>> From theCUBE studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> Confidential computing is a technology that aims to enhance data privacy and security by providing encrypted computation on sensitive data and isolating data from apps in a fenced off enclave during processing. The concept of confidential computing is gaining popularity, especially in the cloud computing space where sensitive data is often stored and of course processed. However, there are some who view confidential computing as an unnecessary technology in a marketing ploy by cloud providers aimed at calming customers who are cloud phobic. Hello and welcome to this week's Wikibon CUBE Insights powered by ETR. In this Breaking Analysis, we revisit the notion of confidential computing, and to do so, we'll invite two Google experts to the show, but before we get there, let's summarize briefly. There's not a ton of ETR data on the topic of confidential computing. I mean, it's a technology that's deeply embedded into silicon and computing architectures. But at the highest level, security remains the number one priority being addressed by IT decision makers in the coming year as shown here. And this data is pretty much across the board by industry, by region, by size of company. I mean we dug into it and the only slight deviation from the mean is in financial services. The second and third most cited priorities, cloud migration and analytics, are noticeably closer to cybersecurity in financial services than in other sectors, likely because financial services has always been hyper security conscious, but security is still a clear number one priority in that sector. The idea behind confidential computing is to better address threat models for data in execution. Protecting data at rest and data and transit have long been a focus of security approaches, but more recently, silicon manufacturers have introduced architectures that separate data and applications from the host system. Arm, Intel, AMD, Nvidia and other suppliers are all on board, as are the big cloud players. Now the argument against confidential computing is that it narrowly focuses on memory encryption and it doesn't solve the biggest problems in security. Multiple system images updates different services and the entire code flow aren't directly addressed by memory encryption, rather to truly attack these problems, many believe that OSs need to be re-engineered with the attacker and hacker in mind. There are so many variables and at the end of the day, critics say the emphasis on confidential computing made by cloud providers is overstated and largely hype. This tweet from security researcher Rodrigo Branco sums up the sentiment of many skeptics. He says, "Confidential computing is mostly a marketing campaign for memory encryption. It's not driving the industry towards the hard open problems. It is selling an illusion." Okay. Nonetheless, encrypting data in use and fencing off key components of the system isn't a bad thing, especially if it comes with the package essentially for free. There has been a lack of standardization and interoperability between different confidential computing approaches. But the confidential computing consortium was established in 2019 ostensibly to accelerate the market and influence standards. Notably, AWS is not part of the consortium, likely because the politics of the consortium were probably a conundrum for AWS because the base technology defined by the the consortium is seen as limiting by AWS. This is my guess, not AWS's words, and but I think joining the consortium would validate a definition which AWS isn't aligned with. And two, it's got a lead with this Annapurna acquisition. This was way ahead with Arm integration and so it probably doesn't feel the need to validate its competitors. Anyway, one of the premier members of the confidential computing consortium is Google, along with many high profile names including Arm, Intel, Meta, Red Hat, Microsoft, and others. And we're pleased to welcome two experts on confidential computing from Google to unpack the topic, Nelly Porter is head of product for GCP confidential computing and encryption, and Dr. Patricia Florissi is the technical director for the office of the CTO at Google Cloud. Welcome Nelly and Patricia, great to have you. >> Great to be here. >> Thank you so much for having us. >> You're very welcome. Nelly, why don't you start and then Patricia, you can weigh in. Just tell the audience a little bit about each of your roles at Google Cloud. >> So I'll start, I'm owning a lot of interesting activities in Google and again security or infrastructure securities that I usually own. And we are talking about encryption and when encryption and confidential computing is a part of portfolio in additional areas that I contribute together with my team to Google and our customers is secure software supply chain. Because you need to trust your software. Is it operate in your confidential environment to have end-to-end story about if you believe that your software and your environment doing what you expect, it's my role. >> Got it. Okay. Patricia? >> Well, I am a technical director in the office of the CTO, OCTO for short, in Google Cloud. And we are a global team. We include former CTOs like myself and senior technologists from large corporations, institutions and a lot of success, we're startups as well. And we have two main goals. First, we walk side by side with some of our largest, more strategic or most strategical customers and we help them solve complex engineering technical problems. And second, we are devise Google and Google Cloud engineering and product management and tech on there, on emerging trends and technologies to guide the trajectory of our business. We are unique group, I think, because we have created this collaborative culture with our customers. And within OCTO, I spend a lot of time collaborating with customers and the industry at large on technologies that can address privacy, security, and sovereignty of data in general. >> Excellent. Thank you for that both of you. Let's get into it. So Nelly, what is confidential computing? From Google's perspective, how do you define it? >> Confidential computing is a tool and it's still one of the tools in our toolbox. And confidential computing is a way how we would help our customers to complete this very interesting end-to-end lifecycle of the data. And when customers bring in the data to cloud and want to protect it as they ingest it to the cloud, they protect it at rest when they store data in the cloud. But what was missing for many, many years is ability for us to continue protecting data and workloads of our customers when they running them. And again, because data is not brought to cloud to have huge graveyard, we need to ensure that this data is actually indexed. Again, there is some insights driven and drawn from this data. You have to process this data and confidential computing here to help. Now we have end to end protection of our customer's data when they bring the workloads and data to cloud, thanks to confidential computing. >> Thank you for that. Okay, we're going to get into the architecture a bit, but before we do, Patricia, why do you think this topic of confidential computing is such an important technology? Can you explain, do you think it's transformative for customers and if so, why? >> Yeah, I would maybe like to use one thought, one way, one intuition behind why confidential commuting matters, because at the end of the day, it reduces more and more the customer's thresh boundaries and the attack surface. That's about reducing that periphery, the boundary in which the customer needs to mind about trust and safety. And in a way, is a natural progression that you're using encryption to secure and protect the data. In the same way that we are encrypting data in transit and at rest, now we are also encrypting data while in use. And among other beneficials, I would say one of the most transformative ones is that organizations will be able to collaborate with each other and retain the confidentiality of the data. And that is across industry, even though it's highly focused on, I wouldn't say highly focused, but very beneficial for highly regulated industries. It applies to all of industries. And if you look at financing for example, where bankers are trying to detect fraud, and specifically double finance where you are, a customer is actually trying to get a finance on an asset, let's say a boat or a house, and then it goes to another bank and gets another finance on that asset. Now bankers would be able to collaborate and detect fraud while preserving confidentiality and privacy of the data. >> Interesting. And I want to understand that a little bit more but I'm going to push you a little bit on this, Nelly, if I can because there's a narrative out there that says confidential computing is a marketing ploy, I talked about this upfront, by cloud providers that are just trying to placate people that are scared of the cloud. And I'm presuming you don't agree with that, but I'd like you to weigh in here. The argument is confidential computing is just memory encryption and it doesn't address many other problems. It is over hyped by cloud providers. What do you say to that line of thinking? >> I absolutely disagree, as you can imagine, with this statement, but the most importantly is we mixing multiple concepts, I guess. And exactly as Patricia said, we need to look at the end-to-end story, not again the mechanism how confidential computing trying to again, execute and protect a customer's data and why it's so critically important because what confidential computing was able to do, it's in addition to isolate our tenants in multi-tenant environments the cloud covering to offer additional stronger isolation. They called it cryptographic isolation. It's why customers will have more trust to customers and to other customers, the tenant that's running on the same host but also us because they don't need to worry about against threats and more malicious attempts to penetrate the environment. So what confidential computing is helping us to offer our customers, stronger isolation between tenants in this multi-tenant environment, but also incredibly important, stronger isolation of our customers, so tenants from us. We also writing code, we also software providers will also make mistakes or have some zero days. Sometimes again us introduced, sometimes introduced by our adversaries. But what I'm trying to say by creating this cryptographic layer of isolation between us and our tenants and amongst those tenants, we're really providing meaningful security to our customers and eliminate some of the worries that they have running on multi-tenant spaces or even collaborating to gather this very sensitive data knowing that this particular protection is available to them. >> Okay, thank you. Appreciate that. And I think malicious code is often a threat model missed in these narratives. Operator access, yeah, maybe I trust my clouds provider, but if I can fence off your access even better, I'll sleep better at night. Separating a code from the data, everybody's, Arm, Intel, AMD, Nvidia, others, they're all doing it. I wonder if, Nelly, if we could stay with you and bring up the slide on the architecture. What's architecturally different with confidential computing versus how operating systems and VMs have worked traditionally. We're showing a slide here with some VMs, maybe you could take us through that. >> Absolutely. And Dave, the whole idea for Google and now industry way of dealing with confidential computing is to ensure that three main property is actually preserved. Customers don't need to change the code. They can operate on those VMs exactly as they would with normal non-confidential VMs, but to give them this opportunity of lift and shift or no changing their apps and performing and having very, very, very low latency and scale as any cloud can, something that Google actually pioneer in confidential computing. I think we need to open and explain how this magic was actually done. And as I said, it's again the whole entire system have to change to be able to provide this magic. And I would start with we have this concept of root of trust and root of trust where we will ensure that this machine, when the whole entire post has integrity guarantee, means nobody changing my code on the most low level of system. And we introduce this in 2017 called Titan. It was our specific ASIC, specific, again, inch by inch system on every single motherboard that we have that ensures that your low level former, your actually system code, your kernel, the most powerful system is actually proper configured and not changed, not tampered. We do it for everybody, confidential computing included. But for confidential computing, what we have to change, we bring in AMD, or again, future silicon vendors and we have to trust their former, their way to deal with our confidential environments. And that's why we have obligation to validate integrity, not only our software and our former but also former and software of our vendors, silicon vendors. So we actually, when we booting this machine, as you can see, we validate that integrity of all of the system is in place. It means nobody touching, nobody changing, nobody modifying it. But then we have this concept of AMD secure processor, it's special ASICs, best specific things that generate a key for every single VM that our customers will run or every single node in Kubernetes or every single worker thread in our Hadoop or Spark capability. We offer all of that. And those keys are not available to us. It's the best keys ever in encryption space because when we are talking about encryption, the first question that I'm receiving all the time, where's the key, who will have access to the key? Because if you have access to the key then it doesn't matter if you encrypted or not. So, but the case in confidential computing provides so revolutionary technology, us cloud providers, who don't have access to the keys. They sitting in the hardware and they head to memory controller. And it means when hypervisors that also know about these wonderful things saying I need to get access to the memories that this particular VM trying to get access to, they do not decrypt the data, they don't have access to the key because those keys are random, ephemeral and per VM, but the most importantly, in hardware not exportable. And it means now you would be able to have this very interesting role that customers or cloud providers will not be able to get access to your memory. And what we do, again, as you can see our customers don't need to change their applications, their VMs are running exactly as it should run and what you're running in VM, you actually see your memory in clear, it's not encrypted, but God forbid is trying somebody to do it outside of my confidential