proof of concept the agency decided to move forward with Red Hats, three skill API Management Platform, Red Hat Fuse for Integration and OpenShift Container Platform that offered the auto-scaling continuous integration tools and out of the box monitoring and reporting capabilities proactively monitor the health of the solution. I often describe a little bit of OpenShift as a data center or DevSecOps in the box. It just is all there. You don't need to add layers on top of OpenShift install and configure it, tune it and just you're off and running in a short amount of time. So three outcomes I'll mention, go ahead, John. >> NO continue, I thought you were finished. So on the outcomes side, the first outcome the agency substantially lower the cost of ownership using commercially supported open source while increasing access to innovative emerging technology. So the agency wanted a solution not only to meet their current needs, but extend the solution going forward. The beautiful thing about OpenShift is you can drop a container images into the platform without installing an operating system. It's all just there and it's spreading to be extended. The number two outcome cloud migration. Deloitte work collaboratively with the agencies and infrastructure and managed services team to successfully migrate the health benefit exchange to the cloud. And the last thing a bit obvious, but that's successful release, working collaboratively with our client. We were able to migrate the solution within 100 days from making the products decision. The cut over to the new solution was seamless with minimal downtime and zero production issues or exceptionally proud of that. >> Great stuff, great use case. And again, those are great business examples. Dave, I want to get this last question to you and Mike can chime in too. As Red Hat Summit evolves, and we're hearing the theme here at the event about transformation is the innovation, Innovation is about scale. When you hear the words like in a box or Hybrid Cloud you hear about an operating environment. So it's an opportunity to set the table for the next generation, this is what I see. What do you guys see as people talk about Hybrid Cloud and soon to be Multiple Cloud? Because you guys you said have tough relationships. You deal with IBM and Red Hat and you probably deal with other people. Clients want, from what we hear they want back to the Multi Vendor Open Connection Distributed Environment. That's what they want. So how does your relationship evolve, given all this is happening? How do you see the future, please chime in. >> Thanks, that's a fantastic question. I actually think the market is coming catching up to where I've been thinking for quite a while. And that is the Hybrid is kind of where it's at. A lot of customers have been in some sort of Hybrid mode as part of the step or a journey to the cloud, getting all the way to the cloud. But I think we're seeing some transition. I know customers are starting to ask me more and more about Hybrid solutions for a variety of reasons, right? The easy workloads for the most part have either been moved or be are being moved, or at least there's a strategy and a plan to get them moved. And now we're starting to be asked about some of the more difficult architecture type questions, right? The workloads that are a little bit more sticky to the on-premise model. And so Hybrid becoming more of the endpoint as opposed to a step along the journey. The other big thing is some repatriation, right? Workloads coming off of cloud. Maybe they seem like good candidates but for whatever reason, the cost drivers or other things weren't realized, let's get them back on premise. Maybe it's a regulatory thing and new regulations are making folks uncomfortable. So I see Hybrid as a pretty interesting next wave of cloud, Deloitte as a far or we're skilling up or tooling up in order to address the needs of our customers, again are starting to ask us these really challenging questions about Hybrid Cloud and Hybrid Cloud Architectures. >> Yeah and just the key point there is that you think about it like with the way you're discussing it, it's a platform, not a tool, right? So if you think about it like a platform then you can move things around and look at architectures and changes of how resources and workloads are deployed and then what data you're getting from it. Whether you bring it to a factory, for instance you say, Hey, okay, we're going to put it on prem because it's a factory or whatever, and you need more data. What was the changeover? This is like a day to operations kind of mindset. What's your comment on that? >> Well I mean I have actually going back three years now, one of the marketing lines that we developed internally, was moved to a platform, not a provider. But because you get that flexibility, now, the reality is what works stay where they're put for a variety of reasons. But I think one of those reasons could be, because they're put in places where they tend to not want to move, right? So if we could put them into a platform where, there is some portability built into the platform, I think we might have a different sort of outcomes for customers. And I think architecture is absolutely the key, right? That to me is the secret sauce here. >> Mike set up for you to close us out here, platform, Public Sector, Hybrid, that's what they want. It's an ideal scenario for anyone in Public Sector and in general, and why wouldn't you want to have a great platform that's it can be programmed, and rearchitected at will for the benefit of the business powered by software. What's your thoughts? >> Yeah, all good points and I will agree with Dave that Hybrid is certainly evolving. Eight years ago, Hybrid was consuming and address validation API in the cloud and not custom coding that, but today I do agree that Hybrid Cloud is all about a vehicle a way of moving workloads across data centers. It's an architecture that is encapsulated by something like an OpenShift so that you can federate your workloads across data centers. You can put them in one or easily moved them to the other. Maybe that's for a variety of reasons. It could be compute and storage is being reduced by one provider versus the other. So the solutions were we're designing today, they are data center agnostic, we're not being tied to data centers anymore. The best design solutions, you can just let them move in their easy manner. So that that's my take on Hybrid Cloud. And I would say the and Red Hat are making investments to help us advance that thinking help us advance those solutions. We had Deloitte have created a Red Hat OpenShift lab environment, and we've done this purposely to validate reference architectures to show account teams the way we have delivered the very very large accounts to show them what DevSecOps to means from a product perspective and to give them opinionated processes to be successful in delivering these large type solutions. >> Dave, Mike, thanks for coming on, and I appreciate you guys coming on theCUBE and sharing the perspective on the Red Hat Relationship with Deloitte Consulting. Thanks for coming on. >> Thank you. >> Thank you, John. >> This is CUBE Coverage of Red Hat Summit 2021, am John for your host, thanks for watching.

>>from around the globe. >>It's the cube >>With digital coverage of IBM. Think 2021 brought to you by IBM. Welcome to the cubes coverage of IBM Think 2021. I'm lisa martin, exciting conversation coming up about vaccine cloud management. I've got two guests with me, tim Elka is here, the sales and delivery director of IBM Services for Salesforce and fred Thompson joins us as well. The C. I. O. Of the health service executive in Ireland. Gentlemen, welcome to the program. >>Either I have to be here >>so we're very socially distant northern California UK. Glad to have you guys here. We're gonna talk about what the health service executive or HST and Ireland has done with IBM and Salesforce to facilitate vaccine management. But Fran let's go ahead and start with you talk to us a little bit about HSC >>So that the HSC provides public health and social services to everyone living in Ireland. Okay. We that acute hospitals community services nationally. We directly employ about 80,000 people and we fund a further about about 40,000 people. Um and our annual budget is slightly north of 21.6 billion a year. We are the largest employer in the state of the largest organizations the state. Uh you know, we provide a huge range of services right across the whole spectrum and we also fund other organizations who provide those services as well. So we would we would fund some voluntary and charity organizations and we would also uh by services from the latest A GP and other organizations as well. >>So talk to me about a year or so ago when the pandemic hit, what were some of the challenges that HSC faced and then when it came time to we have a vaccine, we have multiple vaccines that roll out um capability. What were some of the challenges that you faced initially? >>So from a an organizational perspective, um, there are, there were huge challenges in that. We were like every other health service worldwide facing uh, an enormous pandemic that was impacting on people. And this is all about people, it's all about people's lives. At the end of the day, people can talk about numbers and they can talk about costs and they can talk about other elements at the end of the day. This is about individual people's lives, their families and their communities. And for the HFC, our challenge was really about how do we manage to protect the totality of the population in Ireland as much as we can from, from the ravages of the virus. Um, and you know, the initial challenge we had was around contact tracing and managing that before a vaccine became available and once the vaccine became available it was then how do we stand up and national vaccine solution that we would be able to deliver and record vaccine to the totality of the population who were getting back? >>Yeah. So there was no pre existing vaccination program. Of course, probably in most places, you needed to get health care workers vaccinated ASAP. And it's also needed to be a national program. So what did you do next? After determining? All right, we need to work with some partners to be able to build technology to facilitate uh equitable, efficient rollout of the vaccine. >>So we did have regional vaccine systems and we do have a number of vaccine programs out there that were that were managing flu vaccine, heP C vaccine. But we needed we did we didn't have a national program and we needed to vaccinate people immediately. Um, and we also wanted to make sure that vaccine program was not dependent on the HSC infrastructure because, you know, we want to be able to vaccinate people in non HSC sites and we wanted non HSC staff to be able to vaccination. Uh, and we didn't want a huge pre dependent on our existing infrastructure. Um, so the first thing we did, we we looked at a number of vendors. Um, and we chose IBM as our partner with Salesforce. And that partnership is really a strategic partnership and it's a partnership that we worked through all the bumps and all the lumps of the program together. Um, and you know, and and there there have been challenges, but like it's too working with him and his team and through our team that we've overcome some of those challenges. Um, and like when we started off, remember the very first conversation I had with him as legislators, we need to vaccinate healthcare workers now, okay, you've got two weeks to start, um and we need to configure a system, get it up and running and to be able to um roll it out to the hospital And two. I'm very quickly then to all of our nursing care homes. Now, that was the challenge. >>And let's bring tIM in is this is a radically quick project from MPB to roll out in two weeks to talk to us about first about the IBM partnership with Salesforce and what you're building together. >>Absolutely. And it's great and Fran. It's interesting to hear you speaking about the run into this because from my perspective, a week before we all started this, we had a simple conversation called into Health Service Executive has some talking about some vaccination program, how can we help? And then within a week we've gone from zero to having how many calls with Fran and team just to understand and with the salesforce team to really understand how the 33 parties can bring the best of IBM, the best of Salesforce and the best of HSC in terms of the adaptability and what we need to get done to get those vaccinations up and running for the health care workers. Now, you know when franz said to me, we need something in two weeks, there was absolutely clarity. If you can't do it in two weeks there's a door, right? So we knew exactly the challenge and that's the kind of thing right before christmas that we were so fortunate to really bring in the team like everyone you think about this, everyone has probably the 14th of december, I was thinking of winding down thinking of having their christmas holidays and vacation time and everybody from the irish team and from the english team said no or cancel, christmas will cancel everything. So it's really christmas came early and christmas was canceled all at once, so and the key bit here, the strategic partnership is, I'm in the sales force have been working together for years and years and years growing out a partnership, we know their products really well, we've got huge capability in that space, but actually with the new health cloud part of it, the vaccine management parts are quite new to salesforce as well, only launched back in august september time, so it's quite new, so we had to go in together as a sort of partnership there to say to just get this done. So we had the best people from salesforce, I know the product, the best people from IBM all turning up on the 14th of december and saying right, we've got to get this done By the 29th with christmas and christmas holidays in the way the vacation time in the way, I think we have 36 hours of time off to eat turkey and fill ourselves before getting back to the wheel and really getting this done and to get I think was four acute hospitals we went into as of the 29th to start the vaccination program, so trying to do that, understanding everything is a compromise at that point, but it has to be secure, you know, this, this is, this is personal data going into these systems, so you can't forget about all the aspects, it's got this minimum but minimum with those kind of constraints as a health system. So it needs to be secure, it needs to also be that national platform going forward as well. So basing on a great platform like Salesforce, you know, you can scale out, you know, you've got those options to grow in the future, but yeah, not without a lot of challenge and then working out what's now getting to know each other, but if we only talked about twice before, we have to know each other pretty well now, um, but just trying to work out how we then structure, what's going to happen every two weeks afterwards, How is that going to move forward? We're going live every two weeks and we haven't done that now for the last three months, So good fun. >>So yeah, good fun. And but so much work to get done and according huge, coordinated effort in a very short time period, during a very challenging time. Talk to me a little bit about France, but you launched this um cloud management vaccine, Cloud management in january 2021 today to thank you. Told me one million people have been vaccinated so far. Talk to me about what the IBM Salesforce solution enables you to deliver to the HSC and to the irish citizens. >>So we have delivered a million vaccines. Okay to uh to stage is uh there's a dose one of those two for most people in Ireland. Um and there's about 720,000 people have got their dose one and the balance I've got, I've got the dose too, that's about sort of just about one in five of the population. That has to be that there has to be vaccinated. And one of these were very conscious of is that, you know, an organization is that we need to take a risk-based approach to this. So we need to look at the most vulnerable groups. There were lots of people who were dying from, you know, from this and they were all the a lot of people are elderly groups and people who were who were vulnerable with uh with pre medical condition. So our challenge was how do we, how do we vaccinate those people quickly and effectively uh and also vaccinate health care workers who are going to care for these people? Uh and and that's what we're, we prioritize the work. So we have to go into 50 acute sites, about 600 or so care homes. We set up a lot of what we call pop up clinics literally attended the in a location or we took over a sports hall or whatever we did. We rolled it out to the GPS to about 2.5 1000 G. P. Site. Um and all of that was being done while we were building the system. So we were, you know, building the system and designing the system on two weeks prints. We have to be agile way too quick. We can make huge compromises and we know that okay. I mean everyone wants a perfect system which is to make the compromise and look and see what you need to do now to keep the program running and how you manage that were, you know, Uh about 3000 users all to be set up fairly quickly or a little over between 1000 users so you can manage all that as you're going through everything. >>I think agile is the name of the game here. Tim talked to us about how you're delivering the agility in such a 10uous time. >>Well, we're all virtual which is added to the mix. But the funny thing with that agility, we've got a span of people across all the countries and everywhere that we can bring to that that party and we're running a normal but I was kind of a normal agile project except normally it would take 23 months to really get that team working effectively, getting to know each other and we just not had time to that to do that. So there's been a core team here and we're bringing in the experts around it. But really just everything is working with Fran work very hand in glove, trying just to work out what we need to do here to look at the next sprint, to look at the next go Live, to look at the compromise. How do we compromise for two weeks? What can we live with for two weeks? What's in the backlog for now? And Fran and I have many conversations, what do we need to do this week and then what's next week? And that's the level of fluidity And that's in part because of the way the pandemics and the response to pandemic is mapping out as we saw the vaccines are changing availability, is changing the rollout plan is changing. None of us have worked through a pandemic before. So agility is the name of the game at the highest level. I think we're all now very used to being sorry, there's a problem. Something's changed. Can we adapt the system to you know where normally in a sprint, I'd be thinking I've got some fixed requirements for two weeks. I'll build that and then do the next two weeks, everything is up for grabs and we're just having to maintain quality at the pace, the responsiveness and balancing it all as an IBM team and you think, and whilst we're also doing that on a platform that it takes time to configure and build these things as well. So it's some of it is you're gonna have to wait a few days. So sorry, you know, in a few days is really probably sometimes the maximum amount of time that can be, you can differ. But as Fran and everyone in the HRC and the, the national immunization office, everyone's pragmatic about realizing we're all in this together and it's really just being one single team, one unit working out and very open and transparent about the, after the possible >>we're doing something, go ahead. >>And we had a phrase, there was like, those are the pieces, we just just do it now and, and we did a lot of that. Okay. Um, you know, where there were things that were prioritized, we're in the middle of a sprint. Um, there were there were changes in the program or there were changes in how, how the vaccination was going to be delivered. Um, and we couldn't wait the week. Just it wasn't available. So we have this thing is just gonna do it now and him and the team, you know, drop what they were doing, you know, made the changes, we test them fast and we put them in and and that gave us then, you know, an extra time to actually then deliver the rest of the sprint and we have to do that. Several Okay. Several very, very late night to deliver >>and I imagine that's still going on. But to wrap here guys, amazing work that you've done together so far with the Salesforce vaccine Club Management rolling out across the HSC, you said one million vaccinations delivered many hundreds of thousands in the queue. I'm sure more iterative work and sleepless nights. But what you're doing for the country of Ireland is literally as friends in the beginning. Life saving Gentlemen, thank you so much for joining me today on the program. >>You're welcome. Thank you. You're very welcome. Thank you. >>Tim and Fran. I'm lisa martin. You're watching two cubes coverage of IBM think 2021. >>Mhm >>mm.

