(inspirational music) (music ends) >> Okay, so now that we've heard Scott talk about smart data fabrics, it's time to see this in action. Right now we're joined by Jess Jowdy, who's the manager of Healthcare Field Engineering at InterSystems. She's going to give a demo of how smart data fabrics actually work, and she's going to show how embedding a wide range of analytics capabilities, including data exploration business intelligence, natural language processing and machine learning directly within the fabric makes it faster and easier for organizations to gain new insights and power intelligence predictive and prescriptive services and applications. Now, according to InterSystems, smart data fabrics are applicable across many industries from financial services to supply chain to healthcare and more. Jess today is going to be speaking through the lens of a healthcare focused demo. Don't worry, Joe Lichtenberg will get into some of the other use cases that you're probably interested in hearing about. That will be in our third segment, but for now let's turn it over to Jess. Jess, good to see you. >> Hi, yeah, thank you so much for having me. And so for this demo, we're really going to be bucketing these features of a smart data fabric into four different segments. We're going to be dealing with connections, collections, refinements, and analysis. And so we'll see that throughout the demo as we go. So without further ado, let's just go ahead and jump into this demo, and you'll see my screen pop up here. I actually like to start at the end of the demo. So I like to begin by illustrating what an end user's going to see, and don't mind the screen 'cause I gave you a little sneak peek of what's about to happen. But essentially what I'm going to be doing is using Postman to simulate a call from an external application. So we talked about being in the healthcare industry. This could be, for instance, a mobile application that a patient is using to view an aggregated summary of information across that patient's continuity of care or some other kind of application. So we might be pulling information in this case from an electronic medical record. We might be grabbing clinical history from that. We might be grabbing clinical notes from a medical transcription software, or adverse reaction warnings from a clinical risk grouping application, and so much more. So I'm really going to be simulating a patient logging in on their phone and retrieving this information through this Postman call. So what I'm going to do is I'm just going to hit send, I've already preloaded everything here, and I'm going to be looking for information where the last name of this patient is Simmons, and their medical record number or their patient identifier in the system is 32345. And so as you can see, I have this single JSON payload that showed up here of, just, relevant clinical information for my patient whose last name is Simmons, all within a single response. So fantastic, right? Typically though, when we see responses that look like this there is an assumption that this service is interacting with a single backend system, and that single backend system is in charge of packaging that information up and returning it back to this caller. But in a smart data fabric architecture, we're able to expand the scope to handle information across different, in this case, clinical applications. So how did this actually happen? Let's peel back another layer and really take a look at what happened in the background. What you're looking at here is our mission control center for our smart data fabric. On the left we have our APIs that allow users to interact with particular services. On the right we have our connections to our different data silos. And in the middle here, we have our data fabric coordinator which is going to be in charge of this refinement and analysis, those key pieces of our smart data fabric. So let's look back and think about the example we just showed. I received an inbound request for information for a patient whose last name is Simmons. My end user is requesting to connect to that service, and that's happening here at my patient data retrieval API location. Users can define any number of different services and APIs depending on their use cases. And to that end, we do also support full life cycle API management within this platform. When you're dealing with APIs, I always like to make a little shout out on this, that you really want to make sure you have enough, like a granular enough security model to handle and limit which APIs and which services a consumer can interact with. In this IRIS platform, which we're talking about today we have a very granular role-based security model that allows you to handle that, but it's really important in a smart data fabric to consider who's accessing your data and in what context. >> Can I just interrupt you for a second, Jess? >> Yeah, please. >> So you were showing on the left hand side of the demo a couple of APIs. I presume that can be a very long list. I mean, what do you see as typical? >> I mean you could have hundreds of these APIs depending on what services an organization is serving up for their consumers. So yeah, we've seen hundreds of these services listed here. >> So my question is, obviously security is critical in the healthcare industry, and API securities are like, really hot topic these days. How do you deal with that? >> Yeah, and I think API security is interesting 'cause it can happen at so many layers. So, there's interactions with the API itself. So can I even see this API and leverage it? And then within an API call, you then have to deal with all right, which end points or what kind of interactions within that API am I allowed to do? What data am I getting back? And with healthcare data, the whole idea of consent to see certain pieces of data is critical. So, the way that we handle that is, like I said, same thing at different layers. There is access to a particular API, which can happen within the IRIS product, and also we see it happening with an API management layer, which has become a really hot topic with a lot of organizations. And then when it comes to data security, that really happens under the hood within your smart data fabric. So, that role-based access control becomes very important in assigning, you know, roles and permissions to certain pieces of information. Getting that granular becomes the cornerstone of the security. >> And that's been designed in, it's not a bolt on as they like to say. >> Absolutely. >> Okay, can we get into collect now? >> Of course, we're going to move on to the collection piece at this point in time, which involves pulling information from each of my different data silos to create an overall aggregated record. So commonly, each data source requires a different method for establishing connections and collecting this information. So for instance, interactions with an EMR may require leveraging a standard healthcare messaging format like Fire. Interactions with a homegrown enterprise data warehouse for instance, may use SQL. For a cloud-based solutions managed by a vendor, they may only allow you to use web service calls to pull data. So it's really important that your data fabric platform that you're using has the flexibility to connect to all of these different systems and applications. And I'm about to log out, so I'm going to (chuckles) keep my session going here. So therefore it's incredibly important that your data fabric has the flexibility to connect to all these different kinds of applications and data sources, and all these different kinds of formats and over all of these different kinds of protocols. So let's think back on our example here. I had four different applications that I was requesting information for to create that payload that we saw initially. Those are listed here under this operations section. So these are going out and connecting to downstream systems to pull information into my smart data fabric. What's great about the IRIS platform is, it has an embedded interoperability platform. So there's all of these native adapters that can support these common connections that we see for different kinds of applications. So using REST, or SOAP, or SQL, or FTP, regardless of that protocol, there's an adapter to help you work with that. And we also think of the types of formats that we typically see data coming in as in healthcare we have HL7, we have Fire, we have CCDs, across the industry, JSON is, you know, really hitting a market strong now, and XML payloads, flat files. We need to be able to handle all of these different kinds of formats over these different kinds of protocols. So to illustrate that, if I click through these when I select a particular connection on the right side panel, I'm going to see the different settings that are associated with that particular connection that allows me to collect information back into my smart data fabric. In this scenario, my connection to my chart script application in this example, communicates over a SOAP connection. When I'm grabbing information from my clinical risk grouping application I'm using a SQL based connection. When I'm connecting to my EMR, I'm leveraging a standard healthcare messaging format known as Fire, which is a REST based protocol. And then when I'm working with my health record management system, I'm leveraging a standard HTTP adapter. So you can see how we can be flexible when dealing with these different kinds of applications and systems. And then it becomes important to be able to validate that you've established those connections correctly, and be able to do it in a reliable and quick way. Because if you think about it, you could have hundreds of these different kinds of applications built out and you want to make sure that you're maintaining and understanding those connections. So I can actually go ahead and test one of these applications and put in, for instance my patient's last name and their MRN, and make sure that I'm actually getting data back from that system. So it's a nice little sanity check as we're building out that data fabric to ensure that we're able to establish these connections appropriately. So turnkey adapters are fantastic, as you can see we're leveraging them all here, but sometimes these connections are going to require going one step further and building something really specific for an application. So why don't we go one step further here and talk about doing something custom or doing something innovative. And so it's important for users to have the ability to develop and go beyond what's an out-of-the box or black box approach to be able to develop things that are specific to their data fabric, or specific to their particular connection. In this scenario, the IRIS data platform gives users access to the entire underlying code base. So you not only get an opportunity to view how we're establishing these connections or how we're building out these processes, but you have the opportunity to inject your own kind of processing, your own kinds of pipelines into this. So as an example, you can leverage any number of different programming languages right within this pipeline. And so I went ahead and I injected Python. So Python is a very up and coming language, right? We see more and more developers turning towards Python to do their development. So it's important that your data fabric supports those kinds of developers and users that have standardized on these kinds of programming languages. This particular script here, as you can see actually calls out to our turnkey adapters. So we see a combination of out-of-the-box code that is provided in this data fabric platform from IRIS, combined with organization specific or user specific customizations that are included in this Python method. So it's a nice little combination of how do we bring the developer experience in and mix it with out-of-the-box capabilities that we can provide in a smart data fabric. >> Wow. >> Yeah, I'll pause. (laughs) >> It's a lot here. You know, actually- >> I can pause. >> If I could, if we just want to sort of play that back. So we went to the connect and the collect phase. >> Yes, we're going into refine. So it's a good place to stop. >> So before we get there, so we heard a lot about fine grain security, which is crucial. We heard a lot about different data types, multiple formats. You've got, you know, the ability to bring in different dev tools. We heard about Fire, which of course big in healthcare. And that's the standard, and then SQL for traditional kind of structured data, and then web services like HTTP you mentioned. And so you have a rich collection of capabilities within this single platform. >> Absolutely. And I think that's really important when you're dealing with a smart data fabric because what you're effectively doing is you're consolidating all of your processing, all of your collection, into a single platform. So that platform needs to be able to handle any number of different kinds of scenarios and technical challenges. So you've got to pack that platform with as many of these features as you can to consolidate that processing. >> All right, so now we're going into refinement. >> We're going into refinement. Exciting. (chuckles) So how do we actually do refinement? Where does refinement happen? And how does this whole thing end up being performant? Well the key to all of that is this SDF coordinator, or stands for Smart Data Fabric coordinator. And what this particular process is doing is essentially orchestrating all of these calls to all of these different downstream systems. It's aggregating, it's collecting that information, it's aggregating it, and it's refining it into that single payload that we saw get returned to the user. So really this coordinator is the main event when it comes to our data fabric. And in the IRIS platform we actually allow users to build these coordinators using web-based tool sets to make it intuitive. So we can take a sneak peek at what that looks like. And as you can see, it follows a flow chart like structure. So there's a start, there is an end, and then there are these different arrows that point to different activities throughout the business process. And so there's all these different actions that are being taken within our coordinator. You can see an action for each of the calls to each of our different data sources to go retrieve information. And then we also have the sync call at the end that is in charge of essentially making sure that all of those responses come back before we package them together and send them out. So this becomes really crucial when we're creating that data fabric. And you know, this is a very simple data fabric example where we're just grabbing data and we're consolidating it together. But you can have really complex orchestrators and coordinators that do any number of different things. So for instance, I could inject SQL logic into this or SQL code, I can have conditional logic, I can do looping, I can do error trapping and handling. So we're talking about a whole number of different features that can be included in this coordinator. So like I said, we have a really very simple process here that's just calling out, grabbing all those different data elements from all those different data sources and consolidating it. We'll look back at this coordinator in a second when we introduce, or we make this data fabric a bit smarter, and we start introducing that analytics piece to it. So this is in charge of the refinement. And so at this point in time we've looked at connections, collections, and refinements. And just to summarize what we've seen 'cause I always like to go back and take a look at everything that we've seen. We have our initial API connection, we have our connections to our individual data sources and we have our coordinators there in the middle that are in charge of collecting the data and refining it into a single payload. As you can imagine, there's a lot going on behind the scenes of a smart data fabric, right? There's all these different processes that are interacting. So it's really important that your smart data fabric platform has really good traceability, really good logging, 'cause you need to be able to know, you know, if there was an issue, where did that issue happen in which connected process, and how did it affect the other processes that are related to it? In IRIS, we have this concept called a visual trace. And what our clients use this for is basically to be able to step through the entire history of a request from when it initially came into the smart data fabric, to when data was sent back out from that smart data fabric. So I didn't record the time, but I bet if you recorded the time it was this time that we sent that request in and you can see my patient's name and their medical record number here, and you can see that that instigated four different calls to four different systems, and they're represented by these arrows going out. So we sent something to chart script, to our health record management system, to our clinical risk grouping application, into my EMR through their Fire server. So every request, every outbound application gets a request and we pull back all of those individual pieces of information from all of those different systems, and we bundle them together. And from my Fire lovers, here's our Fire bundle that we got back from our Fire server. So this is a really good way of being able to validate that I am appropriately grabbing the data from all these different applications and then ultimately consolidating it into one payload. Now we change this into a JSON format before we deliver it, but this is those data elements brought together. And this screen would also be used for being able to see things like error trapping, or errors that were thrown, alerts, warnings, developers might put log statements in just to validate that certain pieces of code are executing. So this really becomes the one stop shop for understanding what's happening behind the scenes with your data fabric. >> Sure, who did what when where, what did the machine do what went wrong, and where did that go wrong? Right at your fingertips. >> Right. And I'm a visual person so a bunch of log files to me is not the most helpful. While being able to see this happened at this time in this location, gives me that understanding I need to actually troubleshoot a problem. >> This business orchestration piece, can you say a little bit more about that? How people are using it? What's the business impact of the business orchestration? >> The business orchestration, especially in the smart data fabric, is really that crucial part of being able to create a smart data fabric. So think of your business orchestrator as doing the heavy lifting of any kind of processing that involves data, right? It's bringing data in, it's analyzing that information it's transforming that data, in a format that your consumer's not going to understand. It's doing any additional injection of custom logic. So really your coordinator or that orchestrator that sits in the middle is the brains behind your smart data fabric. >> And this is available today? It all works? >> It's all available today. Yeah, it all works. And we have a number of clients that are using this technology to support these kinds of use cases. >> Awesome demo. Anything else you want to show us? >> Well, we can keep going. I have a lot to say, but really this is our data fabric. The core competency of IRIS is making it smart, right? So I won't spend too much time on this, but essentially if we go back to our coordinator here, we can see here's that original, that pipeline that we saw where we're pulling data from all these different systems and we're collecting it and we're sending it out. But then we see two more at the end here, which involves getting a readmission prediction and then returning a prediction. So we can not only deliver data back as part of a smart data fabric, but we can also deliver insights back to users and consumers based on data that we've aggregated as part of a smart data fabric. So in this scenario, we're actually taking all that data that we just looked at, and we're running it through a machine learning model that exists within the smart data fabric pipeline, and producing a readmission score to determine if this particular patient is at risk for readmission within the next 30 days. Which is a typical problem that we see in the healthcare space. So what's really exciting about what we're doing in the IRIS world, is we're bringing analytics close to the data with integrated ML. So in this scenario we're actually creating the model, training the model, and then executing the model directly within the IRIS platform. So there's no shuffling of data, there's no external connections to make this happen. And it doesn't really require having a PhD in data science to understand how to do that. It leverages all really basic SQL-like syntax to be able to construct and execute these predictions. So, it's going one step further than the traditional data fabric example to introduce this ability to define actionable insights to our users based on the data that we've brought together. >> Well that readmission probability is huge, right? Because it directly affects the cost for the provider and the patient, you know. So if you can anticipate the probability of readmission and either do things at that moment, or, you know, as an outpatient perhaps, to minimize the probability then that's huge. That drops right to the bottom line. >> Absolutely. And that really brings us from that data fabric to that smart data fabric at the end of the day, which is what makes this so exciting. >> Awesome demo. >> Thank you! >> Jess, are you cool if people want to get in touch with you? Can they do that? >> Oh yes, absolutely. So you can find me on LinkedIn, Jessica Jowdy, and we'd love to hear from you. I always love talking about this topic so we'd be happy to engage on that. >> Great stuff. Thank you Jessica, appreciate it. >> Thank you so much. >> Okay, don't go away because in the next segment, we're going to dig into the use cases where data fabric is driving business value. Stay right there. (inspirational music) (music fades)

>> Okay, so now that we've heard Scott talk about smart data fabrics, it's time to see this in action. Right now we're joined by Jess Jowdy, who's the manager of Healthcare Field Engineering at InterSystems. She's going to give a demo of how smart data fabrics actually work, and she's going to show how embedding a wide range of analytics capabilities including data exploration, business intelligence natural language processing, and machine learning directly within the fabric, makes it faster and easier for organizations to gain new insights and power intelligence, predictive and prescriptive services and applications. Now, according to InterSystems, smart data fabrics are applicable across many industries from financial services to supply chain to healthcare and more. Jess today is going to be speaking through the lens of a healthcare focused demo. Don't worry, Joe Lichtenberg will get into some of the other use cases that you're probably interested in hearing about. That will be in our third segment, but for now let's turn it over to Jess. Jess, good to see you. >> Hi. Yeah, thank you so much for having me. And so for this demo we're really going to be bucketing these features of a smart data fabric into four different segments. We're going to be dealing with connections, collections, refinements and analysis. And so we'll see that throughout the demo as we go. So without further ado, let's just go ahead and jump into this demo and you'll see my screen pop up here. I actually like to start at the end of the demo. So I like to begin by illustrating what an end user's going to see and don't mind the screen 'cause I gave you a little sneak peek of what's about to happen. But essentially what I'm going to be doing is using Postman to simulate a call from an external application. So we talked about being in the healthcare industry. This could be for instance, a mobile application that a patient is using to view an aggregated summary of information across that patient's continuity of care or some other kind of application. So we might be pulling information in this case from an electronic medical record. We might be grabbing clinical history from that. We might be grabbing clinical notes from a medical transcription software or adverse reaction warnings from a clinical risk grouping application and so much more. So I'm really going to be assimilating a patient logging on in on their phone and retrieving this information through this Postman call. So what I'm going to do is I'm just going to hit send, I've already preloaded everything here and I'm going to be looking for information where the last name of this patient is Simmons and their medical record number their patient identifier in the system is 32345. And so as you can see I have this single JSON payload that showed up here of just relevant clinical information for my patient whose last name is Simmons all within a single response. So fantastic, right? Typically though when we see responses that look like this there is an assumption that this service is interacting with a single backend system and that single backend system is in charge of packaging that information up and returning it back to this caller. But in a smart data fabric architecture we're able to expand the scope to handle information across different, in this case, clinical applications. So how did this actually happen? Let's peel back another layer and really take a look at what happened in the background. What you're looking at here is our mission control center for our smart data fabric. On the left we have our APIs that allow users to interact with particular services. On the right we have our connections to our different data silos. And in the middle here we have our data fabric coordinator which is going to be in charge of this refinement and analysis those key pieces of our smart data fabric. So let's look back and think about the example we just showed. I received an inbound request for information for a patient whose last name is Simmons. My end user is requesting to connect to that service and that's happening here at my patient data retrieval API location. Users can define any number of different services and APIs depending on their use cases. And to that end we do also support full lifecycle API management within this platform. When you're dealing with APIs I always like to make a little shout out on this that you really want to make sure you have enough like a granular enough security model to handle and limit which APIs and which services a consumer can interact with. In this IRIS platform, which we're talking about today we have a very granular role-based security model that allows you to handle that, but it's really important in a smart data fabric to consider who's accessing your data and in what contact. >> Can I just interrupt you for a second? >> Yeah, please. >> So you were showing on the left hand side of the demo a couple of APIs. I presume that can be a very long list. I mean, what do you see as typical? >> I mean you can have hundreds of these APIs depending on what services an organization is serving up for their consumers. So yeah, we've seen hundreds of these services listed here. >> So my question is, obviously security is critical in the healthcare industry and API securities are really hot topic these days. How do you deal with that? >> Yeah, and I think API security is interesting 'cause it can happen at so many layers. So there's interactions with the API itself. So can I even see this API and leverage it? And then within an API call, you then have to deal with all right, which end points or what kind of interactions within that API am I allowed to do? What data am I getting back? And with healthcare data, the whole idea of consent to see certain pieces of data is critical. So the way that we handle that is, like I said, same thing at different layers. There is access to a particular API, which can happen within the IRIS product and also we see it happening with an API management layer, which has become a really hot topic with a lot of organizations. And then when it comes to data security, that really happens under the hood within your smart data fabric. So that role-based access control becomes very important in assigning, you know, roles and permissions to certain pieces of information. Getting that granular becomes the cornerstone of security. >> And that's been designed in, >> Absolutely, yes. it's not a bolt-on as they like to say. Okay, can we get into collect now? >> Of course, we're going to move on to the collection piece at this point in time, which involves pulling information from each of my different data silos to create an overall aggregated record. So commonly each data source requires a different method for establishing connections and collecting this information. So for instance, interactions with an EMR may require leveraging a standard healthcare messaging format like FIRE, interactions with a homegrown enterprise data warehouse for instance may use SQL for a cloud-based solutions managed by a vendor. They may only allow you to use web service calls to pull data. So it's really important that your data fabric platform that you're using has the flexibility to connect to all of these different systems and and applications. And I'm about to log out so I'm going to keep my session going here. So therefore it's incredibly important that your data fabric has the flexibility to connect to all these different kinds of applications and data sources and all these different kinds of formats and over all of these different kinds of protocols. So let's think back on our example here. I had four different applications that I was requesting information for to create that payload that we saw initially. Those are listed here under this operations section. So these are going out and connecting to downstream systems to pull information into my smart data fabric. What's great about the IRIS platform is it has an embedded interoperability platform. So there's all of these native adapters that can support these common connections that we see for different kinds of applications. So using REST or SOAP or SQL or FTP regardless of that protocol there's an adapter to help you work with that. And we also think of the types of formats that we typically see data coming in as, in healthcare we have H7, we have FIRE we have CCDs across the industry. JSON is, you know, really hitting a market strong now and XML, payloads, flat files. We need to be able to handle all of these different kinds of formats over these different kinds of protocols. So to illustrate that, if I click through these when I select a particular connection on the right side panel I'm going to see the different settings that are associated with that particular connection that allows me to collect information back into my smart data fabric. In this scenario, my connection to my chart script application in this example communicates over a SOAP connection. When I'm grabbing information from my clinical risk grouping application I'm using a SQL based connection. When I'm connecting to my EMR I'm leveraging a standard healthcare messaging format known as FIRE, which is a rest based protocol. And then when I'm working with my health record management system I'm leveraging a standard HTTP adapter. So you can see how we can be flexible when dealing with these different kinds of applications and systems. And then