box. No, no, no, no, no, they would not be able to do it. Now you'll see cyber and it's exactly what combination of these multiple hardware pieces and software pieces have to do. So OS is also modified. And OS is modified such way to provide integrity. It means even OS that you're running in your VM box is not modifiable and you, as customer, can verify. But the most interesting thing, I guess, how to ensure the super performance of this environment because you can imagine, Dave, that encrypting and it's additional performance, additional time, additional latency. So we were able to mitigate all of that by providing incredibly interesting capability in the OS itself. So our customers will get no changes needed, fantastic performance and scales as they would expect from cloud providers like Google. >> Okay, thank you. Excellent. Appreciate that explanation. So, again, the narrative on this as well, you've already given me guarantees as a cloud provider that you don't have access to my data, but this gives another level of assurance, key management as they say is key. Now humans aren't managing the keys, the machines are managing them. So Patricia, my question to you is, in addition to, let's go pre confidential computing days, what are the sort of new guarantees that these hardware-based technologies are going to provide to customers? >> So if I am a customer, I am saying I now have full guarantee of confidentiality and integrity of the data and of the code. So if you look at code and data confidentiality, the customer cares and they want to know whether their systems are protected from outside or unauthorized access, and that recovered with Nelly, that it is. Confidential computing actually ensures that the applications and data internals remain secret, right? The code is actually looking at the data, the only the memory is decrypting the data with a key that is ephemeral and per VM and generated on demand. Then you have the second point where you have code and data integrity, and now customers want to know whether their data was corrupted, tampered with or impacted by outside actors. And what confidential computing ensures is that application internals are not tampered with. So the application, the workload as we call it, that is processing the data, it's also, it has not been tampered and preserves integrity. I would also say that this is all verifiable. So you have attestation and these attestation actually generates a log trail and the log trail guarantees that, provides a proof that it was preserved. And I think that the offer's also a guarantee of what we call ceiling, this idea that the secrets have been preserved and not tampered with, confidentiality and integrity of code and data. >> Got it. Okay, thank you. Nelly, you mentioned, I think I heard you say that the applications, it's transparent, you don't have to change the application, it just comes for free essentially. And we showed some various parts of the stack before. I'm curious as to what's affected, but really more importantly, what is specifically Google's value add? How do partners participate in this, the ecosystem, or maybe said another way, how does Google ensure the compatibility of confidential computing with existing systems and applications? >> And a fantastic question by the way. And it's very difficult and definitely complicated world because to be able to provide these guarantees, actually a lot of work was done by community. Google is very much operate in open, so again, our operating system, we working with operating system repository OSs, OS vendors to ensure that all capabilities that we need is part of the kernels, are part of the releases and it's available for customers to understand and even explore if they have fun to explore a lot of code. We have also modified together with our silicon vendors a kernel, host kernel to support this capability and it means working this community to ensure that all of those patches are there. We also worked with every single silicon vendor as you've seen, and that's what I probably feel that Google contributed quite a bit in this whole, we moved our industry, our community, our vendors to understand the value of easy to use confidential computing or removing barriers. And now I don't know if you noticed, Intel is pulling the lead and also announcing their trusted domain extension, very similar architecture. And no surprise, it's, again, a lot of work done with our partners to, again, convince, work with them and make this capability available. The same with Arm this year, actually last year, Arm announced their future design for confidential computing. It's called Confidential Computing Architecture. And it's also influenced very heavily with similar ideas by Google and industry overall. So it's a lot of work in confidential computing consortiums that we are doing, for example, simply to mention, to ensure interop, as you mentioned, between different confidential environments of cloud providers. They want to ensure that they can attest to each other because when you're communicating with different environments, you need to trust them. And if it's running on different cloud providers, you need to ensure that you can trust your receiver when you are sharing your sensitive data workloads or secret with them. So we coming as a community and we have this attestation sig, the, again, the community based systems that we want to build and influence and work with Arm and every other cloud providers to ensure that we can interrupt and it means it doesn't matter where confidential workloads will be hosted, but they can exchange the data in secure, verifiable and controlled by customers way. And to do it, we need to continue what we are doing, working open, again, and contribute with our ideas and ideas of our partners to this role to become what we see confidential computing has to become, it has to become utility. It doesn't need to be so special, but it's what we want it to become. >> Let's talk about, thank you for that explanation. Let's talk about data sovereignty because when you think about data sharing, you think about data sharing across the ecosystem and different regions and then of course data sovereignty comes up. Typically public policy lags, the technology industry and sometimes is problematic. I know there's a lot of discussions about exceptions, but Patricia, we have a graphic on data sovereignty. I'm interested in how confidential computing ensures that data sovereignty and privacy edicts are adhered to, even if they're out of alignment maybe with the pace of technology. One of the frequent examples is when you delete data, can you actually prove that data is deleted with a hundred percent certainty? You got to prove that and a lot of other issues. So looking at this slide, maybe you could take us through your thinking on data sovereignty. >> Perfect. So for us, data sovereignty is only one of the three pillars of digital sovereignty. And I don't want to give the impression that confidential computing addresses it all. That's why we want to step back and say, hey, digital sovereignty includes data sovereignty where we are giving you full control and ownership of the location, encryption and access to your data. Operational sovereignty where the goal is to give our Google Cloud customers full visibility and control over the provider operations, right? So if there are any updates on hardware, software stack, any operations, there is full transparency, full visibility. And then the third pillar is around software sovereignty where the customer wants to ensure that they can run their workloads without dependency on the provider's software. So they have sometimes is often referred as survivability, that you can actually survive if you are untethered to the cloud and that you can use open source. Now let's take a deep dive on data sovereignty, which by the way is one of my favorite topics. And we typically focus on saying, hey, we need to care about data residency. We care where the data resides because where the data is at rest or in processing, it typically abides to the jurisdiction, the regulations of the jurisdiction where the data resides. And others say, hey, let's focus on data protection. We want to ensure the confidentiality and integrity and availability of the data, which confidential computing is at the heart of that data protection. But it is yet another element that people typically don't talk about when talking about data sovereignty, which is the element of user control. And here, Dave, is about what happens to the data when I give you access to my data. And this reminds me of security two decades ago, even a decade ago, where we started the security movement by putting firewall protections and login accesses. But once you were in, you were able to do everything you wanted with the data. An insider had access to all the infrastructure, the data and the code. And that's similar because with data sovereignty we care about whether it resides, where, who is operating on the data. But the moment that the data is being processed, I need to trust that the processing of the data will abide by user control, by the policies that I put in place of how my data is going to be used. And if you look at a lot of the regulation today and a lot of the initiatives around the International Data Space Association, IDSA, and Gaia-X, there is a movement of saying the two parties, the provider of the data and the receiver of the data are going to agree on a contract that describes what my data can be used for. The challenge is to ensure that once the data crosses boundaries, that the data will be used for the purposes that it was intended and specified in the contract. And if you actually bring together, and this is the exciting part, confidential computing together with policy enforcement, now the policy enforcement can guarantee that the data is only processed within the confines of a confidential computing environment, that the workload is cryptographically verified that there is the workload that was meant to process the data and that the data will be only used when abiding to the confidentiality and integrity safety of the confidential computing environment. And that's why we believe confidential computing is one necessary and essential technology that will allow us to ensure data sovereignty, especially when it comes to user control. >> Thank you for that. I mean it was a deep dive, I mean brief, but really detailed. So I appreciate that, especially the verification of the enforcement. Last question, I met you two because as part of my year end prediction post, you guys sent in some predictions and I wasn't able to get to them in the predictions post. So I'm thrilled that you were able to make the time to come on the program. How widespread do you think the adoption of confidential computing will be in 23 and what's the maturity curve look like, this decade in your opinion? Maybe each of you could give us a brief answer. >> So my prediction in five, seven years, as I started, it'll become utility. It'll become TLS as of, again, 10 years ago we couldn't believe that websites will have certificates and we will support encrypted traffic. Now we do and it's become ubiquity. It's exactly where confidential computing is getting and heading, I don't know we deserve yet. It'll take a few years of maturity for us, but we will be there. >> Thank you. And Patricia, what's your prediction? >> I will double that and say, hey, in the future, in the very near future, you will not be able to afford not having it. I believe as digital sovereignty becomes evermore top of mind with sovereign states and also for multi national organizations and for organizations that want to collaborate with each other, confidential computing will become the norm. It'll become the default, if I say, mode of operation. I like to compare that today is inconceivable. If we talk to the young technologists, it's inconceivable to think that at some point in history, and I happen to be alive that we had data at rest that was not encrypted, data in transit that was not encrypted, and I think that will be inconceivable at some point in the near future that to have unencrypted data while in use. >> And plus I think the beauty of the this industry is because there's so much competition, this essentially comes for free. I want to thank you both for spending some time on Breaking Analysis. There's so much more we could cover. I hope you'll come back to share the progress that you're making in this area and we can double click on some of these topics. Really appreciate your time. >> Anytime. >> Thank you so much. >> In summary, while confidential computing is being touted by the cloud players as a promising technology for enhancing data privacy and security, there are also those, as we said, who remain skeptical. The truth probably lies somewhere in between and it will depend on the specific implementation and the use case as to how effective confidential computing will be. Look, as with any new tech, it's important to carefully evaluate the potential benefits, the drawbacks, and make informed decisions based on the specific requirements in the situation and the constraints of each individual customer. But the bottom line is silicon manufacturers are working with cloud providers and other system companies to include confidential computing into their architectures. Competition, in our view, will moderate price hikes. And at the end of the day, this is under the covers technology that essentially will come for free. So we'll take it. I want to thank our guests today, Nelly and Patricia from Google, and thanks to Alex Myerson who's on production and manages the podcast. Ken Schiffman as well out of our Boston studio, Kristin Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our editor-in-chief over at siliconangle.com. Does some great editing for us, thank you all. Remember all these episodes are available as podcasts. Wherever you listen, just search Breaking Analysis podcast. I publish each week on wikibon.com and siliconangle.com where you can get all the news. If you want to get in touch, you can email me at david.vellante@siliconangle.com or dm me @DVellante. And you can also comment on my LinkedIn post. Definitely you want to check out etr.ai for the best survey data in the enterprise tech business. I know we didn't hit on a lot today, but there's some amazing data and it's always being updated, so check that out. This is Dave Vellante for theCUBE Insights, powered by ETR. Thanks for watching and we'll see you next time on Breaking Analysis. (upbeat music)