>>Hello, and welcome to today's event, dealing government emergency responses beyond the pandemic. This is Bob Wooley, senior fellow for the center for digital government and formerly the chief tech clerk for the state of Utah. I'm excited to serve as moderator for today's event. And just want to say, thank you for joining us. I know we're in for an informative session over the next 60 minutes before we begin a couple of brief housekeeping notes or recording of this presentation will be emailed to all registrants within 48 hours. You can use the recording for your reference or feel free to pass it along to colleagues. This webcast is designed to be interactive and you can participate in Q and a with us by asking questions at any time during the presentation, you should see a Q and a box on the bottom left of the presentation panel. >>Please send in your questions as they come out throughout the presentation, our speakers will address as many of these questions as we can during the Q and a portion of the close of our webinar today, if you would like to download the PDF of the slides for this presentation, you can do so by clicking the webinar resources widget at the bottom of the console. Also during today's webinar, you'll be able to connect with your peers by LinkedIn, Twitter and Facebook. Please use the hashtag gov tech live to connect with your peers across the government technology platform, via Twitter. At the close of the webinar, we encourage you to complete a brief survey about the presentation. We would like to hear what you think if you're unable to see with us for the entire webinar, but we're just like to complete the survey. As much as you're able, please click the survey widget at the bottom of the screen to launch the survey. Otherwise it will pop up once the webinar concludes at this time, we recommend that you disable your pop-up blockers, and if you experiencing any media player issues or have any other problems, please visit our webcast help guide by clicking on the help button at the bottom of the console. >>Joining me today to discuss this very timely topic are Karen revolt and Tim Burch, Kim Berge currently serves as the administrator of human services for Clark County Nevada. He's invested over 20 years in improving health and human service systems of care or working in the private public and nonprofit sectors. 18 of those years have been in local government in Clark County, Las Vegas, where you served in a variety of capacities, including executive leadership roles as the director of department of social services, as well as the director for the department of family services. He has also served as CEO for provider of innovative hosted software solutions, as well as chief strategy officer for a boutique public sector consulting firm. Karen real-world is the social program management offering lead for government health and human services with IBM Watson health. Karen focuses delivering exciting new offerings by focusing on market opportunities, determining unmet needs and identifying innovative solutions. >>Much of her career has been in health and human services focused on snap, TANIF, Medicaid, affordable care act, and child welfare prior to joining IBM. Karen was the senior director of product management for a systems integrator. She naturally fell in love with being a project manager. She can take her user requirements and deliver offerings. Professionals would use to make their job easier and more productive. Karen has also found fulfillment in working in health and human services on challenges that could possibly impact the outcome of people's lives. Now, before we begin our discussion of the presentation, I want to one, we'd like to learn a little more about you as an audience. So I'm going to ask you a polling question. Please take a look at this. Give us an idea of what is your organization size. I won't bother to read all these to you, but there are other a range of sizes zero to 250 up to 50,000. Please select the one that is most appropriate and then submit. >>It looks like the vast majority are zero to two 50. Don't have too many over 250,000. So this is a very, very interesting piece of information. Now, just to set up our discussion today, what I want to do is just spend just a moment and talk about the issue that we're dealing with. So when you look the COVID-19 pandemic, it's put immense pressure on States. I've been a digital state judge and had been judging a lot of the responses from States around the country. It's been very interesting to me because they bifurcate really into two principle kinds of reactions to the stress providing services that COVID environment present. One is we're in a world of hurt. We don't have enough money. I think I'm going to go home and engage as little as I have to. Those are relatively uncommon. Thankfully, most of them have taken the COVID-19 pandemic has immense opportunity for them to really do a lot more with telework, to do more with getting people, employees, and citizens involved with government services. >>And I've done some really, really creative things along the way. I find that to be a really good thing, but in many States systems have been overloaded as individuals and families throughout the country submitted just an unprecedented number of benefit applications for social services. At the same time, government agencies have had to contend with social distance and the need for a wholly different approach to engage with citizens. Um, overall most public agencies, regardless of how well they've done with technology have certainly felt some strain. Now, today we have the opportunity to go into a discussion with our speakers, have some wonderful experience in these areas, and I'm going to be directing questions to them. And again, we encourage you as you hear what they have to say. Be sure and submit questions that we can pick up later at the time. So Tim, let's start with you. Given that Las Vegas is a hub for hospitality. An industry hit severely as a result of this pandemic. How's the County doing right now and how are you prioritizing the growing needs of the County? >>Thanks Bob. Thanks for having me. Let me start off by giving just a little, maybe context for Clark County too, to our audience today. So, uh, Clark County is, you know, 85% of the state of Nevada if we serve not just as a regional County by way of service provision, but also direct municipal services. Well, if, uh, the famous Las Vegas strip is actually in unincorporated Clark County, and if we were incorporated, we would be the largest city in the state. So I say all of that to kind of help folks understand that we provide a mix of services, not just regional services, like health and human services, the direct and, and missable, uh, services as well as we work with our other five jurisdiction partners, uh, throughout the area. Uh, we are very much, um, I think during the last recession we were called the Detroit of the West. >>And, uh, that was because we're very much seen as a one industry town. Uh, so most like when the car plants, the coal plants closed back East and in the communities fuel that very rapidly, the same thing happens to us when tourism, uh, it's cut. Uh, so of course, when we went into complete shutdown and March, uh, we felt it very rapidly, not just on, uh, uh, tax receipts and collectibles, but the way in which we could deliver services. So of course our first priority was to, uh, like I think you mentioned mobilized staff. We, we mobilized hundreds of staff overnight with laptops and phones and cars and the things they needed to do to get mobile and still provide the priority services that we're mandated to provide from a safety standpoint. Um, and then we got busy working for our clients and that's really where our partnership with IBM and Watson, uh, came in and began planning that in July. And we're able to open that portal up in October to, to really speed up the way in which we're giving assistance to, to our residents. Um, re focus has been on making sure that people stay housed. We have, uh, an estimated, uh, 2.5 million residents and over 150,000 of those households are anticipated to be facing eviction, uh, as of January one. So we, we've got a, a big task ahead of us. >>All of this sounds kind of expensive. Uh, one of the common threads as you know, runs throughout government is, ah, I don't really have the money for that. I think I'd be able to afford that a diaper too, as well. So what types of funding has been made available for counties, a result of a pandemic, >>Primarily our funding stream that we're utilizing to get these services out the door has been the federal cares act. Uh, now we had some jurisdictions regionally around us and even locally that prioritize those funds in a different way. Um, our board of County commissioners, uh, took, um, a sum total of about $85 million of our 240 million that said, this will go directly to residents in the form of rental assistance and basic needs support. No one should lose their home or go hungry during this pandemic. Uh, so we've really been again working through our community partners and through our IBM tools to make sure that happens. >>So how does, how does, how does the cares act funding then support Clark County? Cause it seems to me that the needs would be complex, diverse >>Pretty much so. So as you, as folks may know him a call there's several tronches of the cares act, the original cares act funding that has come down to us again, our board, uh, identified basic needs or rental assistance and, and gave that the department of social service to go to the tunicate, uh, through the community. We then have the cares act, uh, uh, coronavirus relief funds that have, uh, impacted our CDBG and our emergency solutions grants. We've taken those. And that's what we was going to keep a lot of the programs and services, uh, like our IBM Watson portal open past January one when the cares act dollars expire. Uh, our initial response was a very manual one, uh, because even though we have a great home grown homeless management information system, it does not do financials. Uh, so we had 14 local nonprofits adjudicating, uh, this rental assistance program. >>And so we could get our social service visitor portal up, uh, to allow us to take applications digitally and run that through our program. Uh, and, uh, so those partners were obviously very quickly overwhelmed and were able to stand up our portal, uh, which for the reason we were driving so hard, even from, uh, beginning of the conversations where after going into lockdown into contracting in July and getting the portal open in October, which was an amazing turnaround. Uh, so the kudos that IBM team, uh, for getting us up and out the door so quickly, uh, was a tie in, uh, to our, uh, Curam IBM, uh, case management system that we utilize to adjudicate benefits on daily basis in Clark County for all our local indigent population, uh, and high needs folks. Uh, and then that ties into our SAP IBM platform, which gets the checks out the door. >>So what, what we've been able to do with these dollars is created in Lucian, uh, that has allowed us in the last 60 days to get as much money out the door, as our nonprofits were able go out the door in the first six months pandemic. So it really has helped us. Uh, so I'm really grateful to our board of County commissioners for recognizing the investment in technology to, to not only get our teams mobile, but to create ease of access for our constituents and our local residents to give them the help they need quickly and the way that they need it. >>Just to follow up question to that, Tim, that I'm curious about having done a lot of work like this in government, sometimes getting procurement through in a timely way is a bit challenging. How were you able to work through those issues and getting this up and provision so quickly? >>Uh, yeah, so we, we put together a, what we call a pandemic playbook, which is kind of lessons learned. And what we've seen is the folks who were essential workers in the first 60 days of the, uh, pandemic. We were able to get a lot done quickly because we were taking full advantage of the emergency. Uh, it may sound a little crass to folks not inside the service world, but it was, uh, you know, don't want you to crisis. It was things we've been planning or trying to do for years. We need them yesterday. We should have had them yesterday, but let's get them tomorrow and get it moving very quickly. Uh, this IBM procurement was something we were able to step through very quickly because of our longstanding relationship. Our countywide, uh, system of record for our financials is SAP. Uh, we've worked with Curam, uh, solution, uh, for years. >>So we've got this long standing relationship and trust in the product and the teams, which helped us build the business case of why we did it, no need to go out for competitive procurement that we didn't have time. And we needed something that would integrate very quickly into our existing systems. Uh, so that part was there. Now when the folks who were non essential came back in June and the reopening, it was whiplash, uh, the speed at which we were moving, went back to the pace of normal business, uh, which feels like hitting a wall, doing a hundred miles an hour when you're used to having that, uh, mode of doing business. Uh, so that's certainly been a struggle, uh, for all of those involved, uh, in trying to continue to get things up. Um, but, uh, once again, the teams have been great because we've probably tripled our licensure on this portal since we opened it, uh, because of working with outside vendors, uh, to, uh, literally triple the size of our staff that are processing these applications by bringing on temporary staff, uh, and short-term professionals. Uh, and so we've been able to get those things through, uh, because we'd already built the purchasing vehicle during the early onset of the crisis. >>That's very helpful. Karen, IBM has played a really pivotal role in all of this. Uh, IBM Watson health works with a number of global government agencies, raging from counties like Clark County to federal governments. What are some of the major challenges you've seen with your clients as a result of the pandemic and how is technology supporting them in a time of need and give us some background Watson health too. So we kind of know a little more about it because this is really a fascinating area. >>Yeah. Thank you, Bob. And thanks Tim for the background on Clark County, because I think Clark County is definitely also an example of what federal governments and global governments are doing worldwide today. So, um, Watson health is our division within IBM where we really focus on health and human services. And our goal is to really focus in on, um, the outcomes that we're providing to individuals and families and looking at how we use data and insights to really make that impact and that change. And within that division, we have our government health and human services area, which is the focus of where we are with our clients around social program. But it also allows us to work with, um, different agencies and really look at how we can really move the ball in terms of, um, effecting change and outcomes for, um, really moving the needle of how we can, uh, make an impact on individuals and families. >>So as we look at the globe globally as well, you know, everything that Tim had mentioned about how the pandemic has really changed the way that government agencies operate and how they do services, I think it's amazing that you have that pandemic playbook because a lot of agencies in the same way also had these set of activities that they always wanted to go and take part on, but there was no impetus to really allow for that to happen. And with the pandemic, it allowed that to kind of open and say, okay, we can try this. And unfortunately I'm in a very partial house way to do that. And, um, what Tim has mentioned about the new program that they set up for the housing, some of those programs could take a number of years to really get a program online and get through and allowing, uh, the agencies to be able to do that in a matter of weeks is amazing. >>And I think that's really gonna set a precedent as we go forward and how you can bring on programs such as the housing and capability in Canada with the economic, uh, social, um, uh, development and, and Canada need that the same thing. They actually had a multi benefit delivery system that was designed to deliver benefits for three programs. And as part of the department of fisheries and oceans Canada, the, um, the state had an emergency and they really need to set up on how they could provide benefits to the fishermen who had been at that impacted, um, from that. And they also did set up a digital front-end using IBM citizen engagement to start to allow the applications that benefits, um, and they set it up in a matter of weeks. And as I mentioned, we, uh, Clark County had a backend legacy system where they could connect to and process those applications. And this case, this is a brand new program and the case management system that they brought up was on cloud. And they had to set up a new one, but allow them to set up a, what we used to call straight through processing, I think has been now turned, turned or coined contact less, uh, processing and allowing us to really start to move those benefits and get those capabilities out to the citizens in even a faster way than has been imagined. Uh, pre pandemic. >>Karen, I have one follow-up question. I want to ask you, having had a lot of experience with large projects in government. Sometimes there's a real gap between getting to identified real requirements and then actions. How do you, how do you work with clients to make sure that process time to benefit is shortened? >>So we really focus on the user themselves and we take a human centered design focus and really prioritizing what those needs are. Um, so working with the clients, uh, effectively, and then going through agile iterations of brain, that capability out as, um, in, in a phased approach