it becomes important to be able to validate that you've established those connections correctly and be able to do it in a reliable and quick way. Because if you think about it, you could have hundreds of these different kinds of applications built out and you want to make sure that you're maintaining and understanding those connections. So I can actually go ahead and test one of these applications and put in, for instance my patient's last name and their MRN and make sure that I'm actually getting data back from that system. So it's a nice little sanity check as we're building out that data fabric to ensure that we're able to establish these connections appropriately. So turnkey adapters are fantastic, as you can see we're leveraging them all here, but sometimes these connections are going to require going one step further and building something really specific for an application. So let's, why don't we go one step further here and talk about doing something custom or doing something innovative. And so it's important for users to have the ability to develop and go beyond what's an out of the box or black box approach to be able to develop things that are specific to their data fabric or specific to their particular connection. In this scenario, the IRIS data platform gives users access to the entire underlying code base. So you cannot, you not only get an opportunity to view how we're establishing these connections or how we're building out these processes but you have the opportunity to inject your own kind of processing your own kinds of pipelines into this. So as an example, you can leverage any number of different programming languages right within this pipeline. And so I went ahead and I injected Python. So Python is a very up and coming language, right? We see more and more developers turning towards Python to do their development. So it's important that your data fabric supports those kinds of developers and users that have standardized on these kinds of programming languages. This particular script here, as you can see actually calls out to our turnkey adapters. So we see a combination of out of the box code that is provided in this data fabric platform from IRIS combined with organization specific or user specific customizations that are included in this Python method. So it's a nice little combination of how do we bring the developer experience in and mix it with out of the box capabilities that we can provide in a smart data fabric. >> Wow. >> Yeah, I'll pause. >> It's a lot here. You know, actually, if I could >> I can pause. >> If I just want to sort of play that back. So we went through the connect and the collect phase. >> And the collect, yes, we're going into refine. So it's a good place to stop. >> Yeah, so before we get there, so we heard a lot about fine grain security, which is crucial. We heard a lot about different data types, multiple formats. You've got, you know the ability to bring in different dev tools. We heard about FIRE, which of course big in healthcare. >> Absolutely. >> And that's the standard and then SQL for traditional kind of structured data and then web services like HTTP you mentioned. And so you have a rich collection of capabilities within this single platform. >> Absolutely, and I think that's really important when you're dealing with a smart data fabric because what you're effectively doing is you're consolidating all of your processing, all of your collection into a single platform. So that platform needs to be able to handle any number of different kinds of scenarios and technical challenges. So you've got to pack that platform with as many of these features as you can to consolidate that processing. >> All right, so now we're going into refine. >> We're going into refinement, exciting. So how do we actually do refinement? Where does refinement happen and how does this whole thing end up being performant? Well the key to all of that is this SDF coordinator or stands for smart data fabric coordinator. And what this particular process is doing is essentially orchestrating all of these calls to all of these different downstream systems. It's aggregating, it's collecting that information it's aggregating it and it's refining it into that single payload that we saw get returned to the user. So really this coordinator is the main event when it comes to our data fabric. And in the IRIS platform we actually allow users to build these coordinators using web-based tool sets to make it intuitive. So we can take a sneak peek at what that looks like and as you can see it follows a flow chart like structure. So there's a start, there is an end and then there are these different arrows that point to different activities throughout the business process. And so there's all these different actions that are being taken within our coordinator. You can see an action for each of the calls to each of our different data sources to go retrieve information. And then we also have the sync call at the end that is in charge of essentially making sure that all of those responses come back before we package them together and send them out. So this becomes really crucial when we're creating that data fabric. And you know, this is a very simple data fabric example where we're just grabbing data and we're consolidating it together. But you can have really complex orchestrators and coordinators that do any number of different things. So for instance, I could inject SQL Logic into this or SQL code, I can have conditional logic, I can do looping, I can do error trapping and handling. So we're talking about a whole number of different features that can be included in this coordinator. So like I said, we have a really very simple process here that's just calling out, grabbing all those different data elements from all those different data sources and consolidating it. We'll look back at this coordinator in a second when we introduce or we make this data fabric a bit smarter and we start introducing that analytics piece to it. So this is in charge of the refinement. And so at this point in time we've looked at connections, collections, and refinements. And just to summarize what we've seen 'cause I always like to go back and take a look at everything that we've seen. We have our initial API connection we have our connections to our individual data sources and we have our coordinators there in the middle that are in charge of collecting the data and refining it into a single payload. As you can imagine, there's a lot going on behind the scenes of a smart data fabric, right? There's all these different processes that are interacting. So it's really important that your smart data fabric platform has really good traceability, really good logging 'cause you need to be able to know, you know, if there was an issue, where did that issue happen, in which connected process and how did it affect the other processes that are related to it. In IRIS, we have this concept called a visual trace. And what our clients use this for is basically to be able to step through the entire history of a request from when it initially came into the smart data fabric to when data was sent back out from that smart data fabric. So I didn't record the time but I bet if you recorded the time it was this time that we sent that request in. And you can see my patient's name and their medical record number here and you can see that that instigated four different calls to four different systems and they're represented by these arrows going out. So we sent something to chart script to our health record management system, to our clinical risk grouping application into my EMR through their FIRE server. So every request, every outbound application gets a request and we pull back all of those individual pieces of information from all of those different systems and we bundle them together. And for my FIRE lovers, here's our FIRE bundle that we got back from our FIRE server. So this is a really good way of being able to validate that I am appropriately grabbing the data from all these different applications and then ultimately consolidating it into one payload. Now we change this into a JSON format before we deliver it, but this is those data elements brought together. And this screen would also be used for being able to see things like error trapping or errors that were thrown alerts, warnings, developers might put log statements in just to validate that certain pieces of code are executing. So this really becomes the one stop shop for understanding what's happening behind the scenes with your data fabric. >> Etcher, who did what, when, where what did the machine do? What went wrong and where did that go wrong? >> Exactly. >> Right in your fingertips. >> Right, and I'm a visual person so a bunch of log files to me is not the most helpful. Well, being able to see this happened at this time in this location gives me that understanding I need to actually troubleshoot a problem. >> This business orchestration piece, can you say a little bit more about that? How people are using it? What's the business impact of the business orchestration? >> The business orchestration, especially in the smart data fabric is really that crucial part of being able to create a smart data fabric. So think of your business orchestrator as doing the heavy lifting of any kind of processing that involves data, right? It's bringing data in, it's analyzing that information, it's transforming that data, in a format that your consumer's not going to understand it's doing any additional injection of custom logic. So really your coordinator or that orchestrator that sits in the middle is the brains behind your smart data fabric. >> And this is available today? This all works? >> It's all available today. Yeah, it all works. And we have a number of clients that are using this technology to support these kinds of use cases. >> Awesome demo. Anything else you want to show us? >> Well we can keep going. 'Cause right now, I mean we can, oh, we're at 18 minutes. God help us. You can cut some of this. (laughs) I have a lot to say, but really this is our data fabric. The core competency of IRIS is making it smart, right? So I won't spend too much time on this but essentially if we go back to our coordinator here we can see here's that original that pipeline that we saw where we're pulling data from all these different systems and we're collecting it and we're sending it out. But then we see two more at the end here which involves getting a readmission prediction and then returning a prediction. So we can not only deliver data back as part of a smart data fabric but we can also deliver insights back to users and consumers based on data that we've aggregated as part of a smart data fabric. So in this scenario, we're actually taking all that data that we just looked at and we're running it through a machine learning model that exists within the smart data fabric pipeline and producing a readmission score to determine if this particular patient is at risk for readmission within the next 30 days. Which is a typical problem that we see in the healthcare space. So what's really exciting about what we're doing in the IRIS world is we're bringing analytics close to the data with integrated ML. So in this scenario we're actually creating the model, training the model, and then executing the model directly within the IRIS platform. So there's no shuffling of data, there's no external connections to make this happen. And it doesn't really require having a PhD in data science to understand how to do that. It leverages all really basic SQL like syntax to be able to construct and execute these predictions. So it's going one step further than the traditional data fabric example to introduce this ability to define actionable insights to our users based on the data that we've brought together. >> Well that readmission probability is huge. >> Yes. >> Right, because it directly affects the cost of for the provider and the patient, you know. So if you can anticipate the probability of readmission and either do things at that moment or you know, as an outpatient perhaps to minimize the probability then that's huge. That drops right to the bottom line. >> Absolutely, absolutely. And that really brings us from that data fabric to that smart data fabric at the end of the day which is what makes this so exciting. >> Awesome demo. >> Thank you. >> Fantastic people, are you cool? If people want to get in touch with you? >> Oh yes, absolutely. So you can find me on LinkedIn, Jessica Jowdy and we'd love to hear from you. I always love talking about this topic, so would be happy to engage on that. >> Great stuff, thank you Jess, appreciate it. >> Thank you so much. >> Okay, don't go away because in the next segment we're going to dig into the use cases where data fabric is driving business value. Stay right there.

(upbeat music) >> Welcome back to Supercloud 2. This is Dave Vellante. We're here exploring the intersection of data and analytics in the future of cloud and data. In this segment, we're going to look deeper into the life sciences business with Jesse Cugliotta, who leads the Healthcare and Life Sciences industry practice at Snowflake. And Nicholas Nick Taylor, who's the executive director of Informatics at Ionis Pharmaceuticals. Gentlemen, thanks for coming in theCUBE and participating in the program. Really appreciate it. >> Thank you for having us- >> Thanks for having me. >> You're very welcome, okay, we're go really try to look at data sharing as a use case and try to understand what's happening in the healthcare industry generally and specifically, how Nick thinks about sharing data in a governed fashion whether tapping the capabilities of multiple clouds is advantageous long term or presents more challenges than the effort is worth. And to start, Jesse, you lead this industry practice for Snowflake and it's a challenging and vibrant area. It's one that's hyper-focused on data privacy. So the first question is, you know there was a time when healthcare and other regulated industries wouldn't go near the cloud. What are you seeing today in the industry around cloud adoption and specifically multi-cloud adoption? >> Yeah, for years I've heard that healthcare and life sciences has been cloud diverse, but in spite of all of that if you look at a lot of aspects of this industry today, they've been running in the cloud for over 10 years now. Particularly when you look at CRM technologies or HR or HCM, even clinical technologies like EDC or ETMF. And it's interesting that you mentioned multi-cloud as well because this has always been an underlying reality especially within life sciences. This industry grows through acquisition where companies are looking to boost their future development pipeline either by buying up smaller biotechs, they may have like a late or a mid-stage promising candidate. And what typically happens is the larger pharma could then use their commercial muscle and their regulatory experience to move it to approvals and into the market. And I think the last few decades of cheap capital certainly accelerated that trend over the last couple of years. But this typically means that these new combined institutions may have technologies that are running on multiple clouds or multiple cloud strategies in various different regions to your point. And what we've often found is that they're not planning to standardize everything onto a single cloud provider. They're often looking for technologies that embrace this multi-cloud approach and work seamlessly across them. And I think this is a big reason why we, here at Snowflake, we've seen such strong momentum and growth across this industry because healthcare and life science has actually been one of our fastest growing sectors over the last couple of years. And a big part of that is in fact that we run on not only all three major cloud providers, but individual accounts within each and any one of them, they had the ability to communicate and interoperate with one another, like a globally interconnected database. >> Great, thank you for that setup. And so Nick, tell us more about your role and Ionis Pharma please. >> Sure. So I've been at Ionis for around five years now. You know, when when I joined it was, the IT department was pretty small. There wasn't a lot of warehousing, there wasn't a lot of kind of big data there. We saw an opportunity with Snowflake pretty early on as a provider that would be a lot of benefit for us, you know, 'cause we're small, wanted something that was fairly hands off. You know, I remember the days where you had to get a lot of DBAs in to fine tune your databases, make sure everything was running really, really well. The notion that there's, you know, no indexes to tune, right? There's very few knobs and dials, you can turn on Snowflake. That was appealing that, you know, it just kind of worked. So we found a use case to bring the platform in. We basically used it as a logging replacement as a Splunk kind of replacement with a platform called Elysium Analytics as a way to just get it in the door and give us the opportunity to solve a real world use case, but also to help us start to experiment using Snowflake as a platform. It took us a while to A, get the funding to bring it in, but B, build the momentum behind it. But, you know, as we experimented we added more data in there, we ran a few more experiments, we piloted in few more applications, we really saw the power of the platform and now, we are becoming a commercial organization. And with that comes a lot of major datasets. And so, you know, we really see Snowflake as being a very important part of our ecology going forward to help us build out our infrastructure. >> Okay, and you are running, your group runs on Azure, it's kind of mono cloud, single cloud, but others within Ionis are using other clouds, but you're not currently, you know, collaborating in terms of data sharing. And I wonder if you could talk about how your data needs have evolved over the past decade. I know you came from another highly regulated industry in financial services. So what's changed? You sort of touched on this before, you had these, you know, very specialized individuals who were, you know, DBAs, and, you know, could tune databases and the like, so that's evolved, but how has generally your needs evolved? Just kind of make an observation over the last, you know, five or seven years. What have you seen? >> Well, we, I wasn't in a group that did a lot of warehousing. It was more like online trade capture, but, you know, it was very much on-prem. You know, being in the cloud is very much a dirty word back then. I know that's changed since I've left. But in, you know, we had major, major teams of everyone who could do everything, right. As I mentioned in the pharma organization, there's a lot fewer of us. So the data needs there are very different, right? It's, we have a lot of SaaS applications. One of the difficulties with bringing a lot of SaaS applications on board is obviously data integration. So making sure the data is the same between them. But one of the big problems is joining the data across those SaaS applications. So one of the benefits, one of the things that we use Snowflake for is to basically take data out of these SaaS applications and load them into a warehouse so we can do those joins. So we use technologies like Boomi, we use technologies like Fivetran, like DBT to bring this data all into one place and start to kind of join that basically, allow us to do, run experiments, do analysis, basically take better, find better use for our data that was siloed in the past. You mentioned- >> Yeah. And just to add on to Nick's point there. >> Go ahead. >> That's actually something very common that we're seeing across the industry is because a lot of these SaaS applications that you mentioned, Nick, they're with from vendors that are trying to build their own ecosystem in walled garden. And by definition, many of them do not want to integrate with one another. So from a, you know, from a data platform vendor's perspective, we see this as a huge opportunity to help organizations like Ionis and others kind of deal with the challenges that Nick is speaking about because if the individual platform vendors are never going to make that part of their strategy, we see it as a great way to add additional value to these customers. >> Well, this data sharing thing is interesting. There's a lot of walled gardens out there. Oracle is a walled garden, AWS in many ways is a walled garden. You know, Microsoft has its walled garden. You could argue Snowflake is a walled garden. But the, what we're seeing and the whole reason behind the notion of super-cloud is we're creating an abstraction layer where you actually, in this case for this use case, can share data in a governed manner. Let's forget about the cross-cloud for a moment. I'll come back to that, but I wonder, Nick, if you could talk about how you are sharing data, again, Snowflake sort of, it's, I look at Snowflake like the app store, Apple, we're going to control everything, we're going to guarantee with data clean rooms and governance and the standards that we've created within that platform, we're going to make sure that it's safe for you to share data in this highly regulated industry. Are you doing that today? And take us through, you know, the considerations that you have in that regard. >> So it's kind of early days for us in Snowflake in general, but certainly in data sharing, we have a couple of examples. So data marketplace, you know, that's a great invention. It's, I've been a small IT shop again, right? The fact that we are able to just bring down terabyte size datasets straight into our Snowflake and run analytics directly on that is huge, right? The fact that we don't have to FTP these massive files around run jobs that may break, being able to just have that on tap is huge for us. We've recently been talking to one of our CRO feeds- CRO organizations about getting their data feeds in. Historically, this clinical trial data that comes in on an FTP file, we have to process it, take it through the platforms, put it into the warehouse. But one of the CROs that we talked to recently when we were reinvestigate in what data opportunities they have, they were a Snowflake customer and we are, I think, the first production customer they have, have taken that feed. So they're basically exposing their tables of data that historically came in these FTP files directly into our Snowflake instance now. We haven't taken advantage of that. It only actually flipped the switch about three or four weeks ago. But that's pretty big for us again, right? We don't have to worry about maintaining those jobs that take those files in. We don't have to worry about the jobs that take those and shove them on the warehouse. We now have a feed that's directly there that we can use a tool like DBT to push through directly into our model. And then the third avenue that's came up, actually fairly recently as well was genetics data. So genetics data that's highly, highly regulated. We had to be very careful with that. And we had a conversation with Snowflake about the data white rooms practice, and we see that as a pretty interesting opportunity. We are having one organization run genetic analysis being able to send us those genetic datasets, but then there's another organization that's actually has the in quotes "metadata" around that, so age, ethnicity, location, et cetera. And being able to join those two datasets through some kind of mechanism would be really beneficial to the organization. Being able to build a data white room so we can put that genetic data in a secure place, anonymize it, and then share the amalgamated data back out in a way that's able to be joined to the anonymized metadata, that could be pretty huge for us as well. >> Okay, so this is interesting. So you talk about FTP, which was the common way to share data. And so you basically, it's so, I got it now you take it and do whatever you want with it. Now we're talking, Jesse, about sharing the same copy of live data. How common is that use case in your industry? >> It's become very common over the last couple of years. And I think a big part of it is having the right technology to do it effectively. You know, as Nick mentioned, historically, this was done by people sending files around. And the challenge with that approach, of course, while there are multiple challenges, one, every time you send a file around your, by definition creating a copy of the data because you have to pull it out of your system of record, put it into a file, put it on some server where somebody else picks it up. And by definition at that point you've lost governance. So this creates challenges in general hesitation to doing so. It's not that it hasn't happened, but the other challenge with it is that the data's no longer real time. You know, you're working with a copy of data that was as fresh as at the time at that when that was actually extracted. And that creates limitations in terms of how effective this can be. What we're starting to see now with some of our customers is live sharing of information. And there's two aspects of that that are important. One is that you're not actually physically creating the copy and sending it to someone else, you're actually exposing it from where it exists and allowing another consumer to interact with it from their own account that could be in another region, some are running in another cloud. So this concept of super-cloud or cross-cloud could becoming realized here. But the other important aspect of it is that when that other- when that other entity is querying your data, they're seeing it in a real time state. And this is particularly important when you think about use cases like supply chain planning, where you're leveraging data across various different enterprises. If I'm a manufacturer or if I'm a contract manufacturer and I can see the actual inventory positions of my clients, of my distributors, of the levels of consumption at the pharmacy or the hospital that gives me a lot of indication as to how my demand profile is changing over time versus working with a static picture that may have been from three weeks ago. And this has become incredibly important as supply chains are becoming more constrained and the ability to plan accurately has never been more important. >> Yeah. So the race is on to solve these problems. So it start, we started with, hey, okay, cloud, Dave, we're going to simplify database, we're going to put it in the cloud, give virtually infinite resources, separate compute from storage. Okay, check, we got that. Now we've moved into sort of data clean rooms and governance and you've got an ecosystem that's forming around this to make it safer to share data. And then, you know, nirvana, at least near term nirvana is we're going to build data applications and we're going to be able to share live data and then you start to get into monetization. Do you see, Nick, in the near future where I know you've got relationships with, for instance, big pharma like AstraZeneca, do you see a situation where you start sharing data with them? Is that in the near term? Is that more long term? What are the considerations in that regard? >> I mean, it's something we've been thinking about. We haven't actually addressed that yet. Yeah, I could see situations where, you know, some of these big relationships where we do need to share a lot of data, it would be very nice to be able to just flick a switch and share our data assets across to those organizations. But, you know, that's a ways off for us now. We're mainly looking at bringing data in at the moment. >> One of the things that we've seen in financial services in particular, and Jesse, I'd love to get your thoughts on this, is companies like Goldman or Capital One or Nasdaq taking their stack, their software, their tooling actually putting it on the cloud and facing it to their customers and selling that as a new monetization vector as part of their digital or business transformation. Are you seeing that Jesse at all in healthcare or is it happening today or do you see a day when that happens or is healthier or just too scary to do that? >> No, we're seeing the early stages of this as well. And I think it's for some of the reasons we talked about earlier. You know, it's a much more secure way to work with a colleague if you don't have to copy your data and potentially expose it. And some of the reasons that people have historically copied that data is that they needed to leverage some sort of algorithm or application that a third party was providing. So maybe someone was predicting the ideal location and run a clinical trial for this particular rare disease category where there are only so many patients around the world that may actually be candidates for this disease. So you have to pick the ideal location. Well, sending the dataset to do so, you know, would involve a fairly complicated process similar to what Nick was mentioning earlier. If the company who was providing the logic or the algorithm to determine that location could bring that algorithm to you and you run it against your own data, that's a much more ideal and a much safer and more secure way for this industry to actually start to work with some of these partners and vendors. And that's one of the things that we're looking to enable going into this year is that, you know, the whole concept should be bring the logic to your data versus your data to the logic and the underlying sharing mechanisms that we've spoken about are actually what are powering that today. >> And so thank you for that, Jesse. >> Yes, Dave. >> And so Nick- Go ahead please. >> Yeah, if I could add, yeah, if I could add to that, that's something certainly we've been thinking about. In fact, we'd started talking to Snowflake about that a couple of years ago. We saw the power there again of the platform to be able to say, well, could we, we were thinking in more of a data share, but could we share our data out to say an AI/ML vendor, have them do the analytics and then share the data, the results back to us. Now, you know, there's more powerful mechanisms to do that within the Snowflake ecosystem now, but you know, we probably wouldn't need to have onsite AI/ML people, right? Some of that stuff's very sophisticated, expensive resources, hard to find, you know, it's much better for us to find a company that would be able to build those analytics, maintain those analytics for us. And you know, we saw an opportunity to do that a couple years ago and we're kind of excited about the opportunity there that we can just basically do it with a no op, right? We share the data route, we have the analytics done, we get the result back and it's just fairly seamless. >> I mean, I could have a whole another Cube session on this, guys, but I mean, I just did a a session with Andy Thurai, a Constellation research about how difficult it's been for organization to get ROI because they don't have the expertise in house so they want to either outsource it or rely on vendor R&D companies to inject that AI and machine intelligence directly into applications. My follow-up question to you Nick is, when you think about, 'cause Jesse was talking about, you know, let the data basically stay where it is and you know bring the compute to that data. If that data lives on different clouds, and maybe it's not your group, but maybe it's other parts of Ionis or maybe it's your partners like AstraZeneca, or you know, the AI/ML partners and they're potentially on other clouds or that data is on other clouds. Do you see that, again, coming back to super-cloud, do you see it as an advantage to be able to have a consistent experience across those clouds? Or is that just kind of get in the way and make things more complex? What's your take on that, Nick? >> Well, from the vendors, so from the client side, it's kind of seamless with Snowflake for us. So we know for a fact that one of the datasets we have at the moment, Compile, which is a, the large multi terabyte dataset I was talking about. They're on AWS on the East Coast and we are on Azure on the West Coast. And they had to do a few tweaks in the background to make sure the data was pushed over from, but from my point of view, the data just exists, right? So for me, I think it's hugely beneficial that Snowflake supports this kind of infrastructure, right? We don't have to jump through hoops to like, okay, well, we'll download it here and then re-upload it here. They already have the mechanism in the background to do these multi-cloud shares. So it's not important for us internally at the moment. I could see potentially at some point where we start linking across different groups in the organization that do have maybe Amazon or Google Cloud, but certainly within our providers. We know for a fact that they're on different services at the moment and it just works. >> Yeah, and we learned from Benoit Dageville, who came into the studio on August 9th with first Supercloud in 2022 that Snowflake uses a single global instance across regions and across clouds, yeah, whether or not you can query across you know, big regions, it just depends, right? It depends on latency. You might have to make a copy or maybe do some tweaks in the background. But guys, we got to jump, I really appreciate your time. Really thoughtful discussion on the future of data and cloud, specifically within healthcare and pharma. Thank you for your time. >> Thanks- >> Thanks for having us. >> All right, this is Dave Vellante for theCUBE team and my co-host, John Furrier. Keep it right there for more action at Supercloud 2. (upbeat music)