>> Welcome Nelly and Patricia, great to have you. >> Great to be here. >> Thank you so much for having us. >> You're very welcome. Nelly, why don't you start, and then Patricia you can weigh in. Just tell the audience a little bit about each of your roles at Google Cloud. >> So I'll start, I'm honing a lot of interesting activities in Google and again, security or infrastructure securities that I usually hone, and we're talking about encryption, Antware encryption, and confidential computing is a part of portfolio. In additional areas that I contribute to get with my team to Google and our customers is secure software supply chain. Because you need to trust your software. Is it operating your confidential environment to have end to end story about if you believe that your software and your environment doing what you expect, it's my role. >> Got it, okay. Patricia? >> Well I am a technical director in the office of the CTO, OCTO for short, in Google Cloud. And we are a global team. We include former CTOs like myself and senior technologies from large corporations, institutions, and a lot of success for startups as well. And we have two main goals. First, we work side by side with some of our largest, more strategic or most strategic customers and we help them solve complex engineering technical problems. And second, we are device Google and Google Cloud engineering and product management on emerging trends in technologies to guide the trajectory of our business. We are unique group, I think, because we have created this collaborative culture with our customers. And within OCTO I spend a lot of time collaborating with customers in the industry at large on technologies that can address privacy, security, and sovereignty of data in general. >> Excellent, thank you for that both of you. Let's get into it. So Nelly, what is confidential computing from Google's perspective? How do you define it? >> Confidential computing is a tool. And it's one of the tools in our toolbox. And confidential computing is a way how would help our customers to complete this very interesting end to end lifecycle of their data. And when customers bring in the data to Cloud and want to protect it, as they ingest it to the Cloud, they protect it address when they store data in the Cloud. But what was missing for many, many years is ability for us to continue protecting data and workloads of our customers when they running them. And again, because data is not brought to Cloud to have huge graveyard, we need to ensure that this data is actually indexed. Again there is some insights driven and drawn from this data. You have to process this data and confidential computing here to help. Now we have end to end protection of our customer's data when they bring the workloads and data to Cloud, thanks to confidential computing. >> Thank you for that. Okay, we're going to get into the architecture a bit but before we do Patricia, why do you think this topic of confidential computing is such an important technology? Can you explain, do you think it's transformative for customers and if so, why? >> Yeah, I would maybe like to use one thought, one way, one intuition behind why confidential matters. Because at the end of the day it reduces more and more the customers thrush boundaries and the attack surface, that's about reducing that periphery, the boundary, in which the customer needs to mind about trust and safety. And in a way is a natural progression that you're using encryption to secure and protect data in the same way that we are encrypting data in transit and at rest. Now we are also encrypting data while in use. And among other beneficial I would say one of the most transformative ones is that organizations will be able to collaborate with each other and retain the confidentiality of the data. And that is across industry. Even though it's highly focused on, I wouldn't say highly focused, but very beneficial for highly regulated industries. It applies to all of industries. And if you look at financing for example, where bankers are trying to detect fraud and specifically double finance where you are a customer is actually trying to get a finance on an asset, let's say a boat or a house and then it goes to another bank and gets another finance on that asset. Now bankers would be able to collaborate and detect fraud while preserving confidentiality and privacy of the of the data. >> Interesting, and I want to understand that a little bit more but I'm going to push you a little bit on this, Nelly, if I can, because there's a narrative out there that says confidential computing is a marketing ploy. I talked about this upfront, by Cloud providers that are just trying to placate people that are scared of the Cloud. And I'm presuming you don't agree with that but I'd like you to weigh in here. The argument is confidential computing is just memory encryption, it doesn't address many other problems, it is overhyped by Cloud providers. What do you say to that line of thinking? >> I absolutely disagree as you can imagine, it's a crazy statement. But the most importantly is we mixing multiple concepts I guess. And exactly as Patricia said, we need to look at the end-to-end story not again the mechanism of how confidential computing trying to again execute and protect customer's data, and why it's so critically important. Because what confidential computing was able to do it's in addition to isolate our tenants in multi-tenant environments the Cloud over. To offer additional stronger isolation, we called it cryptographic isolation. It's why customers will have more trust to customers and to other customers, the tenants that's running on the same host but also us, because they don't need to worry about against threats and more malicious attempts to penetrate the environment. So what confidential computing is helping us to offer our customers, stronger isolation between tenants in this multi-tenant environment but also incredibly important, stronger isolation of our customers. So tenants from us, we also writing code, we also software providers will also make mistakes or have some zero days sometimes again us introduced, sometimes introduced by our adversaries. But what I'm trying to say by creating this cryptographic layer of isolation between us and our tenants, and amongst those tenants, they're really providing meaningful security to our customers and eliminate some of the worries that they have running on multi-tenant spaces or even collaborating together this very sensitive data, knowing that this particular protection is available to them. >> Okay, thank you, appreciate that. And I, you know, I think malicious code is often a threat model missed in these narratives. You know, operator access, yeah, could maybe I trust my Clouds provider, but if I can fence off your access even better I'll sleep better at night. Separating a code from the data, everybody's arm Intel, AM, Invidia, others, they're all doing it. I wonder if Nell, if we could stay with you and bring up the slide on the architecture. What's architecturally different with confidential computing versus how operating systems and VMs have worked traditionally? We're showing a slide here with some VMs, maybe you could take us through that. >> Absolutely, and Dave, the whole idea for Google and industry way of dealing with confidential computing is to ensure as it's three main property is actually preserved. Customers don't need to change the code. They can operate in those VMs exactly as they would with normal non-confidential VMs. But to give them this opportunity of lift and shift or no changing their apps and performing and having very, very, very low latency and scale as any Cloud can, something that Google actually pioneered in confidential computing. I think we need to open and explain how this magic was actually done. And as I said, it's again the whole entire system have to change to be able to provide this magic. And I would start with we have this concept of root of trust and root of trust where we will ensure that this machine, the whole entire post has integrity guarantee, means nobody changing my code on the most low level of system. And we introduce this in 2017 code Titan. Those our specific ASIC specific, again inch by inch system on every single motherboard that we have, that ensures that your low level former, your actually system code, your kernel, the most powerful system, is actually proper configured and not changed, not tempered. We do it for everybody, confidential computing concluded. But for confidential computing what we have to change we bring in a MD again, future silicon vendors, and we have to trust their former, their way to deal with our confidential environments. And that's why we have obligation to validate integrity not only our software and our firmware but also firmware and software of our vendors, silicon vendors. So we actually, when we booting this machine as you can see, we validate that integrity of all of this system is in place. It means nobody touching, nobody changing, nobody modifying it. But then we have this concept of the secure processor. It's special Asics best, specific things that generate a key for every single VM that our customers will run or every single node in Kubernetes, or every single worker thread in our Spark capability. We offer all of that, and those keys are not available to us. It's the best keys ever in encryption space. Because when we are talking about encryption the first question that I'm receiving all the time, where's the key, who will have access to the key? Because if you have access to the key then it doesn't matter if you encrypt it enough. But the case in confidential computing quite so revolutionary technology, ask Cloud providers who don't have access to the keys. They're sitting in the hardware and they fed to memory controller. And it means when Hypervisors that also know about these wonderful things, saying I need to get access to the memories that this particular VM I'm trying to get access to. They do not encrypt the data, they don't have access to the key. Because those keys are random, ephemeral and VM, but the most importantly in hardware not exportable. And it means now you will be able to have this very interesting role that customers all Cloud providers, will not be able to get access to your memory. And what we do, again, as you can see our customers don't need to change their applications. Their VMs are running exactly as it should run. And what you're running in VM you actually see your memory in clear, it's not encrypted. But God forbid is trying somebody to do it outside of my confidential box. No, no, no, no, no, you will not be able to do it. Now you'll see cybernet. And it's exactly what combination of these multiple hardware pieces and software pieces have to do. So OS is also modified, and OS is modified such way to provide integrity. It means even OS that you're running in UVM bucks is not modifiable and you as customer can verify. But the most interesting thing I guess how to ensure the super performance of this environment because you can imagine, Dave, that's increasing it's additional performance, additional time, additional latency. So we're able to mitigate all of that by providing incredibly interesting capability in the OS itself. So our customers will get no changes needed, fantastic performance, and scales as they would expect from Cloud providers like Google. >> Okay, thank you. Excellent, appreciate that explanation. So you know again, the narrative on this is, well you know you've already given me guarantees as a Cloud provider that you don't have access to my data but this gives another level of assurance. Key management as they say is key. Now you're not, humans aren't managing the keys the machines are managing them. So Patricia, my question to you is in addition to, you know, let's go pre-confidential computing days what are the sort of new guarantees that these hardware-based technologies are going to provide to customers? >> So if I am a customer, I am saying I now have full guarantee of confidentiality and integrity of the data and of the code. So if you look at code and data confidentiality the customer cares then they want to know whether their systems are protected from outside or unauthorized access. And that we covered with Nelly that it is. Confidential computing actually ensures that the applications and data antennas remain secret, right? The code is actually looking at the data only the memory is decrypting the data with a key that is ephemeral, and per VM, and generated on demand. Then you have the second point where you have code and data integrity and now customers want to know whether their data was corrupted, tempered, with or impacted by outside actors. And what confidential computing insures is that application internals are not tampered with. So the application, the workload as we call it, that is processing the data it's also it has not been tempered and preserves integrity. I would also say that this is all verifiable. So you have attestation, and this attestation actually generates a log trail and the log trail guarantees that provides a proof that it was preserved. And I think that the offers also a guarantee of what we call ceiling, this idea that the secrets have been preserved and not tempered with. Confidentiality and integrity of code and data. >> Got it, okay, thank you. You know, Nelly, you mentioned, I think I heard you say that the applications, it's transparent,you don't have to change the application it just comes for free essentially. And I'm, we showed some various parts of the stack before. I'm curious as to what's affected but really more importantly what is specifically Google's value add? You know, how do partners, you know, participate in this? The ecosystem or maybe said another way how does Google ensure the compatibility of confidential computing with existing systems and applications? >> And a fantastic question by the way. And it's very difficult and definitely complicated world because to be able to provide these guarantees actually a lot of works was done by community. Google is very much operate and open. So again, our operating system we working in this operating system repository OS vendors to ensure that all capabilities that we need is part of their kernels, are part of their releases, and it's available for customers to understand and even explore if they have fun to explore a lot of code. We have also modified together with our silicon vendors, kernel, host kernel, to support this capability and it means working this community to ensure that all of those patches are there. We also worked with every single silicon vendor as you've seen, and that's what I probably feel that Google contributed quite a bit in this role. We moved our industry, our community, our vendors to understand the value of easy to use confidential computing or removing barriers. And now I don't know if you noticed Intel is pulling the lead and also announcing the trusted domain extension very similar architecture and no surprise, it's again a lot of work done with our partners to again, convince, work with them, and make this capability available. The same with ARM this year, actually last year, ARM unknowns