to, so the idea of getting what we can bring out that provides quality and capability to the users, and then over time starting to really roll out additional functions and, um, other, uh, things that citizens or individuals and families would need >>Very helpful. Tim, this is an interesting partnership. It's always good to see partnerships between private sector and government. Tell us a little bit about how the partnership with IBM Watson health was established and what challenges or they were brought into assist, where they brought into assist with back to requirements. Again, within the requirements definitely shifted on us. You know, we had the con looking at, uh, Watson on our child welfare, uh, side of the house that I'm responsible for and how that we could, uh, increase access to everything from tele-health to, to, uh, foster parent benefit, uh, kinship, placement benefits, all those types of things that, that right now are very manual, uh, on the child welfare side. Uh, and then the pandemic kid. And we very quickly realized that we needed, uh, to stand up a, um, a new program because, uh, a little bit for context, uh, the park County, we don't administer TANIF or Medicaid at the County level. >>It is done at the state level. So we don't have, uh, unemployment systems or Medicaid, 10 of snap benefits systems to be able to augment and enroll out. We provide, uh, the indigent supports the, the homelessness prevention, referee housing continuum of care, long-term care, really deep emergency safety net services for our County, which is a little bit different and how those are done. So that was really our focus, which took a lot of in-person investigation. We're helping people qualify for disability benefits so they can get into permanent supportive housing, uh, things that are very intensive. And yet now we have a pandemic where we need things to happen quickly because the cares act money expires at the end of December. And people were facing eviction and eviction can help spread exposure to, to COVID. Uh, so, uh, be able to get in and very rapidly, think about what is the minimal pelvis to MVP. >>What's the minimum viable product that we can get out the door that will help people, uh, entrance to a system as contactless as possible, which again was a complete one 80 from how we had been doing business. Um, and, uh, so the idea that you could get on and you have this intelligent chat bot that can walk you through questions, help you figure out if you look like you might be eligible, roll you right into an application where you can upload the few documents that we're going to require to help verify your coat would impact and do that from a smartphone and under, you know, 20 minutes. Um, it, it, it is amazing. And the fact that we've stood that up and got it out the door in 90 days, it's just amazing to me, uh, when it shows the, uh, strength of partnership. Um, I think we can, we have some shared language because we had that ongoing partnership, but we were able to actually leverage some system architects that we had that were familiar with our community and our other products. So it really helped expedite, uh, getting this, uh, getting this out to the citizens. >>So, uh, I assume that there are some complexities in doing this. So overall, how has this deployment of citizen engagement with Watson gone and how do you measure success other than you got it out quick? How do you know if it's working? >>Yeah. Right. So it's the adage of, you know, quick, fast and good, right. Um, or fast, good and cheap. So, uh, we measure success in this way. Um, how are we getting access as our number one quality measurement here? So we were able to collect, uh, about 13,000 applications, uh, manual NRC, manually folks had to go onto our website, download a PDF, fill it out, email it, or physically drop it off along with their backup. One of their choice of 14 non-profits in town, whichever is closest to them. Um, and, uh, and then wait for that process. And they were able to get 13,000 of those, uh, process for the last six months. Uh, we have, I think we had about 8,000 applications the first month come into the portal and about an equal amount of folks who could not provide the same documentation that it was needed. >>And self-selected out. If we had not had the, the tool in place, we would have had 16,000 applications, half of which would have been non-eligible would have been jamming up the system, uh, when we don't have the bandwidth to deal to deal with that, we, we need to be able to focus in on, uh, Judy Kenny applications that we believe are like a 95% success rate from the moment our staff gets them, but because we have the complex and he was on already being dependent upon the landlord, having to verify the rent amount and be willing to work with us, um, which is a major hurdle. Um, but, uh, so w we knew we could not do is go, just reinvent the manual process digitally that that would have been an abject failure on our behalf. So, uh, the ideas that, uh, folks had can go on a very, had this very intuitive conversation to the chat bot, answer some questions and find out if they're eligible. >>And then self-select out was critical for us to not only make sure that the citizens got the help they needed, but not so burnt out and overload our workforce, which is already feeling the strain of the COVID pandemic on their own personal lives and in their homes and in the workplace. Um, so that was really critical for us. So it's not just about speed, ease of access was important. Uh, the ability to quickly automate things on the fly, uh, we have since changed, uh, the area median income, a qualifier for the rental assistance, because we were able to reallocate more money, uh, to the program. So we were able to open it up to more people. We were able to make that, uh, change to the system very quickly. Uh, the idea that we can go on the home page and put updates, uh, we recognized that, uh, some of our monolingual Hispanic residents were having difficulty even with some guidance getting through the system. >>So we're able to record a, a Spanish language walkthrough and get done on the home page the next day, right into the fordable, there'll be a fine, so they could literally run the YouTube video while they're walking through their application. Side-by-side so things like that, that those are how we are able to, for us measured success, not just in the raw dollars out the door, not just in the number of applications that have come in, but our ability to be responsive when we hear from our constituents and our elected officials that, Hey, I want, I appreciate the 15,000 applications as you all, a process and record time, I've got three, four, five, six, 10 constituents that having this type of problem and be able to go back and retool our systems to make them more intuitive, to do, be able to keep them responsive for us is definitely a measure of success and all of this, probably more qualitative than here we're looking >>For, but, uh, that's for us, that's important. Actually the qualitative side is what usually gets ignored. Uh, Karen, I've got a question that's a follow up for you on the same topic. How does IBM facilitate reporting within this kind of an environment given the different needs of stakeholders, online managers and citizens? What kinds of things do you, are you able to do >>So with, um, the influx of digitalization? I think it allows us to really take a more data-driven approach to start looking at that. So, as, as Tim was mentioning, you can see where potentially users are spending more time on certain questions, or if they're stuck on a question, you can see where the abandoned rate is. So using a more data-driven approach to go in to identify, you know, how do we actually go and, um, continue to drive that user experience that may not be something that we drive directly from the users. So I would say that analytics is really, uh, I think going to continue to be a driving force as government agencies go forward, because now they are capturing the data. But one thing that they have to be careful of is making sure that the data that they're getting is the right data to give them the information, to make the right next steps and decisions. >>And Tim, you know, use a really good example with, um, the chatbot in terms of, you know, with the influx of everything going on with COVID, the citizens are completely flooded with information and how do they get the right information to actually help them decide, can I apply for this chap program? Or should I, you know, not even try and what Tim mentioned just saved the citizens, you know, the people that may not be eligible a lot of time and going through and applying, and then getting denied by having that upfront, I have questions and I need answers. Um, so again, more data-driven of how do we provide that information? And, you know, we've seen traditionally citizens having to go on multiple website, web pages to get an answer to the question, because they're like, I think I have a question in this area, but I'm not exactly sure. And they, then they're starting to hunt and hunt and hunt and not even potentially get an answer. So the chocolate really like technology-wise helps to drive, you know, more data-driven answers to what, um, whether it's a citizen, whether it's, um, Tim who needs to understand how and where my citizens getting stuck, are they able to complete the application where they are? Can we really get the benefits to, um, this individual family for the housing needs >>Too many comments on the same thing. I know you have to communicate measures of success to County executives and others. How do you do that? I mean, are you, do you have enough information to do it? Yeah, we're able to, we actually have a standup meeting every morning where the first thing I learn is how many new applications came in overnight. How many of those were completed with full documentation? How many will be ported over into our system, assigned the staff to work, where they're waiting >>On landlord verification. So I can see the entire pipeline of applications, which helps us then determine, um, Oh, it's, it's not, you know, maybe urban legend is that folks are having difficulty accessing the system. When I see really the bottleneck there, it got gotten the system fine, the bottlenecks laying with our landlord. So let's do a landlord, a town hall and iterate and reeducate them about what their responsibilities are and how easy it is for them to respond with the form they need to attest to. And so it lets us see in real time where we're having difficulties, uh, because, uh, there's a constant pressure on this system. Not just that, uh, we don't want anyone to lose their home, uh, but these dollars also go away within a December. So we've got this dual pressure of get it right and get it right now. >>Uh, and so th the ability to see these data and these metrics on, on a daily basis is critical for us to, to continue to, uh, ModuLite our response. Um, and, and not just get comfortable are baked into well, that's why we developed the flowchart during requirements, and that's just the way things are gonna stay. Uh, that's not how you respond to a pandemic. Uh, and so having a tool and a partner that helps us, uh, stay flexible, state agile, I guess, to, to, to leverage some terminology, uh, is important. And, and it's, it's paid dividends for our citizens. Karen, again, is another up to the same thing. I'm kind of curious about one of the problems of government from time to time. And Tim, I think attest to this is how do you know when Dunn has been reached? How did you go about defining what done would look like for the initial rollout with this kind of a customer? >>So I think Doug, I guess in this case, um, is, is this, isn't able to get the benefits that they're looking for and how do we, uh, you know, starting from, I think what we were talking about earlier, like in terms of requirements and what is the minimum viable, um, part of that, and then you start to add on the bells and whistles that we're really looking to do. So, um, you know, our team worked with him to really define what are those requirements. I know it's a new program. So some of those policy decisions were still also being worked out as the requirements were being defined as well. So making sure that you are staying on top of, okay, what are the key things and what do we really need to do from a compliance standpoint, from a functionality, and obviously, um, the usability of how, uh, an assistant can come on and apply and, um, have those, uh, requirements, make sure that you can meet that, that version before you start adding on additional scope. >>Very helpful. Jim, what's your comment on this since I know done matters to you? Yeah. And look, I I've lived through a, again, multiple, uh, county-wide it implementations and some department wide initiatives as well. So I think we know that our staff always want more so nothing's ever done, uh, which is a challenge and that's on our side of the customer. Um, but, uh, for this, it really was our, our experience of recognizing the, the time was an essence. We didn't have a chance. We didn't have, uh, the space to get into these endless, uh, conversations, uh, the agile approach, rather than doing the traditional waterfall, where we would have been doing requirements tracking for months before we ever started coding, it was what do we need minimally to get a check in the hands of a landlord on behalf of a client, so they don't get evicted. >>And we kept just re honing on that. That's nice. Let's put that in the parking lot. We'll come back to it because again, we want to leverage this investment long term, uh, because we've got a we, and we've got the emergency solutions and CDBG, and then our, uh, mainstream, uh, services we brought on daily basis, but we will come back to those things speed and time are of the essence. So what do we need, uh, to, to get this? So a chance to really, um, educate our staff about the concepts of agile iteration, um, and say, look, this is not just on the it side. We're gonna roll a policy out today around how you're doing things. And we may figure out through data and metrics that it's not working next week, and we'll have to have that. You want it. And you're going to get the same way. >>You're getting updated guidance from the CDC on what to do and what not to do. Uh, health wise, you're getting the same from us, uh, and really to helping the staff understand that process from the beginning was key. And, uh, so, and, and that's, again, partnering with, with our development team in that way was helpful. Um, because once we gave them that kind of charter as I am project champion, this is what we're saying. They did an equally good job of staying on task and getting to the point of is this necessary or nice. And if it wasn't necessary, we put it in the nice category and we'll come back to it. So I think that's really helpful. My experience having done several hundred sheet applications also suggest the need for MBP matters, future stages really matter and not getting caught. My flying squirrels really matters. So you don't get distracted. So let's move on to, let's do a polling question before we go on to some of our other questions. So for our audience, do you have a digital front ends for your benefit delivery? Yes, no. Or we're planning to a lot of response here yet. There we go. Looks like about half, have one and half note. So that's an interesting question. What's going to one more polling question, learn a little more here. Has COVID-19 >>Accelerated or moved cloud. Yes, no. We already run a majority of applications on cloud. Take a moment and respond if you would, please. So this is interesting. No real acceleration was taken place and in terms of moving to cloud is not what I was expecting, but that's interesting. So let's go onto another question then. And Karen, let me direct this one to you, given that feedback, how do you envision technologies such as citizen engagement and watching the system will be used, respond to emergency situations like the pandemic moving forward? I mean, what should government agencies consider given the challenges? This kind of a pandemic is brought upon government and try to tie this in, if you would, what, what is the role of cloud in all of this for making this happen in a timely way? Karen, take it away. >>Okay. Thanks Bob. So as we started the discussion around the digital expansion, you know, we definitely see additional programs and additional capabilities coming online as we continue on. Um, I think, uh, agencies have really seen a way to connect with their citizens and families and landlords, um, in this case an additional way. And he prepared them like there were, uh, presuppose assumptions that the, um, the citizens or landlords really wanted to interact with agency face-to-face and have that high touch part. And I think, um, through this, the governments have really learned that there is a way to still have an impact on the citizen without having a slow, do a face to face. And so I think that's a big realization for them to now really explore other ways to digitally explain, expand their programs and capabilities. Another area that we touched on was around the AI and chat bot piece. >>So as we start to see capabilities like this, the reason why Clark County was able to bring it up quickly and everything was because it was housed on cloud, we are seeing the push of starting to move some of the workloads. I know from a polling question perspective that it's been, um, lighter in terms of getting, uh, moving to the cloud. But we have seen the surge of really chatbots. I think we've been talking about chatbots for a while now. And, um, agencies hadn't really had the ability to start to implement that and really put it into effect. But with the pandemic, they were able to bring things up and, you know, very short amount of time to solve, um, a big challenge of not having the call center be flooded and have a different way to direct that engagement between the citizen and the government. >>So really