>>Now welcome back to the Cube as we continue our coverage here. AWS Reinvent 2022, going out here at the Venetian in Las Vegas. Tens of thousands of attendees. That exhibit Hall is full. Let me tell you, it's been something else. Well, here in the executive summit, sponsored by Accenture. Accenture rather. We're gonna talk about Baptist Health, what's going on with that organization down in South Florida with me. To do that, I have Tony Abro, who's the SVP and Chief Digital and Information Officer. I have Ashley Lane, the managing director of the Accenture Healthcare Practice, and on the far end Poop Kumar, who is the VP and cto Baptist Health Florida won and all. Welcome. Thank you. First off, let's just talk about Baptist Health, the size of your footprint. One and a half million patient visits a year, not a small number. >>That was probably last year's number, but okay. >>Right. But not a small number about your footprint and, and what, I guess the client base basically that you guys are serving in it. >>Absolutely. So we are the largest organization in South Florida system provider and the 11 hospitals soon to be 12, as you said, it's probably about 1.8 million by now. People were, were, were supporting a lot of other units and you know, we're focusing on the four southern counties of South Florida. Okay. >>So got day Broward. Broward, yep. Down that way. Got it. So now let's get to your migration or your cloud transformation. As we're talking about a lot this week, what's been your, I guess, overarching goal, you know, as you worked with Accenture and, and developed a game plan going forward, you know, what was on the front end of that? What was the motivation to say this is the direction we're going to go and this is how we're gonna get there? >>Perfect. So Baptist started a digital transformation initiative before I came about three years ago. The board, the executive steering committee, decided that this is gonna be very important for us to support us, to help our patients and, and consumers. So I was brought in for that digital transformation. And by the way, digital transformation is kind of an umbrella. It's really business transformation with technology, digital technologies. So that's, that's basically where we started in terms of consumer focused and, and, and patient focus. And digital is a big word that really encompasses a lot of things. Cloud is one of, of course. And, you know, AI and ML and all the things that we are here for this, this event, you know, and, and we've started that journey about two years ago. And obviously cloud is very important. AWS is our main cloud provider and clearly in AWS or any club providers is not just the infrastructure they're providing, it's the whole ecosystem that provides us back value into, into our transformation. And then somebody, I think Adam this morning at the keynote said, this is a team sport. So with this big transformation, we need all the help and that we can get to mines and, and, and hands. And that's where Accenture has been invaluable over the last two years. >>Yeah, so as a team sport then depu, you, you've got external stakeholders, otherwise we talked about patience, right? Internal, right. You've, you've got a whole different set of constituents there, basically, but it takes that team, right? You all have to work together. What kind of conversations or what kind of actions, I guess have you had with different departments and what different of sectors of, of the healthcare business as Baptist Health sees it in order to bring them along too, because this is, you know, kind of a shocking turn for them too, right? And how they're gonna be doing business >>Mostly from an end user perspective. This is something that they don't care much about where the infrastructure is hosted or how the services are provided from that perspective. As long as the capabilities function in a better way, they are seemingly not worried about where the hosting is. So what we focus on is in terms of how it's going to be a better experience for, from them, from, from their perspective, right? How is it going to be better responsiveness, availability, or stability overall? So that's been the mode of communication from that perspective. Other than that, from a, from a hosting and service perspective, the clientele doesn't care as much as the infrastructure or the security or the, the technology and digital teams themselves. >>But you know, some of us are resistant to change, right? We're, we're just, we are old dogs. We don't like new tricks and, and change can be a little daunting sometimes. So even though it is about my ease of use and my efficiency and why I can then save my time on so and so forth, if I'm used to doing something a certain way, and that's worked fine for me and here comes Tony and Depo and here comes a, >>They're troublemaker >>And they're stir my pot. Yeah. So, so how do you, the work, you were giving advice maybe to somebody watching this and say, okay, you've got internal, I wouldn't say battles, but discussions to be held. How did you navigate through that? >>Yeah, no, absolutely. And Baptist has been a very well run system, very successful for 60 something odd years. Clearly that conversation did come, why should we change? But you always start with, this is what we think is gonna happen in the future. These are the changes that very likely will happen in the future. One is the consumer expectations are the consumer expectations in terms of their ability to have access to information, get access to care, being control of the process and their, their health and well-being. Everything else that happens in the market. And so you start with the, with that, and that's where clearly there are, there are a lot of signs that point to quite a lot of change in the ecosystem. And therefore, from there, the conversation is how do we now meet that challenge, so to speak, that we all face in, in, in healthcare. >>And then from there, you kind of designed the, a vision of where we want to be in terms of that digital transformation and how do we get there. And then once that is well explained and evangelized, and that's part of our jobs with the help of our colleagues who have, have been doing this with others, then is the, what I call a tell end show. We're gonna say, okay, in this, in this road, we're gonna start with this. It's a small thing and we're gonna show you how it works in terms of, in terms of the process, right? And then as, as you go along and you deliver some things, people understand more, they're on board more and they're ready for for more. So it's iterative from small to larger. >>The proof is always in the place, right? If you can show somebody, so actually I, I obviously we know about Accenture's role, but in terms of almost, almost what Tony was just saying, that you have to show people that it works. How, how do you interface with a client? And when you're talking about these new approaches and you're suggesting changes and, and making these maybe rather dramatic proposals, you know, to how they do things internally, from Accenture's perspective, how do you make it happen? How, how do you bring the client along in this case, batches >>Down? Well, in this case, with Tony and Depu, I mean, they have been on this journey already at another client, right? So they came to Baptist where they had done a similar journey previously. And so it wasn't really about convincing >>Also with Accenture's >>Health, also with Accenture's Health, correct. But it wasn't about telling Tony Dupe, how do we do this? Or anything like that. Cuz they were by far the experts and have, you know, the experience behind it. Well, it's really like, how do we make sure that we're providing the right, right team, the right skills to match, you know, what they wanted to do and their aspirations. So we had brought the, the healthcare knowledge along with the AWS knowledge and the architects and you know, we said that we gotta, you know, let's look at the roadmap and let's make sure that we have the right team and moving at the right pace and, you know, testing everything out and working with all the different vendors in the provider world specifically, there's a lot of different vendors and applications that are, you know, that are provided to them. It's not a lot of custom activity, you know, applications or anything like that. So it was a lot of, you know, working with other third party that we really had to align with them and with Baptist to make sure that, you know, we were moving together at speed. >>Yeah, we've heard about transformation quite a bit. Tony, you brought it up a little bit ago, depu, just, if you had to define transformation in this case, I mean, how big of a, of a, of a change is that? I mean, how, how would you describe it when you say we're gonna transform our, you know, our healthcare business? I mean, I think there are a lot of things that come to my mind, but, but how do you define it and, and when you're, when you're talking to the folks with whom you've got to bring along on this journey? >>So there's the transformation umbrella and compos two or three things. As Tony said, there is this big digital transformation that everybody's talking about. Then there is this technology transformation that powers the digital transformation and business transformation. That's the outcome of the digital transformation. So I think we, we started focusing on all three areas to get the right digital experience for the consumers. We have to transform the way we operate healthcare in its current state or, or in the existing state. It's a lot of manual processes, a lot of antiquated processes, so to speak. So we had to go and reassess some of that and work with the respective business stakeholders to streamline those because in, it's not about putting a digital solution out there with the anti cured processes because the outcome is not what you expect when you do that. So from that perspective, it has been a heavy lifting in terms of how we transform the operations or the processes that facilitates some of the outcomes. >>How do you know it's working >>Well? So I I, to add to what Deep was saying is I think we are fortunate and that, you know, there are a lot of folks inside Baptist who have been wanting this and they're instrumental to this. So this is not a two man plus, you know, show is really a, you know, a, a team sport. Again, that same. So in, in that, that in terms of how do we know it works well when, when we define what we want to do, there is some level of precision along the way. In those iterations, what is it that we want to do next, right? So whatever we introduce, let's say a, a proper fluid check in for a patient into a, for an appointment, we measure that and then we measure the next one, and then we kind of zoom out and we look at the, the journey and say, is this better? >>Is this better for the consumer? Do they like it better? We measure that and it's better for the operations in terms of, but this is the interesting thing is it's always a balance of how much you can change. We want to improve the consumer experience, but as deeply said, there's lot to be changed in, in the operations, how much you do at the same time. And that's where we have to do the prioritization. But you know, the, the interesting thing is that a lot of times, especially on the self servicing for consumers, there are a lot of benefits for the operations as well. And that's, that's where we're in, we're in it together and we measure. Yeah, >>Don't gimme too much control though. I don't, I'm gonna leave the hard lifting for you. >>Absolutely, absolutely right. Thank you. >>So, and, and just real quick, Ashley, maybe you can shine some light on this, about the relationship, about, about next steps, about, you know, you, you're on this, this path and things are going well and, and you've got expansion plans, you want, you know, bring in other services, other systems. Where do you want to take 'em in the big picture in terms of capabilities? >>Well, I, I mean, they've been doing a fantastic job just being one of the first to actually say, Hey, we're gonna go and make an investment in the cloud and digital transformation. And so it's really looking at like, what are the next problems that we need to solve, whether it's patient care diagnosis or how we're doing research or, you know, the next kind of realm of, of how we're gonna use data and to improve patient care. So I think it's, you know, we're getting the foundation, the basics and everything kind of laid out right now. And then it's really, it's like what's the next thing and how can we really improve the patient care and the access that they have. >>Well, it sure sounds like you have a winning accommodation, so I I keep the team together. >>Absolutely. >>Teamwork makes the dream >>Work. Absolutely. It is, as you know. So there's a certain amount of, if you look at the healthcare industry as a whole, and not, not just Baptist, Baptist is, you know, fourth for thinking, but entire industry, there's a lot of catching up to do compared to whatever else is doing, whatever else the consumers are expecting of, of an entity, right? But then once we catch up, there's a lot of other things that we were gonna have to move on, innovate for, for problems that we maybe we don't know we have will have right now. So plenty of work to do. Right. >>Which is job security for everybody, right? >>Yes. >>Listen, thanks for sharing the story. Yeah, yeah. Continued success. I wish you that and I appreciate the time and expertise here today. Thank you. Thanks for being with us. Thank you. Thank you. We'll be back with more. You're watching the Cube here. It's the Executive Summit sponsored by Accenture. And the cube, as I love to remind you, is the leader in tech coverage.

foreign [Music] my name is Savannah Peterson and I am very excited to be coming to you today from the cube in Palo Alto we're going to be talking about kubecon giving a little preview of the hype and what you might be able to expect in Detroit with the one and only co-founder and CEO of the cube and siliconangle John ferriere John hello how are you today thanks for hosting and doing the preview with me my goodness a pleasure I we got acquainted this time last year how do you think the ecosystem has changed are you excited well first of all I missed kubecon Valencia because I had covid I was so excited to be there this big trip plan and then couldn't make it but so much has gone on I mean we've been at every kubecon the cube was there at the beginning when openstack was still going on kubernetes just started came out of Google we were there having beers with Lou Tucker and a bunch of The Luminaries when it all kind of came together and then watch it year by year progress through and how it's changed the industry and mainly how open source has been really the wave behind it combining with the Linux foundation and then cncf and then open source movement and good kubernetes has been amazing and under it all containers has been the real driver and all this so you know Docker containers Docker was a well-funded company they had to Pivot and were restructured now they're pure open source so containers have gone Supernova on top of that kubernetes and with that's a complete ecosystem of opportunity to create the next operating system in in software development so to me kubecon is at the center of software software 2030 what do you want to call it super cloud it's that it's really action it's not where the old school is it's where the new school is excellent so what has you most excited this year what's the biggest change from this time last year and now well two things I'm looking at this year uh carefully both from an editorial lens and also from a sponsorship lenses where is the funding going on the sponsorships because again a very diverse ecosystem of Builders but also vendors so I'm going to see how that Dynamics going on but also on the software side a lot of white space going on in the stack or in the map if you will you know the run times you've got observability you got a lot of competition maybe projects might be growing some Rising some falling maybe merge together I'm going to see how that but there's a lot of white spaces developing so I'm curious to see what's new on that area and then service meshes is a big deal this year so I'm looking for what's going on so it's been kind of a I won't say cold war but kind of like uh you know where is this going to go and because it's a super important part of of the of the orchestration and managing containers and so be very interested to see how service mesh does istio and other versions out there have been around for a while so that and also the other controversy is the number of stars on GitHub a project may have so sometimes that carries a lot of weight but we're going to look at which ones are rising which ones are falling again um which ones are getting the most votes by the developers vote with their code yeah absolutely well we did definitely miss you down in Los Angeles but it will be great to be in Detroit what has you most excited do you think that we're going to see the number of people in person that we have in the past I know you've seen it since the beginning so I think this year is going to be explosive from that psychology angle because I think it was really weird because La was on they were a bold to make that move we're all there is first conference back it was a lot a lot of like badges don't touch me only handshakes fist pumps but it was at the beginning of the covid second wave right so it was kind of still not yet released where everyone's was not worried about it so I think it's in the past year in the past eight months I mean I've been places with no masks people have no masks Vegas other places so I think it's going to be a year where it will be a lot more people in person because the growth and the opportunities are so big it's going to drive a lot of people in person just like Amazon reinvent those yeah absolutely and as the most important and prominent event in the kubernetes space I think everyone's very excited to to get back together when we think about this space do you think there that anyone's the clear winner yet or do you think it's still a bit of a open territory in terms of the companies and Partnerships I think Red Hat has done a great job and they're you know I think they're going to see how well they can turn this into gold for them because they've positioned themselves very well open shift years ago was kind of waffling I won't say it in a bad way but like but once they got view on containers and kubernetes red has done an exceptional job in how they position their company being bought by ibms can be very interesting to see how that influences change so if Red Hat can stay red hat I think IBM will win I think customers that's one company I like the startups we're seeing companies like platform nine Rafi systems young companies coming out in the kubernetes as a service space because I think whoever can make kubernetes easier because I think that's the hard part right now even though that the show is called kubecon is a lot more than kubernetes I think the container layer what docker's doing has been exceptional that's the real action the question is how does that impact the kubernetes layers so kubernetes is not a done deal yet I think it hasn't really crossed the chasm yet it's certainly popular but not every company is adopting it so we're starting to see that we need to see more adoption of kubernetes seeing that happen it's going to decide who the winners are totally agree with that if you look at the data a lot of companies are and people are excited about kubernetes but they haven't taken the plunge to shifting over their stack or fully embracing it because of that complexity so I'm very curious to see what we learn this week about who those players might be moving forward how does it feel to be in Detroit when was the last time you were here I was there in 2007 was the last time I was in that town so uh we'll see what's like wow yeah but things have changed yeah the lions are good this year they've got great hockey goalies there so you know all right you've heard that sports fans let John know what you're thinking your Sports predictions for this season I love that who do you hope to get to meet while we're at the show I want to meet more end user customers we're gonna have Envoy again on the cube I think Red Hat was going to be a big sponsor this year they've been great um we're looking for end user project most looking for some editorial super cloud like um commentary because the cncf is kind of the developer Tech Community that's powering in my opinion this next wave of software development Cloud native devops is now Cloud native developers devops is kind of going away that's killed I.T in my opinion data and security Ops is the new kind of Ops the new it so it's good to see how devops turns into more of a software engineering meet supercloud so I think you're going to start to see the infrastructure become more programmable it's infrastructure as code so I think if anything I'm more excited to hear more stories about how infrastructure as code is now the new standard so if when that truly happens the super cloud model be kicking into high gear I love that let's you touched on it a little bit right there but I want to dig in a bit since you've been around since the beginning what is it that you appreciate or enjoy so much about the kubernetes community and the people around this I think there are authentic people and I think they're they're building they're also Progressive they're very diverse um they're open and inclusive they try stuff and um they can be critical but they're not jerks about it so when people try something um they're open-minded of a failure so it's a classic startup mentality I think that is embodied throughout the Linux Foundation but CNC in particular has to bridge the entrepreneurial and corporate Vibe so they've done an exceptional job doing that and that's what I like about this money making involved but there's also a lot of development and Innovation that comes out of it so the next big name and startup could come out of this community and that's what I hope to see coming out here is that next brand that no one's heard of that just comes out of nowhere and just takes a big position in the marketplace so that's going to be interesting to see hopefully we have on our stage there yeah that's the goal we're going to interview them all a year from now when we're sitting here again what do you hope to be able to say about this space or this event that we might not be able to say today I think it's going to be more of clarity around um the new modern software development techniques software next gen using AI more faster silicon chips you see Amazon with what they're doing the custom silicon more processing but I think Hardware matters we've been talking a lot about that I think I think it's we're going to shift from what's been innovative and what's changed I think I think if you look at what's been going on in the industry outside of crypto the infrastructure hasn't really changed much except for AWS what they've done so I'm expecting to see more Innovations at the physics level way down in the chips and then that lower end of the stack is going to be dominated by either one of the three clouds probably AWS and then the middle layer is going to be this where the abstraction is around making infrastructure as code really happen I think that's going to be Clarity coming out of this year next year we should have some visibility into the vertical applications and of the AI and machine learning absolutely digging in on that actually even more because I like what you're saying a lot what verticals do you think that kubernetes is going to impact the most looking even further out than say a year I mean I think that hot ones Healthcare fintech are obvious to get the most money they're spending I think they're the ones who are already kind of creating these super cloud models where they're actually changed over their their spending from capex to Opex and they're driving top line revenue as part of that so you're seeing companies that wants customers of the I.T vendors are now becoming the providers that's a big super cloud Trend we see the other verticals are going to be served by a lot of men in Surprise oil and gas you know all the classic versus Healthcare I mentioned that one those are the classic verticals retail is going to I think be massively huge as you get more into the internet of things that's truly internet based you're going to start to see a lot more Edge use cases so Telecom I think it's going to be completely disrupted by new brands so I think once that you see see how that plays out but all verticals are going to be disrupted just a casual statement to say yeah yeah no doubt in my mind that's great I'm personally really excited about the edge applications that are possible here and can't wait to see can't wait to see what happens next I'm curious as to your thoughts how based given your history here and we don't have to say number of years that you've been participating in in Cape Cod but give them your history what's the evolution looked like from that Community perspective when you were all just starting out having that first drink did you anticipate that we would be here with thousands of people in Detroit you know I knew the moment was happening around um 2017-2018 Dan Coney no longer with us he passed away I ran into him randomly in China and it was like what are you doing here he was with a bunch of Docker guys so they were already investing in so I knew that the cncf was a great Steward for this community because they were already doing the work Dan led a great team at that time and then they were they were they were kicking ass and they were just really setting the foundation they dig in they set the architecture perfectly so I knew that that was a moment that was going to be pretty powerful at the early days when we were talking about kubernetes before it even started we were always always talking about if this this could be the tcpip of of cloud then we could have kind of a de facto interoperability and Lou Tucker was working for Cisco at the time and we were called it interclouding inter-networking what that did during the the revolution Cloud yeah the revolution of the client server and PC Revolution was about connectivity and so tcpip was the disruptive enable that created massive amounts of wealth created a lot of companies created a whole generation of companies so I think this next inflection point is kind of happening right now I think kubernetes is one step of this abstraction layer but you start to see companies like snowflake who's built on AWS and then moved to multiple clouds Goldman Sachs Capital One you're going to see insurance companies so we believe that the rise of the super cloud is here that's going to be Cloud 3.0 that's software 3.0 it's software three what do you want to call it it's not yesterday's Cloud lift and shift and run a SAS application it's a true Enterprise digital digital transformation so that's that's kind of the trend that we see riding in now and so you know if you're not on that side of the street you're going to get washed away from that wave so it's going to be interesting to see how how it all plays out so it's fun to watch who's on the wrong side it is very fun I hope you all are listening to this really powerful advice from John he's dropping some serious knowledge bombs on us well holding the back for kubecon because we've got we got all the great guests coming on and that's where all the content comes from I mean the best part of the community is that they're sharing yeah absolutely so just for old time's sake and it's because it's how I met your fabulous team last year Define kubernetes for the audience kubernetes is like what someone said it was a magical Christmas I heard that was a well good explanation with that when I heard that one um you mean the technical definition or like the business definition or maybe both you can give us an interpretive dance if you'd like I mean the simplest way to describe kubernetes is an orchestration layer that orchestrates containers that are containing applications and it's a way to keep things running and runtime assembly of like the of the data so if you've got you're running containers you can containerize applications kubernetes gives you that capability to run applications at scale which feeds into uh the development uh cycle of the pipelining of apps so if you're writing applications and you want to scale up it's a fast way to stand up massive amounts of scale using containers and kubernetes so a variety of other things that are in the in the in the system too so that was pretty good there's a lot more under the hood but that's the oversimplified version I think that's what we were going for I think it's actually I mean it's harder to oversimplify it sometimes in this case it connects it connects well it's the connective tissue between all the container applications yes last question for you John we are here at the cube we're very excited to be headed to Detroit very soon what can people expect from the cube at coupon this year so we'll be broadcasting Wednesday Thursday and Friday we'll be there early I'll be there Monday and Tuesday we'll do our normal kind of hanging around getting some scoop on the on the ground floor you'll see us there Monday and Tuesday probably in the in the lounge too um come up and say hi to us um again we're looking for more stories this year we believe this is the year that you're going to hear a lot more storytelling coming out of this community as people get more proof points so come up to us share your email your your handle give us yours give us your story we'll publish it we think we think this is going to be the year that cloud native developers start showing the signs of the of the rise of the supercloud that's going to come out of this this community so you know if you got something to say you know we're open to share stories so we're here all that speaking of John how can people say hi to you and the team on Twitter at Furrier at siliconangle at thecube thecube.net siliconangle.com LinkedIn Dave vellantis they were open on all channels all right signal Instagram WhatsApp perfect well pick your channel we really hope to hear from you John thank you so much for joining us for this preview session and thank you for tuning in my name is Savannah Peterson here in Palo Alto at thecube Studios looking forward to Detroit we can't wait to hear your thoughts do let us know in the comments and let us know if you're headed to Michigan cheers [Music] thank you