are future design for confidential computing. It's called confidential computing architecture. And it's also influenced very heavily with similar ideas by Google and industry overall. So it's a lot of work in confidential computing consortiums that we are doing. For example, simply to mention to ensure interop, as you mentioned, between different confidential environments of Cloud providers. We want to ensure that they can attest to each other. Because when you're communicating with different environments, you need to trust them. And if it's running on different Cloud providers you need to ensure that you can trust your receiver when you are sharing your sensitive data workloads or secret with them. So we coming as a community and we have this at the station, the community based systems that we want to build and influence and work with ARM and every other Cloud providers to ensure that they can interrupt. And it means it doesn't matter where confidential workloads will be hosted but they can exchange the data in secure, verifiable, and controlled by customers way. And to do it, we need to continue what we are doing. Working open again and contribute with our ideas and ideas of our partners to this role to become what we see confidential computing has to become, it has to become utility. It doesn't need to be so special but it's what what we've wanted to become. >> Let's talk about, thank you for that explanation. Let talk about data sovereignty, because when you think about data sharing you think about data sharing across, you know, the ecosystem and different regions and then of course data sovereignty comes up. Typically public policy lags, you know, the technology industry and sometimes is problematic. I know, you know, there's a lot of discussions about exceptions, but Patricia, we have a graphic on data sovereignty. I'm interested in how confidential computing ensures that data sovereignty and privacy edicts are adhered to even if they're out of alignment maybe with the pace of technology. One of the frequent examples is when you you know, when you delete data, can you actually prove the data is deleted with a hundred percent certainty? You got to prove that and a lot of other issues. So looking at this slide, maybe you could take us through your thinking on data sovereignty. >> Perfect, so for us, data sovereignty is only one of the three pillars of digital sovereignty. And I don't want to give the impression that confidential computing addresses at all. That's why we want to step back and say, hey, digital sovereignty includes data sovereignty where we are giving you full control and ownership of the location, encryption, and access to your data. Operational sovereignty where the goal is to give our Google Cloud customers full visibility and control over the provider operations, right? So if there are any updates on hardware, software, stack, any operations, that is full transparency, full visibility. And then the third pillar is around software sovereignty where the customer wants to ensure that they can run their workloads without dependency on the provider's software. So they have sometimes is often referred as survivability that you can actually survive if you are untethered to the Cloud and that you can use open source. Now let's take a deep dive on data sovereignty, which by the way is one of my favorite topics. And we typically focus on saying, hey, we need to care about data residency. We care where the data resides because where the data is at rest or in processing it typically abides to the jurisdiction, the regulations of the jurisdiction where the data resides. And others say, hey, let's focus on data protection. We want to ensure the confidentiality and integrity and availability of the data which confidential computing is at the heart of that data protection. But it is yet another element that people typically don't talk about when talking about data sovereignty, which is the element of user control. And here Dave, is about what happens to the data when I give you access to my data. And this reminds me of security two decades ago, even a decade ago, where we started the security movement by putting firewall protections and login accesses. But once you were in, you were able to do everything you wanted with the data, an insider had access to all the infrastructure, the data, and the code. And that's similar because with data sovereignty we care about whether it resides, who is operating on the data. But the moment that the data is being processed, I need to trust that the processing of the data will abide by user control, by the policies that I put in place of how my data is going to be used. And if you look at a lot of the regulation today and a lot of the initiatives around the International Data Space Association, IDSA, and Gaia X, there is a movement of saying the two parties, the provider of the data and the receiver of the data going to agree on a contract that describes what my data can be used for. The challenge is to ensure that once the data crosses boundaries, that the data will be used for the purposes that it was intended and specified in the contract. And if you actually bring together, and this is the exciting part, confidential computing together with policy enforcement. Now the policy enforcement can guarantee that the data is only processed within the confines of a confidential computing environment. That the workload is cryptographically verified that there is the workload that was meant to process the data and that the data will be only used when abiding to the confidentiality and integrity, safety of the confidential computing environment. And that's why we believe confidential computing is one, necessary and essential technology that will allow us to ensure data sovereignty especially when it comes to user control. >> Thank you for that. I mean it was a deep dive, I mean brief, but really detailed, so I appreciate that, especially the verification of the enforcement. Last question, I met you two because as part of my year end prediction post you guys sent in some predictions, and I wasn't able to get to them in the predictions post. So I'm thrilled that you were able to make the time to come on the program. How widespread do you think the adoption of confidential computing will be in '23 and what's the maturity curve look like, you know, this decade in, in your opinion? Maybe each of you could give us a brief answer. >> So my prediction in five, seven years as I started, it'll become utility. It'll become TLS. As of, again, 10 years ago we couldn't believe that websites will have certificates and we will support encrypted traffic. Now we do, and it's become ubiquity. It's exactly where our confidential computing is heading and heading, I don't know if we are there yet yet. It'll take a few years of maturity for us, but we'll do that. >> Thank you, and Patricia, what's your prediction? >> I would double that and say, hey, in the future, in the very near future you will not be able to afford not having it. I believe as digital sovereignty becomes ever more top of mind with sovereign states and also for multinational organizations and for organizations that want to collaborate with each other, confidential computing will become the norm. It'll become the default, If I say mode of operation, I like to compare that, today is inconceivable if we talk to the young technologists. It's inconceivable to think that at some point in history and I happen to be alive that we had data at address that was not encrypted. Data in transit, that was not encrypted. And I think that we will be inconceivable at some point in the near future that to have unencrypted data while we use. >> You know, and plus, I think the beauty of the this industry is because there's so much competition this essentially comes for free. I want to thank you both for spending some time on Breaking Analysis. There's so much more we could cover. I hope you'll come back to share the progress that you're making in this area and we can double click on some of these topics. Really appreciate your time. >> Anytime. >> Thank you so much.

>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> Confidential computing is a technology that aims to enhance data privacy and security, by providing encrypted computation on sensitive data and isolating data, and apps that are fenced off enclave during processing. The concept of, I got to start over. I fucked that up, I'm sorry. That's not right, what I said was not right. On Dave in five, four, three. Confidential computing is a technology that aims to enhance data privacy and security by providing encrypted computation on sensitive data, isolating data from apps and a fenced off enclave during processing. The concept of confidential computing is gaining popularity, especially in the cloud computing space, where sensitive data is often stored and of course processed. However, there are some who view confidential computing as an unnecessary technology in a marketing ploy by cloud providers aimed at calming customers who are cloud phobic. Hello and welcome to this week's Wikibon Cube Insights powered by ETR. In this Breaking Analysis, we revisit the notion of confidential computing, and to do so, we'll invite two Google experts to the show. But before we get there, let's summarize briefly. There's not a ton of ETR data on the topic of confidential computing, I mean, it's a technology that's deeply embedded into silicon and computing architectures. But at the highest level, security remains the number one priority being addressed by IT decision makers in the coming year as shown here. And this data is pretty much across the board by industry, by region, by size of company. I mean we dug into it and the only slight deviation from the mean is in financial services. The second and third most cited priorities, cloud migration and analytics are noticeably closer to cybersecurity in financial services than in other sectors, likely because financial services has always been hyper security conscious, but security is still a clear number one priority in that sector. The idea behind confidential computing is to better address threat models for data in execution. Protecting data at rest and data in transit have long been a focus of security approaches, but more recently, silicon manufacturers have introduced architectures that separate data and applications from the host system, ARM, Intel, AMD, Nvidia and other suppliers are all on board, as are the big cloud players. Now, the argument against confidential computing is that it narrowly focuses on memory encryption and it doesn't solve the biggest problems in security. Multiple system images, updates, different services and the entire code flow aren't directly addressed by memory encryption. Rather to truly attack these problems, many believe that OSs need to be re-engineered with the attacker and hacker in mind. There are so many variables and at the end of the day, critics say the emphasis on confidential computing made by cloud providers is overstated and largely hype. This tweet from security researcher Rodrigo Bronco, sums up the sentiment of many skeptics. He says, "Confidential computing is mostly a marketing campaign from memory encryption. It's not driving the industry towards the hard open problems. It is selling an illusion." Okay. Nonetheless, encrypting data in use and fencing off key components of the system isn't a bad thing, especially if it comes with the package essentially for free. There has been a lack of standardization and interoperability between different confidential computing approaches. But the confidential computing consortium was established in 2019 ostensibly to accelerate the market and influence standards. Notably, AWS is not part of the consortium, likely because the politics of the consortium were probably a conundrum for AWS because the base technology defined by the consortium is seen as limiting by AWS. This is my guess, not AWS' words. But I think joining the consortium would validate a definition which AWS isn't aligned with. And two, it's got to lead with this Annapurna acquisition. It was way ahead with ARM integration, and so it's probably doesn't feel the need to validate its competitors. Anyway, one of the premier members of the confidential computing consortium is Google, along with many high profile names, including Aem, Intel, Meta, Red Hat, Microsoft, and others. And we're pleased to welcome two experts on confidential computing from Google to unpack the topic. Nelly Porter is Head of Product for GCP Confidential Computing and Encryption and Dr. Patricia Florissi is the Technical Director for the Office of the CTO at Google Cloud. Welcome Nelly and Patricia, great to have you. >> Great to be here. >> Thank you so much for having us. >> You're very welcome. Nelly, why don't you start and then Patricia, you can weigh in. Just tell the audience a little bit about each of your roles at Google Cloud. >> So I'll start, I'm owning a lot of interesting activities in Google and again, security or infrastructure securities that I usually own. And we are talking about encryption, end-to-end encryption, and confidential computing is a part of portfolio. Additional areas that I contribute to get with my team to Google and our customers is secure software supply chain because you need to trust your software. Is it operate in your confidential environment to have end-to-end security, about if you believe that your software and your environment doing what you expect, it's my role. >> Got it. Okay, Patricia? >> Well, I am a Technical Director in the Office of the CTO, OCTO for short in Google Cloud. And we are a global team, we include former CTOs like myself and senior technologies from large corporations, institutions and a lot of success for startups as well. And we have two main goals, first, we walk side by side with some of our largest, more strategic or most strategical customers and we help them solve complex engineering technical problems. And second, we advice Google and Google Cloud Engineering, product management on emerging trends and technologies to guide the trajectory of our business. We are unique group, I think, because we have created this collaborative culture with our customers. And within OCTO I spend a lot of time collaborating with customers in the industry at large on technologies that can address privacy, security, and sovereignty of data in general. >> Excellent. Thank you for that both of you. Let's get into it. So Nelly, what is confidential computing from Google's perspective? How do you define it? >> Confidential computing is a tool and one of the tools in our toolbox. And confidential computing is a way how we would help our customers to complete this very interesting end-to-end lifecycle of the data. And when customers bring in the data to cloud and want to protect it as they ingest it to the cloud, they protect it