building a different type of channel for them to engage rather than having to call or to come into an office, which wasn't really allowed in terms of, um, the pandemic. Um, the other thing I'll touch on is, um, 10 mentioned, you know, the backlog of applications that are coming in and we're starting to see the, um, the increase in automation. How do we automate areas where it's administratively highly burdened, but it's really a way that we can start to automate those processes, to give our workers the ability to focus on more of those complex situations that really need attention. So we're starting to see where the trends of trying to push there of can we automate some of those processes, um, uh, uploading documents and verification documents is another way of like, trying to look at, is there a way that we can make that easier? >>Not only for the applicant that's applying, but also for the caseworker. So there's not having to go through that. Um, does the name match, um, the applicant, uh, information and what we're looking on here, and Bob, you mentioned cloud. So behind the scenes of, you know, why, uh, government agencies are really pushing the cloud is, um, you heard about, I mean, with the pandemic, you see a surge of applicants coming in for those benefits and how do we scale for that kind of demand and how do you do that in an inappropriate way, without the huge pressures that you put on to your data center or your staff who's already trying to help our citizens and applicants, applicants, and families get the benefits they need. And so the cloud, um, you know, proposition of trying, being able to be scalable and elastic is really a key driver that we've seen in terms of, uh, uh, government agencies going to cloud. >>We haven't really seen during a pandemic, the core competencies, some of them moving those to cloud, it's really been around that digital front end, the chat bot area of how do we start to really start with that from a cloud perspective and cloud journey, and then start to work in the other processes and other areas. Um, security is also huge, uh, focus right now with the pandemic and everything going online. And with cloud allows you to be able to make sure that you're secure and be able to apply the right security so that you're always covered in terms of the type of demand and, um, impact, uh, that is coming through >>Very helpful. Tim, I'm going to ask to follow up on this of a practical nature. So you brought this up very quickly. Uh, there's a certain amount of suspicion around state government County government about chatbots. How did you get a chat much and be functional so quickly? And were you able to leverage the cloud in this process? Yeah, so on the trust is important. Uh, and I'll go back to my previous statement about individuals being able to see upfront whether they believe they're eligible or not, because nothing will erode trust more than having someone in hours applying and weeks waiting to find out they were denied because they weren't eligible to begin with, uh, that erodes trust. So being able to let folks know right up front, here's what it looks like to be eligible, actually help us build some of that, uh, cause they don't feel like, uh, someone in the bureaucracy is just putting them through the ringer for no reason. >>Um, now in regard to how do we get the chat bot out? I will say, uh, we have a, uh, dynamic it and leadership, uh, team at the highest level of County government who we have been already having conversations over the last year about what it meant to be smart government, uh, the department of social service and family services that I'm responsible for. We're already, uh, hands up first in line, you know, Guinea pigs volunteering to be on the front end of, uh, certain projects. So w we have primed ourselves for, for some of this readiness in that aspect. Um, but for citizen trust, um, the timeliness of application right now is the biggest element of trust. Uh, so I've applied I've I feel like I put my housing future in your hands. Are you going to deliver and having the ability for us to rapidly scale up? >>Uh, we typically have 120 staff in the department of social service that, that are adjudicating benefits for programs on daily basis. We've doubled that with temporary staff, uh, through some partnerships, uh, we're, we're gonna, as of next week, probably have more temporary per professional staff helping an adjudicator applications. No, do full-time County staff, because again, this rush to get the dollars out, out the door. So having a system where I can easily, uh, ramp on new users and manage them without having to be solely dependent upon an already, uh, overworked it staff who were trying to support 37 other departments in the County, um, around infrastructure needs has been greatly helpful. Sounds to me like a strong outcome focus and one that seems to work. Let's move on now to our audience questions. We're getting close to the end of our time. So let's jump into some questions from the audience. A number of you have been asking about getting copies of today's presentation within the next 48 hours. Government technology will provide all attendees with the link to the recording for your reference, or to share with colleagues. Well, let's go to our first question. So this is an interesting one. And Karen, this is for you did IBM work with other counties and States to provide digital engagement portals. >>We did Bob, uh, we've worked, um, so globally we've provided guidance on this. We work closely with New York city. They've been the integral part of the development also with our citizen engagement offering. Um, we work closely with the States. So we worked with New York city. Um, North Carolina was also another state who, um, improved their, uh, citizen engagement piece, bring up their Medicaid and snap, um, applications along with Medicaid. COVID testing along that. And I mentioned, um, the economic and social development in Canada as well. And we also work with the ministry of social development in Singapore. So a number of our customers had put up, uh, a global, uh, or sorry, a citizen engagement frontend. And during this timeframe, >>Very helpful. I don't know how much did you hear your mom provide you, but how much did it cost for initial deployment and what are the ongoing costs in other words, is this thing going to be sustainable over time? >>Yeah, absolutely. So total, uh, to date, we've spent about a $1.8 million on development implementations and licensure. A big chunk of that again has been the rapid extended of licensure, uh, for this program. Um, I think over a third of that is probably licensing because again, we need to get the dollars out and we need staff to do that and making the short term several hundred thousand dollar investment in a professional support staff and having them be able to work this portal is much cheaper than the long-term investment of bringing on a staff, printing a job, uh, during a financial difficulty that we're facing, uh, the single largest fiscal cliff let's get into that us history. Um, so it's not smart to create jobs that have a 30 year, one way to retirement, uh, inside our in unionized government environment here. So having this, the staff that would come on and do this and get out the door on these federal dollars was critical for us. Um, and there is a $800,000 a year, I believe so ongoing costs associated with licensure and, and the programming support. Uh, but once again, we're going to be moving, um, our traditional services into this digital front end. We'll be continuing this because we're, we're, we're facing, it took us, I think, six and a half, seven years to come back from the previous recession. Undoubtedly, take a little longer to get back >>From this one. Here's another interesting question, I guess really primarily Tim Tim was the solution on primarily on premise or in the cloud. >>So we'll, we've done a mix. Uh, the, and I'm starting a lot of feedbacks. I don't know if you all can hear that or not, but the, uh, I think we went on prem for, uh, some people because of the, uh, bridge into our service case manager system, which is on prem. So we did some management there. I do believe the chat bot piece of it though is in the cloud. So we're bringing it down to, from one system to the other. Uh, and, and part of that was a student negotiations and costs and worrying about what long-term is that we have a very stated goal of moving, uh, our Curam platform, which is on-prem, this is the backend. So how are we? We, we set our IBM Watson, uh, portal up, uh, and moving all of that on cloud, uh, because I mean, we've got, uh, a workforce who, uh, has the ability to retire at a very high rate over the next five years. >>And, uh, having 24 seven support in the cloud is, is as a, someone who would be called to respond to emergency situations like the is, is a much better Cod deal for, for myself and the citizen. So migrating, uh, and, um, our typical on-prem stuff up into the cloud, uh, as we continue on this, uh, evolution of what IBM Watson, uh, and the plug into our Curam, uh, system looks like Karen related question for another user is the portal provided with Clara County and others linked to other third-party backend office apps, or can it be, >>Yeah, the answer is it can be it's interoperable. So through APIs, uh, rest, uh, however, um, assistance that they need to be integrated with can definitely be integrated with, uh, like, uh, Tim mentioned, we, we went to the case management solution, but it can be integrated with other applications as well. >>Tim, did you use some other backend third party apps with yours? Uh, we did not. Uh, again, just for speed of getting, uh, this MVP solution out the door. Uh, now what we do with that on the go forward, it is going to look different and probably will include some, another practical question. Given the cares funding should be expended by December. Can this application even be employed at this late date? And you want to take a cut at that? Yeah, for us, uh, once again, we brought up earlier, um, the emergency solutions grants and the community development block grants, which have a Corona virus, uh, CV traunch, each one of those, and those have two to three year expenditure timeframes on them. Uh, so we were going to leverage those to keep this system and some of these programs going once again, that the housing needs, uh, will outstrip our capacity for years to come. >>I guess probably I should have said upfront Las Vegas has one of the worst affordable housing inventories in the nation. Uh, so we know we're going to be facing a housing issue, um, because of this for, for a long time. So we'll be using those two traunches of dollars, ESE, ESPs, uh, CV CDBG, CB funds, uh, in addition to dollars earmarked through some, uh, recreational marijuana license fees that have been dedicated to our homelessness. And when you consider this housing, uh, stability program was part of that homelessness prevention. That's our funding mix locally. Very helpful. So questions maybe for bolts for you on this one, you can probably also teach respond is the system has been set up helping the small business community. Um, this user's been canvassing and the general feeling is that small businesses have been left behind and they've been unable to access funds. What's your response on that? Karen, do you want to take that first? >>Um, yes. So in terms of, uh, the security and sorry. Um, but, uh, can you repeat the last part of that? I just missed the last part when you >>Behind it, but unable to access funds. >>Uh, yeah, so I think from a funding perspective, there's different types of, I think what Tim mentioned in terms of the cares funding, there was different types of funding that came out from a government perspective. Uh, I think there were also other grants and things that are coming out one, uh, that we're still looking at. And I think as we go into the new year, it'll be interesting to see, you know, what additional funding, um, hopefully is, is provided. Uh, but in terms of creativity, we've seen other creative ways that organizations come together to kind of, uh, help with the different agencies, to provide some, some guidance to the community, um, and helping to, uh, provide efforts and, uh, maybe looking at different ways of, um, providing, uh, some of the capabilities that the, either at the County or at the state level that they're able to leverage. But Tim happy to maybe have you chime in here too. >>Yeah. So I'll first start with my wheelhouse and I'll expand out to, to some of my partners. Uh, so the primary, small business, we knew the idea was a daily basis inside this realm is going to be landlords. Uh, so actually this afternoon, we're doing a town hall with folks to be able to roll out, uh, which they will go to our portal to find a corporate landlord program. Uh, so that I seem a landlord for Camille the application pack and on behalf of a hundred residents, rather than us having to adjudicate a hundred individual applications and melon a hundred checks. Uh, so that is because we were listening to that particular segment of the, uh, the business community. Now I know early on, we were, we were really hoping that the, the paycheck protection program federally would have, uh, been dispersed in a way that helped our local small businesses. >>Uh, more we did a, our economic development team did a round of small business supports through our cares act. Uh, our quarterly unfortunate was not open yet. It was just about 15, 20 days shy. So we use, uh, another traditional grant mechanism that we have in place to dedicate that. Uh, but on a go forward board, willing to Congress passes something over the next 30 days, um, that if there's a round two of cares or some other programs, we absolutely now have a tool that we know we can create a digital opening for individuals to come figure out if they're eligible or not for whatever program it is, the it housing, the it, uh, small business operations supports, uh, and it would apply through that process and in a very lightweight, so we're looking forward to how we can expand our footprint to help all of the needs that are present in our community. This leads to another question which may be our last one, but this is an interesting question. How can agencies use COVID-19 as a proof point providing a low cost configurable solutions that can scale across government. Karen, do you want to respond to that? And then Tim also, >>Thanks, Bob. So I believe like, you know, some of the things that we've said in terms of examples of how we were able to bring up the solution quicker, I definitely see that scaling as you go forward and trying to really, um, focus in on the needs and getting that MVP out the door. Uh, and then Tim alluded to this as well. A lot of the change management processes that went into re-imagining what these processes look like. I definitely see a additional, you know, growth mindset of how do we get better processes in place, or really focusing on the core processes so that we can really move the ball forward and continuing to go that path of delivering on a quicker path, uh, leveraging cloud, as we mentioned of, um, some, some of the capabilities around the chat bot and other things to really start to push, um, uh, the capabilities out to those citizens quicker and really reduce that timeline that we have to take on the backend side, um, that that would be our hope and goal, um, given, you know, sort of what we've been able to accomplish and hoping using that as a proof point of how we can do this for other types of, uh, either programs or other processes. >>Yeah, I think, um, the, you know, the tool has given us capability now there, whether we use local leaders leverage that to the fullest really becomes a coming upon us. So do we take a beat, uh, when we can catch our breath and then, you know, work through our executive leadership to say, look, here's all the ways you can use this tool. You've made an enterprise investment in. Um, and I know for us, uh, at Clark County, we've stood up, uh, enterprise, uh, kind of governance team where we can come and talk through all of our enterprise solutions, uh, encourage our other department head peers, uh, to, to examine how you might be able to use this. Is there a way that, um, you know, parks and rec might use this to better access their scholarship programs to make sure that children get into youth sports leagues and don't get left out, uh, because we know youth suicide on the rise and they need something positive to do when this pandemic is clear, I'm there for them to get out and do those things. >>So the possibilities really are out there. It really becomes, um, how do we mind those internally? And I know that being a part of listservs and, uh, you know, gov tech and all the magazines and things are out there to help us think about how do we better use our solutions, um, as well as our IBM partners who are always eager to say, Hey, have you seen how they're using this? Um, it is important for us to continue to keep our imaginations open, um, so that we continue to iterate through this process. Um, cause I, I would hate to see the culture of, um, iteration go away with this pandemic. >>Okay. We have time for one final question. We've already addressed this in part two, and this one is probably for you and that you've used the cares act to eliminate some of the procurement red tape that's shown up. Well, how do you somehow that's been very positive. How do you see that impacting you going forward? What happens when the red tape all comes back? >>Yeah, so I think I mentioned a little bit, uh, about that when some of the folks who are deemed non essential came back during our reopening phases and they're operating at the speed of prior business and red tape where we had all been on this, these green tape, fast tracks, uh, it, it was a bit of a organizational whiplash. Uh, but it, for us, we've had the conversation with executive management of like, we cannot let this get in the way of what our citizens need. So like keep that pressure on our folks to think differently. Don't and, uh, we've gone so far as to, uh, even, uh, maybe take it a step further and investigate what had been done in, in, in Canada. Some other places around, um, like, like going right from in a 48 hour period, going from a procurement statement through a proof of concept and doing purchasing on the backside, like how can we even get this even more streamlined so that we can get the things we need quickly, uh, because the citizens don't understand, wait, we're doing our best, uh, your number 3000 and queue on the phone line that that's not what they need to hear or want to hear during times of crisis. >>Very helpful. Well, I want to be respectful of our one hour commitment, so we'll have to wrap it up here in closing. I want to thank everyone for joining us for today's event and especially a big, thank you goes to Karen and Tim. You've done a really great job of answering a lot of questions and laying this out for us and a special thanks to our partners at IBM for enabling us to bring this worthwhile discussion to our audience. Thanks once again, and we look forward to seeing you at another government technology event,