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 music) >> theCUBE presents KubeCon and CloudNativeCon Europe 22, brought to you by the Cloud Native Computing Foundation. >> Valencia, Spain, a KubeCon, CloudNativeCon Europe 2022. I'm Keith Towns along with Paul Gillon, Senior Editor Enterprise Architecture for Silicon Angle. Welcome Paul. >> Thank you Keith, pleasure to work with you. >> We're going to have some amazing people this week. I think I saw stat this morning, 65% of the attendees, 7,500 folks. First time KubeCon attendees, is this your first conference? >> It is my first KubeCon and it is amazing to see how many people are here and to think of just a couple of years ago, three years ago, we were still talking about, what the Cloud was, what the Cloud was going to do and how we were going to integrate multiple Clouds. And now we have this whole new framework for computing that is just rifled out of nowhere. And as we can see by the number of people who are here this has become the dominant trend in Enterprise Architecture right now how to adopt Kubernetes and containers, build microservices based applications, and really get to that transparent Cloud that has been so elusive. >> It has been elusive. And we are seeing vendors from startups with just a few dozen people, to some of the traditional players we see in the enterprise space with 1000s of employees looking to capture kind of lightning in a bottle so to speak, this elusive concept of multicloud. >> And what we're seeing here is very typical of an early stage conference. I've seen many times over the years where the floor is really dominated by companies, frankly, I've never heard of that. The many of them are only two or three years old, you don't see the big dominant computing players with the presence here that these smaller companies have. That's very typical. We saw that in the PC age, we saw it in the early days of Unix and it's happening again. And what will happen over time is that a lot of these companies will be acquired, there'll be some consolidation. And the nature of this show will change, I think dramatically over the next couple or three years but there is an excitement and an energy in this auditorium today that is really a lot of fun and very reminiscent of other new technologies just as they requested. >> Well, speaking of new technologies, we have Dave Cole, CRO, Chief Revenue Officer. >> That's right. >> Chief Marketing Officer of Spectrum Cloud. Welcome to the show. >> Thank you. It's great to be here. >> So let's talk about this big ecosystem, Kubernetes. >> Yes. >> Solve problem? >> Well the dream is... Well, first of all applications are really the lifeblood of a company, whether it's our phone or whether it's a big company trying to connect with its customers about applications. And so the whole idea today is how do I build these applications to build that tight relationship with my customers? And how do I reinvent these applications rapidly in along comes containerization which helps you innovate more quickly? And certainly a dominant technology there is Kubernetes. And the question is, how do you get Kubernetes to help you build applications that can be born anywhere and live anywhere and take advantage of the places that it's running? Because everywhere has pluses and minuses. >> So you know what, the promise of Kubernetes from when I first read about it years ago is, runs on my laptop? >> Yeah. >> I can push it to any Cloud, any platforms. >> That's right, that's right. >> Where's the gap? Where are we in that phase? Like talk to me about scale? Is it that simple? >> Well, that is actually the problem is that today, while the technology is the dominant containerization technology in orchestration technology, it really still takes a power user, it really hasn't been very approachable to the masses. And so was these very expensive highly skilled resources that sit in a dark corner that have focused on Kubernetes, but that now is trying to evolve to make it more accessible to the masses. It's not about sort of hand wiring together, what is a typical 20 layer stack, to really manage Kubernetes and then have your engineers manually can reconfigure it and make sure everything works together. Now it's about how do I create these stacks, make it easy to deploy and manage at scale? So we've gone from sort of DIY Developer Centric to all right, now how do I manage this at scale? >> Now this is a point that is important, I think is often overlooked. This is not just about Kubernetes. This is about a whole stack of Cloud Native Technologies. And you who is going to integrate that all that stuff, piece that stuff together? Obviously, you have a role in that. But in the enterprise, what is the awareness level of how complex this stack is and how difficult it is to assemble? >> We see a recognition of that we've had developers working on Kubernetes and applications, but now when we say, how do we weave it into our production environments? How do we ensure things like scalability and governance? How do we have this sort of interesting mix of innovation, flexibility, but with control? And that's sort of an interesting combination where you want developers to be able to run fast and use the latest tools, but you need to create these guardrails to deploy it at scale. >> So where do the developers fit in that operation stack then? Is Kubernetes an AIOps or an ops task or is it sort of a shared task across the development spectrum? >> Well, I think there's a desire to allow application developers to just focus on the application and have a Kubernetes related technology that ensures that all of the infrastructure and related application services are just there to support them. And because the typical stack from the operating system to the application can be up to 20 different layers, components, you just want all those components to work together, you don't want application developers to worry about those things. And the latest technologies like Spectra Cloud there's others are making that easy application engineers focus on their apps, all of the infrastructure and the services are taken care of. And those apps can then live natively on any environment. >> So help paint this picture for us. I get AKS, EKS, Anthos, all of these distributions OpenShift, the Tanzu, where's Spectra Cloud helping me to kind of cobble together all these different distros, I thought distro was the thing just like Linux has different distros, Randy said different distros. >> That actually is the irony, is that sort of the age of debating the distros largely is over. There are a lot of distros and if you look at them there are largely shades of gray in being different from each other. But the Kubernetes distribution is just one element of like 20 elements that all have to work together. So right now what's happening is that it's not about the distribution it's now how do I again, sorry to repeat myself, but move this into scale? How do I move it into deploy at scale to be able to manage ongoing at scale to be able to innovate at-scale, to allow engineers as I said, use the coolest tools but still have technical guardrails that the enterprise knows, they'll be in control of. >> What does at-scale mean to the enterprise customers you're talking to now? What do they mean when they say that? >> Well, I think it's interesting because we think scale's different because we've all been in the industry and it's frankly, sort of boring old word. But today it means different things, like how do I automate the deployment at-scale? How do I be able to make it really easy to provision resources for applications on any environment, from either a virtualized or bare metal data center, Cloud, or today Edge is really big, where people are trying to push applications out to be closer to the source of the data. And so you want to be able to deploy it-scale, you want to manage at-scale, you want to make it easy to, as I said earlier, allow application developers to build their applications, but ITOps wants the ability to ensure security and governance and all of that. And then finally innovate at-scale. If you look at this show, it's interesting, three years ago when we started Spectra Cloud, there are about 1400 businesses or technologies in the Kubernetes ecosystem, today there's over 1800 and all of these technologies made up of open source and commercial all version in a different rates, it becomes an insurmountable problem, unless you can set those guardrails sort of that balance between flexibility, control, let developers access the technologies. But again, manage it as a part of your normal processes of a scaled operation. >> So Dave, I'm a little challenged here, because I'm hearing two where I typically consider conflicting terms. Flexibility, control. >> Yes. >> In order to achieve control, I need complexity, in order to choose flexibility, I need t-shirt, one t-shirt fits all and I get simplicity. How can I get both that just doesn't compute. >> Well, that's the opportunity and the challenge at the same time. So you're right. So developers want choice, good developers want the ability to choose the latest technology so they can innovate rapidly. And yet ITOps, wants to be able to make sure that there are guardrails. And so with some of today's technologies, like Spectra Cloud, it is, you have the ability to get both. We actually worked with dimensional research, and we sponsor an annual state of Kubernetes survey. We found this last summer, that two out of three IT executives said, you could not have both flexibility and control together, but in fact they want it. And so it is this interesting balance, how do I give engineers the ability to get anything they want, but ITOps the ability to establish control. And that's why Kubernetes is really at its next inflection point. Whereas I mentioned, it's not debates about the distro or DIY projects. It's not big incumbents creating siloed Kubernetes solutions, but in fact it's about allowing all these technologies to work together and be able to establish these controls. And that's really where the industry is today. >> Enterprise , enterprise CIOs, do not typically like to take chances. Now we were talking about the growth in the market that you described from 1400, 1800 vendors, most of these companies, very small startups, our enterprises are you seeing them willing to take a leap with these unproven companies? Or are they holding back and waiting for the IBMs, the HPS, the MicrosoftS to come in with the VMwares with whatever they solution they have? >> I think so. I mean, we sell to the global 2000. We had yesterday, as a part of Edge day here at the event, we had GE Healthcare as one of our customers telling their story, and they're a market share leader in medical imaging equipment, X-rays, MRIs, CAT scans, and they're starting to treat those as Edge devices. And so here is a very large established company, a leader in their industry, working with people like Spectra Cloud, realizing that Kubernetes is interesting technology. The Edge is an interesting thought but how do I marry the two together? So we are seeing large corporations seeing so much of an opportunity that they're working with the smaller companies, the latest technology. >> So let's talk about the Edge a little, you kind of opened it up there. How should customers think about the Edge versus the Cloud Data Center or even bare metal? >> Actually it's a... Well bare metal is fairly easy is that many people are looking to reduce some of the overhead or inefficiencies of the virtualized environment. But we've had really sort of parallel little white tornadoes, we've had bare metal as infrastructure that's been developing, and then we've had orchestration developing but they haven't really come together very well. Lately, we're finally starting to see that come together. Spectra Cloud contributed to open source a metal as a service technology that finally brings these two worlds together, making bare metal much more approachable to the enterprise. Edge is interesting, because it seems pretty obvious, you want to push your application out closer to your source of data, whether it's AI inferencing, or IoT or anything like that, you don't want to worry about intermittent connectivity or latency or anything like that. But people have wanted to be able to treat the Edge as if it's almost like a Cloud, where all I worry about is the app. So really, the Edge to us is just the next extension in a multi-Cloud sort of motif where I want these Edge devices to require low IT resources, to automate the provisioning, automate the ongoing version management, patch management, really act like a Cloud. And we're seeing this as very popular now. And I just used the GE Healthcare example of that, imagine a CAT scan machine, I'm making this part up in China and that's just an Edge device and it's doing medical imagery which is very intense in terms of data, you want to be able to process it quickly and accurately, as close to the endpoint, the healthcare provider is possible. >> So let's talk about that in some level of details, we think about kind of Edge and these fixed devices such as imaging device, are we putting agents on there, or we looking at something talking back to the Cloud? Where does special Cloud inject and help make that simple, that problem of just having dispersed endpoints all over the world simpler? >> Sure. Well we announced our Edge Kubernetes, Edge solution at a big medical conference called HIMMS, months ago. And what we allow you to do is we allow the application engineers to develop their application, and then you can de you can design this declarative model this cluster API, but beyond Cluster profile which determines which additional application services you need and the Edge device, all the person has to do with the endpoint is plug in the power, plug in the communications, it registers the Edge device, it automates the deployment of the full stack and then it does the ongoing versioning and patch management, sort of a self-driving Edge device running Kubernetes. And we make it just very easy. No IT resources required at the endpoint, no expensive field engineering resources to go to these endpoints twice a year to apply new patches and things like that, all automated. >> But there's so many different types of Edge devices with different capabilities, different operating systems, some have no operating system. I mean that seems, like a much more complex environment, just calling it the Edge is simple, but what you're really talking about is 1000s of different devices, that you have to run your applications on how are you dealing with that? >> So one of the ways is that we're really unbiased. In other words, we're OS and distro agnostic. So we don't want to debate about which distribution you like, we don't want to debate about which OS you want to use. The truth is, you're right. There's different environments and different choices that you'll want to make. And so the key is, how do you incorporate those and also recognize everything beyond those, OS and Kubernetes and all of that and manage that full stack. So that's what we do, is we allow you to choose which tools you want to use and let it be deployed and managed on any environment. >> And who's... >> So... >> I'm sorry Keith, who's responsible for making Kubernetes run on the Edge device. >> We do. We provision the entire stack. I mean, of course the company does using our product, but we provision the entire Kubernetes infrastructure stack, all the application services and the application itself on that device. >> So I would love to dig into like where pods happen and all that. But, provisioning is getting to the point that is a solve problem. Day two. >> Yes. >> Like you just mentioned HIMMS, highly regulated environments. How does Spectra Cloud helping with configuration management, change control, audit, compliance, et cetera, the hard stuff. >> Yep. And one of the things we do, you bring up a good point is we manage the full life cycle from day zero, which is sort of create, deploy, all the way to day two, which is about access control, security, it's about ongoing versioning in a patch management. It's all of that built into the platform. But you're right, like the medical industry has a lot of regulations. And so you need to be able to make sure that everything works, it's always up to the latest level have the highest level of security. And so all that's built into the platform. It's not just a fire and forget it really is about that full life cycle of deploying, managing on an ongoing basis. >> Well, Dave, I'd love to go into a great deal of detail with you about kind of this day two ops and I think we'll be covering a lot more of that topic, Paul, throughout the week, as we talk about just as we've gotten past, how do I deploy Kubernetes pod, to how do I actually operate IT? >> Absolutely, absolutely. The devil is in the details as they say. >> Well, and also too, you have to recognize that the Edge has some very unique requirements, you want very small form factors, typically, you want low IT resources, it has to be sort of zero touch or low touch because if you're a large food provider with 20,000 store locations, you don't want to send out field engineers two or three times a year to update them. So it really is an interesting beast and we have some exciting technology and people like GE are using that. >> Well, Dave, thanks a lot for coming on theCUBE, you're now KubeCon, you've not been on before? >> I have actually, yes its... But I always enjoy it. >> Great conversation. From Valencia, Spain. I'm Keith Towns, along with Paul Gillon and you're watching theCUBE, the leader in high tech coverage. (upbeat music)

>>The cube presents, Dell technologies world brought to you by Dell. >>Welcome back to the cube. Lisa Martin and Dave Vale are live in Las Vegas. We are covering our third day of covering Dell technologies world 2022. The first live in-person event since 2019. It's been great to be here. We've had a lot of great conversations about all the announcements that Dell has made in the last couple of days. And we're gonna unpack a little bit more of that. Now. One of our alumni is back with us. Shannon champion joins us again, vice president product marketing at Dell technologies, and she's a company by Pete Robinson, the director of infrastructure engineering at Salesforce. Welcome. Thank >>You. >>So Shannon, you had a big announcement yesterday. I run a lot of new software innovations. Did >>You hear about that? I heard a little something >>About that. Unpack that for us. >>Yeah. Awesome. Yeah, it's so exciting to be here in person and have such a big moment across our storage portfolio, to see that on the big stage, the boom to announce major updates across power store, PowerMax and power flex all together, just a ton of innovation across the storage portfolio. And you probably also heard a ton of focus on our software driven innovation across those products, because our goal is really to deliver a continuously modern storage experience. That's what our customers are asking us for that cloud experience. Let's take the most Val get the most value from data no matter where it lives. That's on premises in the public clouds or at the edge. And that's what we, uh, unveil. That's what we're releasing. And that's what we're excited to talk about. >>Now, Pete, you, Salesforce is a long time Dell customer, but you're also its largest PowerMax customer. The biggest in the world. Tell us a little bit about what you guys are doing with PowerMax and your experience. >>Yeah, so, um, for Salesforce, trust is our number one value and that carries over into the infrastructure that we develop, we test and, and we roll out and Parex has been a key part of that. Um, we really like the, um, the technology in terms of availability, reliability, um, performance. And it, it has allowed us to, you know, continue to grow our customers, uh, continue needs for more and more data. >>So what was kind of eye popping to me was the emphasis on security. Not that you've not always emphasized security, but maybe Shannon, you could do a rundown of, yeah. Maybe not all the features, but give us the high level. And at Pete, I, I wonder how I, if you could comment on how, how you think about that as a practitioner, but please give us that. >>Sure. Yeah. So, you know, PowerMax has been leading for, uh, a long time in its space and we're continuing to lean into that and continue to lead in that space. And we're proud to say PowerMax is the world's most secure mission, critical storage platform. And the reason we can say that is because it really is designed for comprehensive cyber resiliency. It's designed with a zero trust security architecture. And in this particular release, there's 19 different security features really embedded in there. So I'm not gonna unpack all 19, but a couple, um, examples, right? So multifactor authentication also continuous ransomware anomaly detection, a leveraging cloud IQ, which is, uh, huge. Um, and last but not least, um, we have the industry's most granular cyber recovery at scale PowerMax can do up to 65 million imutable snapshots per array. So just, uh, and that's 30 times more than our next nearest competitor. So, you know, really when you're talking about recovery point objectives, power max can't be beat. >>So what does that mean to you, Pete? >>Uh, well, it's it's same thing that I was mentioning earlier about that's a trust factor. Uh, security is a big, a big part of that. You know, Salesforce invests heavily into the securing our customer data because it really is the, the core foundation of our success and our customers trust us with their data. And if we, if we were to fail at that, you know, we would lose that trust. And that's simply not, it's not an option. >>Let's talk about that trust for a minute. We know we've heard a lot about trust this week from Michael Dell. Talk to us about trust, your trust, Salesforce's trust and Dell technologies. You've been using them a long time, but cultural alignment yeah. Seems to be pretty spot on. >>I, I would agree. Um, you know, both companies have a customer first mentality, uh, you know, we, we succeed if the customer succeeds and we see that going back and forth in that partnership. So Dell is successful when Salesforce is successful and vice versa. So, um, when we've it's and it goes beyond just the initial, you know, the initial purchase of, of hardware or software, you know, how you operate it, how you manage it, um, how you continue to develop together. You know, our, you know, we work closely with the Dell engineering teams and we've, we've worked closely in development of the new, new PowerMax lines to where it's actually able to help us build our, our business. And, and again, you know, continue to help Dell in the process. So you've >>Got visibility on the new, a lot of these new features you're playing around with them. What I, I, I obviously started with security cuz that's on top of everybody's mind, but what are the things are important to you as a customer? And how do these features the new features kind of map into that? Maybe you could talk about your experience with the, I think you're in beta, maybe with these features. Maybe you could talk about that. >>Yeah. Um, probably the, the biggest thing that we're seeing right now, other than OB the obvious enhancements in hardware, which, which we love, uh, you know, better performance, better scalability, better, and a better density. Um, but also the, some of the software functionality that Dells starting to roll out, you know, we've, we've, we've uh, implemented cloud IQ for all of our PowerMax systems and it's the same thing. We continue to, um, find features that we would like. And we've actually, you know, worked closely with the cloud IQ team. And within a matter of weeks or months, those features are popping up in cloud IQ that we can then continue to, to develop and, and use. >>Yeah. I think trust goes both ways in our partnership, right? So, you know, Salesforce can trust Dell to deliver the, you know, the products they need to deliver their business outcomes, but we also have a relationship to where we can trust that Salesforce is gonna really help us develop the next generation product that's gonna, you know, really deliver the most value. Yeah. >>Can you share some business outcomes that you've achieved so far leveraging power max and how it's really enabled, maybe it's your organization's productivity perspective, but what are some of those outcomes that you've achieved so far? >>Um, there there's so many to, to, to choose from, but I would say the, probably the biggest thing that we've seen is a as we roll out new infrastructure, we have various generations that we deploy. Um, when we went to the new PowerMax, um, initially we were concerned about whether our storage infrastructure could keep up with the new compute, uh, systems that we were rolling out. And when we went through and began testing it, we came to realize that the, the performance improvements alone, that we were seeing were able to keep up with the compute demand, making that transition from the older VMAX platforms to the PMAX practically seamless and able to just deploy the new SKUs as, as they came out. >>Talk about the portfolio that you apply to PowerMax. I mean, it's the highest of the highest end mission critical the toughest workloads in the planet. Salesforce has made a lot of acquisitions. Yeah. Um, do you throw everything at PowerMax? Are you, are you selective? What's your strategy there? So >>It's, it's selective. In other words that there's no square peg that meets every need, um, you know, acquisitions take some time to, to ingest, um, you know, some run into cloud, some run in first, in, in first party. Um, but so we, we try to take a very, very intentional approach to where we deploy that technology. >>So 10 years ago, someone in your position, or maybe someone who works for you was probably do spent a lot of time managing lawns and tuning performance. And how has that changed? >>We don't do that. <laugh> we? >>We can, right. So what do you do with right. Talk, talk more double click on that. So how talk about how that transition occurred from really non-productive activities, managing storage boxes. Yeah. And, and where you are today, what are you doing with those resources? >>It, it, it all comes outta automation. Like, you know, the, you know, hardware is hardware to a point, um, but you reach a point where the, the manageability scale just goes exponential and, and we're way, well past that. And the only way we've been able to meet that, meet that need is to, to automate and really develop our operations, to be able to not just manage at a lung level or even at the system level, but manage at the data center level at the geographical, you know, location level and then being able to, to manage from there. >>Okay. Really stupid question. But I'm gonna ask it cause I wanna hear your answer. True. Why can't you just take a software defined storage platform and just run everything on that? Why do you need all these different platforms and why do you gotta spend all this money on PowerMax? Why, why can't you just do >>That? That's the million dollar question. Uh, I, I ask that all the time. <laugh>, um, I think software defined is it's on its way. Um, it's come a long way just in the last decade. Yeah. Um, but in terms of supporting what I consider mission critical, large scale, uh, applications, it's, it's not, it's just simply not on par just yet with what we do with PowerMax, for example. >>And that's exactly how we position it in our portfolio. Right? So PowerMax runs on 95% of the fortune 100 companies, top 20 healthcare companies, top 10 financial services companies in the world. So it's really mission critical high end has all of the enterprise level features and capabilities to really have that availability. That's so important to a lot of companies like Salesforce and, and Pete's right, you know, software define is on its way and it provides a lot of agility there. But at the end of the day for mission critical storage, it's all about PowerMax. >>I wonder if we're ever gonna get to, I mean, you, you, you, it was interesting answer cuz you kind of, I inferred from your that you're hopeful and even optimistic that someday will get to parody. But I wonder because you can't be just close enough. It's almost, you have to be. >>I think, I think the key answer to that is it's it's the software flying gets you halfway there. The other side of the coin is the application ecosystem has to change to be able to solve that other, other side of it. Cuz if you simply simply take an application that runs on a PowerMax and try to run it, just forklift it over to a software defined. You're not gonna have very much luck. >>Recovery has to be moved up to stack >>Operations recovery, the whole, whole whole works. >>Jenny, can you comment on how customers like Salesforce? Like what's your process for involving them in testing in roadmap and in that direction, strategic direction that you guys are going? Great >>Question. Sure. Yeah. So, you know, customer feedback is huge. You've heard it. I'm sure this is not new right product development and engineering. We love to hear from our customers. And there's multiple ways you heard about beta testing, which we're really fortunate that Salesforce can help us provide that feedback for our new releases. But we have user groups, we have forums. We, we hear directly from our sales teams, our, you know, our customers, aren't shy, they're willing to give us their feedback. And at the end of the day, we take that feedback and make sure that we're prioritizing the right things in our product management and engineering teams so that we're delivering the things that matter. Most first, >>We've heard a lot of that this week. So I would agree guys, thank you so much for joining Dave and me talking about Salesforce. What you doing with PowerMax? All the stuff that you announced yesterday, alone. Hopefully you get to go home and get a little bit of rest. >>Yes. >>I'm sure that there's, there's never a dull moment. Never. Can't wait guys. Great to have you. >>Thank you. You guys, >>For our guests on Dave Volante, I'm Lisa Martin and you're watching the queue. We are live day three of our coverage of Dell technologies world 2022, Dave and I will be right back with our final guest of the show.