at rest when they store data in the cloud. But what was missing for many, many years is ability for us to continue protecting data and workloads of our customers when they run them. And again, because data is not brought to cloud to have huge graveyard, we need to ensure that this data is actually indexed. Again, there is some insights driven and drawn from this data. You have to process this data and confidential computing here to help. Now we have end-to-end protection of our customer's data when they bring the workloads and data to cloud thanks to confidential computing. >> Thank you for that. Okay, we're going to get into the architecture a bit, but before we do Patricia, why do you think this topic of confidential computing is such an important technology? Can you explain? Do you think it's transformative for customers and if so, why? >> Yeah, I would maybe like to use one thought, one way, one intuition behind why confidential computing matters because at the end of the day, it reduces more and more the customer's thrush boundaries and the attack surface. That's about reducing that periphery, the boundary in which the customer needs to mind about trust and safety. And in a way is a natural progression that you're using encryption to secure and protect data in the same way that we are encrypting data in transit and at rest. Now, we are also encrypting data while in the use. And among other beneficials, I would say one of the most transformative ones is that organizations will be able to collaborate with each other and retain the confidentiality of the data. And that is across industry, even though it's highly focused on, I wouldn't say highly focused but very beneficial for highly regulated industries, it applies to all of industries. And if you look at financing for example, where bankers are trying to detect fraud and specifically double finance where a customer is actually trying to get a finance on an asset, let's say a boat or a house, and then it goes to another bank and gets another finance on that asset. Now bankers would be able to collaborate and detect fraud while preserving confidentiality and privacy of the data. >> Interesting and I want to understand that a little bit more but I got to push you a little bit on this, Nellie if I can, because there's a narrative out there that says confidential computing is a marketing ploy I talked about this up front, by cloud providers that are just trying to placate people that are scared of the cloud. And I'm presuming you don't agree with that, but I'd like you to weigh in here. The argument is confidential computing is just memory encryption, it doesn't address many other problems. It is over hyped by cloud providers. What do you say to that line of thinking? >> I absolutely disagree as you can imagine Dave, with this statement. But the most importantly is we mixing a multiple concepts I guess, and exactly as Patricia said, we need to look at the end-to-end story, not again, is a mechanism. How confidential computing trying to execute and protect customer's data and why it's so critically important. Because what confidential computing was able to do, it's in addition to isolate our tenants in multi-tenant environments the cloud offering to offer additional stronger isolation, they called it cryptographic isolation. It's why customers will have more trust to customers and to other customers, the tenants running on the same host but also us because they don't need to worry about against rats and more malicious attempts to penetrate the environment. So what confidential computing is helping us to offer our customers stronger isolation between tenants in this multi-tenant environment, but also incredibly important, stronger isolation of our customers to tenants from us. We also writing code, we also software providers, we also make mistakes or have some zero days. Sometimes again us introduce, sometimes introduced by our adversaries. But what I'm trying to say by creating this cryptographic layer of isolation between us and our tenants and among those tenants, we really providing meaningful security to our customers and eliminate some of the worries that they have running on multi-tenant spaces or even collaborating together with very sensitive data knowing that this particular protection is available to them. >> Okay, thank you. Appreciate that. And I think malicious code is often a threat model missed in these narratives. You know, operator access. Yeah, maybe I trust my cloud's provider, but if I can fence off your access even better, I'll sleep better at night separating a code from the data. Everybody's ARM, Intel, AMD, Nvidia and others, they're all doing it. I wonder if Nell, if we could stay with you and bring up the slide on the architecture. What's architecturally different with confidential computing versus how operating systems and VMs have worked traditionally? We're showing a slide here with some VMs, maybe you could take us through that. >> Absolutely, and Dave, the whole idea for Google and now industry way of dealing with confidential computing is to ensure that three main property is actually preserved. Customers don't need to change the code. They can operate in those VMs exactly as they would with normal non-confidential VMs. But to give them this opportunity of lift and shift though, no changing the apps and performing and having very, very, very low latency and scale as any cloud can, some things that Google actually pioneer in confidential computing. I think we need to open and explain how this magic was actually done, and as I said, it's again the whole entire system have to change to be able to provide this magic. And I would start with we have this concept of root of trust and root of trust where we will ensure that this machine within the whole entire host has integrity guarantee, means nobody changing my code on the most low level of system, and we introduce this in 2017 called Titan. So our specific ASIC, specific inch by inch system on every single motherboard that we have that ensures that your low level former, your actually system code, your kernel, the most powerful system is actually proper configured and not changed, not tempered. We do it for everybody, confidential computing included, but for confidential computing is what we have to change, we bring in AMD or future silicon vendors and we have to trust their former, their way to deal with our confidential environments. And that's why we have obligation to validate intelligent not only our software and our former but also former and software of our vendors, silicon vendors. So we actually, when we booting this machine as you can see, we validate that integrity of all of this system is in place. It means nobody touching, nobody changing, nobody modifying it. But then we have this concept of AMD Secure Processor, it's special ASIC best specific things that generate a key for every single VM that our customers will run or every single node in Kubernetes or every single worker thread in our Hadoop spark capability. We offer all of that and those keys are not available to us. It's the best case ever in encryption space because when we are talking about encryption, the first question that I'm receiving all the time, "Where's the key? Who will have access to the key?" because if you have access to the key then it doesn't matter if you encrypted or not. So, but the case in confidential computing why it's so revolutionary technology, us cloud providers who don't have access to the keys, they're sitting in the hardware and they fed to memory controller. And it means when hypervisors that also know about this wonderful things saying I need to get access to the memories, that this particular VM I'm trying to get access to. They do not decrypt the data, they don't have access to the key because those keys are random, ephemeral and per VM, but most importantly in hardware not exportable. And it means now you will be able to have this very interesting world that customers or cloud providers will not be able to get access to your memory. And what we do, again as you can see, our customers don't need to change their applications. Their VMs are running exactly as it should run. And what you've running in VM, you actually see your memory clear, it's not encrypted. But God forbid is trying somebody to do it outside of my confidential box, no, no, no, no, no, you will now be able to do it. Now, you'll see cyber test and it's exactly what combination of these multiple hardware pieces and software pieces have to do. So OS is also modified and OS is modified such way to provide integrity. It means even OS that you're running in your VM box is not modifiable and you as customer can verify. But the most interesting thing I guess how to ensure the super performance of this environment because you can imagine Dave, that's increasing and it's additional performance, additional time, additional latency. So we're able to mitigate all of that by providing incredibly interesting capability in the OS itself. So our customers will get no changes needed, fantastic performance and scales as they would expect from cloud providers like Google. >> Okay, thank you. Excellent, appreciate that explanation. So you know again, the narrative on this is, well, you've already given me guarantees as a cloud provider that you don't have access to my data, but this gives another level of assurance, key management as they say is key. Now humans aren't managing the keys, the machines are managing them. So Patricia, my question to you is in addition to, let's go pre-confidential computing days, what are the sort of new guarantees that these hardware based technologies are going to provide to customers? >> So if I am a customer, I am saying I now have full guarantee of confidentiality and integrity of the data and of the code. So if you look at code and data confidentiality, the customer cares and they want to know whether their systems are protected from outside or unauthorized access, and that we covered with Nelly that it is. Confidential computing actually ensures that the applications and data antennas remain secret. The code is actually looking at the data, only the memory is decrypting the data with a key that is ephemeral, and per VM, and generated on demand. Then you have the second point where you have code and data integrity and now customers want to know whether their data was corrupted, tempered with or impacted by outside actors. And what confidential computing ensures is that application internals are not tempered with. So the application, the workload as we call it, that is processing the data is also has not been tempered and preserves integrity. I would also say that this is all verifiable, so you have attestation and this attestation actually generates a log trail and the log trail guarantees that provides a proof that it was preserved. And I think that the offers also a guarantee of what we call sealing, this idea that the secrets have been preserved and not tempered with, confidentiality and integrity of code and data. >> Got it. Okay, thank you. Nelly, you mentioned, I think I heard you say that the applications is transparent, you don't have to change the application, it just comes for free essentially. And we showed some various parts of the stack before, I'm curious as to what's affected, but really more importantly, what is specifically Google's value add? How do partners participate in this, the ecosystem or maybe said another way, how does Google ensure the compatibility of confidential computing with existing systems and applications? >> And a fantastic question by the way, and it's very difficult and definitely complicated world because to be able to provide these guarantees, actually a lot of work was done by community. Google is very much operate and open. So again our operating system, we working this operating system repository OS is OS vendors to ensure that all capabilities that we need is part of the kernels are part of the releases and it's available for customers to understand and even explore if they have fun to explore a lot of code. We have also modified together with our silicon vendors kernel, host kernel to support this capability and it means working this community to ensure that all of those pages are there. We also worked with every single silicon vendor as you've seen, and it's what I probably feel that Google contributed quite a bit in this world. We moved our industry, our community, our vendors to understand the value of easy to use confidential computing or removing barriers. And now I don't know if you noticed Intel is following the lead and also announcing a trusted domain extension, very similar architecture and no surprise, it's a lot of work done with our partners to convince work with them and make this capability available. The same with ARM this year, actually last year, ARM announced future design for confidential computing, it's called confidential computing architecture. And it's also influenced very heavily with similar ideas by Google and industry overall. So it's a lot of work in confidential computing consortiums that we are doing, for example, simply to mention, to ensure interop as you mentioned, between different confidential environments of cloud providers. They want to ensure that they can attest to each other because when you're communicating with different environments, you need to trust them. And if it's running on different cloud providers, you need to ensure that you can trust your receiver when you sharing your sensitive data workloads or secret with them. So we coming as a community and we have this at Station Sig, the community-based systems that we want to build, and influence, and work with ARM and every other cloud providers to ensure that they can interop. And it means it doesn't matter where confidential workloads will be hosted, but they can exchange the data in secure, verifiable and controlled by customers really. And to do it, we need to continue what we are doing, working open and contribute with our ideas and ideas of our partners to this role to become what we see confidential computing has to become, it has to become utility. It doesn't need to be so special, but it's what what we've wanted to become. >> Let's talk about, thank you for that explanation. Let's talk about data sovereignty because when you think about data sharing, you think about data sharing across the ecosystem in different regions and then of course data sovereignty comes up, typically public policy, lags, the technology industry and sometimes it's problematic. I know there's a lot of discussions about exceptions but Patricia, we have a graphic on data sovereignty. I'm interested in how confidential computing ensures that data sovereignty and privacy edicts are adhered to, even if they're out of alignment maybe with the pace of technology. One of the frequent examples is when you delete data, can you