>>from around the globe. It's the Cube presenting Cuban Cloud brought to you by Silicon Angle. >>Welcome back to the Cubes. Special Presentation on the Future of Cloud. Three years ago, Alan Nance said to me that in order to really take advantage of Cloud and Dr Billions of dollars of value, you have to change the operating model. I've never forgotten that statement have explored it from many angles over the last three years. In fact, it was one of the motivations for me actually running this program for our audience. Of course with me is Alan Nance. He's a change agent. He's led transformations that large organizations, including I N G Bank, Royal, Philips, Barclays Bank and many others. He's also a co founder of Citrus Collab. Alan, great to see you. Thanks for coming on the program. >>Thanks for having me again there. >>All right. So when we were preparing for this interview you shared with me the following you said enterprise, I t often hasn't really tapped the true powers that are available to them to make real connections to take advantage of that opportunity. Connections to the business, That is What >>do >>you mean by that. >>Well, I think, you know, we've been saying for quite a long time that enterprise. It is certainly a big part of our past in technology. But you know, just how much is it going to be in the future on, you know, enterprise, I t has had a difficult time under The pressure's off being a centralized organization with large expanse of large Catholics, while at the same time we see obviously the digital operations growing oftentimes in separate reporting structures and closer to the business on. And what I'm thinking right now is enterprise i t. If it has made this transition to cloud operating models, whether they are proprietary or whether they are public cloud, there's a huge opportunity for enterprise. I t. Thio connect the dots in a way that no other part of the organization can do that. And when they connect those dots working closely with the business, they unleash a huge amount of value that is beyond things like efficiency or things like just just just providing cloud computing to be flexible. It has to be much more about value generation. Andi. I think that a lot of leaders of enterprise I t have not really grasped that, Andi. I think that's the opportunity is sitting right in front of them right now. >>You know what I've seen lately? I wonder if you could. Comment is You know, obviously we always talk about the stove pipes, but you've you've seen, you know, the CEO, >>the chief >>data officer that you just mentioned the chief digital officer, the chief information security officer. They've largely been in their own silos. I'm definitely seeing a move to bring those together. I'm seeing a lot of CDOs and CEO roles come together and even the chief information or the head of security reporting up into that where there's there seems to be as your sort of suggesting just a lot more visibility across the entire organization. Is it Is it an organizational issue? Is it? Ah, is it a mindset? But only if you could comment. >>Well, I would say it zits, two or three different things, but certainly it's an organizational issue. But I think it starts off with a cultural issue. Andi, I think what you're seeing, and if you look at the more progressive companies that you see, I think you are also seeing a new emergence off the enlightened technology leader s O. With all respect to me and my generation, our tenure as the owners off the large enterprise, it is coming to an end. And we grew up trying to master the complexity of the off the silos. As you so definitely pointed out, we were battling this falling technology, trying to get it under control, trying to get the costs down, trying to reduce Catholics. And a lot of that was focused on the partnerships that we had with technology suppliers on DSO. That mindset of being engineers struggling for control. Having your most important part of being a technology company itself that now I think is giving way is giving way to a new generation of technology leaders who haven't grown up with that culture. Onda. Oftentimes what I see is that the new enlightened CEOs are female, and they are coming into the role outside of the regular promotion change. So they're coming to these rolls through finance H R marketing on their bringing. A different focus on the focus is much more about how do we work together to create an amazing experience for our employees and for our customers on an experience that drives value. So I think there's a reset in the culture. And clearly, when you start talking about creating a value chain to improve experience, you're also talking about bringing people together from different multidisciplinary backgrounds to make that happen. >>Well, that's kind of, you know, it makes me think about Amazon's mantra of working backwards. You know, start with the experience and and and a lot of a lot of CEOs that I know would love tow beam or involved in the business. But they're just so busy trying to keep the lights on like you said, trying to manage vendors. And like, you know, I had a discussion the other day, Allen with an individual. We were talking about how you know, you got a shift from a product mindset to a platform mindset. But you know, you've said that that platform thinking you're always ahead of the game platform, thinking it needs to make way for ecosystem thinking, you know, unless you're Internet giant scale business like Amazon or Spotify, you said you're gonna be in a niche market if you really don't tap that ecosystem again. If you could explain what you mean by that. >>I think right now if this movement to experience is fundamental, right? So Joe Pine and Gilmore wrote about the experience economy as far back in 1990. But the things that they predicted then are here now. And so what we're now seeing is that consumers have choice. Employees have choice. I think the pandemic has accelerated that. And so what happens when you, when you when you put an enterprise under that type of external pressure, is that it fragments and even fragment into ways it can fragment dysfunctional E so that every silo tries to go into a a defensive mode protective mode? That's obviously the wrong way to go. But the fragmentation that's exciting is when it fragments into ecosystems that are actually working together to solve an experience problem. And those are not platforms. They're too big, you know, When I was Phillips, I was very enthusiastic about working on this connected health care platform, but I think what I started to realize was it takes too much time. It requires too much investment on you are bringing people to you based on your capability. Where is what the market needs is much more agile than that. So if we look in health care, for instance, and you want to connect patients at home with patient with the doctors in the hospital, in the old model you so I'm gonna build a platform for this. I'm gonna have doctors with a certain competence and they're gonna be connecting into this. And so are the patients in some way. And so are the insurers. I think what you're going to see now is different. We're going to say, Let's get together A small team that understands it's called, For instance, let's get a an insurance provider. Let's get a health care operator. Let's get a healthcare tech company on. Let's pull their data in a way that helps us to create solutions now that that can roll out in 30 60 or 90 days. And the thing that that makes that possible is the move to the public crowd because now there are so many specialized supplier, specialized skill sets available that you can connect to through Amazon through Google, through through azure that that these these things that we usedto I think we're very, very difficult are now much easier. I don't want to minimize the effort, but these things are on the table right now. Thio Revalue. >>So you're also a technologist and I wanna ask you and and everybody always says, it's the technology is easy part. It's the people in the process and, you know, way we can all agree on that. However, sometimes technology could be a blocker. And the example that you just mentioned, I have a couple of takeaways from that. First of all, you know the platform thinking it sounds like it's more command and control, and you're advocating for Let's get the ecosystem who are closest to the problem. To solve those problems, however, they decide and leverage the cloud. So my question is from a technology standpoint, does that echo have system have to be on the same cloud with the state of today's technology? Can it be across clouds can be there pieces on Prem? What's your thinking on that? >>I think I think exactly the opposite. It cannot be monolithic and centralized. It's just not practical because that was that was that would cause you too much time on interoperability and who owns what you see The power behind experience is data. And so the most important technical part of this is dealing with data liquidity. So the data that for instance, um, somebody like Kaiser has or the the Harvard Health Care have or the Philips have that's not going to be put into a central place. But for the ecosystem mobilization, there will be subsets of that data flowing between those parties. So the technical, the heart there is how do we manage data liquidity? How do we manage the security around the data liquidity on How do we also understand that what we're building is going to be ever changing and maybe temporary, because on idea may not work, eh? So you've got this idea that the timeliness is very, very important. The duration is very uncertain. The motor the energy for this is data liquidity data transfer, data sharing. But the vehicle is the combination off. Probably crowd in my mind. >>Somebody said to me, Hey, that data is like water. It'll go. It'll go where it wants to go where it needs to go. You can't try to control it. It's let it go. Uh, now, of course, many organizations, particularly large incumbent organizations there. They have many, many data pipelines. They have many processes, many roles, and they're struggling toe actually kind of inject automation into those pipelines. Maybe that's machine intelligence, uh, really doom or data sharing across that pipeline and and ultimately compress the end and cycle. Time to go from raw data insights that are actionable. What are you seeing there and what's your advice? >>Well, I think the the you make some really good points. But what I hear also a little bit in your observation is you're still observing Enterprises on the end of the focus of the enterprise has been on optimizing the processes within the boundaries of its own system. That's why we have s a P. And that's why we have a sales force and, to some degree, even service. Now it's all been about optimizing how we move data, how we create products and services on. That's not the game. Now that's not an important game. Three important game right now is how do I connect to my employees? How do I connect to my customers in a way that provides them a memorable experience? And the realization is we've seen this already a manufacturing for some years. I can't be allowed things to people. So I have to understand where the first part of data comes in. I have to understand who this person is that I am trying to target. Who is the person that needs this memorable experience on what is that memorable experience gonna look like? And I'm going to need my data. But I'm also going to need the data of other actors in that ecosystem. And then I'm gonna have to build that ecosystem really quickly to take advantage off the system. So this throws a monkey wrench in traditional ideas of standardization. It throws a monkey wrench in the idea that enterprise I t is about efficiency on. But if I may, I just want to come back to the day I because I think we're looking in the wrong places. Things like a I let me give you an example. Today there are 2.2 million people working in call centers around the world. If we imagine that they work in three shifts, that means that any one time there are 700,000 people on the phone to a customer on that customer is calling that company because they're vested. They're calling them with advice. They're calling them with a question. They're calling them with a complaint. It is the most important source off valuable data that any company has. And yet what have we done with that? What we've done with that is we have attacked it with efficiency. So instead of saying these are the most valuable sources of information, let's use a I to to tag the sentiment in the recordings that we make with our most valuable stakeholders on this and analyze them for trends, ideas, things that need to change. We don't do that. What we do is we were going to give every call agent two minutes to get them off the phone. For God's sake, don't ask so many import difficult questions. Don't spend money talking to the customer. Try to make them happy so they get a score and say they hire you at the end of the core and then you're done. So so where the AI and automation needs to come in is not in improving efficiency but in mining value. And the real opportunity with a I Is that Joe Pine says this. If you are able to understand the customer rather than interpret them, that is so valuable to the customer that they will pay money for that. I think that's where the whole focus needs to be in this new teaming of enterprise I t. And that's true business. >>It's a great observations. I think we can all relate to that in your call center example, or you've been in a restaurant. You're trying to turn the tables fast and get you out of there. And that's the last time you ever go to that restaurant and you're you're taking that notion of systems thinking and broadening it to ecosystems thinking. And you've said ecosystems have a better chance of success when they're used to stage an experience for whether it's the employees for the brand and of course, the customer and the partners. >>That's it. That's exactly yet. So every technology leader should be asking themselves what contribution can can my and my organization makes of this movement because the business understands the problem, they don't understand how to solve it, and we've chosen a different dialogues. We've been talking a lot about what cloud could do and the functionality that clown has and the potential that clown has on those aerial good things. But it really comes together now when we work together and we, as the technology group brings in, they know how we know how toe connect quickly through the public cloud. We know how to do that in a secure way. We know how to manage data, liquidity at scale, and we can stand these things up through our, you know, our new learning of agile and devils we can stand. These ecosystems are fairly quickly now. There's still a whole bunch of culture between different businesses that have to work together through the idea that I have to protect my data rather than serve the customer. But once you get past that, there's a whole new conversation enterprise. It you can have that, I think, gives them a new lease of life, new value. And I just think it's a really, really exciting time. Yes, >>so you're seeing the intersection of a lot of different things. You talk about cloud as you know, an enabler for sure, and that's great. We could talk about that, but you've got this what you're referring to before is, you know, maybe you're in a niche market, but you have your marketplace and like you're saying, you can actually use that through an ecosystem to really leave her a much, much broader available market and then vector that into the experience economy. You know, we talk about subscriptions, the AP economy. That really is new thinking, >>yes, and I think what you're seeing here is it zits, not radical. Inasmuch as all of these ideas have been around, some of them have been around since the nineties. But what's radical is the way in which we can now mix and match these technologies to make this happen. That's gone so quickly on, I would argue to you, and I've argued this before. Scale scale is a concept within an organization is dead. It doesn't give you enough value. It gives you enough efficiency, and it gives you a cloud. But it doesn't give you three opportunity to target the niche experiences that you need to do. So. If we start to think off an organization as a a combination off known and unknown potential ecosystems, you start to build a different operating model, a different architectural idea you start to look outside more than you start to look insight. Which is why the cultural change that we were talking about just now goes hand in hand with this because people have to be comfortable thinking in ecosystems that may not yet exist on partnering with people where they bring to the table there, you know, 2030 years of experience in a new and different way. >>Let me make sure I understand that. So you're basically if I understand