(contemplative upbeat music) >> Hello and welcome to this CUBE Conversation. I'm John Furrier, your host of theCUBE, here in Palo Alto, California. Got a great topic on expanding capabilities for urgent computing. Dan Stanzione, he's Executive Director of TACC, the Texas Advanced Computing Center, and Rajesh Pohani, VP of PowerEdge, HPC Core Compute at Dell Technologies. Gentlemen, welcome to this CUBE Conversation. >> Thanks, John. >> Thanks, John, good to be here. >> Rajesh, you got a lot of computing in PowerEdge, HPC, Core Computing. I mean, I get a sense that you love compute, so we'll jump right into it. And of course, I got to love TACC, Texas Advanced Computing Center. I can imagine a lot of stuff going on there. Let's start with TACC. What is the Texas Advanced Computing Center? Tell us a little bit about that. >> Yeah, we're part of the University of Texas at Austin here, and we build large-scale supercomputers, data systems, AI systems, to support open science research. And we're mainly funded by the National Science Foundation, so we support research projects in all fields of science, all around the country and around the world. Actually, several thousand projects at the moment. >> But tied to the university, got a lot of gear, got a lot of compute, got a lot of cool stuff going on. What's the coolest thing you got going on right now? >> Well, for me, it's always the next machine, but I think science-wise, it's the machines we have. We just finished deploying Lonestar6, which is our latest supercomputer, in conjunction with Dell. A little over 600 nodes of those PowerEdge servers that Rajesh builds for us. Which makes more than 20,000 that we've had here over the years, of those boxes. But that one just went into production. We're designing new systems for a few years from now, where we'll be even larger. Our Frontera system was top five in the world two years ago, just fell out of the top 10. So we've got to fix that and build the new top-10 system sometime soon. We always have a ton going on in large-scale computing. >> Well, I want to get to the Lonestar6 in a minute, on the next talk track, but... What are some of the areas that you guys are working on that are making an impact? Take us through, and we talked before we came on camera about, obviously, the academic affiliation, but also there's a real societal impact of the work you're doing. What are some of the key areas that the TACC is making an impact? >> So there's really a huge range from new microprocessors, new materials design, photovoltaics, climate modeling, basic science and astrophysics, and quantum mechanics, and things like that. But I think the nearest-term impacts that people see are what we call urgent computing, which is one of the drivers around Lonestar and some other recent expansions that we've done. And that's things like, there's a hurricane coming, exactly where is it going to land? Can we refine the area where there's going to be either high winds or storm surge? Can we assess the damage from digital imagery afterwards? Can we direct first responders in the optimal routes? Similarly for earthquakes, and a lot recently, as you might imagine, around COVID. In 2020, we moved almost a third of our resources to doing COVID work, full-time. >> Rajesh, I want to get your thoughts on this, because Dave Vellante and I have been talking about this on theCUBE recently, a lot. Obviously, people see what cloud's, going on with the cloud technology, but compute and on-premises, private cloud's been growing. If you look at the hyperscale on-premises and the edge, if you include that in, you're seeing a lot more user consumption on-premises, and now, with 5G, you got edge, you mentioned first responders, Dan. This is now pointing to a new architectural shift. As the VP of PowerEdge and HPC and Core Compute, you got to look at this and go, "Hmm." If Compute's going to be everywhere, and in locations, you got to have that compute. How does that all work together? And how do you do advanced computing, when you have these urgent needs, as well as real-time in a new architecture? >> Yeah, John, I mean, it's a pretty interesting time when you think about some of the changing dynamics and how customers are utilizing Compute in the compute needs in the industry. Seeing a couple of big trends. One, the distribution of Compute outside of the data center, 5G is really accelerating that, and then you're generating so much data, whether what you do with it, the insights that come out of it, that we're seeing more and more push to AI, ML, inside the data center. Dan mentioned what he's doing at TACC with computational analysis and some of the work that they're doing. So what you're seeing is, now, this push that data in the data center and what you do with it, while data is being created out at the edge. And it's actually this interesting dichotomy that we're beginning to see. Dan mentioned some of the work that they're doing in medical and on COVID research. Even at Dell, we're making cycles available for COVID research using our Zenith cluster, that's located in our HPC and AI Innovation Lab. And we continue to partner with organizations like TACC and others on research activities to continue to learn about the virus, how it mutates, and then how you treat it. So if you think about all the things, and data that's getting created, you're seeing that distribution and it's really leading to some really cool innovations going forward. >> Yeah, I want to get to that COVID research, but first, you mentioned a few words I want to get out there. You mentioned Lonestar6. Okay, so first, what is Lonestar6, then we'll get into the system aspect of it. Take us through what that definition is, what is Lonestar6? >> Well, as Dan mentioned, Lonestar6 is a Dell technology system that we developed with TACC, it's located at the University of Texas at Austin. It consists of more than 800 Dell PowerEdge 6525 servers that are powered with 3rd Generation AMD EPYC processors. And just to give you an example of the scale of this cluster, it could perform roughly three quadrillion operations per second. That's three petaFLOPS, and to match what Lonestar6 can compute in one second, a person would have to do one calculation every second for a hundred million years. So it's quite a good-size system, and quite a powerful one as well. >> Dan, what's the role that the system plays, you've got petaFLOPS, what, three petaFLOPS, you mentioned? That's a lot of FLOPS! So obviously urgent computing, what's cranking through the system there? Take us through, what's it like? >> Sure, well, there there's a mix of workloads on it, and on all our systems. So there's the urgent computing work, right? Fast turnaround, near real-time, whether it's COVID research, or doing... Project now where we bring in MRI data and are doing sort of patient-specific dosing for radiation treatments and chemotherapy, tailored to your tumor, instead of just the sort of general for people your size. That all requires sort of real-time turnaround. There's a lot AI research going on now, we're incorporating AI in traditional science and engineering research. And that uses an awful lot of data, but also consumes a huge amount of cycles in training those models. And then there's all of our traditional, simulation-based workloads and materials and digital twins for aircraft and aircraft design, and more efficient combustion in more efficient photovoltaic materials, or photovoltaic materials without using as much lead, and things like that. And I'm sure I'm missing dozens of other topics, 'cause, like I said, that one really runs every field of science. We've really focused the Lonestar line of systems, and this is obviously the sixth one we built, around our sort of Texas-centric users. It's the UT Austin users, and then with contributions from Texas A&M , and Texas Tech and the University of Texas system, MD Anderson Healthcare Center, the University of North Texas. So users all around the state, and every research problem that you might imagine, those are into. We're just ramping up a project in disaster information systems, that's looking at the probabilities of flooding in coastal Texas and doing... Can we make building code changes to mitigate impact? Do we have to change the standard foundation heights for new construction, to mitigate the increasing storm surges from these sort of slow storms that sit there and rain, like hurricanes didn't used to, but seem to be doing more and more. All those problems will run on Lonestar, and on all the systems to come, yeah. >> It's interesting, you mentioned urgent computing, I love that term because it could be an event, it could be some slow kind of brewing event like that rain example you mentioned. It could also be, obviously, with the healthcare, and you mentioned COVID earlier. These are urgent, societal challenges, and having that available, the processing capability, the compute, the data. You mentioned digital twins. I can imagine all this new goodness coming from that. Compare that, where we were 10 years ago. I mean, just from a mind-blowing standpoint, you have, have come so far, take us through, try to give a context to the level of where we are now, to do this kind of work, and where we were years ago. Can you give us a feel for that? >> Sure, there's a lot of ways to look at that, and how the technology's changed, how we operate around those things, and then sort of what our capabilities are. I think one of the big, first, urgent computing things for us, where we sort of realized we had to adapt to this model of computing was about 15 years ago with the big BP Gulf Oil spill. And suddenly, we were dumping thousands of processors of load to figure out where that oil spill was going to go, and how to do mitigation, and what the potential impacts were, and where you need to put your containment, and things like that. And it was, well, at that point we thought of it as sort of a rare event. There was another one, that I think was the first real urgent computing one, where the space shuttle was in orbit, and they knew something had hit it during takeoff. And we were modeling, along with NASA and a bunch of supercomputers around the world, the heat shield and could they make reentry safely? You have until they come back to get that problem done, you don't have months or years to really investigate that. And so, what we've sort of learned through some of those, the Japanese tsunami was another one, there have been so many over the years, is that one, these sort of disasters are all the time, right? One thing or another, right? If we're not doing hurricanes, we're doing wildfires and drought threat, if it's not COVID. We got good and ready for COVID through SARS and through the swine flu and through HIV work, and things like that. So it's that we can do the computing very fast, but you need to know how to do the work, right? So we've spent a lot of time, not only being able to deliver the computing quickly, but having the data in place, and having the code in place, and having people who know the methods who know how to use big computers, right? That's been a lot of what the COVID Consortium, the White House COVID Consortium, has been about over the last few years. And we're actually trying to modify that nationally into a strategic computing reserve, where we're ready to go after these problems, where we've run drills, right? And if there's a, there's a train that derails, and there's a chemical spill, and it's near a major city, we have the tools and the data in place to do wind modeling, and we have the terrain ready to go. And all those sorts of things that you need to have to be ready. So we've really sort of changed our sort of preparedness and operational model around urgent computing in the last 10 years. Also, just the way we scheduled the system, the ability to sort of segregate between these long-running workflows for things that are really important, like we displaced a lot of cancer research to do COVID research. And cancer's still important, but it's less likely that we're going to make an impact in the next two months, right? So we have to shuffle how we operate things and then just, having all that additional capacity. And I think one of the things that's really changed in the models is our ability to use AI, to sort of adroitly steer our simulations, or prune the space when we're searching parameters for simulations. So we have the operational changes, the system changes, and then things like adding AI on the scientific side, since we have the capacity to do that kind of things now, all feed into our sort of preparedness for this kind of stuff. >> Dan, you got me sold, I want to come work with you. Come on, can I join the team over there? It sounds exciting. >> Come on down! We always need good folks around here, so. (laughs) >> Rajesh, when I- >> Almost 200 now, and we're always growing. >> Rajesh, when I hear the stories about kind of the evolution, kind of where the state of the art is, you almost see the innovation trajectory, right? The growth and the learning, adding machine learning only extends out more capabilities. But also, Dan's kind of pointing out this kind of response, rapid compute engine, that they could actually deploy with learnings, and then software, so is this a model where anyone can call up and get some cycles to, say, power an autonomous vehicle, or, hey, I want to point the machinery and the cycles at something? Is the service, do you guys see this going that direction, or... Because this sounds really, really good. >> Yeah, I mean, one thing that Dan talked about was, it's not just the compute, it's also having the right algorithms, the software, the code, right? The ability to learn. So I think when those are set up, yeah. I mean, the ability to digitally simulate in any number of industries and areas, advances the pace of innovation, reduces the time to market of whatever a customer is trying to do or research, or even vaccines or other healthcare things. If you can reduce that time through the leverage of compute on doing digital simulations, it just makes things better for society or for whatever it is that we're trying to do, in a particular industry. >> I think the idea of instrumenting stuff is here forever, and also simulations, whether it's digital twins, and doing these kinds of real-time models. Isn't really much of a guess, so I think this is a huge, historic moment. But you guys are pushing the envelope here, at University of Texas and at TACC. It's not just research, you guys got real examples. So where do you guys see this going next? I see space, big compute areas that might need some data to be cranked out. You got cybersecurity, you got healthcare, you mentioned oil spill, you got oil and gas, I mean, you got industry, you got climate change. I mean, there's so much to tackle. What's next? >> Absolutely, and I think, the appetite for computing cycles isn't going anywhere, right? And it's only going to, it's going to grow without bound, essentially. And AI, while in some ways it reduces the amount of computing we do, it's also brought this whole new domain of modeling to a bunch of fields that weren't traditionally computational, right? We used to just do engineering, physics, chemistry, were all super computational, but then we got into genome sequencers and imaging and a whole bunch of data, and that made biology computational. And with AI, now we're making things like the behavior of human society and things, computational problems, right? So there's this sort of growing amount of workload that is, in one way or another, computational, and getting bigger and bigger. So that's going to keep on growing. I think the trick is not only going to be growing the computation, but growing the software and the people along with it, because we have amazing capabilities that we can bring to bear. We don't have enough people to hit all of them at once. And so, that's probably going to be the next frontier in growing out both our AI and simulation capability, is the human element of it. >> It's interesting, when you think about society, right? If the things become too predictable, what does a democracy even look like? If you know the election's going to be over two years from now in the United States, or you look at these major, major waves >> Human companies don't know. >> of innovation, you say, "Hmm." So it's democracy, AI, maybe there's an algorithm for checking up on the AI 'cause biases... So, again, there's so many use cases that just come out of this. It's incredible. >> Yeah, and bias in AI is something that we worry about and we work on, and on task forces where we're working on that particular problem, because the AI is going to take... Is based on... Especially when you look at a deep learning model, it's 100% a product of the data you show it, right? So if you show it a biased data set, it's going to have biased results. And it's not anything intrinsic about the computer or the personality, the AI, it's just data mining, right? In essence, right, it's learning from data. And if you show it all images of one particular outcome, it's going to assume that's always the outcome, right? It just has no choice, but to see that. So how we deal with bias, how do we deal with confirmation, right? I mean, in addition, you have to recognize, if you haven't, if it gets data it's never seen before, how do you know it's not wrong, right? So there's about data quality and quality assurance and quality checking around AI. And that's where, especially in scientific research, we use what's starting to be called things like physics-informed or physics-constrained AI, where the neural net that you're using to design an aircraft still has to follow basic physical laws in its output, right? Or if you're doing some materials or astrophysics, you still have to obey conservation of mass, right? So I can't say, well, if you just apply negative mass on this other side and positive mass on this side, everything works out right for stable flight. 'Cause we can't do negative mass, right? So you have to constrain it in the real world. So this notion of how we bring in the laws of physics and constrain your AI to what's possible is also a big part of the sort of AI research going forward. >> You know, Dan, you just, to me just encapsulate the science that's still out there, that's needed. Computer science, social science, material science, kind of all converging right now. >> Yeah, engineering, yeah, >> Engineering, science, >> slipstreams, >> it's all there, >> physics, yeah, mmhmm. >> it's not just code. And, Rajesh, data. You mentioned data, the more data you have, the better the AI. We have a world what's going from silos to open control planes. We have to get to a world. This is a cultural shift we're seeing, what's your thoughts? >> Well, it is, in that, the ability to drive predictive analysis based on the data is going to drive different behaviors, right? Different social behaviors for cultural impacts. But I think the point that Dan made about bias, right, it's only as good as the code that's written and the way that the data is actually brought into the system. So making sure that that is done in a way that generates the right kind of outcome, that allows you to use that in a predictive manner, becomes critically important. If it is biased, you're going to lose credibility in a lot of that analysis that comes out of it. So I think that becomes critically important, but overall, I mean, if you think about the way compute is, it's becoming pervasive. It's not just in selected industries as damage, and it's now applying to everything that you do, right? Whether it is getting you more tailored recommendations for your purchasing, right? You have better options that way. You don't have to sift through a lot of different ideas that, as you scroll online. It's tailoring now to some of your habits and what you're looking for. So that becomes an incredible time-saver for people to be able to get what they want in a way that they want it. And then you look at the way it impacts other industries and development innovation, and it just continues to scale and scale and scale. >> Well, I think the work that you guys are doing together is scratching the surface of the future, which is digital business. It's about data, it's about out all these new things. It's about advanced computing meets the right algorithms for the right purpose. And it's a really amazing operation you guys got over there. Dan, great to hear the stories. It's very provocative, very enticing to just want to jump in and hang out. But I got to do theCUBE day job here, but congratulations on success. Rajesh, great to see you and thanks for coming on theCUBE. >> Thanks for having us, John. >> Okay. >> Thanks very much. >> Great conversation around urgent computing, as computing becomes so much more important, bigger problems and opportunities are around the corner. And this is theCUBE, we're documenting it all here. I'm John Furrier, your host. Thanks for watching. (contemplative music)

(calm electronic music) >> Hey, welcome back everyone to theCUBE coverage of AWS re:Invent 2021. I'm John Furrier, your host. We're here with two sets with live content, pumping out 120 years over the course of a couple of days, 28 hours of programming from the people making things happen, sharing the news, and the insight. We've got Sandy Carter, worldwide public sector vice president of partners and programs for Amazon web services. Sandy, CUBE alumni, welcome back to theCUBE. Great to see you. >> Great to see you too, John. It's so awesome to be here in person, right? >> The news is coming more and more. We got health care news. We got this news, we got all kinds of certification. We just recently talked on a segment about all the great stuff on certifications, but healthcare is booming, okay? We got talking about delivering the kind of performance that people need in healthcare with data, and you've got delivery, destination is healthcare. Let's talk health care, what's going on? >> Yeah, so we made a couple of really awesome announcements around healthcare today. So if you think about it, one of the big trends in healthcare is digitizing health records, so electronic healthcare records to really help and assist with patient care. So, because that is so big, we launched an initiative for electronic healthcare records, migration assistance. And what that means is that, we have now added technical subject matter experts and industry subject matter experts in the healthcare space who understand EHR, electronic health records, to help us migrate at least 500 ISV applications over to AWS. This is really big news, because so far, most of those applications are running on-premises. So getting them over to the cloud gives them the scalability, gives them the agility, that they need to provide all of us better healthcare. >> Well, one of the big themes is the Epic performance, the database on the cloud. Cloud has given so much agility and has changed the game. I mean, I'm old enough to remember, I mean, we can look back on the shifts in technology. You had that era of healthcare where data and the records were super important. Privacy, lock it down. Don't talk to each other. Are we going to respect the privacy of the individuals? That's all now changed with horizontal scalable data, as Swami pointed out, who's the SVP leader of AI and the data for AWS, whole new paradigm of data architecture. This is disrupting healthcare. >> Yes And you've got the Epic situation. Take us through, why is this important? Why are we talking about Epic? >> Well, so EHR is one of the announcements. And then the second big announcement, is our Epic on AWS announcement. So, you may have covered this back in the August, September timeframe, we announced a new EC2 instance, called the M6I. And Epic, which is one of the leading global healthcare providers in the world, has been migrated to the cloud. And so, they started testing themselves, Epic started testing on the M6I. And so what we saw is a 40% performance improvement. Now that is, that's huge, as well as a 30% reduction in total cost of ownership. So if you're a partner out there, you're going to see, as your application runs on top of Epic, you're going to get that performance gain. And Epic has an amazing ecosystem, John. They have what they call the code travelers. They kind of exist on Epic, cause everybody uses Epic. Those ISBs are now going to get that benefit, and 90% of the current Epic customers. And then, our consulting partners are also going to see the benefit, because of that total cost of ownership reduction of 30%. So imagine you're a consulting partner, you're now going to go into a hospital that's using Epic and tell them that you can reduce their total cost of ownership by 30%. That's amazing! >> Well, first of all, the cost thing is amazing. But also, when you mentioned the instances, what's happening with the graviton and the processors and the performance you're getting in the cloud now, the applications are running faster and lower cost. So, you know, databases, they really want the boast horsepower. So you've got the cloud performance, you've got the lower cost. Why wouldn't anyone want to run it anywhere else? This is what I'm saying on my story I wrote Sunday night. All the modern applications will go to the best performance, even legacy apps. >> That's right, and I think this is so important because you know, you need performance, you need speed. You need to get the rest of this application migrated over. That's why we got the EHR migration initiative. And then if you couple that with our third announcement around authority to operate that now gives you that security and compliance, right? Because if you're a hospital, you can't risk having that patient information exposed. And so we introduced as an authority to operate a program that enables our partners to get HIPAA and high trust authorization faster, cheaper, so that they can move with this new digital trend that's happening all across healthcare. I mean, it is our fastest growing area today, growing at 105%. >> Yeah, it points to examine, it's another one of those areas that is urgent under COVID. It's exploding because of the demand, just on performance. And Swami said it today, also in the keynote, the AI data keynote, governance should be an enabler, not an inhibitor. >> Sandy: That's right. So when you start getting into governance where you can start managing the data in a way that's cool for people to use the data, but protect the privacy, you then can have the modern apps. >> And if I could just add on one thing there, today we talked about, you know, when you go on your digital transformation journey, it requires digital security, especially in healthcare. And so as you have those requirements, you have to be able to, not just get stuff to the cloud, it's got to be secure. And that's why HIPAA and high trust exist today. >> And these fine grain controls now available are amazing. So again, I love the way you guys are going in this direction with AWS. I got to say every year, it's like, wow, again. But I want to get back to this ISV angle because I think this is super important. Again, I teased this out on my post Sunday night, when I, after my sit down with Adam Selipski was that, if I'm a software vendor, an ISV, an independent software vendor, or a software owner, I want my app to run faster, period, okay? I want my app to make money, which means valued by customers. I don't want my app to be slower and not be seen in front of my customers. So again, ISV is now an opportunity, Epic is a shining example of that, where now as an ISV, I can innovate and not have to do the heavy lifting. This is a huge point. Can you just share some color on this, because this is like, I think kind of the elephant in the room. The ISVs are going to go where the action is. >> That's right, and you know, the Epic ecosystem is such a force. Epic being a global healthcare leader, getting that performance level, all of those codes, they call them code travelers, that exist around Epic. All of those applications can now take advantage of that performance improvement, which for me is a game changer because all that data, I mean, I know that, you know, I was just in an emergency room with my daughter. She had a trouble, we thought she broke her elbow. And, you know, we were sitting there waiting as the person's entering and waiting and entering and waiting. So that performance really makes a difference, right? In your customer satisfaction, in your patient care, all the things that really matter, the business outcome areas, not just the technology side. It's a game changer for healthcare. >> It's the delivery of one, your health, your life. And two, hassle time, avoiding the steps, waiting in the wrong room, going here, waiting for this, getting a test you don't need. >> Sandy: That's right. >> It's a hassle for the customer, but also puts pressure on the supply chain, the operational bandwidth, and with telemedicine around the corner, you know, everything is happening with telemedicine. Why I might not need to go to the hospital if I don't have to, so again, another big wave coming is telemedicine. >> Yeah, that's right, and in fact, we launched that healthcare startup accelerator, where we invited healthcare companies from around the world to come in and get extra support as a brand new partner, as a next gen partner, and that was actually one of the top areas of focus. About 40% of the companies came in around telemedicine. And one of the really interesting partners that came in through that accelerator was a partner named Get lab. They do, you know, surgeon training, which is quite fascinating, and they were doing that and Time named them one of the top, most innovative companies of the year in 2021. And they accredited a lot of their success to the healthcare accelerator that we just launched as well. >> So much action going on. I got to get your thoughts on just in general healthcare, do you find the vibe to be more from the doctors and the service providers? Because they're the ones on the front lines. They're in the foxhole, so to speak. It always seems to me that they always wish things went faster, similar to government workers, right? It's like, I wish there