actually prove the data is deleted with a hundred percent certainty, you got to prove that and a lot of other issues. So looking at this slide, maybe you could take us through your thinking on data sovereignty. >> Perfect. So for us, data sovereignty is only one of the three pillars of digital sovereignty. And I don't want to give the impression that confidential computing addresses it at all, that's why we want to step back and say, hey, digital sovereignty includes data sovereignty where we are giving you full control and ownership of the location, encryption and access to your data. Operational sovereignty where the goal is to give our Google Cloud customers full visibility and control over the provider operations, right? So if there are any updates on hardware, software stack, any operations, there is full transparency, full visibility. And then the third pillar is around software sovereignty, where the customer wants to ensure that they can run their workloads without dependency on the provider's software. So they have sometimes is often referred as survivability that you can actually survive if you are untethered to the cloud and that you can use open source. Now, let's take a deep dive on data sovereignty, which by the way is one of my favorite topics. And we typically focus on saying, hey, we need to care about data residency. We care where the data resides because where the data is at rest or in processing need to typically abides to the jurisdiction, the regulations of the jurisdiction where the data resides. And others say, hey, let's focus on data protection, we want to ensure the confidentiality, and integrity, and availability of the data, which confidential computing is at the heart of that data protection. But it is yet another element that people typically don't talk about when talking about data sovereignty, which is the element of user control. And here Dave, is about what happens to the data when I give you access to my data, and this reminds me of security two decades ago, even a decade ago, where we started the security movement by putting firewall protections and logging accesses. But once you were in, you were able to do everything you wanted with the data. An insider had access to all the infrastructure, the data, and the code. And that's similar because with data sovereignty, we care about whether it resides, who is operating on the data, but the moment that the data is being processed, I need to trust that the processing of the data we abide by user's control, by the policies that I put in place of how my data is going to be used. And if you look at a lot of the regulation today and a lot of the initiatives around the International Data Space Association, IDSA and Gaia-X, there is a movement of saying the two parties, the provider of the data and the receiver of the data going to agree on a contract that describes what my data can be used for. The challenge is to ensure that once the data crosses boundaries, that the data will be used for the purposes that it was intended and specified in the contract. And if you actually bring together, and this is the exciting part, confidential computing together with policy enforcement. Now, the policy enforcement can guarantee that the data is only processed within the confines of a confidential computing environment, that the workload is in cryptographically verified that there is the workload that was meant to process the data and that the data will be only used when abiding to the confidentiality and integrity safety of the confidential computing environment. And that's why we believe confidential computing is one necessary and essential technology that will allow us to ensure data sovereignty, especially when it comes to user's control. >> Thank you for that. I mean it was a deep dive, I mean brief, but really detailed. So I appreciate that, especially the verification of the enforcement. Last question, I met you two because as part of my year-end prediction post, you guys sent in some predictions and I wasn't able to get to them in the predictions post, so I'm thrilled that you were able to make the time to come on the program. How widespread do you think the adoption of confidential computing will be in '23 and what's the maturity curve look like this decade in your opinion? Maybe each of you could give us a brief answer. >> So my prediction in five, seven years as I started, it will become utility, it will become TLS. As of freakin' 10 years ago, we couldn't believe that websites will have certificates and we will support encrypted traffic. Now we do, and it's become ubiquity. It's exactly where our confidential computing is heeding and heading, I don't know we deserve yet. It'll take a few years of maturity for us, but we'll do that. >> Thank you. And Patricia, what's your prediction? >> I would double that and say, hey, in the very near future, you will not be able to afford not having it. I believe as digital sovereignty becomes ever more top of mind with sovereign states and also for multinational organizations, and for organizations that want to collaborate with each other, confidential computing will become the norm, it will become the default, if I say mode of operation. I like to compare that today is inconceivable if we talk to the young technologists, it's inconceivable to think that at some point in history and I happen to be alive, that we had data at rest that was non-encrypted, data in transit that was not encrypted. And I think that we'll be inconceivable at some point in the near future that to have unencrypted data while we use. >> You know, and plus I think the beauty of the this industry is because there's so much competition, this essentially comes for free. I want to thank you both for spending some time on Breaking Analysis, there's so much more we could cover. I hope you'll come back to share the progress that you're making in this area and we can double click on some of these topics. Really appreciate your time. >> Anytime. >> Thank you so much, yeah. >> In summary, while confidential computing is being touted by the cloud players as a promising technology for enhancing data privacy and security, there are also those as we said, who remain skeptical. The truth probably lies somewhere in between and it will depend on the specific implementation and the use case as to how effective confidential computing will be. Look as with any new tech, it's important to carefully evaluate the potential benefits, the drawbacks, and make informed decisions based on the specific requirements in the situation and the constraints of each individual customer. But the bottom line is silicon manufacturers are working with cloud providers and other system companies to include confidential computing into their architectures. Competition in our view will moderate price hikes and at the end of the day, this is under-the-covers technology that essentially will come for free, so we'll take it. I want to thank our guests today, Nelly and Patricia from Google. And thanks to Alex Myerson who's on production and manages the podcast. Ken Schiffman as well out of our Boston studio. Kristin Martin and Cheryl Knight help get the word out on social media and in our newsletters, and Rob Hoof is our editor-in-chief over at siliconangle.com, does some great editing for us. Thank you all. Remember all these episodes are available as podcasts. Wherever you listen, just search Breaking Analysis podcast. I publish each week on wikibon.com and siliconangle.com where you can get all the news. If you want to get in touch, you can email me at david.vellante@siliconangle.com or DM me at D Vellante, and you can also comment on my LinkedIn post. Definitely you want to check out etr.ai for the best survey data in the enterprise tech business. I know we didn't hit on a lot today, but there's some amazing data and it's always being updated, so check that out. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching and we'll see you next time on Breaking Analysis. (subtle music)

>>Good afternoon, I'm wanting or evening depending >>On where you are and welcome to this breakout session around insurance, improve underwriting with better insights. >>So first and >>Foremost, let's summarize very quickly, um, who we're with and what we're talking about today. My name is Mooney castling, and I'm the managing director at Cloudera for the insurance vertical. And we have a sizeable presence in insurance. We have been working with insurance companies for a long time now, over 10 years, which in terms of insurances, maybe not that long, but for technology, it really is. And we're working with, as you can see some of the largest companies in the world and in the continents of the world. However, we also do a significant amount of work with smaller insurance companies, especially around specialty exposures and the regionals, the mutuals in property, casualty, general insurance, life, annuity, and health. So we have a vast experience of working with insurers. And, um, we'd like to talk a little bit today about what we're seeing recently in the underwriting space and what we can do to support the insurance industry >>In there. So >>Recently what we have been seeing, and it's actually accelerated as a result of their recent pandemic that we all have been going through. We see that insurers are putting even more emphasis on accounting for every individual customer's risks, lotta via commercial, a client or a personal person, personal insurance risk in a dynamic and a bespoke way. And what I mean with that is in a dynamic way, it means that risks and risk assessments change very regularly, right? Companies go into different business situations. People behave differently. Risks are changing all the time and they're changing per person. They're not changing the narrow generically my risk at a certain point of time in travel, for example, it might be very different than any of your risks, right? So what technology has started to enable is underwrite and assess those risks at those very specific individual levels. And you can see that insurers are investing in depth capability. The value of, um, artificial intelligence and underwriting is growing dramatically. As you see from some of those quotes here and also risks that were historically very difficult to assess such as networks, uh, vendor is global supply chains, um, works workers' compensation that has a lot of moving parts to it all the time and anything that deals with rapidly changing risks, exposures and people, and businesses have been supported more and more by technology such as ours to help account for that. >>And this is a bit a difficult slide. So bear with me for a second here. What this slide shows specifically for underwriting is how data-driven insights help manage underwriting. And what you see on the left side of this slide is the progress insurers make in analytical capabilities. And quite often the first steps are around reporting and that tends to be run from a data warehouse, operational data store, Starsky, Matt, um, data, uh, models. And then, and reporting really is, uh, quite often as a BI function, of course, a business intelligence function. And it really, you know, at a regular basis informs the company of what has been taken place now in the second phase, the middle dark, the middle color blue. The next step that is shore stage is to get into descriptive analytics. And what descriptive analytics really do is they try to describe what we're learning in reporting. >>So we're seeing certain events and sorts and findings and sorts of numbers and certain trends happening in reporting. And in the descriptive phase, we describe what this means and you know why this is happening. And then ultimately, and this is the holy grill, the end goal we like to get through predictive analytics. So we like to try to predict what is going to happen, uh, which risk is a good one to underwrite, you know, Watts next policy, a customer might need or wants water claims as we discuss it. And not a session today, uh, might become fatherless or a which one we can move straight through because they're not supposed to be any issues with it, both on the underwriting and the claims side. So that's where every insurer is shooting for right now. But most of them are not there yet. Totally. Right. So on the right side of this slide specifically for underwriting, we would, we like to show what types of data generally are being used in use cases around underwriting, in the different faces of maturity and analytics that I just described. >>So you will see that on the reporting side, in the beginning, we start with braids, information, quotes, information, submission information, bounding information. Um, then if you go to the descriptive phase, we start to add risk engineering information, risk reports, um, schedules of assets on the commercial side, because some are profiles, uh, as the descriptions move into some sort of an unstructured data environments, um, notes, diaries, claims notes, underwriting notes, risk engineering notes, transcripts of customer service calls, and then totally to the outer side of this baseball field looking slide, right? You will see the relatively new data sources that can add tremendous value. Um, but I'm not Whitely integrated yet. So I will walk through some use cases around specifically. So think about sensors, wearables, you know, sense of some people's bodies, sensors, moving assets for transportation, drone images for underwriting. It's not necessary anymore to send, uh, an inspection person and inspector or a risk risk inspector or engineer to every building. You know, insurers now fly drones over it, to look at the roofs, et cetera, photos. You know, we see it a lot in claims first notice of loss, but we also see it for underwriting purposes that policies all done out at pretty much say sent me pictures of your five most valuable assets in your home and we'll price your home and all its contents for you. So we start seeing more and more movements towards those, as I mentioned earlier, dynamic and bespoke types of underwriting. >>So this is how Cloudera supports those initiatives. So on the left side, you see data coming into your insurance company. There are all sorts of different states, Dara. Some of them aren't managed and controlled by you. Some audits you get from third parties and we'll talk about Della medics in a little bit. It's one of the use cases, the move into the data life cycle, the data journey. So the data is coming into your organization. You collected, you store it, you make it ready for utilization. You plop it, eat it in an operational environment for processing what in an analytical environment for analysis. And then you close on the loop and adjusted from the beginning if necessary, no specifically for insurance, which is if not the most regulated industry in the world it's coming awfully close. And it will come in as