you're saying that if you're sort of end goal is scale and efficiency at scale, you're you're gonna have a vanilla solution for your customers and your ecosystem. Whereas if you will allow this outside in thinking to come in, you're gonna be able to actually customize those experience experiences and get the value of scale and efficiency. >>Right? So, I mean, Rory Sutherland, who is ah, big finger in the in. The marketing world has always said, ultimately, scale standardization and best practice lead to mediocrity because you are not focused on the most important thing for your employees or your brand, or you're you're focused on the efficiency factors on. They create very little value in fact, we know that they subvert value. So, yes, we need to have a very big mindset change. >>Yeah, You're a top line thinker, Allen. And and always at the forefront. I really appreciate you coming on to the to the Cuban. Participate in this program. Give us the last word. So if you're a change agent, I wanna I'm an organization, and I want to inject this type of change. Where do I >>start? Well, I think it starts by identifying. Are we going to? Is it are we gonna work on the employee experience? Do we feel that we have a model where the employees that are on stage with customers are so important that the focus has to be employees? We go down that route and we look at what happened to the pandemic. What type of experiences are we going to bring to those employees around their ability to have flow in their work, to get returned on energy, to excite the customers? Let's do that. Let's figure out what experience are we driving now? What does that experience need to be if we're the customer side? As I said, let's look ALS. The sources of information that we already have. You know, I know companies to spend hundreds of millions a year trying to figure out what consumers what. And yet if we look in their call centers, you will call up and and they will say to Your call may be recorded for quality purposes and training on this is not true. Less than 10% of those calls that ever listened to on if they are listening to its compliance that's driving that, not the burning desire to better understand the consumer. So if we change that, then we say Okay, so what can we change? What is the experience that we are now able to stage with all we know and with all weaken dio on debts? Start there. Let's start with what is the experience you want to stage? What's the experience landscape look like now? And who do we bring together to make that happen? >>Allen. Fantastic. Having you back in the Cube, it's always a pleasure. And, uh, and thanks so much for participating. >>Thank you, Dave. It's always a pleasure to speak with you. >>Thank you. Everybody, this is Dave Volonte. The Cuban cloud will be right back right after this short break. Stay with

>>From around the globe. It's the cube with digital coverage of AWS reinvent 2020 sponsored by Intel and AWS. >>Welcome back to the cubes live coverage of AWS reinvent 2020 I'm Lisa Martin and I have with me a cube alumni back, please. Welcome Scott Mullins, the worldwide financial services business development leader at AWS. Scott. Welcome back. Great to have you joining us, >>Lisa. It's great to be back on the cube and to be visiting with you today from virtual re-invent 2020. >>Yes. Reinventing reinvent. The last show that I got to host in-person for the cube was reinvent last year. And here we have this three week virtual event that started last week. So lots more even going on. I think I even saw a hundred thousand or so registered, so massive event, lots of news. So walk us through some of the highlights that have been announced at reinvent this year and some of the things that you're seeing the most interest from customers in. >>Well, I think one of the big highlights is 500,000 registrants that are reinvented 50,000 attendees last year to reinvent or 50,000 or so to 500,000 re registered for the event. So that's, that's, that's worth talking about in its own. Right. But I think, you know, one of the things, and you mentioned this, you know, more re-invent three weeks, uh, this year, as opposed to the four days that we normally spend in Las Vegas together, physically, when you do, when you do it digitally, you have the ability to actually include more things and more leaders talking about things. And so when we think about the announcements that are having impacts, uh, with financial services customers specifically I'd point to a couple of things and, you know, they're obviously gonna mention Andy's keynote, but there's going to be some things that you might go wait a minute. >>I didn't even see that announcement. Uh, and then maybe I could point you and the viewers to some other, other, um, keynotes or some other sessions that were announced. So obviously I think, uh, first and foremost in Andy's keynote, uh, hybrid, uh, was something that was a very, uh, big focus for him and I for a very long time, we've had the messaging of the right tool for the right job when it comes to any of your services. I think you could alter that today to say it's the right tool for the right job at the right time and in the right place. That makes sense for you and especially for financial institutions. Um, you could look at the announcements around containers, the announcements around Amazon EKS, distro, Amazon EKS, anywhere, and then also Amazon ECS anywhere, which allows our customers to actually, uh, put AWS container technology anywhere they would like to put it. >>You could look also at the additions of the one you and two you form factors to outposts. So no longer do you have to do the, the, the large for you, uh, foreign factor for outposts, smaller outposts for smaller spaces, uh, that particular will play well in the financial service industry. You may not have necessarily as much room for a full cabinet. You could also look from the hybrid perspective in the announcement we made, um, around red hat OpenShift on AWS, all of are giving customers the ability to choose how they actually want to deploy, um, and pursue a hybrid. I'd also point to some announcements we made around management and governance in the financial services, industry governance, uh, is a very important topic. Uh, we announced the management and government lens for the AWS well architected, um, uh, program, uh, that is focused on breath practices for evolving governance for the cloud. >>It has recommended combination of AWS services integrations with our partner network and vetted reference architectures and guidance for addressing regulatory obligations as well. I'd also point to some things we made around audits. I was specifically in Steve Smith's, um, session today, he talked about AWS audit manager. That's a new tool for continually assessing areas and environments for controls or risk compliance. That includes prebuilt compliance frameworks for things like PCI DSS and GDPR, uh, two things that are very important in the financial services industry and last, but certainly not least I'd point to the announcement around the AWS audit Academy. This is training for auditors to actually be able to audit clouds from an agnostic perspective. Any cloud, not specifically AWS that's tree, uh, digital training to do that. And then also an instructor led course specifically on how to audit AWS. So some very key announcements, both from the standpoint of services, uh, as well as additional layers of helping customers in the financial services industry in regulated industries actually use our services. >>So typical, re-invent typical in a lot of news, a lot of announcements, the 500,000 Mark in terms of registering. I hadn't heard that. That's amazing. Let's talk that this has been an Andy. Jassy had an exclusive with John furrier just a couple of weeks ago before. I think it was last week, actually. And we've been talking about this acceleration of digital business transformation because of COVID we've been talking about it, the entire pandemic on the virtual cube, talking about how companies it's really about right now, surviving and thriving to be able to go forward and companies that haven't accelerated are probably in some trouble. Talk to me about how AWS has been working with your financial services customers to help them pivot and move to the cloud faster, really to not just help them survive now, but thrive in the long-term. >>Yeah. Immediately when COVID hit and it hit at different times in different, in different parts of the world. Immediately when COVID hit, we saw the conversation that we were having turning from, Hey, what's my digital strategy to immediately, what are my digital capabilities? And what that really means is what do I have the ability to do tomorrow? Because tomorrow is going to really matter. I don't have necessarily the time to plan for the next several quarters or the next several years, what can I do tomorrow to, um, really, uh, support my, my own workforce and support my own customers and the obligations I have as a financial institution. The first thing we saw people do was to try and make sure that those who financial services work can work. You can look at the adoption of Amazon workspaces, as well as our, uh, Amazon connect, uh, call centers as a service. >>As two examples there at the RBL bank in India was able to move to Amazon workspaces in just 10 days to enable its teams to actually work remotely from home. When they couldn't come into the office, you can look at Barclays. Barclays is actually a presenter at re-invent this year. They'll have a session on how they use Amazon connect, which again is our call center as a service offering to enable 25,000 contacts and our agents to work from home when they can no longer work out of the, out of their traditional contact center. The second thing we saw a financial institutions joining was making sure that customer engagements could still be meaningful when digital was the only option, um, specifically here in the U S you could look at the work that each of us did with FinTech companies like biz two X or fins Zack, or BlueVine Stripe and cabbage in support of the care act in the U S you might remember that the cares act, um, hasn't provisions for funding for small businesses. >>This small business administration had a program called the paycheck protection program, and those organizations were active in providing funding, uh, to small businesses. Uh, through that program. I'll give you an example of cabbage cabbage had previously not been an SBA lender, um, but they were able to, in two weeks build a fully automated system for small businesses to access PPP funding using Amazon text track, to extract information from documentation that those folks submitted to get alone. That reduced approval times from multiple days to about a median of four hours to actually get approval, to get funding through the PPP program. And then just four months cabbage became the second largest PPP lender. They lent over $7 billion in funding, which was twice the amount of funding that they went last year in 2019 loans. So we were happy to support organizations like cabbage and those other FinTech companies, as they help small businesses in the U S get access to funding, uh, during this critical time. >>And as we know, as you said, critical time, but really life or death for a lot of businesses. And as we continue to go through these ways, but it's interesting that you talked about that the speed of facilitation that during such unprecedented times, AWS and this massive machine was able to continue moving at full speed ahead and helping those customers to pivot. You talked about the cloud connect. I had a conversation with a guest on the queue last week about that. And, and I now think about if I have to call in a contact center and that person might be from home. So, you know, we're fortunate that the cloud computing technology and people like you and AWS, or are able to power that because it's, it's literally essential, which is probably one of the words of the year, but being able to keep the machinery going and innovate at the same time has been, make or break for a lot of businesses. >>Absolutely. And you, you look at, you know, kind of one of the last year is that I'll point to is, um, financial institutions. Uh, anti-virus, we're were very much focused on making sure that that cannot fail, that they scaled. And so you can look at the work we did with, uh, with the, with FINRA FINRA is the primary capital markets regulator here in the U S and on a daily basis frame or processes about 400 billion market events on every night to do surveillance on our markets, that when COVID hit, we had unprecedented volume and volatility in the market. And FINRA was, was, um, looking at processing, uh, anywhere from two to three times, their normal daily market volumes that's anywhere from 800 billion market events to 1.2 trillion a night. And if you look at how they were able to scale, they're actually able to scale up compute resources in AWS. We're on a nightly basis. They're able to automatically turn on and off up to a hundred thousand compute nodes in a single day. That automatic ability to scale is, is the power you're talking about. Being able to actually turn things up when you needed it and turn things down when you, when you don't need it based on the volumes. >>Well, and that's going to be something key going forward. As we know that there will be one thing I think that I always say we can count on right now is uncertainty and continued uncertainty, but we've also seen I'm calling them COVID catalysts. You know, the, what you talked about with cabbage, for example, and how that business pivoted quickly, because of the power of cloud computing and emerging technologies, what are some of the things that you think as we go into 2021 in the financial services arena, what are some of the big tech trends that you think were maybe born during COVID that are going to be critical going forward? >>Well, you know, you, you, you had Melanie Frank from capital one on cube a couple of days ago, and she was talking about, you know, their shift to cloud and what that's really enabled, and it, and she kind of sums it up nicely. She says, look, we want to give our customers experience that are real time, and that are intelligent. And you just can't do that with legacy technology. That's sitting in, you know, kind of a legacy data center. And so I think that's going to be kind of the, the, the all encompassing statement for what's happening in the financial services industry. As I mentioned, you know, organizations overnight said, okay, wait a minute, let's take that strategy. And then let's put it aside. Let's talk about capabilities. What can we do? And I think, you know, necessity is the mother of invention. Um, and when you're faced with limitations and challenges, like we all have been faced with around the world and not just in the financial services industry, it, it breeds, um, invention and the, and the desire and the need to actually meet those challenges head on, in very engineered of ways. >>And I think you're going to see more invention and specifically more invention from the established players in the financial services industry. Cloud use is not just experimental on the edges anymore. You're going to see more organizations coming out of COVID. Um, having had those experiences where they actually stood up a context center and scaled it. And, and just a matter of a few days to, to thousands of agents, you're going to find, um, organizations saying, wait a minute, we, we can do remote work. We could, we have access to things like Amazon workspaces. So I think you're, you're gonna, you're going to see that, uh, be a, be a trend. I think you're also gonna see, um, w what Lori beer said in the keynote with Andy, you know, she, she made a very, very astute statement, and I don't know if people caught it, cause it's kind of neat in the middle of her conversation. >>She said, look, we're trying to infuse analytics into everything that we do at JP Morgan. I think you're going to see more and more financial institutions looking to do that, to actually leverage the power of analytics, to power everything we do as a financial institution. So I think those, those are a couple of things that you're going to see. Um, and then, you know, looking, uh, you know, kind of around the corner, I think you're going to continue to see more re-invention within the industry. And what I mean by that is you've seen many financial institutions over the last week, uh, with, uh, re-invent making announcements, you saw bank and we towel saying, Hey, look, we are completely transforming ourselves with AWS. Uh, just a few weeks before we even saw standard charter, the same thing HSBC said, the same thing, global payments earlier in the year said the same thing. And you're going to see more and more organizations coming out and talking about these strategic decisions to reinvent everything that they do to make the financial systems of the world work. And so we're really pleased to be partnering with those organizations to make those transformations possible. We're seeing a lot of invention within the industry, and we're very pleased to be a part of the reinvention of the financial systems around the world. >>It's interesting to hear that you, you see, even the JP Morgan, some of those legacy, big houses are going to be really pivoting. They have to, to be competitive and to be able to utilize analytics, to deliver those real-time services. Because as we all know, as consumers, our patients is wearing thin these days, but I agree with you. I think there's a lot of opportunity there that innovation is exciting and there will have to be reinvention of entire industries, but I think there's a lot of silver linings there. Scott. I wish we had more time, cause I know we could keep talking, but thank you for sharing your insights on this reinvented reinvent this year. >>I appreciate it. Thank you, Lisa. It's always a pleasure to be on the cube. >>Chris Scott Mullins, I'm Lisa Martin. You're watching the cubes coverage of AWS reinvent 2020.