wasn't red tape. I wish it was easier. Why aren't we doing this? That seems to have been like, the culture. And now it's shifting back to, all right, now we're having fun. We're delivering care. We're riding the right wave. >> I agree, you know, these business outcomes make a huge difference, I think. And I think that that transformation that you're talking about, is occurring much faster than anybody anticipated. I predict in 2022, you're going to see this increased focus, not just on telemedicine, patient care overall. Like how do you combine the two together? How are you able to move quicker to provide more diagnostics? So for example, one of our partners, GE Healthcare, was using AI and ML with one of our partner programs and was able to automate the radiology workflow. I mean, just think about radiology, reading X-rays, how fast that can be with AI and ML. It increased the diagnostic accuracy by 30%. I think you're going to see lots more use of technology to speed up diagnosis, to increase that customer, patient care. I think that's really going to be the trend in 2022. And it's great for all of us. >> And computer vision, by the way, with explainable AI, can come in, talk about analyzing x-rays and or film, more and more tech coming in and machine learning is driving a lot of it. >> I completely agree. Machine learning, I would say machine learning and analytics, you know? Now that we've got the data and you know, the data, IDC says that data coming in from IOT sensors increased by four x since COVID, so imagine, you know, there are now robots working in the hospital, gathering your readings of your, you know, how strong you breathe, your temperature, all your vital signs are now coming in from IOT sensors. So you're just seeing this explosion of data and healthcare, which only makes diagnosis and hopefully cures, new vaccines, more possible because now you've got more data to work with, right? That data accuracy is going up. Data sources are going up. It's just a really powerful combination. >> Yeah, healthcare is great. Sandy, it's been an amazing run on the healthcare side. It's continuing to change, in a good way, how care is managed and delivered and dispensed and cost savings. I do want to ask you if you could point out to the audience, just from within the partner base, what's the big trend there? Because obviously they're all engaged, seeing all kinds of new things. Where's the innovation vibe? What are some, what's the pattern in the partners, more software development, more cloud, more AI? What's the, what would you, how would you rank the activities of innovation? >> Yeah, I would say there are five prime drivers today on the technology side, you know. First and foremost right now is IOT, believe it or not. And IOT, because it's driving so much data and you have to have data for the second big trend, which is artificial intelligence and machine learning. So that data is essential for feeding all the modeling that's going on. We're also seeing the edge come to pass really fast, right? A lot of work on outpost. In fact, at the conference, we announced that we just opened an outpost innovation center with WWT and Intel MDC. We already have an innovation center for outpost in Seattle. So we opened one in DC for our partner community as well. So we're seeing a lot of focus on that edge. Containers, as we talked about earlier, 60% of customers want containers. So our partners to be, need to be all over it. And then another huge trend in public sector is blockchain. So if you think about, you know, Panama, El Salvador, Ukraine, they're all moving to Bitcoin. And I just went over to the Wynn hotel cause we're here in Vegas, did you see how many vendors are taking Bitcoin out? It's amazing! And so all of that is built on blockchain. So we also introduced a set of workshops and POCs with our partners around blockchain because we see it happening in states, in countries, and then the countries drive everything else to have to use or leverage that chain for Bitcoin. >> Great trends, the tailwind, the wave is here. It's a big wave, healthcare, public sector, a lot of change. Sandy Carter. Thank you for the great commentary. Great insight, great to see you. Thanks for coming back on theCUBE. >> Nice to see you too, yep. >> It's theCUBE coverage. I'm John Furrier, your host of theCUBE. We got two sets wall-to-wall coverage, here in person, live event, as well as hybrid, we have the software as well. You're watching theCUBE, the leader in global tech coverage. I'm John Furrier, thanks for watching. (calming electronic music)

>> Welcome back to Los Angeles. TheCUBE is live. I can't say that enough. The cube is live. We're at KubeCon Cloud Native Con 21. We've been here all day yesterday, and today and tomorrow I'm talking with lots of guests, really uncovering what's going on in the world of Kubernetes. Lisa Martin, here with Dave Nicholson. We've got some folks. Next we're going to be talking about a customer use case, which is always one of my favorite things to talk about. Please welcome Micah Coletti, the principal platform engineer at CHG healthcare, and Venkat Ramakrishnan VP of products from Portworx by Pure Storage, guys welcome to the program. >> Thank you. >> Happy to be here. >> Yeah. So Micah, first of all, let's go ahead and start with you. Give the audience an overview of CHG healthcare. >> Yeah. So CHG healthcare, we're a staffing company. So we try like a little companion. So our clients are doctors and hospitals, so we help staff hospitals with temporary doctors or even permanent placing. So we deal with a lot of doctors, a lot of nursing and we're a combination of multiple companies. So CHG is the parent. So, and yeah, we're known in the industry as one of the leaders in this field and providing hospitals with high quality doctors and nurses. And, you know, our customer service is like number one, and one of the things our CEO is really focused on is now how do we make that more digital? How do we provide that same level of quality of service, but a digital experience as rich for her. >> I can imagine it was a massive need for that in the last 18 months alone. >> COVID definitely really raised that awareness up for us and the importance of that digital experience and that we need to be out there in the digital market. >> Absolutely. So you're a customer port works by pure storage, we're going to get into that, but then Venkat talk to us about what's going on, the acquisition of port works by pure storage was about a year ago. Talk to us about your VP of products what's going on. >> Yeah, I mean, you know, first of all, I think I could not say how much of a great fit for a Portworx will be part of pure storage, it's, pure itself is a very fast moving, large startup that's a dominant leader in the flash and data center space, and, you know, pure recognizes the fact that Kubernetes is the new operating system of the cloud is not how, you know, it's kind of virtualizing the cloud itself, and there's a, you know, a big burgeoning need for data management and Kubernetes and how you can kind of orchestrate workloads between your on-prem data centers and the cloud and back. So Portworx fits right into the story as complete vision of data management for our customers, and it's been phenomenal. Our business has grown as part of being part of a pure, and you know, we're looking at launching some new products as well, and it's all exciting times. >> So you must've been pretty delighted to be acquired as a startup by essentially a startup because, because although pure has reached significant milestones in the storage business and is a leader in flash storage still that that startup mindset is absolutely unique. That's not, that's not the same as being acquired by a company that's been around for a hundred years seeking to revitalize itself. >> Absolutely. >> Can you talk a little bit about that aspect? >> Yeah, So I think, you know, purist culture is a highly innovation-driven and it's a very open, flat culture, right? I mean, it's, everybody in pure is accessible. It can easily have a composition with folks and everybody has his learning mindset and Portworx is and has always been the same way. Right? So when you put these teams together, if we can create wonders, I mean, we right after the acquisition, just within a few months, we announced an integrated solution that portworx orchestrates volumes and file shares in pure splash products and then delivers as an integrated solution for our customers, and pure has a phenomenal cloud-based monitoring and management system called pure one that we integrated well into. Now, we're bringing the power of all of the observability that pure's customers are used to for all of the corporate customers, and I've been super happy, you know, delegating that capability to our customers and our customers are delighted. Now they can have a complete view all the way from Kubernetes app to the flash. and I don't think any one company in the planet can even plan they can do that. >> I think it's fair to acknowledge that pure one was observability before observability was a word that everyone used regularly. >> Yep. >> Sounds very interesting. >> Micah Talk to us about, obviously you are a customer. CHG is a customer of Portworx now Portworx by Pure Storage. Talk to us about the use case. What, what was the compellent? Was there a compelling event and from a storage perspective that led you to Portworx in the first place. >> So we beat, they began this, our CEO base came to the vision, we need to have a digital presence we need enhances. and this was even before COVID. So they brought me on board and my, my manager read glossary. We basically had this task to, how are we going to get out into the cloud? How are we going to make that happen? And we chose to follow a very much a cloud native strategy and the platform of choice, I mean, it just made sense with Kubernetes. And so when we were looking at Kubernetes, we were starting to figure out how we're doing. We knew that data is going to be a big factor. You know, being a, provide data. We're very much focused on an event driven. We're really pushing to event driven architecture. So we leverage Kafka on top of Kubernetes, but at the time we were actually leveraging Kafka with a MSK down, out in AWS, and that was just a huge cost to us. So I came on board, I had experienced with Portworx, a prior company before that, and I basically said, we need to figure out a great storage relay overlay. and the only way to do is we got to have high performance storage, we've got to have secure. We got to be able to backup and recover that storage. And the Portworx was the right match. And that allowed us to have a very smooth transition off of MSK onto Kubernetes saving us a significant amount of money per month, and just leverage that already existing hardware that our existing compute memory and just, and the, and move right to Portworx. >> Leveraging your existing investments. >> Exactly. >> Which is key, >> Very key, very key so. >> So how common are the challenges that when you guys came together with CHG, how common are the challenges? >> It's actually a, that's a great question. You know, this is, you know, I'll tell you the challenges that Micah and his team are running into is what we see a lot in the industry where people pay a ton of money, you know to other vendors are, you know, especially in some cases use some cloud native services, but they want to have control over the data. They want to control the cost and they want higher performance and they want to have, you know, there's also governance and regulatory things that they need to control better. So they want to kind of bring these services and have more control over them. Right? So now we will work very well with all of our partners, including the cloud providers, as well as, you know, on-prem and server vendors and everybody, but different customers have different kinds of needs. And Portworx gives them that flexibility. If you are a customer who want, you know, have a lot of control over your applications, the performance, the latency, and want to control costs very well and leverage your existing investments Portworx can deliver that for you in your data center. Right now, you can integrate that with pure slash and you get a complete solution, or you want to run it in cloud, and you still want to have leverage the agility of the cloud and scale Portworx delivers a solution for you as well. So it kind of not only protects their investment its future proves their architecture, you get future proving your architecture completely. So if you want to tear the cloud or burst the cloud, you have a great solution that you can continue to leverage >> Micah, when you hear future-proof and I'm a marketer. So I always go, I love to know what it means to different people. What does that mean to you in your environment? >> My environment. So a future-proof means like one of the things we've been addressing lately, that's just a real big challenge. And I'm sure it's a challenge in the industry, especially the Q and A's is upgrading our clusters. The ability to actually maintain a consistent flow with how fast Kubernetes is growing, you know, they're, they they're out. I think he cast, we leverage the cast. So it's like 121 or 122 now, and that effort to upgrade a cluster, it can be a daunting one. With Portworx, we actually were able to make that to where we could actually spin up a brand new cluster. And with Portworx shift, all our applications, services, data migrated completely over, Portworx handles all of that for us and stand up that new cluster in, in less than a day. And that effort, I mean, it would take us a week, two weeks to do so, not even man hours and time spent there, but just the reliability of being able to do that in the cost, you know, instead of standing up a new cluster and configuring it and doing all that and spending all that time, we can just really, we move to what we call blue green cut-over strategy. And Portworx is an essential piece of that. >> So Venkat, is it fair to say that there are a variety of ways that people approach Portworx from a value perspective in terms of, I know that one area that you are particularly good in is the area of backups in this environment, but then you get data management and there's a third kind of vector there. What is the third vector? >> As all of the data services, >> Data services, >> Yeah Like for example, deep database as a service on any Kubernetes cluster feed on your cloud or your on-prem data centers. >> Which data, what kind of databases are you talking about? >> I mean we're talking about anything from Reddit Kafka, Post-stress my sequel console, we are supporting. We just announced something called a Portworx Data Services Offering that essentially delivers all these databases as a service on any Kubernetes cluster that a customer can point to and lets them kind of get the automated management of the database from day one to day three, the entire life cycle, you know, through regular Kubernetes, scoop cuddle experience through APIs and SDKs and a nice slick UI that they can, you know, that's, role-based access control and all of that, that they can completely control their data and their applications through it. And you know, that's the third vector of Portworx office. >> Micah a question for you. So Portworx has been a part of pure storage? You've known it since obviously for several years before you were at CHG, you brought it to CHG. You now know it a year into being acquired by a fast paced startup. Talk to me about the relationship and some of the benefits that you're getting with Portworx as a part of pure storage? >> Well, I mean, one of the things I, you know, when I heard about the acquisition, my first thing was, I was a little bit concerned is that relationship going to change? And when we were acquiring, when we were looking at adopting Portworx, one thing I would tell my management is Portworx is not just a vendor that wants to throw a solution on you and provide some capability. They're a partner. They want to partner with you and your success in your journey and this whole cloud native journey to provide this rich digital experience in the, for not only our platform engineering team, but our Dev teams, but also be able to really accelerate the development of our services. So we can provide that digital portal for our end users. And that didn't change. If anything, that it accelerated that relationship did not change. You know, I came to Venkat with an issue. We just we're, we're dealing with, he immediately got someone on a phone call with me. And so that has not changed. So it's really exciting to see that now that they've been acquired, that they still are very much invested in the success of their customers and making sure we're successful. You know, it's not all of a sudden. I was worried I was going to have to do a whole different support PA process, and it was going to go into a black hole. Didn't happen. They still are very much involved with their customers. >> It's sounds kind of Venkat similar to what you talked about with the cultural alignment. I've known here for a long time and they're very customer centric sounds like one of the areas in which there was a very strong alignment with Portworx >> Absolutely. and Portworx has always taken pride in being customer first company. Our founders are heavily customer focused. You know, they are aligned. They want, they have always aligned. our portraits business to our customers' needs. Now Pure is a company that's maniacally focused on customers, right? I mean, that's all in a pure pounder cars and everybody cared about. And so, you know, bringing these companies together and being part of the Pure team, I kind of see how, how synergistic it is. And, you know, we have, you know, that has enabled us to serve our customer's customers even better than before. >> So I'm curious about the two of you personally, in terms of your, your histories, I'm going to assume that you didn't both just bounce out of high school into the world of Kubernetes, right? So like Lisa and I you're spanning the generations between the world of say virtualization based on x86 architecture, virtualization, where you're not, you don't have microservices, you have a full blown operating system that you're working with. Kind of talk about, you know, Micah with you first talk about what that's been like navigating that change. We were in the midst of that. Do you have advice for others that are navigating that change? >> Don't be afraid of it. You know, a lot of people want to, you know, I call it we're moving from where we're name me. We still have cats and dogs. They have a name that the VMs either whether or not they're physical boxes or their VMs to where it's more like, he'd say cattle, you know, it's like we don't own the OOS and not to be afraid of afraid of that, because change is really good. You know, the ability for me to not have to worry about patching and operating system, it's huge, you know, where I can rely on someone like EKS and, and the version and allow them to, if a CV comes out, they let me know. I go and I use their tools to be able to upgrade. So I don't have to literally worry about owning that OOS and containers as the same thing. You know, you, you know, it's all about being fault-tolerant right. And being able to be changed or where, you know, you can actually roll out a new version of a container, a base image with a lot of ease without having to go and patch a bunch of servers. I mean, patch night was hell and sorry if I could say that, but it was a nightmare, you know, but this whole world has just been a game changer with that. >> So Venkat from your perspective, you were coming at it, going into a startup, looking at the landscape in the future and seeing opportunity. What what's that been like for you? I guess the question for you is more something, Lisa and I talk about this concept of peak Kubernetes, where are we in the wave? Is this just, is this just the beginning? Are we in the thick of it? >> I think I would say we're kind of transitioning from early adopters, early majority phase in the whole, you know, crossing the chasm analogy, right? So I would say we're still early stages of this big wave. That's going to transform how infrastructure is built. Apps are apps are built and managed and run in production. I think some of the pieces, the key pieces are falling in place and maturing. There are some other pieces like observability and security, you know, kind of edge use cases need to be, you know, they're kind of going to get a lot more mature and you'll see that the cloud, as we know today, and the apps, as we know today, they're going to be radically different. And you know, if you're not building your apps and your business on this modern platform, on this modern infrastructure, you're going to be left behind. You know, I, my wife's birthday was a couple of days ago. I was telling the story to my couple of friends is that I, I used another flowers delivery website. They miss delivering the flowers on the same day, right. So they told me all kinds of excuses. Then I just went and looked up a, you know, like door dash, which is delivers, you know, and then, you know, like your food, but there's also flower delivery and door dash and I don't do I door dash flowers to her, and I can track the flower delivery all the way she did not need them, but my kids love the chocolates though. Right. So, and you know, the case in point is that you cannot be in a building, a modern business without leveraging the model tool chain and modern tool chain and how the business is going to be delivered at that thing is going to be changing dramatically. And those kinds of customer experience, if you don't deliver, you're not going to be successful in business. And Kubernetes is the fundamental technology that enables this containers is a fundamental piece of technology that enables building new businesses, you know, modernizing existing businesses. And the 5G is going to be, there's going to be new innovations. It's going to get unleashed. And again, Kubernetes and containers enable us to leverage those. And so we're still scratching the surface on this. It's big. Now, it's going to be much, much bigger, you know, as, as we go into the next couple of years. >> Speaking, scratching the surface, Micah, take us out in the last 30 seconds or so with where CHG healthcare is on institutional transformation, how is Portworx facilitating that? >> So we're, we're right in the thick of it. I mean, we are, we still have what we call the legacy. We're working on getting those, but I mean, we're really moving forward to provide that rich experience, especially with event driven platforms like Kafka and Kubernetes and partnering with Portworx is one of the key things for us with that. And AWS along with that. But we're a, and I remember I heard a talk and I can't, I can't remember her name, but he talked about how, how Pure Kubernetes is sort of like the 56K modem, right. You're hearing it and see, but it's got to get to the point where it's just there. It's just the high-speed internet and Kelsey Hightower. That's great. But yeah, and I really liked that because that's true, you know, and that's where we are. We're all in that transition where we're still early, it's still at 50. So you still want to hear note, you still want to do cube CTL. You want to learn it the hard way and do all that fun stuff. But eventually it's going to be where it's just, it's just there. And it's running everything like 5G. I mean, stripped down doing micro, you know, Kate's things like that. You know, we're going to see it in a lot of other areas and just periphery and really accelerate the industry in compute and memory and storage, and. >> Yeah, a lot of acceleration. Guys thank you. This has been a really interesting session. I always love digging into customer use cases. How CHG is really driving its evolution with Portworx. Venkat, thanks for sharing with us, What's going on with Portworx a year after the acquisition. It sounds like all good stuff. >> Thank you. Thanks for having us. >> Pleasure. All right. For Dave Nicholson, I'm Lisa Martin. You're watching theCUBE live from Los Angeles. This is our coverage of KubeCon Cloud Native Con 21.

>>Mhm Welcome back to Los Angeles. The Cubans live, I can't say that enough. The Cubans live. We're at cu con cloud Native Con 21. We've been here all day yesterday and today and tomorrow talking with lots of gas. Really uncovering what's going on in the world of kubernetes, lisa martin here with Dave Nicholson. We've got some folks. Next we're gonna be talking about a customer use case, which is always one of my favorite things to talk about. Please welcome Michael Coletti, the principal platform engineer at CHG Healthcare and then cat from a christian VP of products from port works by pure storage. Guys, welcome to the program, Thank you. Happy to be here. Yeah. So Michael, first of all, let's go ahead and start with you, give the audience an overview of CHG healthcare. >>Yeah, so CHG Healthcare were a staffing company so we sure like a locum pen and so our clients are doctors and hospitals, so we help staff hospitals with temporary doctors or even permanent placing. So we deal with a lot of doctors, a lot of nursing and we're were a combination of multiple companies to see if she is the parents. So and uh yeah, we're known in the industry is one of the leaders in this, this field and providing uh hospitals with high quality uh doctors and nurses and uh you know, our customer services like number one and one of these are Ceos really focused on is now how do we make that more digital, how we provide that same level of quality of service, but a digital experience as rich for >>I can imagine there was a massive need for that in the last 18 months alone. >>Covid definitely really raised that awareness out for us and the importance of that digital experience and that we need to be out there in the digital market. >>Absolutely. So your customer report works by pure storage, we're gonna get into that. But then can talk to us about what's going on. The acquisition of port works by peer storage was about a year ago I talked to us about your VP of product, what's going on? >>Yeah, I mean, you know, first of all, I think I could not say how much of a great fit for a port works to be part of your storage. It's uh uh Pure itself is a very fast moving large start up that's a dominant leader in a flash and data center space. And you know, pure recognizes the fact that Cuban it is is the new operating system of the cloud is now how you know, it's kind of virtualizing the cloud itself and there is a, you know, a big burgeoning need for data management in communities and how you can kind of orchestrate work lords between your on prem data centers in the cloud and back. So port books fits right into the story as complete vision of data management for our customers and uh spend phenomenal or business has grown as part of being part of Pure and uh you know, we're looking at uh launching some new products as well and it's all exciting times. >>So you must have been pretty delighted to be acquired as a startup by essentially a startup because because although pure has reached significant milestones in the storage business and is a leader in flash storage still, that, that startup mindset is there, that's unique, that's not, that's not the same as being acquired by a company that's been around for 100 years seeking to revitalize >>itself. Can >>you talk a little bit about that >>aspect? So I think it will uh, Purest culture is highly innovation driven and it's a very open flat culture. Right? I mean everybody impure is accessible, it can easily have a conversation with folks and everybody has his learning mindset and Port works is and has always been in the same way. Right? So when you put these teams together, if we can create wonders, I mean we, right after that position, just within a few months we announced an integrated solution that Port works orchestrates volumes and she file shares in Pure flash products and then delivers as an integrated solution for our customers. And Pure has a phenomenal uh, cloud based monitoring and management system called Pure one that we integrated well into. Now we're bringing the power of all of the observe ability that Purest customers are used to for all of the partners customers and having super happy, you know, delivering that capability to our customers and our customers are delighted now they can have a complete view all the way from community is an >>app to the >>flash and I don't think any one company on the planet can even climb, they can do that. >>I think, I think it's fair to acknowledge that pure one was observe ability before observe ability was a word. Exactly one used regularly. So that's very interesting. >>I could talk to us about obviously you are a customer CHD as a customer of court works now Port works by peer storage. Talk to us about the use case, what what was the compelling? It was their compelling event and from a storage perspective that that led you to Port works in the >>first so we be, they began this our Ceo basically in the vision, we we need to have a digital presence, we need and hazards and this was even before Covid, so they brought me on board and my my manager read uh glass or he we basically had this task to how are we going to get out into the cloud, how we're going to make that happen And we we chose to follow very much cloud native strategy and the platform of choice. I mean it just made sense with kubernetes and so when we were looking at kubernetes, we're starting to figure out how we're doing, we knew that data is going to be a big factor, you know, um being to provide data, we're very much focused on an event driven, were really pushing to event driven architecture. So we leverage Kafka on top of kubernetes, but at the time we were actually leveraging Kafka with M S K down out in a W S and that was just a huge cost to us. So I came on board, I had experienced with poor works prior company before that and I basically said we need to figure out a great storage away overlay. And the only way to do is we gotta have high performance storage, we've got to have