a, as a very admirable second or third. >>Um, it's critically important that that data is controlled and managed in the correct way on all the different regulations that, that we are subject to. So we do that in the cloud era share data experiment experience, which is where we make sure that the data is accessed by the right people. And that we always can track who did watch to any point in time to that data. Um, and that's all part of the Cloudera data platform. Now that whole environment that we run on premise as well as in the cloud or in multiple clouds or in hybrid, most insurers run hybrid models, which are part of that data on premise and part of the data and use cases and workloads in the cloud. We support enterprise use cases around on the writing in risk selection, individualized pricing, digital submissions, quote processing, the whole quote, quote bound process, digitally fraud and compliance evaluations and network analysis around, um, service providers. So I want to walk you through some of the use cases that we've seen in action recently that showcases how this >>Work in real life. First one >>Is to seize that group plus Cloudera, um, uh, full disclosure is obviously for the people that know a Dutch health insurer. I did not pick the one because I happen to be Dutch is just happens to be a fantastic use case and what they were struggling with as many, many insurance companies is that they had a legacy infrastructure that made it very difficult to combine data sets and get a full view of the customer and its needs. Um, as any ensure customer demands and needs are rapidly changing competition is changing. So C-SAT decided that they needed to do something about it. And they built a data platform on Cloudera that helps them do a couple of things. It helps them support customers better or proactively. So they got really good in pinging customers on what potential steps they need to take to improve on their health in a preventative way. >>But also they sped up rapidly their, uh, approvals of medical procedures, et cetera. And so that was the original intent, right? It's like serve the customers better or retain the customers, make sure what they have the right access to the right services when they need us in a proactive way. As a side effect of this, um, data platform. They also got much better in, um, preventing and predicting fraud and abuse, which is, um, the topic of the other session we're running today. So it really was a good success and they're very happy with it. And they're actually starting to see a significant uptick in their customer service, KPIs >>And results. >>The other one that I wanted to quickly mention is Octo as most of you know, Optune is a very, very large telemedics provider, telematics data provider globally speaking with Cloudera for quite some time, this one I want to showcase because it showcases what we can do with data in mass amounts. So for Octo, we, um, analyze on Cloudera 5 million connected cars, ongoing with 11 billion data points and really want to doing as the creating the algorithms and the models and insurers use to, um, to, um, run, um, tell them insurance telematics programs, right to pay as you drive B when you drive the, how you drive. And this whole telemedics part of insurance is actually growing very fast too in, in, still in solidified proof of concept mini projects, kind of initiatives. But, um, what we're succeeding is that companies are starting to offer more and more services around it. >>So they become preventative and predictive too. So now you got to the program staff being me as a dry for seeing Monique you're hopping in the car for two hours. Now, maybe it's time to take a break. Um, we see that there's a Starbucks coming up on the right or any coffee shop. That's part of a bigger chain. Uh, we know because you have that app on your phone, that you are a Starbucks user. So if you stop there, we'll give you a 50 discount on your regular coffee. So we start seeing these types of programs coming through to, again, keep people safe and keep cars safe, but primarily of course the people in it, and those are the types of use cases that we start seeing in that telematic space. >>This looks more complicated than it is. So bear with me for a second. This is a commercial example because we see a data work. A lot of data were going on in commercial insurance. It's not Leah personal insurance thing. Commercial is near and dear to my heart. It's where I started. I actually, for a long time, worked in global energy insurance. So what this one wheelie explains is how we can use sensors on people's outfits and people's clothes to manage risks and underwrite risks better. So there are programs now for manufacturing companies and for oil and gas, where the people that work in those places are having sensors as part of their work outfits. And it does a couple of things. It helps in workers' comp underwriting and claims because you can actually see where people are moving, what they are doing, how long they're working. >>Some of them even tracks some very basic health-related information like blood pressure and heartbeat and stuff like that, temperature. Um, so those are all good things. The other thing that had to us, it helps, um, it helps collect data on the specific risks and exposures. Again, we're getting more and more to individual underwriting or individual risk underwriting, who insurance companies that, that ensure these, these, um, commercial commercial enterprises. So they started giving discounts if the workers were sensors and ultimately if there is an unfortunate event and it like a big accident or big loss, it helps, uh, first responders very quickly identify where those workers are and, and, and if, and how they're moving, which is all very important to figure out who to help first in case something bad happens. Right? So these are the type of data that quite often got implements in one specific use case, and then get broadly move to other use cases or deployed into other use cases to help price risks better, better, and keep, you know, risks, better control, manage, and provide preventative care. Right? >>So these were some of the use cases that we run in the underwriting space that are very excited to talk about. So as a next step, what we would like you to do is considered opportunities in your own companies to advance whisk assessment specific to your individual customer's need. And again, customers can be people they can be enterprises to can be other, any, any insurable entity, right? The police physical dera.com solutions insurance, where you will find all our documentation assets and thought leadership around the topic. And if you ever want to chat about this, you know, please give me a call or schedule a meeting with us. I get very passionate about this topic. I'll gladly talk to you forever. If you happen to be based in the us and you ever need somebody to filibuster on insurance, please give me a call. I'll easily fit 24 hours on this one. Um, so please schedule a call with me. I promise to keep it short. So thank you very much for joining this session. And as the last thing I would like to remind all of you read our blogs, read our tweets. We'd our thought leadership around insurance. And as we all know, insurance is sexy.

>>Good morning or good afternoon or good evening, depending on where you are and welcome to this session, reduce claims, fraud, we're data, very excited to have you all here. My name is Winnie castling and I'm Cloudera as managing director for the insurance vertical. First and foremost, we want to let you know that we know insurance. We have done it for a long time. Collectively, personally, I've done it for over 30 years. And, you know, as a proof of that, we want to let you know that we insure, we insure as well as we do data management work for the top global companies in the world, in north America, over property casualty, general insurance health, and, um, life and annuities. But besides that, we also take care of the data needs for some smaller insurance companies and specialty companies. So if you're not one of the huge Glomar conglomerates in the world, you are still perfectly fine with us. >>So >>Why are we having this topic today? Really digital claims and digital claims management is accelerating. And that's based on a couple of things. First and foremost, customers are asking for it. Customers are used to doing their work more digitally over the last descending year or two. And secondly, with the last year or almost two, by now with the changes that we made in our work processes and in society at large around cuvettes, uh, both regulators, as well as companies have enabled digital processing and the digital journey to a degree that they've never done before. Now that had some really good impacts for claims handling. It did meant that customers were more satisfied. They felt they have more control over their processes in the cloud and the claims experience. It also reduced in a lot of cases, both in commercial lines, as well as in personal lines, the, um, the, the time periods that it took to settle on a claim. However, um, the more digital you go, it, it opened up more access points for fraud, illicit activities. So unfortunately we saw indicators of fraud and fraud attempts, you know, creeping up over the last time period. So we thought it was a good moment to look at, you know, some use cases and some approaches insurers can take to manage that even better than they already >>Are. >>And this is how we plan to do that. And this is how we see this in action. On the left side, you see progress of data analytics and data utilization, um, around, in this case, we're talking about claims fraud, but it's a generic picture. And really what it means is most companies that start with data affords pretty much start around data warehousing and we eliminate analytics and all around BI and reporting, which pretty much is understanding what we know, right? The data that we already have utilizing data to understand better what we know already. Now, when we move to the middle blue collar, we get into different types of analytics. We get into exploratory data science, we get to predictions and we start getting in the space of describing what we can learn from what we know, but also start moving slowly into predicting. So first of all, learn and gather insights of what we already know, and then start augmenting with that with other data sets and other findings, so that we can start predicting for the future, what might happen. >>And that's the point where we get to AI, artificial intelligence and machine learning, which will help us predict which of our situations and claims are most likely to have a potential fraud or abuse scenario attached to it. So that's the path that insurers and other companies take in their data management and analytics environments. Now, if you look at the right side of this light, you see data complexity per use cases in this case in fraud. So the bubbles represent the types of data that are being used, or the specific faces that we discussed on the left side. So for reporting, we used a TPA data, policy verification, um, claims file staff data, that it tends to be heavily structured and already within the company itself. And when you go to the middle to the more descriptive basis, you start getting into unstructured data, you see a lot of instructor texts there, and we do a use case around that later. >>And this really enables us to better understand what the scenarios are that we're looking at and where the risks are around. In our example today, fraud, abuse and issues of resources. And then the more you go to the upper right corner, you see the outside of the baseball field, people refer to it, you see new unstructured data sources that are being used. You tend to see the more complex use cases. And we're looking at picture analysis, we're looking at voice analysis there. We're looking at geolocation. That's quite often the first one we look at. So this slide actually shows you the progress and the path in complexity and in utilization of data and analytical tool sets to manage data fraud, fraud, use cases, optimally. >>Now how we do that and how we look at at a Cloudera is actually not as complicated as, as this slight might want to, um, to, to give you an impression. So let's start at the left side at the left side, you see the enterprise data, which is data that you as an organization have, or that you have access to. It doesn't have to be internal data, but quite often it is now that data goes into a data journey, right? It gets collected first. It gets manipulated and engineered so that people can do something with it. It gets stored something, you know, people need to have access to it. And then they get into analytical capabilities who are inside gathering and utilization. Now, especially for insurance companies that all needs to be underpinned by a very, very strong security and governance, uh, environment. Because if not the most regulated industry in the world, insurance is awfully close. >>And if it's not the most regulated one, it's a close second. So it's critically important that insurers know, um, where the data is, who has access to it for Rodriguez, uh, what is being used for so terms like lineage, transparency are crucial, crucially important for insurance. And we manage that in the shared data experience. So it goes over the whole Cloudera platform and every application or tool or experience you use would include Dao. And on the right side, you see the use cases that tend to be deployed around claims and claims fraud, claims, fraud management. So over the last year or so, we've seen a lot of use cases around upcoding people get one treatment or one fix on a car, but it gets coded as a more expensive one. That's a fraud scenario, right? We see also the more classical fraud things and we see anti money laundering. So those are the types of use cases on the right side that we are supporting, um, on the platform, uh, around, um, claims fraud. >>And this is an example of how that actually looks like now, this is a one that it's actually a live one of, uh, a company that had, um, claims that dealt with health situations and being killers. So that obviously is relevant for health insurers, but you also see it in, um, in auto claims and counterclaims, right, you know, accidents. There are a lot of different claims scenarios that have health risks associated with it. And what we did in this one is we joined tables in a complex schema. So we have to look at the claimant, the physician, the hospital, all the providers that are involved procedures that are being deployed. Medically medicines has been utilized to uncover the full picture. Now that is a hard effort in itself, just for one claim and one scenario. But if you want to see if people are abusing, for example, painkillers in this scenario, you need to do that