>>from around the globe. It's the Cube with digital coverage of Miranda's launchpad 2020 brought to you by more antis. >>Hi, I'm stupid man. And this is the cubes coverage of Miran Tous Launchpad 2020. Happy to welcome to the program First time guest William Do places. He's the head of customer success in operations with Miran Tous William. Thanks so much for joining us, >>Steve. Thanks for two. Thanks for having me. >>Yeah, why don't we start with a little bit? You know, customer success operations. Tell us what that's entail, What's what's under your purview, Right? >>So is everything basically, you know, post sales, right? So after a customer has portions, their their subscription, we basically take it from there Going forward, you know, looking after the relationship with the customer, ensure they you know, the whole, you know, subscription fulfillment element off it. Whether that is just bored with that is to cut the relationship management from a post sales perspective and so on, so forth. So that is basically into end from the point off purchase to the renewal face. Would would would fall with any supporting operations. >>Well, that's such an important piece of the whole cloud conversation. Of course, people, you know, we talked for such a long time cap ex op X. We talk about descriptions and manage services. Of course, has been a riel. You know, growth segment of the market place. Love to hear a little bit, you know, What are you hearing from your customers? And, you know, give us the lay of the land As to the various options that that that Miranda is offering today and we'll get into any of the new pieces also. >>Yeah. So the the the options that we're making available for our customers primary called Prod Care, which is a 24 7 mission critical support subscription. Andi Ops Care, which is a fully managed service offering. Um, what we hear from our customers is is, you know, the the the notion of having a development environment and a production environment with different, you know, sls and entitlements and so on. You know that that that notion is disappearing because your divots chain or pipeline is all connected. So you could just think for yourself. If you have a group of developers like 50 or 100 or 1000 developers that are basically standing there still, because they cannot push code because there's a problem or a new issue on the development cloud. But the development cloud is not. Beings is not seen or is treated as a mission critical platform. You know, those developers are standing date stole, so that is a very expensive problem for a customer at that point in time, so that the whole chain, the whole pipeline that makes part off your your develop cycle, should be seen as one entity. And that's what we've seen in the market at the moment that we're realizing with a large customers that are really embracing the kind of the approach to modern applications. Andi. This is why we're making these options available. Thio, our Doctor Enterprise customers We've been running with them for quite a while on the on the Miranda's cloud platform, which is our Infrastructures service offering on. We've had some great success with that, and we now in a position to make that available to our customers. So it's really providing a customer that true enterprise mission critical regardless of time off they the day of the week availability off support whether that is a my question or whether that is really an outage or a failure. You know, you know, you've got that safety net that is that is online and available for you. Thio to sort Whatever problem you have about, you know, that is from the support perspective, you know. And if we go over into the manage service offering we have for on up Skate that is a really hardened Eitel based, um infrastructure or platform as a service offering that we provide eso. We've had some great success. Like I said on the on the Miranda's cloud platform Peace. And we're now making that available for Doc Enterprise customers as well. So that is taking the whole the whole chain through. We look after the the whole platform for the customer and allow the customer to get on with what is important to them. You know, how do they develop their applications? You know, optimize that for their business instead, off spending their times and keep spending their time on keeping the lights on, so to speak, you know? So we take care of all of that. They have that responsibility over to us on DWI. We manage that as our own and we basically could become an extension of their business. So we have a fully integrated into the environment, the whole logging and not monitoring piece we take over the whole life cycle. Management off the environment. We take over, we do the whole change Management piece Incident Management Incident Management piece on. This whole process is truly transparent to the customer. At no point are they, you know, in the dark what's going on where we're going and we have the and the whole pieces wrapped around Bio customer success Manager which is bringing this whole sense off ownership Onda priority. That customer, you've got a single point of contact that is your business partner and that the only piece, the only metric that that individuals measured on is the success off that customer with our our product. So that in a nutshell, at a very high level what these are. But these offerings are all about >>well, we all know these days how important it is toe, you know, make your developers productive. It's funny listening to you, I think back to the Times where you talked about making sure that it's mission critical environment You know, years ago it was like, Oh, well, the developer just gets whatever old hardware we have, and they do it on their own. Now, of course, you know you want Dev in production toe have a very similar environment. And as you said, those manage services offering and be, you know, so important because we want to be able to shift left, let my platform let my vendors take care of some of the things that's gonna be able to enable me to build my new applications toe, respond to the business and do. In fact, I don't want my developers getting bogged down. So do you have any, You know, what are some of the successes there? How do your customers measure that? They Hey, I'm getting great value for going to manage service. Obviously, you know, you talked about that, That technical manager that helps them there. Anybody that's used, you know, enterprise offerings. There's certain times where it's like, Hey, I use it a lot. Other times it's it's just nice to be there, but, you know, why do you bring us in a little bit? Some of the customers, obviously anonymous. You need Teoh you know, how do they say, You know, this is phenomenal value for my business. >>Yes, it's all. It's all about the focus, right? So you're the customer. 100% focus on what is like I said, important to them, they are not being distracted at any point for, you know, on spending time on infrastructure related or platform related issues they purely focused on. Like I said, that is, that is important to their business. Andi, The successes that we see from that it is, is that we have this integration into into our customers like a seamless approach. We work with them is a true, transparent approach to work with our customers. There's a there's an active dialogue off what they developers want to see from the environment, what the customers want to see from from from the environment, what is working well, what we need to optimize. And that is really seeing ah, really good a approach from from from us and we're seeing some some great successes in it. But it all comes down to the customer is focusing on one thing, and that is on what is important to them on. But is there business instead off. You know, like you said, focusing on the stuff that shoot me, that that should be shift left. >>Yeah. And will, um, is there anything that really stands out when you talk about that? The monitoring that you in the reporting that you give the customers Is it all self serve? You know, how did they set that up and make sure that I'm getting valuable data. That's what what my company needs. >>Yes. So that is where your custom success manager comes in is really how to customize that approach to what fit for the customers. So we've got it in the background, very much automated, but we do the tweaks Thio customize it for for the customer that makes sense for them. Some customers want to see very granular details. Other customers just want a glance over it and look at the the high level metrics what they find important. So it is finding that balance and and understanding what your customer find important, and then put that in a way that makes sense for them Now. That might sound might sound kind of obvious, but it's more difficult than you think to put data from the customer That makes sense to them, uh, in their in their context. And then, you know, be in a position where you can take the information that you receive and give your customer the the runway to plan their the application. You know, where are they trending? So be able. Dutilleux. Look. 3452 quarters 345 months to quarters ahead to say this is where you're going to be. If you continue down this path, we might need to look at shifting direction or shift workload around or at Resource is or or, you know, depending on the situation. But it's all about having that insight going forward, looking forward. Rather, um, instead off, you know, playing things by year end, looking, looking at the year. And now because then that ISS that is done and dusted, really. So it's all about what is coming down the line for us and then be able to to plan for it and have an educated conversation of with with with your customer where they want to go. >>You mentioned that part of this offering is making this available for the Docker Enterprise base. Uh, maybe, if you could explain a little bit as to you know, what's gonna be compelling for for those customers. You know what Laurentis is has built specifically for that base? >>Yeah. So, like I said, this is an offering we have available on our Miranda's cloud platform for quite a while. You've seen some great success from it. Um, we're making it now available for the Doctor Enterprise customers. So it is really a true platform as a service offering, um, on your infrastructure of choice, whether that is on prim or whether that is on public cloud, we don't really care. We'll work with customers whichever way it is. And yeah, Like I said, just give that true platform as a service experience for our customers, Onda allow them to to focus on what's important to them. >>Alright, let me let you have the final word. Will tell us what you want your customers to understand about Iran tous when they leave launchpad this year. >>Yeah, So the main thing the main theme that I want to leave with is is that you know, the the we've made significant progress over the last 62 229 months on the doc enterprise side on. We're now in a position where we're taking the next step in making these offerings available for our customers, and we're really for the customers. That's the handful of custom that we have already. My greater to these offerings with getting some really good feedback from them on it is really helping them just thio thio just to expedite. They they, you know, wherever they're gonna go, whatever they want to want to achieve the, you know, expedite, think goals on bond. It is really there to ensure that we provide a customer or customers a true, um, you know, mission critical feeling, uh, giving them the support they need when they needed at the priority or the severity or the intensity that they need as well as they provide them. The ability to to focus on what is important to them on board. Let us look after the infrastructure and platform for them. >>Well, well, okay. Congratulations on Although the work that the team's done and definitely look forward to hearing more in the future. >>Excellent. Thank you very much for your time. >>Be sure to check out all the tracks for Miranda's launchpad 2020 of course. Powered by Cuba 3. 65. Got the infrastructure. The developers Lots of good content. Both live and on demand. And I'm still minimum. Thank you for watching. Thank you.