secure, we gotta be able to back up and recover that storage and the poor works was the right match and that allowed us to have a very smooth transition off of M S K onto kubernetes, saving us, it's a significant amount of money per month and just leverage that already existing hardware that are existing, compute memory and just in the and move right to port works, >>leveraging your existing investments. >>Exactly which is key. Very, very key. So, >>so been kept, how common are the challenges that when you guys came together with the HD, how common are the challenges? It's actually, >>that's a great question, you know, this is, I'll tell you the challenges that Michael and his team are running into is what we see a lot in the, in the industry where people pay a ton of money, you know, to, you know, to to other vendors or especially in some cases use some cloud native services, but they want to have control over the data. They want to control the cost and they want higher performance and they want to have, you know, there's also governance and regulatory things that they need to control better. So they want to kind of bring these services and have more control over them. Right? So now we will work very well with all of our partners including the cloud providers as well as uh, you know, an from several vendors and everybody but different customers are different kinds of needs and port works gives them the flexibility if you are a customer who want, you know, have a lot of control over your applications, the performance of the agency and want to control cars very well in leveraging existing investments board works can deliver that for you in your data center right now you can integrate it with pure slash and you get a complete solution or you won't run it in cloud and you still want to have leverage the agility of the cloud and scale for books delivers a solution for you as well. So it kind of not only protects their investment in future proves their architecture, you get future proving your architecture completely. So if you want to tear the cloud or burst the cloud, you have a great solution that you can continue to leverage >>when you hear a future proof and I'm a marketer. So I always go, I love to know what it means to different people, what does that mean to you in your environment? >>My environment. So a future proof means like one of the things we've been addressing lately, that's just a real big challenge and I'm sure it's a challenge in the industry, especially Q and A's is upgrading our clusters ability to actually maintain a consistent flow with how fast kubernetes is growing, you know, they they're out I think yes, we leverage eks so it's like 1 21 or 1 22 now, uh that effort to upgrade a cluster, it can be a daunting one with port works. We actually were able to make that to where we could actually spin up a brand new cluster and with port work shift, all our application services, data migrated completely over poor works, handles all that for us and stand up that new cluster in less than a day. And that effort, it would take us a week, two weeks to do so not even man hours the time spent there, but just the reliability of being able to do that and the cost, you know, instead of standing up a new cluster and configuring it and doing all that and spending all that time, we can just really, we move to what we call blue green cut over strategy and port works is an essential piece of that. >>So is it fair to say that there are a variety of ways that people approach port works from a, from a value perspective in terms of, I I know that one area that you are particularly good in is the area of backups in this environment, but then you get data management and there's a third kind of vector there. What is the third vector? >>Yeah, it's all of the data services. Data services, like for example, database as a service on any kubernetes cluster paid on your cloud or you're on from data centers, which >>data, what kind of databases >>you were talking about? Anything from Red is Kafka Postgres, my sequel, you know, council were supporting, we just announced something called port books, data services offering that essentially delivers all these databases as a service on any kubernetes cluster uh that that a customer can point to unless than kind of get the automated management of the database on day one to day three, the entire life cycle. Um you know, through regular communities, could curdle experience through Api and SDK s and a nice slick ui that they can, you know, just role based access control and all of that, that they can completely control their data and their applications through it. And, you know, that's the third vector of potatoes Africans >>like a question for you. So what works has been a part of peer storage? You've known it since obviously for several years before you were a c h G, you brought up to see H G, you now know it a year into being acquired by a fast paced startup. Talk to me about the relationship and some of the benefits that you're getting with port works as a part of pure storage. >>Well, I mean one of the things, you know, when, when I heard about the accusation, my first thing was I was a little bit concerned is that relationship going to change and when we were acquiring, when we're looking at a doctor and Poor works, One thing I would tell my management is poor works is not just a vendor that wants to throw a solution on you and provide some capability there, partner, they want to partner with you and your success in your journey and this whole cloud native journey to provide this rich digital experience for not only our platform engineering team, but our dev teams, but also be able to really accelerate the development of our services so we can provide that digital portal for our end users and that didn't change. If anything that accelerated that that relationship did not change. You know, I came to the cat with an issue we just, we're dealing with, he immediately got someone on the phone call with me and so that has not changed. So it's really exciting to see that now that they've been acquired that they still are very much invested in the success of their customers and making sure we're successful. You know, it's not all of a sudden I was worried I was gonna have to do a whole different support process and it's gonna go into a black hole didn't happen. They still are very much involved with their customers. And >>that sounds kind of similar to what you talked about with the cultural alignment I've known here for a long time and they're very customer centric. Sounds like one of the areas in which there was a very strong alignment with port works. >>Absolutely important works has always taken pride in being customer. First company. Our founders are heavily customer focused. Uh, you know, they are aligned. They want, they have always aligned uh, the portraits business to our customers needs. Uh Pure is a company that's men. I actually focused on customers, right? I mean, that's all, you know, purist founder cause and everybody care about and so, you know, bringing these companies together and being part of the pure team. I kind of see how synergistic it is. And you know, we have, you know, that has enabled us to serve our customers customers even better than before. >>So, I'm curious about the two of you personally, in terms of your histories, I'm going to assume that you didn't both just bounce out of high school into the world of kubernetes, right? So like lisa and I your spanning the generations between the world of, say, virtualization based on X 86 architecture and virtualization where you can have microservices, you have a full blown operating system that you're working with, that kind of talk about, you know, Michael with you first talk about what that's been like navigating that change. We were in the midst of that, Do you have advice for others that are navigating that change? >>Don't be afraid of it, you know, a lot of people want to, you know, I call it, we're moving from where we're uh naming, we still have cats and dogs, they have a name, the VMS either whether or not their physical boxes or their VMS to where it's more like it's a cattle, you know, it's like we don't own the Os and not to be afraid afraid of that because change is really good. You know, the ability for me to not have to worry about patching and operating system is huge, you know, where I can rely on someone like the chaos and and the version and allow them to, if CV comes out, they let me know I go and I use their tools to be able to upgrade. So I don't have to literally worry about owning that Os and continues the same thing. You know, you, you, you know, it's all about being fault tolerant, right? And being able to be changed where you can actually brought a new version of a container, a base image with a lot of these without having to go and catch a bunch of servers, I mean patch night was held, I'm sorry if I could say that, but it was a nightmare, you know, but this whole world has just been a game changer >>with that. So Van cut from your perspective, you were coming at it, going into a startup, looking at the landscape in the future and seeing opportunity, um what what what's that been like for you? I guess the question for you is more something lisa and I talk about this concept of peak kubernetes, where are we in the wave, is this just is this just the beginning, are we in the thick of it? >>Yeah, I think I would say we're kind of transitioning from earlier doctors too early majority face in the whole, you know, um crossing the chasm analogy. Right, so uh I would say we're still the early stages of this big wave that's going to transform how infrastructure is built, apps are, apps are built and managed and run in production. Um I think some of the uh pieces, the key pieces are falling in place and maturing, uh there are some other pieces like observe ability and security, uh you know, kind of edge use cases need to be, you know, they're kind of going to get a lot more mature and you'll see that the cloud as we know today and the apps as we know today, they're going to be radically different and you know, if you're not building your apps and your business on this modern platform, on this modern infrastructure, you're gonna be left behind. Um, you know, I, my wife's birthday was a couple of days ago. I was telling this story a couple of friends is that I r I used another flowers delivery website. Uh they missed delivering the flowers on the same day, right? So when they told me all kinds of excuses, then I just went and looked up, you know, like door dash, which delivers uh, you know, and then, you know, like your food, but there's also flower delivery, indoor dash and I don't do it, I door dash flowers to her and I can track the flower does all the way she did not eat them, okay, You need them. But my kids love the chocolates though. So, you know, the case in point is that you cannot be, you know, building a modern business without leveraging the moral toolchain and modern toolchain and how the business is going to be delivered. That that thing is going to be changing dramatically. And those kind of customer experience, if you don't deliver, uh, you're not gonna be successful in business and communities is the fundamental technology that enables these containers. It's a fundamental piece of technology that enables building new businesses, you know, modernizing existing businesses and the five G is gonna be, there's gonna be new innovations that's going to get unleashed. And uh, again, communities and containers enable us to leverage those. And so we're still scratching the surface on this, it's big now, it's going to be much, much bigger as we go to the next couple of years. >>Speaking of scratching the surface, Michael, take us out in the last 30 seconds or so with where CHG healthcare is on its digital transformation. How is port works facilitating that? >>So we're right in the thick of it. I mean we are we still have what we call the legacy, we're working on getting those. But I mean we're really moving forward um to provide that rich experience, especially with inventing driven platforms like Kafka and Kubernetes and partnering with port works is one of the key things for us with that and a W s along with that. But we're, and I remember I heard a talk and I can't, I can't remember me but he he talked about how, how kubernetes just sort of like 56 K. Modem, You're hearing it, see, but it's got to get to the point where it's just there, it's just the high speed internet and Kelsey Hightower, That's who Great. Yeah, and I really like that because that's true, you know, and that's where we're on that transition, where we're still early, it's still that 50. So you still want to hear a note, you still want to do cube Cto, you want to learn it the hard way and do all that fun stuff, but eventually it's gonna be where it's just, it's just there and it's running everything like five G. I mean stripped down doing Micro K. It's things like that, you know, we're gonna see it in a lot of other areas and just proliferate and really accelerate uh the industry and compute and memory and, and storage and >>yeah, a lot of acceleration guys, thank you. This has been a really interesting session. I always love digging into customer use cases how C H. G is really driving its evolution with port works Venkat. Thanks for sharing with us. What's going on with port works a year after the acquisition. It sounds like all good stuff. >>Thank you. Thanks for having us. It's been fun, our >>pleasure. Alright for Dave Nicholson. I'm lisa martin. You're watching the cube live from Los Angeles. This is our coverage of Yukon cloud native Con 21 mhm

>>Welcome back to the cubes coverage of H P S. Green Lake announcement. We've been following Green Lake and the cadence of announcements making. Now we're gonna talk about ransomware, ransomware become a household term. But what people really don't understand is that virtually any bad actor can become a ransomware criminal by going on the dark web hiring a ransomware as a service sticking, putting a stick into a server and taking a piece of the action and that is a really insidious threat. Uh, the adversaries are extremely capable, so we're going to dig into that with Omar assad, who's the storage platform, lead cloud data services at H P E and Deepak verma vice president of product Zito, which is now an H P E company Gentlemen, welcome to the cube. Good to see you. Thank you. >>Thank you. Welcome. Pleasure to be here. So >>over you heard my little narrative upfront. How does the Xarelto acquisition fit into that discourse? >>Thank you. Dave first of all, we're extremely excited to welcome Sir toe into the HP family. Uh, the acquisition of Puerto expands the Green Lake offerings from H P E uh, into the data protection as a service and ransomware protection as a service capabilities and it at the same time accelerates the transformation that the HP storage businesses going through as it transforms itself into more of a cloud native business, which sort of follows on from the May 4th announcements that you helped us cover. Uh, this enables the HP sales teams to now expand the data protection perimeter and to start offering data protection as a service and ransomware as a service with the best in class technologies uh, from a protection site as well as from ransomware recovery side of the house. And so we're all the way down already trying to integrate uh, you know, the little offerings as part of the Green lake offerings and extending support through our services organization. And the more of these announcements are gonna roll out later in the month. >>And I think that's what you want to see from it as a service offering. You want to see a fast cadence of new services that are not a box by a box that are applying. No, it's services that you want to access. So let's, let's talk about before we get into the tech, can we talk about how you're helping customers deal with ransomware? Maybe some of the use cases that you're seeing. >>First of all, extremely excited to be part of the HP family now. Um, Quick history and that we've been around for about 11 years. We've had about 9000 plus customers and they all benefit from essentially the same technology that we invented 11 years ago. First and foremost, one of the use cases has been continuous data protection. So were built on the CdP platform, which means extremely low RTO S and R P O S for recovery. I'll give you example there um, United Airlines is an application that cost them $1 million dollars for every hour that they're down. They use traditional approaches. That would be a lot of loss with Zito, we have that down two seconds of loss in case and the application goes down. So that's kind of core and fundamental to our plaque. The second uh critical use case that for us has been simplicity. A lot of customers have said we make the difficult, simple. So DRS is a complex uh process. Um, give you an example there. Hcea Healthcare Consolidated four different disaster recovery platforms into a single platform in Puerto and saved about $10 million dollars a year. So it's making that operations of having disaster recovery process is much simpler. Um the third kind of critical use case for us as uh, the environment has evolved as the landscape has involved has been around hybrid cloud. So being able to take customers to the platforms that they want to go to that's critical for us And for our customers an example, there is Kingston technology's so Kingston tried some competitive products to move to Azure, it would take them about 24 hours to recover 30 VMS or so with zero technology. They will get about all their 1000 VMS up in Azure instantaneously. So these are three use cases that were foundational. Built. Built the company in the tech. >>Nice. Thank you. Thank you for that. So simple works well these days, especially with all this complexity we have to deal with. Can we get into the secret sauce a little bit. I mean CdP has been around forever. What do you guys do that? That's different. Maybe you can talk about that. Sure. >>Um it's cdp based, I think we've perfected the technology. It's less about being able to just copy the data. It's more about what you do when things go bump. We've made it simpler with driven economies of scale lower and being platform agnostic. We've really brought that up across to whatever platforms once upon a time it was moving from physical to virtual or even across different virtualization platforms and then being able to move across to whatever cloud platform customer may want or or back >>to cbP continuous data protection by the way for the audience that may not know that go ahead. And >>one of the additional points that I want to add to the box comment over here is the the basics of platform independence is what really drew uh hp technologists into the technology because you know, one of the things we have many, we have the high end platform with the H B electra nine Kv of the electro six kids the midrange platform. Then we have a bunch of file and object offerings on the side. What zero does it University universally applies to all those technologies and along with, you know, as you pair them up with our computer offerings to offer a full stack but now the stack is disaster recovery capable. Natively with the integration of certo, you know, one of the things that, you know, Deepak talked about about the as your migrations that a lot of the customers are talking about cloud is also coming up as a D our use case for a lot of our customers, customers, you know, you know, as we went through thousands of customers interviews one of the, one of the key things that came back was investing in a D our data center which is just waiting there for a disaster to happen. It's a very expensive insurance policy. So absurd. Oh, through its native capabilities allows customers to do is to just use public cloud as a D our target and and as a service, it just takes care of all the format conversions and recoveries and although that's completely automated inside the platform and and we feel that, you know, when you combine this either at the high end of data center storage offering or the middle age offering with this replication, D. R. And ransomware protection built into the same package, working under the same hood, it just simplifies and streamlines the customers deployment. >>Come here a couple of things. So first of all historically, if you wanted to recover to appoint within let's say, you know, 10 seconds, five seconds you have to pay up. Big time. Number one. Number two is you couldn't test your D. R. It was too risky. So people just had it in, they had a checkbox on compliance but they actually couldn't really test it because they were afraid they were going to lose data. So it sounds like you're solving both of those problems or >>or you know we remember the D. R. Test where it was a weekend. It was an event right? It was the event and at the end of july that the entire I. T. Organizing honey >>it's not gonna be home this weekend. Exactly what >>we've changed. That is a click of a button. You can D. R. Test today if you want to you can have disaster recovery still running. You can D. R. Test in Azure bring up your environment an isolated network bubble, make sure everything's running and bring it and bring it down. The interesting thing is the technology was invented back when our fear in the industry was losing a data center was losing power was catastrophic, natural disasters. But the technology has lent itself very well to the new threats which which are very much around ransomware as you mentioned because it's a type of disaster. Somebody's going after your data. Physical servers are still around but you still need to go back to a point in time and you need to do that very quickly. So the technology has really just found itself uh appealing to new challenges. >>If a customer asks you can I really eliminate cyber attacks, where should I put my my if I had 100 bucks to spend. Should I spend it on you know layers and defense should I spend it on recovery. Both, what would you tell them? >>I think it's a balanced answer. I think prevention is 100% impossible. Uh It's really I'd say spend it in in thirds. You want to spend a third of it and and prevention a third of it maybe in detection and then a third of it in uh recovery. So it's really that balancing act that means you can't leave the front door open but then have a lot of recovery techniques invested in. It has to be it has to be a balance and it's also not a matter of if it's a matter of when so we invest in all three areas. Hopefully two of them will work to your advantage. >>You dave you you should always protect your perimeter. I mean that that goes without saying but then as you invest in other aspects of the business, as Deepak mentioned, recovery needs to be fast and quick recovery whether from your recovering from a backup disaster. Are you covering from a data center disaster a corrupted file or from a ransomware attack. A couple of things that zero really stitches together like journal based recovery has been allowed for a while but making journal based recovery platform independent in a seamless fashion with the click of a button within five seconds go back to where your situation was. That gives you the peace of mind that even if the perimeter was breached, you're still protected, you know, five minutes into the problem And, and that's the peace of mind, which along with data protection as a service, disaster recovery as a service and now integrating this, you know, recovery from ransomware along with it in a very simple, easy to consume package is what drew us into the >>more you can do this you said on the use the cloud as a target. I could use the cloud as an air gap if I wanted to. It sounds like it's cloud Native, correct? Just wrap your stack in kubernetes and shove it in the cloud and have a host and say we're cloud to No, really I'm serious. So >>absolutely, we we looked at that approach and that that's where the challenge comes in, Right? So I give you the example of Kingston technology just doesn't scale, it's not fast enough. What we did was developed a platform for cloud Native. We consume cloud services where necessary in order to provide that scalability. So one example in Azure is being able to use scale set. So think about a scenario where you just declare a disaster, you've got 1000 VMS to move over, we can spin up the workers that need to do the work to get 1000 VMS spin them down. So you're up and running instantaneously and that involves using cloud Native uh tools and technologies, >>can we stay on that for a minute, So take take us through an example of what life was like would be like without zero trying to recover and what it's like with Puerto resources, complexity time maybe you could sort of paint a picture. Sure. >>Let me, I'll actually use an example from a customer 10 Kata. They uh develop defensive fabrics, especially fabric. So think about firefighters, think about our men and women abroad that need protective clothing that developed the fibers behave. They were hit by ransomware by crypto locker. That this was before zero. Unfortunately it took they took about a two week uh data loss. It took them weeks to recover that environment, bring it back up and the confidence was pretty low. They invested in, they looked at our technology, they invested in the technology and then they were hit with a different variant of crypto locker immediately. The the IT administrators and the ITS folks there were relieved right, they had a sense of confidence to say yes we can recover. And the second time around they had data loss of about 10 seconds, they could recover within a few minutes. So that's the before and after picture giving customers that confidence to say yep, a breach happened, we tried our best but now it's up to recovery and I can recover without having to dig tapes out from some vault and hopefully have a good copy of data sitting there and then try that over and over again and there's a tolerance right before a time before which business will not be able to sustain itself. So what we want to do is minimize that for businesses so that they can recover as quickly as possible with as little data loss as possible. >>Thank you for that. So, Omar, there's a bigger sort of cyber recovery agenda that you have as part of, of green lake, I'm sure. What, what should we expect, what's next? Where do you want to take this? >>So uh excellent question point in the future day. So one of the things that you helped us, uh you know, unveil uh in May was the data services. Cloud console. Data services. Cloud console was the first uh sort of delivery as we took the storage business as it is and start to transform into more of a cloud native business. We introduced electra uh which is the cloud native hardware with the customers buy for persistent storage within their data center. But then data services, cloud console truly cemented that cloud operational model. Uh We separated the management from, from the devices itself and sort of lifted it up as a sas service into the public, public cloud. So now what you're gonna see is, you know, more and more data and data management services come up on the data services. Cloud console and and zero is going to be one of the first ones. Cloud physics was another one that we we talked about, but zero is the is the true data management service that is going to come up on data services, cloud console as part of the Green Lake services agenda that that HP has in the customer's environ and then you're gonna see compliance as a service. You're going to see data protection as a service. You're gonna see disaster recovery as a service. But the beautiful thing about it is, is choice with simplicity as these services get loaded up on data services, clown console. All our customers instantly get it. There's nothing to install, there's nothing to troubleshoot uh, there's nothing to size. All those capabilities are available on the console, customers go in and just start consuming Xarelto capabilities from a management control plane, Disaster recovery control plan are going to be available on the data services, cloud console, automatically detecting electro systems, rian Bear systems, container based systems, whichever our customers have deployed and from there is just a flip of a button. Another way to look at it is it sort of gives you that slider that you have data protection or back up on one side, you've got disaster recovery on one side, you've got ransomware protection on on the extreme right side, you can just move a slider across and choose the service level that you want without worrying about best practices, installation, application integration. All of that just takes control from the data services, cloud concepts. >>Great, great summary because historically you would have to build that right now. You can buy it as a service. You can programmatically, you know, deploy it and that's a game changer. Have to throw it over the fence to some folks. That's okay. Now, you know, make it make it work and then they change the code and you come back a lot of finger pointing. It's now it's your responsibility. >>Absolutely. Absolutely. We're excited to provide Zito continue provides the desert of customers but also integrate with the Green Green Lake platform and let the rest of Green Lake customers experience some of the sort of technology and really make that available as a service. >>That's great. This is a huge challenge for customers. I mean they do, I pay their ransom. Do not pay the ransom. If I pay the ransom the FBI is going to come after me. But if I don't pay the ransom, I'm not gonna get the crypto key. So solutions like this are critical. You certainly see the president pushing for that. The United States government said, hey, we got to do a better job. Good job guys, Thanks for for sharing your story in the cube and congratulations. Thank >>you. Thank you David. >>All right. And thank you for watching everybody. Uh this is the, I want to tell you that everything that you're seeing today as part of the Green Lake announcement is going to be available on demand as part of the HP discover more. So you got to check that out. Thank you. You're watching the cube. >>Mhm mm.

(upbeat music) >> Welcome to the special CUBE presentation of the AWS Global Public Sector Partner Awards Program. I'm here with the leader of the partner program, Sandy Carter, Vice President, AWS, Amazon Web Services @Sandy_Carter on Twitter, prolific on social and great leader. Sandy, great to see you again. And congratulations on this great program we're having here. In fact, thanks for coming out for this keynote. Well, thank you, John, for having me. You guys always talk about the coolest thing. So we had to be part of it. >> Well, one of the things that I've been really loving about this success of public sector we talked to us before is that as we start coming out of the pandemic, is becoming very clear that the cloud has helped a lot of people and your team has done amazing work, just want to give you props for that and say, congratulations, and what a great time to talk about the winners. Because everyone's been working really hard in public sector, because of the pandemic. The internet didn't break. And everyone stepped up with cloud scale and solve some problems. So take us through the award winners and talk about them. Give us an overview of what it is. The criteria and all the specifics. >> Yeah, you got it. So we've been doing this annually, and it's for our public sector partners overall, to really recognize the very best of the best. Now, we love all of our partners, John, as you know, but every year we'd like to really hone in on a couple who really leverage their skills and their ability to deliver a great customer solution. They demonstrate those Amazon leadership principles like working backwards from the customer, having a bias for action, they've engaged with AWS and very unique ways. And as well, they've contributed to our customer success, which is so very important to us and to our customers as well. >> That's awesome. Hey, can we put up a slide, I know we have slide on the winners, I want to look at them, with the tiles here. So here's a list of some of the winners. I see a nice little stars on there. Look at the gold star. I knows IronNet, CrowdStrike. That's General Keith Alexander's company, I mean, super relevant. Presidio, we've interviewed them before many times, got Palantir in there. And is there another one, I want to take a look at some of the other names here. >> In overall we had 21 categories. You know, we have over 1900 public sector partners today. So you'll notice that the awards we did, a big focus on mission. So things like government, education, health care, we spotlighted some of the brand new technologies like Containers, Artificial Intelligence, Amazon Connect. And we also this year added in awards for innovative use of our programs, like think big for small business and PTP as well. >> Yeah, well, great roundup, they're looking forward to hearing more about those companies. I have to ask you, because this always comes up, we're seeing more and more ecosystem discussions when we talk about the future of cloud. And obviously, we're going to, you know, be at Mobile World Congress, theCUBE, back in physical form, again, (indistinct) will continue to go on. The notion of ecosystem is becoming a key competitive advantage for companies and missions. So I have to ask you, why are partners so important to your public sector team? Talk about the importance of partners in context to your mission? >> Yeah, you know, our partners are critical. We drive most of our business and public sector through partners. They have great relationships, they've got great skills, and they have, you know, that really unique ability to meet the customer needs. If I just highlighted a couple of things, even using some of our partners who won awards, the first is, you know, migrations are so critical. Andy talked at Reinvent about still 96% of applications still sitting on premises. So anybody who can help us with the velocity of migrations is really critical. And I don't know if you knew John, but 80% of our migrations are led by partners. So for example, we gave awards to Collibra and Databricks as best lead migration for data as well as Datacom for best data lead migration as well. And that's because they increase the velocity of migrations, which increases customer satisfaction. They also bring great subject matter expertise, in particular around that mission that you're talking about. So for instance, GDIT won best Mission Solution For Federal, and they had just an amazing solution that was a secure virtual desktop that reduced a federal agencies deployment process, from months to days. And then finally, you know, our partners drive new opportunities and innovate on behalf of our customers. So we did award this year for P to P, Partnering to Partner which is a really big element of ecosystems, but it was won by four points and in quizon, and they were able to work together to implement a data, implement a data lake and an AI, ML solution, and then you just did the startup showcase, we have a best startup delivering innovation too, and that was EduTech (indistinct) Central America. And they won for implementing an amazing student registration and early warning system to alert and risks that may impact a student's educational achievement. So those are just some of the reasons why partners are important. I could go on and on. As you know, I'm so passionate about my partners, >> I know you're going to talk for an hour, we have to cut you off a little there. (indistinct) love your partners so much. You have to focus on this mission thing. It was a strong mission focus in the awards this year. Why are customers requiring much more of a mission focused? Is it because, is it a part of the criteria? I mean, we're seeing a mission being big. Why is that the case? >> Well, you know, IDC, said that IT spend for a mission or something with a purpose or line of business was five times greater than IT. We also recently did our CTO study where we surveyed thousands of CTOs. And the biggest and most changing elements today is really not around the technology. But it's around the industry, healthcare, space that we talked about earlier, or government. So those are really important. So for instance, New Reburial, they won Best Emission for Healthcare. And they did that because of their new smart diagnostic system. And then we had a partner when PA consulting for Best Amazon Connect solution around a mission for providing support for those most at risk, the elderly population, those who already had pre existing conditions, and really making sure they were doing what they called risk shielding during COVID. Really exciting and big, strong focus on mission. >> Yeah, and it's also, you know, we've been covering a lot on this, people want to work for a company that has purpose, and that has missions. I think that's going to be part of the table stakes going forward. I got to ask you on the secrets of success when this came up, I love asking this question, because, you know, we're starting to see the playbooks of what I call post COVID and cloud scale 2.0, whatever you want to call it, as you're starting to see this new modern era of success formulas, obviously, large scale value creation mission. These are points we're hearing and keep conversations across the board. What do you see as the secret of success for these parties? I mean, obviously, it's indirect for Amazon, I get that, but they're also have their customers, they're your customers, customers. That's been around for a while. But there's a new model emerging. What are the secrets from your standpoint of success? you know, it's so interesting, John, that you asked me this, because this is the number one question that I get from partners too. I would say the first secret is being able to work backwards from your customer, not just technology. So take one of our award winners Cognizant. They won for their digital tolling solution. And they work backwards from the customer and how to modernize that, or Pariveda, who is one of our best energy solution winners. And again, they looked at some of these major capital projects that oil companies were doing, working backwards from what the customer needed. I think that's number one, working backwards from the customer. Two, is having that mission expertise. So given that you have to have technology, but you also got to have that expertise in the area. We see that as a big secret of our public sector partners. So education cloud, (indistinct) one for education, effectual one for government and not for profit, Accenture won, really leveraging and showcasing their global expansion around public safety and disaster response. Very important as well. And then I would say the last secret of success is building repeatable solutions using those strong skills. So Deloitte, they have a great solution for migration, including mainframes. And then you mentioned early on, CloudStrike and IronNet, just think about the skill sets that they have there for repeatable solutions around security. So I think it's really around working backwards from the customer, having that mission expertise, and then building a repeatable solution, leveraging your skill sets. >> That's a great formula for success. I got you mentioned IronNet, and cybersecurity. One of things that's coming up is, in addition to having those best practices, there's also like real problems to solve, like, ransomware is now becoming a government and commercial problem, right. So (indistinct) seeing that happen a lot in DC, that's a front burner. That's a societal impact issue. That's like a cybersecurity kind of national security defense issue, but also, it's a technical one. And also public sector, through my interviews, I can tell you the past year and a half, there's been a lot of creativity of new solutions, new problems or new opportunities that are not yet identified as problems and I'd love to get your thoughts on my concern is with Jeff Bar yesterday from AWS, who's been blogging all the the news and he is a leader in the community. He was saying that he sees like 5G in the edge as new opportunities where it's creative. It's like he compared to the going to the home improvement store where he just goes to buy one thing. He does other things. And so there's a builder culture. And I think this is something that's coming out of your group more, because the pandemic forced these problems, and they forced new opportunities to be creative, and to build. What's your thoughts? >> Yeah, so I see that too. So if you think about builders, you know, we had a partner, Executive Council yesterday, we had 900, executives sign up from all of our partners. And we asked some survey questions like, what are you building with today? And the number one thing was artificial intelligence and machine learning. And I think that's such a new builders tool today, John, and, you know, one of our partners who won an award for the most innovative AI&ML was Kablamo And what they did was they use AI&ML to do a risk assessment on bushfires or wildfires in Australia. But I think it goes beyond that. I think it's building for that need. And this goes back to, we always talk about #techforgood. Presidio, I love this award that they won for best nonprofit, the Cherokee Nation, which is one of our, you know, Native American heritage, they were worried about their language going out, like completely out like no one being able to speak yet. And so they came to Presidio, and they asked how could we have a virtual classroom platform for the Cherokee Nation? And they created this game that's available on your phone, so innovative, so much of a builder's culture to capture that young generation, so they don't you lose their language. So I do agree. I mean, we're seeing builders everywhere, we're seeing them use artificial intelligence, Container, security. And we're even starting with quantum, so it is pretty powerful of what you can do as a public sector partner. >> I think the partner equation is just so wide open, because it's always been based on value, adding value, right? So adding value is just what they do. And by the way, you make money doing it if you do a good job of adding value. And, again, I just love riffing on this, because Dave and I talked about this on theCUBE all the time, and it comes up all the time in cloud conversations. The lock in isn't proprietary technology anymore, its value, and scale. So you starting to see builders thrive in that environment. So really good points. Great best practice. And I think I'm very bullish on the partner ecosystems in general, and people do it right, flat upside. I got to ask you, though, going forward, because this is the big post COVID kind of conversation. And last time we talked on theCUBE about this, you know, people want to have a growth strategy coming out of COVID. They want to be, they want to have a tail win, they want to be on the right side of history. No one wants to be in the losing end of all this. So last year in 2021 your goals were very clear, mission, migrations, modernization. What's the focus for the partners beyond 2021? What are you guys thinking to enable them, 21 is going to be a nice on ramp to this post COVID growth strategy? What's the focus beyond 2021 for you and your partners? >> Yeah, it's really interesting, we're going to actually continue to focus on those three M's mission, migration and modernization. But we'll bring in different elements of it. So for example, on mission, we see a couple of new areas that are really rising to the top, Smart Cities now that everybody's going back to work and (indistinct) down, operations and maintenance and global defense and using gaming and simulation. I mean, think about that digital twin strategy and how you're doing that. For migration, one of the big ones we see emerging today is data-lead migration. You know, we have been focused on applications and mainframes, but data has gravity. And so we are seeing so many partners and our customers demanding to get their data from on premises to the cloud so that now they can make real time business decisions. And then on modernization. You know, we talked a lot about artificial intelligence and machine learning. Containers are wicked hot right now, provides you portability and performance. I was with a startup last night that just moved everything they're doing to ECS our Container strategy. And then we're also seeing, you know, crippin, quantum blockchain, no code, low code. So the same big focus, mission migration, modernization, but the underpinnings are going to shift a little bit beyond 2021. >> That's great stuff. And you know, you have first of all people don't might not know that your group partners and Amazon Web Services public sector, has a big surface area. You talking about government, health care, space. So I have to ask you, you guys announced in March the space accelerator and you recently announced that you selected 10 companies to participate in the accelerated program. So, I mean, this is this is a space centric, you know, targeting, you know, low earth orbiting satellites to exploring the surface of the Moon and Mars, which people love. And because the space is cool, let's say the tech and space, they kind of go together, right? So take us through, what's this all about? How's that going? What's the selection, give us a quick update, while you're here on this space accelerated selection, because (indistinct) will have had a big blog post that went out (indistinct). >> Yeah, I would be thrilled to do that. So I don't know if you know this. But when I was young, I wanted to be an astronaut. We just helped through (indistinct), one of our partners reach Mars. So Clint, who is a retired general and myself got together, and we decided we needed to do something to help startups accelerate in their space mission. And so we decided to announce a competition for 10 startups to get extra help both from us, as well as a partner Sarafem on space. And so we announced it, everybody expected the companies to come from the US, John, they came from 44 different countries. We had hundreds of startups enter, and we took them through this six week, classroom education. So we had our General Clint, you know, helping and teaching them in space, which he's done his whole life, we provided them with AWS credits, they had mentoring by our partner, Sarafem. And we just down selected to 10 startups, that was what Vernors blog post was. If you haven't read it, you should look at some of the amazing things that they're going to do, from, you know, farming asteroids to, you know, helping with some of the, you know, using small vehicles to connect to larger vehicles, when we all get to space. It's very exciting. Very exciting, indeed, >> You have so much good content areas and partners, exploring, it's a very wide vertical or sector that you're managing. Is there any pattern? Well, I want to get your thoughts on post COVID success again, is there any patterns that you're seeing in terms of the partner ecosystem? You know, whether its business model, or team makeup, or more mindset, or just how they're organizing that that's been successful? Is there like a, do you see a trend? Is there a certain thing, then I've got the working backwards thing, I get that. But like, is there any other observations? Because I think people really want to know, am I doing it right? Am I being a good manager, when you know, people are going to be working remotely more? We're seeing more of that. And there's going to be now virtual events, hybrid events, physical events, the world's coming back to normal, but it's never going to be the same. Do you see any patterns? >> Yeah, you know, we're seeing a lot of small partners that are making an entrance and solving some really difficult problems. And because they're so focused on a niche, it's really having an impact. So I really believe that that's going to be one of the things that we see, I focus on individual creators and companies who are really tightly aligned and not trying to do everything, if you will. I think that's one of the big trends. I think the second we talked about it a little bit, John, I think you're going to see a lot of focus on mission. Because of that purpose. You know, we've talked about #techforgood, with everything going on in the world. As people have been working from home, they've been reevaluating who they are, and what do they stand for, and people want to work for a company that cares about people. I just posted my human footer on LinkedIn. And I got my first over a million hits on LinkedIn, just by posting this human footer, saying, you know what, reply to me at a time that's convenient for you, not necessarily for me. So I think we're going to see a lot of this purpose driven mission, that's going to come out as well. >> Yeah, and I also noticed that, and I was on LinkedIn, I got a similar reaction when I started trying to create more of a community model, not so much have people attend our events, and we need butts in the seats. It was much more personal, like we wanted you to join us, not attend and be like a number. You know, people want to be part of something. This seem to be the new mission. >> Yeah, I completely agree with that. I think that, you know, people do want to be part of something and they want, they want to be part of the meaning of something too, right. Not just be part of something overall, but to have an impact themselves, personally and individually, not just as a company. And I think, you know, one of the other trends that we saw coming up too, was the focus on technology. And I think low code, no code is giving a lot of people entry into doing things I never thought they could do. So I do think that technology, artificial intelligence Containers, low code, no code blockchain, those are going to enable us to even do greater mission-based solutions. >> Low code, no code reduces the friction to create more value, again, back to the value proposition. Adding value is the key to success, your partners are doing it. And of course, being part of something great, like the Global Public Sector Partner Awards list is a good one. And that's what we're talking about here. Sandy, great to see you. Thank you for coming on and sharing your insights and an update and talking more about the 2021, Global Public Sector partner Awards. Thanks for coming on. >> Thank you, John, always a pleasure. >> Okay, the Global Leaders here presented on theCUBE, again, award winners doing great work in mission, modernization, again, adding value. That's what it's all about. That's the new competitive advantage. This is theCUBE. I'm John Furrier, your host, thanks for watching. (upbeat music)

(upbeat music) >> Welcome back to HPE Discover 2021, theCube's virtual coverage, continuous coverage of HPE's annual customer event. My name is Dave Vellante and we're going to dive into the intersection of high-performance computing, data and AI with Dr. Eng Lim Goh who's a Senior Vice President and CTO for AI at Hewlett Packard Enterprise. Dr. Goh, great to see you again. Welcome back to theCube. >> Hey, 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 2 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 some of the biggest problems I think organizations face with data. And that's, you got to look, 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 healthcare and media. But stepping back a little bit we'll zoom out on Discover '21, you know, what do you make of the events so far and some of your big takeaways? >> Hmm, well, you started with the insightful question. Data is everywhere then but we lack the insight. That's also part of the reason why that's a main reason why, Antonio on Day 1 focused and talked about that, the fact that we are in the now in the age of insight and how to thrive in this new age. What I then did on the Day 2 keynote following Antonio is to talk about the challenges that we need to overcome 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 of, 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 were your takeaway from some of the ones you talked about today? >> Very pertinent question, Dave. You know, the two challenges I spoke about how to, that we need to overcome in order to thrive in this new age, the first one is the current challenge. And that current challenge is, you know state of this, you know, barriers to insight, when we are awash with data. So that's a statement. How to overcome those barriers. One of the barriers to insight when we are awash in data, in the Day 2 keynote, I spoke about three main things, three main areas that receive from customers. The first one, the first barrier is with many of our customers, data is siloed. You know, like in a big corporation, you've got data siloed by sales, finance, engineering, manufacturing, and so on supply chain and so on. And 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 first barrier we spoke about, you know, barriers to insight when we are awash with data. The second barrier is that we see amongst our customers is that data is raw and disperse when they are stored. And it's tough to get to value out of them. In that case I use the example of the May 6, 2010 event where the stock market dropped a trillion dollars in tens of minutes. We all know those who are financially attuned with, know about this incident. But that this is not the only incident. There are many of them out there. And for that particular May 6, event, 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. And there were many other incidences like this and the regulators were looking for that one rule that could mitigate many of these incidences. One of our customers decided to take the hard road to go with the tough data. Because data is raw and dispersed. So they went into all the different feeds of financial transaction information, took the tough, you know, took a tough road and analyze that data took a long time to assemble. And he discovered that there was quote stuffing. That people were sending a lot of trades in and then canceling them almost immediately. You have to manipulate the market. And why didn't we see it immediately? Well, the reason is the process reports that everybody sees had 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 100 shares trades to fly under the radar to do this manipulation. So here is, here the second barrier. Data could be raw and disperse. Sometimes it's just have to take the hard road and to get insight. And this is one great example. And then the last barrier has to do with sometimes when you start a project to get insight, to get answers and insight, you realize that all the data's around you, but you don't seem to find the right ones to get what you need. You don't seem to get the right ones, yeah. Here we have three quick examples of customers. One was a great example where they were trying to build a language translator a machine language translator between two languages. But in order to do that they need to get hundreds of millions of word pairs of one language compare with the corresponding other hundreds of millions of them. They say, "Where I'm going to get all these word pairs?" Someone creative thought of a willing source and huge source, 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. The second one has to do with, there was the, sometimes you may just have to generate that data. Interesting one. We had an autonomous car customer that collects all these data from their cars. Massive amounts of data, lots of sensors, collect lots of data. And, 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 in fine weather and collected the car driving on this highway in rain and also in snow. But never had the opportunity to collect the car in hail because that's a rare occurrence. So instead of waiting for a time where the car can drive in hail, they build a simulation by having the car collected in snow and simulated hail. So these are some of the examples where we have customers working to overcome barriers. You have barriers that is associated with the fact, that data silo, if federated barriers associated with data that's tough to get at. They just took the hard road. 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. And as a great example, the flash crash in fact Michael Lewis wrote about this in his book, the "Flash Boys" and essentially. It was high frequency traders trying to front run the market and sending in small block trades trying to get sort of front ended. So that's, 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. Can I guess my question is can technology help us get get out of the problem? And that maybe is where AI fits in. >> Yes. Yes. In fact, a lot of analytics work went in to go back to the raw data that is highly dispersed from different sources, assemble them to see if you can find a material trend. You can see lots of trends. Like, no, we, if humans at things we tend to see patterns in clouds. So sometimes you need to apply statistical analysis, math to be sure that what the model is seeing is real. And that required work. That's one area. The second area is, you know, when this, there are times when you just need to go through that tough approach to find the answer. Now, the issue comes to mind now is that humans put in the rules to decide what goes into a report that everybody sees. And in this case before the change in the rules. By the way, after the discovery, the authorities changed the rules and all shares all trades of different, any sizes it has to be reported. Not, yeah. But the rule was applied to 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 for understandable reasons. I mean, they probably didn't, wanted for various reasons not to put everything in there so that people could still read it in a reasonable amount of time. But we need to understand that rules were being put in by humans for the reports we read. And as such there are times we just need to go back to the raw data. >> I want to ask you-- Or be it that it's going to be tough there. >> Yeah, so I want to ask you a question about AI as obviously it's in your title and it's something you know a lot about and I'm going to make a statement. You tell me if it's on point or off point. Seems that most of the AI going on in the enterprise is modeling data science applied to troves of data. But there's also a lot of AI going on in consumer, whether it's fingerprint technology or facial recognition or natural language processing. Will, to two-part question, will the consumer market, let's say as it has so often in the enterprise sort of inform us is sort of first part. And then will there be a shift from sort of modeling, if you will, to more, you mentioned autonomous vehicles more AI inferencing in real-time, especially with the Edge. I think you can help us understand that better. >> Yeah, this is a great question. There are three stages to just simplify, I mean, you know, it's probably more sophisticated than that, but let's just simplify there're three stages to building an AI system that ultimately can predict, make a prediction. Or 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 starts to evolve a model based on all the data is seeing it starts to evolve. To a 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, you know after you're trained it with all that data to see whether his prediction accuracy is high enough. And once you are satisfied with it, you then deploy the model to make the decision and that's the inference. So a lot of times depending on what we are focusing on. We 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 pick one model and a prediction isn't that a robust, it is good, but then it is not consistent. Now what you do is you try another model. So sometimes you just keep trying different models until you get the right kind, yeah, that gives you a good robust decision-making and prediction. Now, after which, if it's tested well, Q8 you will then take that model and deploy it at the Edge, yeah. And then at the Edge 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 or a decision. So it is these three stages, yeah. But more and more, 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? That's the reason why we spoke about swarm learning the last time, learning at the Edge as a swarm. Because maybe individually they may not have enough power to do so, but as a swarm, they may. >> Is that learning from the Edge or learning at the Edge. In other words, is it-- >> Yes. >> Yeah, you don't understand my question, yeah. >> That's a great question. That's a great question. So answer is learning at the Edge, and also from the Edge, but the main goal, the goal is to learn at the Edge so that you don't have to move the data that Edge sees first back to the Cloud or the call to do the learning. Because that would be the reason, one of the main reasons why you want to learn at the Edge. 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 do the learning. With swarm learning, you can learn it and keep the data at the Edge and learn at that point, yeah. >> And then maybe only selectively send the autonomous vehicle example you gave is great 'cause maybe they're, you know, there may be only persisting. They're not persisting data that is an inclement weather, or when a deer runs across the front and then maybe they do that and then they send that smaller data set back and maybe that's where it's modeling done but the rest can be done at the Edge. It's a new world that's coming to, 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, yeah, well, today full of these insightful questions that actually touches on the second challenge. How do we, to in order to thrive in this new age of insight. The second challenge is our future challenge. What do we do for our future? And in there is 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, and when to organize it when you collect, and then where will your data be going forward that you are collecting from? So what, when, and where. For the what data, for what data to collect that was the question you asked. It's a question that different industries have to ask themselves because it will vary. 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 talking about 10 petabytes a day from a fleet of their cars and these are not production autonomous cars. These are training autonomous cars, collecting data so they can train and eventually deploy a commercial cars. Also these data collection cars, they collect 10 as a fleet of them collect 10 petabytes a day. And then when it came to us, building a storage system to store all of that data they realize they don't want to afford to store all of it. Now here comes the dilemma. What should I, after I spent so much effort building all this cars and sensors and collecting data, I've now decide what to delete. That's a dilemma. Now in working with them on this process of trimming down what they collected. I'm constantly reminded of the 60s and 70s. To remind myself 60s and 70s, we call a large part of our DNA, junk DNA. Today we realized that a large part of that, what we call junk has function has valuable function. They are not genes but they regulate the function of genes. So what's junk in yesterday could be valuable today, or what's junk today could be valuable tomorrow. So there's this tension going on between you deciding not wanting to afford to store everything that you can get your hands on. But on the other hand, you know you worry, you ignore the wrong ones. You can see this tension in our customers. And then it depends on industry here. In healthcare they say, I have no choice. I want it all, why? One very insightful point brought up by one healthcare 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. But we also care for the people we are not caring for. How do we find them? And therefore, they did not just need to collect data that they have with, from their patients they also need to reach out to outside data so that they can figure out who they are not caring for. So they want it all. So I asked them, "So what do you do with funding if you want it all?" They say they have no choice but they'll figure out a way to fund it and perhaps monetization of what they have now is the way to come around and fund that. Of course, they also come back to us, rightfully that you know, we have to then work out a way to to help them build a system. So that healthcare. And if you go to other industries like banking, they say they can afford to keep them all. But they are regulated same like healthcare. They are regulated as to 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 you perhaps deciding not wanting to fund all of that, all that you can store. But on the other hand you know, if you kind of don't want to afford it and decide not to store some, maybe those some become highly valuable in the future. You worry. >> Well, we can make some assumptions about the future, can't we? I mean we know there's going to be a lot more data than we've ever seen before, we know that. We know, well not withstanding supply constraints and things like NAND. We know the price 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, everybody says, Moore's Law is dead. Okay, it's waning but the processing power when you combine the CPUs and NPUs, and GPUs and accelerators and so forth, actually 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? >> Yeah, it's a highly, again another insightful question that we touched on, on our keynote and that goes up to the why, I'll do the where. Where will your data be? We have one estimate that says that by next year, there will be 55 billion connected devices out there. 55 billion. What's the population of the world? Well, off the order of 10 billion, but this thing is 55 billion. And many of them, most of them can collect data. So what do you do? So the amount of data that's going to come in is going to way exceed our drop in storage costs our increasing compute power. So what's the answer? The answer must be knowing that we don't and even a drop in price and increase in bandwidth, it will overwhelm the 5G, it'll will overwhelm 5G, given the amount of 55 billion of them collecting. So the answer must be that there needs to be a balance between you needing to bring all that data from the 55 billion devices of the data back out to a central, as a bunch of central cost because you may not be able to afford to do that. Firstly bandwidth, even with 5G and as the, when you still be too expensive given the number of devices out there. You know given storage costs dropping it'll still be too expensive to try and install them all. So the answer must be to start at least to mitigate the problem to some leave most a lot of the data out there. And only send back the pertinent ones, as you said before. But then if you did that then, how are we going to 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. Sometimes you want to a mix of the positive type data, and the negative type data. So you can train the machine in a more balanced way. So the answer must be you eventually, as we move forward with these huge number of devices are at the Edge to do machine learning at the Edge. Today we don't even have power. The Edge typically is characterized by a lower energy capability and therefore, lower compute power. But soon, you know, even with low energy, they can do more with compute power, improving in energy efficiency. So learning at the Edge today we do inference at the Edge. So we data, model, deploy and you do inference at age. That's what we do today. But more and more, I believe given a massive amount of data at the Edge you have to have to start doing machine learning at the Edge. And if when you don't have enough power then you aggregate multiple devices' compute power into a swarm and learn as a swarm. >> Oh, interesting, so now of course, if I were sitting in a flyer flying the wall on HPE Board meeting I said, "Okay, HPE is a leading provider of compute." How do you take advantage 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 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? >> The wall will have to have a balance. Where today the default, well, the more common mode is to collect the data from the Edge and train at some centralized location or number of centralized location. Going forward, given the proliferation of the Edge devices, we'll need a balance, we need both. We need capability at the Cloud side. And it has to be hybrid. And then we need capability on the Edge side. Yeah that we need to build systems that on one hand is Edge-adapted. Meaning they environmentally-adapted because the Edge differently are on it. A lot of times on the outside, they need to be packaging-adapted and also power-adapted. Because typically many of these devices are battery-powered. So you have to build systems that adapts 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, that's also the insightful for that. Antonio announced in 2018 for the next four years from 2018, $4 billion invested to strengthen our Edge portfolio our Edge product lines, Edge solutions. >> Dr. Goh, I could go on for hours with you. You're just such a great guest. Let's close. What are you most excited about in the future of certainly HPE, but the industry in general? >> Yeah, I think the excitement is the customers. The diversity of customers and the diversity in the way they have approached their different problems with data strategy. So the excitement is around data strategy. Just like, you know, the statement made for us was so, was profound. And Antonio said we are in the age of insight powered by data. That's the first line. The line that comes after that is as such we are becoming more and more data-centric with data the currency. Now the next step is even more profound. That is, you know, we are going as far as saying that data should not be treated as cost anymore, no. But instead, as an investment in a new asset class called data with value on our balance sheet. This is a step change in thinking that is going to change the way we look at data, the way we value it. So that's a statement. So this is the exciting thing, because for me a CTO of AI, a machine is only as intelligent as the data you feed it with. Data is a source of the machine learning to be intelligent. So that's why when the people start to value data 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 huge amounts of data and a diversity of data. So it'd be great if the community values data. >> Well, are you certainly see it in the valuations of many companies these days? And I think increasingly you see it on the income statement, you know data products and people monetizing data services, and yeah, maybe eventually you'll see it in the balance sheet, I know. Doug Laney when he was at Gartner Group wrote a book about this and a lot of people are thinking about it. That's a big change, isn't it? Dr. Goh. >> Yeah, yeah, yeah. Your question is the process and methods in valuation. But I believe we'll get there. We need to get started and then we'll get there, I believe, yeah. >> Dr. Goh it's always my pleasure. >> And then the AI will benefit greatly from it. >> Oh yeah, no doubt. People will better understand how to align some of these technology investments. Dr. Goh, great to see you again. Thanks so much for coming back in theCube. It's been a real pleasure. >> Yes, a system is only as smart as the data you feed it with. (both chuckling) >> Well, excellent, we'll leave it there. Thank you for spending some time with us so keep it right there for more great interviews from HPE Discover '21. This is Dave Vellante for theCube, the leader in enterprise tech coverage. We'll be right back (upbeat music)