>> Announcer: From around the globe, it's theCUBE with coverage of KubeCon + CloudNativeCon Europe 2020 Virtual brought to you by Red Hat, the Cloud Native Computing Foundation and Ecosystem partners. >> Welcome back I'm Stu Miniman, this is theCUBE's coverage of KubeCon + CloudNativeCon Europe 2020, the virtual event. Of course, when we talk about Cloud Native we talk about Kubernetes there's a lot that's happening to modernize the infrastructure but a very important thing that we're going to talk about today is also what's happening up the stack, what sits on top of it and some of the new use cases and applications that are enabled by all of this modern environment and for that we're going to talk about artificial intelligence and machine learning or AI and ML as we tend to talk in the industry, so happy to welcome to the program. We have two first time guests joining us from Red Hat. First of all, we have Abhinav Joshi and Tushar Katarki they are both senior managers, part of the OpenShift group. Abhinav is in the product marketing and Tushar is in product management. Abhinav and Tushar thank you so much for joining us. >> Thanks a lot, Stu, we're glad to be here. >> Thanks Stu and glad to be here at KubeCon. >> All right, so Abhinav I mentioned in the intro here, modernization of the infrastructure is awesome but really it's an enabler. We know... I'm an infrastructure person the whole reason we have infrastructure is to be able to drive those applications, interact with my data and the like and of course, AI and ML are exciting a lot going on there but can also be challenging. So, Abhinav if I could start with you bring us inside your customers that you're talking to, what are the challenges, the opportunities? What are they seeing in this space? Maybe what's been holding them back from really unlocking the value that is expected? >> Yup, that's a very good question to kick off the conversation. So what we are seeing as an organization they typically face a lot of challenges when they're trying to build an AI/ML environment, right? And the first one is like a talent shortage. There is a limited amount of the AI, ML expertise in the market and especially the data scientists that are responsible for building out the machine learning and the deep learning models. So yeah, it's hard to find them and to be able to retain them and also other talents like a data engineer or app DevOps folks as well and the lack of talent can actually stall the project. And the second key challenge that we see is the lack of the readily usable data. So the businesses collect a lot of data but they must find the right data and make it ready for the data scientists to be able to build out, to be able to test and train the machine learning models. If you don't have the right kind of data to the predictions that your model is going to do in the real world is only going to be so good. So that becomes a challenge as well, to be able to find and be able to wrangle the right kind of data. And the third key challenge that we see is the lack of the rapid availability of the compute infrastructure, the data and machine learning, and the app dev tools for the various personas like a data scientist or data engineer, the software developers and so on that can also slow down the project, right? Because if all your teams are waiting on the infrastructure and the tooling of their choice to be provisioned on a recurring basis and they don't get it in a timely manner, it can stall the projects. And then the next one is the lack of collaboration. So you have all these kinds of teams that are involved in the AI project, and they have to collaborate with each other because the work one of the team does has a dependency on a different team like say for example, the data scientists are responsible for building the machine learning models and then what they have to do is they have to work with the app dev teams to make sure the models get integrated as part of the app dev processes and ultimately rolled out into the production. So if all these teams are operating in say silos and there is lack of collaboration between the teams, so this can stall the projects as well. And finally, what we see is the data scientists they typically start the machine learning modeling on their individual PCs or laptops and they don't focus on the operational aspects of the solution. So what this means is when the IT teams have to roll all this out into a production kind of deployment, so they get challenged to take all the work that has been done by the individuals and then be able to make sense out of it, be able to make sure that it can be seamlessly brought up in a production environment in a consistent way, be it on-premises, be it in the cloud or be it say at the edge. So these are some of the key challenges that we see that the organizations are facing, as they say try to take the AI projects from pilot to production. >> Well, some of those things seem like repetition of what we've had in the past. Obviously silos have been the bane of IT moving forward and of course, for many years we've been talking about that gap between developers and what's happening in the operation side. So Tushar, help us connect the dots, containers, Kubernetes, the whole DevOps movement. How is this setting us up to actually be successful for solutions like AI and ML? >> Sure Stu I mean, in fact you said it right like in the world of software, in the world of microservices, in the world of app modernization, in the world of DevOps in the past 10, 15 years, but we have seen this evolution revolution happen with containers and Kubernetes driving more DevOps behavior, driving more agile behavior so this in fact is what we are trying to say here can ease up the cable to EIML also. So the various containers, Kubernetes, DevOps and OpenShift for software development is directly applicable for AI projects to make them move agile, to get them into production, to make them more valuable to organization so that they can realize the full potential of AI. We already touched upon a few personas so it's useful to think about who the users are, who the personas are. Abhinav I talked about data scientists these are the people who obviously do the machine learning itself, do the modeling. Then there are data engineers who do the plumbing who provide the essential data. Data is so essential to machine learning and deep learning and so there are data engineers that are app developers who in some ways will then use the output of what the data scientists have produced in terms of models and then incorporate them into services and of course, none of these things are purely cast in stone there's a lot of overlap you could find that data scientists are app developers as well, you'll see some of app developers being data scientist later data engineer. So it's a continuum rather than strict boundaries, but regardless what all of these personas groups of people need or experts need is self service to that preferred tools and compute and storage resources to be productive and then let's not forget the IT, engineering and operations teams that need to make all this happen in an easy, reliable, available manner and something that is really safe and secure. So containers help you, they help you quickly and easily deploy a broad set of machine learning tools, data tools across the cloud, the hybrid cloud from data center to public cloud to the edge in a very consistent way. Teams can therefore alternatively modify, change a shared container images, machine learning models with (indistinct) and track changes. And this could be applicable to both containers as well as to the data by the way and be transparent and transparency helps in collaboration but also it could help with the regulatory reasons later on in the process. And then with containers because of the inherent processes solution, resource control and protection from threat they can also be very secure. Now, Kubernetes takes it to the next level first of all, it forms a cluster of all your compute and data resources, and it helps you to run your containerized tools and whatever you develop on them in a consistent way with access to these shared compute and centralized compute and storage and networking resources from the data center, the edge or the public cloud. They provide things like resource management, workload scheduling, multi-tendency controls so that you can be a proper neighbors if you will, and quota enforcement right? Now that's Kubernetes now if you want to up level it further if you want to enhance what Kubernetes offers then you go into how do you write applications? How do you actually make those models into services? And that's where... and how do you lifecycle them? And that's sort of the power of Helm and for the more Kubernetes operators really comes into the picture and while Helm helps in installing some of this for a complete life cycle experience. A kubernetes operator is the way to go and they simplify the acceleration and deployment and life cycle management from end-to-end of your entire AI, ML tool chain. So all in all organizations therefore you'll see that they need to dial up and define models rapidly just like applications that's how they get ready out of it quickly. There is a lack of collaboration across teams as Abhinav pointed out earlier, as you noticed that has happened still in the world of software also. So we're talking about how do you bring those best practices here to AI, ML. DevOps approaches for machine learning operations or many analysts and others have started calling as MLOps. So how do you kind of bring DevOps to machine learning, and fosters better collaboration between teams, application developers and IT operations and create this feedback loop so that the time to production and the ability to take more machine learning into production and ML-powered applications into production increase is significant. So that's kind of the, where I wanted shine the light on what you were referring to earlier, Stu. >> All right, Abhinav of course one of the good things about OpenShift is you have quite a lot of customers that have deployed the solution over the years, bring us inside some of your customers what are they doing for AI, ML and help us understand really what differentiates OpenShift in the marketplace for this solution set. >> Yeah, absolutely that's a very good question as well and we're seeing a lot of traction in terms of all kinds of industries, right? Be it the financial services like healthcare, automotive, insurance, oil and gas, manufacturing and so on. For a wide variety of use cases and what we are seeing is at the end of the day like all these deployments are focused on helping improve the customer experience, be able to automate the business processes and then be able to help them increase the revenue, serve their customers better, and also be able to save costs. If you go to openshift.com/ai-ml it's got like a lot of customer stories in there but today I will not touch on three of the customers we have in terms of the different industries. The first one is like Royal Bank of Canada. So they are a top global financial institution based out of Canada and they have more than 17 million clients globally. So they recently announced that they build out an AI-powered private cloud platform that was based on OpenShift as well as the NVIDIA DGX AI compute system and this whole solution is actually helping them to transform the customer banking experience by being able to deliver an AI-powered intelligent apps and also at the same time being able to improve the operational efficiency of their organization. And now with this kind of a solution, what they're able to do is they're able to run thousands of simulations and be able to analyze millions of data points in a fraction of time as compared to the solution that they had before. Yeah, so like a lot of great work going on there but now the next one is the ETCA healthcare. So like ETCA is one of the leading healthcare providers in the country and they're based out of the Nashville, Tennessee. And they have more than 184 hospitals as well as more than 2,000 sites of care in the U.S. as well as in the UK. So what they did was they developed a very innovative machine learning power data platform on top of our OpenShift to help save lives. The first use case was to help with the early detection of sepsis like it's a life-threatening condition and then more recently they've been able to use OpenShift in the same kind of stack to be able to roll out the new applications that are powered by machine learning and deep learning let say to help them fight COVID-19. And recently they did a webinar as well that had all the details on the challenges they had like how did they go about it? Like the people, process and technology and then what the outcomes are. And we are proud to be a partner in the solution to help with such a noble cause. And the third example I want to share here is the BMW group and our partner DXC Technology what they've done is they've actually developed a very high performing data-driven data platform, a development platform based on OpenShift to be able to analyze the massive amount of data from the test fleet, the data and the speed of the say to help speed up the autonomous driving initiatives. And what they've also done is they've redesigned the connected drive capability that they have on top of OpenShift that's actually helping them provide various use cases to help improve the customer experience. With the customers and all of the customers are able to leverage a lot of different value-add services directly from within the car, their own cars. And then like last year at the Red Hat Summit they had a keynote as well and then this year at Summit, they were one of the Innovation Award winners. And we have a lot more stories but these are the three that I thought are actually compelling that I should talk about here on theCUBE. >> Yeah Abhinav just a quick follow up for you. One of the things of course we're looking at in 2020 is how has the COVID-19 pandemic, people working from home how has that impacted projects? I have to think that AI and ML are one of those projects that take a little bit longer to deploy, is it something that you see are they accelerating it? Are they putting on pause or are new project kicking off? Anything you can share from customers you're hearing right now as to the impact that they're seeing this year? >> Yeah what we are seeing is that the customers are now even more keen to be able to roll out the digital (indistinct) but we see a lot of customers are now on the accelerated timeline to be able to say complete the AI, ML project. So yeah, it's picking up a lot of momentum and we talk to a lot of analyst as well and they are reporting the same thing as well. But there is the interest that is actually like ramping up on the AI, ML projects like across their customer base. So yeah it's the right time to be looking at the innovation services that it can help improve the customer experience in the new virtual world that we live in now about COVID-19. >> All right, Tushar you mentioned that there's a few projects involved and of course we know at this conference there's a very large ecosystem. Red Hat is a strong contributor to many, many open source projects. Give us a little bit of a view as to in the AI, ML space who's involved, which pieces are important and how Red Hat looks at this entire ecosystem? >> Thank you, Stu so as you know technology partnerships and the power of open is really what is driving the technology world these days in any ways and particularly in the AI ecosystem. And that is mainly because one of the machine learning is in a bootstrap in the past 10 years or so and a lot of that emerging technology to take advantage of the emerging data as well as compute power has been built on the kind of the Linux ecosystem with openness and languages like popular languages like Python, et cetera. And so what you... and of course tons of technology based in Java but the point really here is that the ecosystem plays a big role and open plays a big role and that's kind of Red Hat's best cup of tea, if you will. And that really has plays a leadership role in the open ecosystem so if we take your question and kind of put it into two parts, what is the... what we are doing in the community and then what we are doing in terms of partnerships themselves, commercial partnerships, technology partnerships we'll take it one step at a time. In terms of the community itself, if you step back to the three years, we worked with other vendors and users, including Google and NVIDIA and H2O and other Seldon, et cetera, and both startups and big companies to develop this Kubeflow ecosystem. The Kubeflow is upstream community that is focused on developing MLOps as we talked about earlier end-to-end machine learning on top of Kubernetes. So Kubeflow right now is in 1.0 it happened a few months ago now it's actually at 1.1 you'll see that coupon here and then so that's the Kubeflow community in addition to that we are augmenting that with the Open Data Hub community which is something that extends the capabilities of the Kubeflow community to also add some of the data pipelining stuff and some of the data stuff that I talked about and forms a reference architecture on how to run some of this on top of OpenShift. So the Open Data Hub community also has a great way of including partners from a technology partnership perspective and then tie that with something that I mentioned earlier, which is the idea of Kubernetes operators. Now, if you take a step back as I mentioned earlier, Kubernetes operators help manage the life cycle of the entire application or containerized application including not only the configuration on day one but also day two activities like update and backups, restore et cetera whatever the application needs. Afford proper functioning that a "operator" needs for it to make sure so anyways, the Kubernetes operators ecosystem is also flourishing and we haven't faced that with the OperatorHub.io which is a community marketplace if you will, I don't call it marketplace a community hub because it's just comprised of community operators. So the Open Data Hub actually can take community operators and can show you how to run that on top of OpenShift and manage the life cycle. Now that's the reference architecture. Now, the other aspect of it really is as I mentioned earlier is the commercial aspect of it. It is from a customer point of view, how do I get certified, supported software? And to that extent, what we have is at the top of the... from a user experience point of view, we have certified operators and certified applications from the AI, ML, ISV community in the Red Hat marketplace. And from the Red Hat marketplace is where it becomes easy for end users to easily deploy these ISVs and manage the complete life cycle as I said. Some of the examples of these kinds of ISVs include startups like H2O although H2O is kind of well known in certain sectors PerceptiLabs, Cnvrg, Seldon, Starburst et cetera and then on the other side, we do have other big giants also in this which includes partnerships with NVIDIA, Cloudera et cetera that we have announced, including our also SaaS I got to mention. So anyways these provide... create that rich ecosystem for data scientists to take advantage of. A TEDx Summit back in April, we along with Cloudera, SaaS Anaconda showcased a live demo that shows all these things to working together on top of OpenShift with this operator kind of idea that I talked about. So I welcome people to go and take a look the openshift.com/ai-ml that Abhinav already referenced should have a link to that it take a simple Google search might download if you need some of that, but anyways and the other part of it is really our work with the hardware OEMs right? And so obviously NVIDIA GPUs is obviously hardware, and that accelerations is really important in this world but we are also working with other OEM partners like HP and Dell to produce this accelerated AI platform that turnkey solutions to run your data-- to create this open AI platform for "private cloud" or the data center. The other thing obviously is IBM, IBM Cloud Pak for Data is based on OpenShift that has been around for some time and is seeing very good traction, if you think about a very turnkey solution, IBM Cloud Pak is definitely kind of well ahead in that and then finally Red Hat is about driving innovation in the open-source community. So, as I said earlier, we are doing the Open Data Hub which that reference architecture that showcases a combination of upstream open source projects and all these ISV ecosystems coming together. So I welcome you to take a look at that at opendatahub.io So I think that would be kind of the some total of how we are not only doing open and community building but also doing certifications and providing to our customers that assurance that they can run these tools in production with the help of a rich certified ecosystem. >> And customer is always key to us so that's the other thing that the goal here is to provide our customers with a choice, right? They can go with open source or they can go with a commercial solution as well. So you want to make sure that they get the best in cloud experience on top of our OpenShift and our broader portfolio as well. >> All right great, great note to end on, Abhinav thank you so much and Tushar great to see the maturation in this space, such an important use case. Really appreciate you sharing this with theCUBE and Kubecon community. >> Thank you, Stu. >> Thank you, Stu. >> Okay thank you and thanks a lot and have a great rest of the show. Thanks everyone, stay safe. >> Thanks you and stay with us for a lot more coverage from KubeCon + CloudNativeCon Europe 2020, the virtual edition I'm Stu Miniman and thank you as always for watching theCUBE. (soft upbeat music plays)