over every instant that is member. >>This claimant has, you know, with different doctors, with different hospitals, with different pharmacies or whatever that classically it's a very complicated and complex, um, the and costly data operation. So nowadays that tends to be done by graph databases, right? So you put fraud rings within a graph database and walk the graph. And if you look at it here in batch, you can see that in this case, that is a member that was shopping around for being killers and went through different systems and different providers to get, um, multiple of the same big LR stat. You know, obviously we don't know what he or she did with it, but that's not the intent of the system. And that was actually a fraud and abuse case. >>So I want to share some customer success stories and recent, uh, AML and fraud use cases. And we have a couple of them and I'm not going to go in an awful lot of detail, um, about them because we have some time to spend on one of them immediately after this. But one of them for example, is voice analytics, which is a really interesting one. And on the baseball slide that I showed you earlier, that would be a right upper corner one. And what happened there is that an insurance company utilized the, uh, the voice records they got from the customer service people to try to predict which one were potentially fraud list. And they did it in two ways. They look at actually the contents of what was being said. So they looked at certain words that were being used certain trigger words, but they also were looking at tone of voice pitch of voice, uh, speed of talking. >>So they try to see trends there and hear trends that would, um, that would bring them for a potential bad situation. Now good and bad news of this proof of concept was it's. We learned that it's very difficult just because every human is different to get an indicator for bad behavior out of the pitch or the tone or the voice, you know, or those types of nonverbal communication in voice. But we did learn that it was easier to, to predict if a specific conversation needed to be transferred to somebody else based on emotion. You know, obviously as we all understand life and health situations tend to come with emotions, or so people either got very sad or they got very angry or so the proof of concept didn't really get us to a firm understanding of potential driverless situation, but it did get us to a much better understanding of workflow around, um, claims escalation, um, in customer service to route people, to the right person, depending on what they need. >>And that specific time, another really interesting one was around social media, geo open source, all sorts of data that we put together. And we linked to the second one that I listed on slide here that was an on-prem deployment. And that was actually an analysis that regulators were asking for in a couple of countries, uh, for anti money laundering scams, because there were some plots out there that networks of criminals would all buy the low value policies, surrendered them a couple of years later. And in that way, God criminal money into the regular amount of monetary system whitewashed the money and this needed some very specific and very, very complex link analysis because there were fairly large networks of criminals that all needed to be tied together, um, with the actions, with the policies to figure out where potential pain points were. And that also obviously included ecosystems, such as lawyers, administrative offices, all the other things, no, but most, you know, exciting. >>I think that we see happening at the moment and we, we, you know, our partner, if analytics just went live with this with a large insurer, is that by looking at different types that insurers already have, um, unstructured data, um, um, their claims nodes, um, repour its claims, filings, um, statements, voice records, augmented with information that they have access to, but that's not their ours such as geo information obituary, social media Boyd on the cloud. And we can analyze claims much more effectively and efficiently for fraud and litigation and alpha before. And the first results over the last year or two showcasing a significant degree is significant degrees in claims expenses and, um, and an increase at the right moment of what a right amount in claims payments, which is obviously a good thing for insurers. Right? So having said all of that, I really would like to give Sri Ramaswami, the CEO of infinite Lytics, the opportunity to walk you through this use case and actually show you how this looks like in real life. So Sheree, here >>You go. So >>Insurers often ask us this question, can AI help insurance companies, lower loss expenses, litigation, and help manage reserves better? We all know that insurance industry is majority. Majority of it is unstructured data. Can AI analyze all of this historically and look for patterns and trends to help workflows and improve process efficiencies. This is exactly why we brought together industry experts at infill lyrics to create the industries where very first pre-trained and prebuilt insights engine called Charlie, Charlie basically summarizes all of the data structured and unstructured. And when I say unstructured, I go back to what money basically traded. You know, it is including documents, reports, third-party, um, it reports and investigation, uh, interviews, statements, claim notes included as well at any third party enrichment that we can legally get our hands on anything that helps the adjudicate, the claims better. That is all something that we can include as part of the analysis. And what Charlie does is takes all of this data and very neatly summarizes all of this. After the analysis into insights within our dashboard, our proprietary naturally language processing semantic models adds the explanation to our predictions and insights, which is the key element that makes all of our insights >>Actually. So >>Let's just get into, um, standing what these steps are and how Charlie can help, um, you know, with the insights from the historical patterns in this case. So when the claim comes in, it comes with a lot of unstructured data and documents that the, uh, the claims operations team have to utilize to adjudicate, to understand and adjudicate the claim in an efficient manner. You are looking at a lot of documents, correspondences reports, third party reports, and also statements that are recorded within the claim notes. What Charlie basically does is crunches all, all of this data removes the noise from that and brings together five key elements, locations, texts, sentiments, entities, and timelines in the next step. >>In the next step, we are basically utilizing Charlie's built-in proprietary, natural language processing models to semantically understand and interpret all of that information and bring together those key elements into curated insights. And the way we do that is by building knowledge, graphs, and ontologies and dictionaries that can help understand the domain language and convert them into insights and predictions that we can display on the dash. Cool. And if you look at what has been presented in the dashboard, these are KPIs and metrics that are very interesting for a management staff or even the operations. So the management team can basically look at the dashboard and start with the summarized data and start to then dig deeper into each of the problematic areas and look at patterns at that point. And these patterns that we learn from not only from what the system can provide, but also from the historic data can help understand and uncover some of these patterns in the newer claims that are coming in so important to learn from the historic learnings and apply those learnings in the new claims that are coming in. >>Let's just take a very quick example of what this is going to look like a claims manager. So here the claims manager discovers from the summarized information that there are some problems in the claims that basically have an attorney involved. They have not even gone into litigation and they still are, you know, I'm experiencing a very large, um, average amount of claim loss when they compare to the benchmark. So this is where the manager wants to dig deeper and understand the patterns behind it from the historic data. And this has to look at the wealth of information that is sitting in the unstructured data. So Charlie basically pulls together all these topics and summarizes these topics that are very specific to certain losses combined with entities and timelines and sentiments, and very quickly be able to show to the manager where the problematic areas are and what are those patterns leading to high, severe claims, whether it's litigation or whether it's just high, severe indemnity payments. >>And this is where the managers can adjust their workflows based on what we can predict using those patterns that we have learned and predict the new claims, the operations team can also leverage Charlie's deep level insights, claim level insights, uh, in the form of red flags, alerts and recommendations. They can also be trained using these recommendations and the operations team can mitigate the claims much more effectively and proactively using these kind of deep level insights that need to look at unstructured data. So at the, at the end, I would like to say that it is possible for us to achieve financial benefits, leveraging artificial intelligence platforms like Charlie and help the insurers learn from their historic data and being able to apply that to the new claims, to work, to adjust their workflows efficiently. >>Thank you very much for you. That was very enlightening as always. And it's great to see that actually, some of the technology that we all work so hard on together, uh, comes to fruition in, in cost savings and efficiencies and, and help insurers manage potential bad situations, such as claims fraud batter, right? So to close this session out as a next step, we would really urge you to a Sasha available data sources and advanced or predictive fraud prevention capabilities aligned with your digital initiatives to digital initiatives that we all embarked on over the last year are creating a lot of new data that we can use to learn more. So that's a great thing. If you need to learn more at one to learn more about Cloudera and our insurance work and our insurance efforts, um, you to call me, uh, I'm very excited to talk about this forever. So if you want to give me a call or find a place to meet when that's possible again, and schedule a meeting with us, and again, we love insurance. We'll gladly talk to anyone until they say in parts of the United States, the cows come home about it. And we're dad. I want to thank you all for attending this session and hanging in there with us for about half an hour. And I hope you have a wonderful rest of the day. >>Good afternoon, I'm wanting or evening depending on where you are and welcome to this breakout session around insurance, improve underwriting with better insights. >>So first and >>Foremost, let's summarize very quickly, um, who we're with and what we're talking about today. My name is goonie castling, and I'm the managing director at Cloudera for the insurance vertical. And we have a sizeable presence in insurance. We have been working with insurance companies for a long time now, over 10 years, which in terms of insurance, it's maybe not that long, but for technology, it really is. And we're working with, as you can see some of the largest companies in the world and in the continents of the world. However, we also do a significant amount of work with smaller insurance companies, especially around specialty exposures and the regionals, the mutuals in property, casualty, general insurance, life, annuity, and health. So we have a vast experience of working with insurers. And, um, we'd like to talk a little bit today about what we're seeing recently in the underwriting space and what we can do to support the insurance industry in there. >>So >>Recently what we have been seeing, and it's actually accelerated as a result of the recent pandemic that we all have been going through. We see that insurers are putting even more emphasis on accounting for every individual customers with lotta be a commercial clients or a personal person, personal insurance risk in a dynamic and a B spoke way. And what I mean with that is in a dynamic, it means that risks and risk assessments change very regularly, right? Companies go into different business situations. People behave differently. Risks are changing all the time and the changing per person they're not changing the narrow generically my risk at a certain point of time in travel, for example, it might be very different than any of your risks, right? So what technology has started to enable is underwrite and assess those risks at those very specific individual levels. And you can see that insurers are investing in that capability. The value of, um, artificial intelligence and underwriting is growing dramatically. As you see from some of those quotes here and also risks that were historically very difficult to assess such as networks, uh, vendors, global supply chains, um, works workers' compensation that has a lot of moving parts to it all the time and anything that deals with rapidly changing risks, exposures and people, and businesses have been supported more and more by technology such as ours to help, uh, gone for that. >>And this is a bit of a difficult slide. So bear with me for a second here. What this slide shows specifically for underwriting is how data-driven insights help manage underwriting. And what you see on the left side of this slide is the progress in make in analytical capabilities. And quite often the first steps are around reporting and that tends to be run from a data warehouse, operational data store, Starsky, Matt, um, data, uh, models and reporting really is, uh, quite often as a BI function, of course, a business intelligence function. And it really, you know, at a regular basis informs the company of what has been taken place now in the second phase, the middle dark, the middle color blue. The next step that is shore stage is to get into descriptive analytics. And what descriptive analytics really do is they try to describe what we're learning in reporting. >>So we're seeing sorts and events and sorts and findings and sorts of numbers and certain trends happening in reporting. And in the descriptive phase, we describe what this means and you know why this is happening. And then ultimately, and this is the holy grill, the end goal we like to get through predictive analytics. So we like to try to predict what is going to happen, uh, which risk is a good one to underwrite, you know, watch next policy, a customer might need or wants water claims as we discuss it. And not a session today, uh, might become fraud or lists or a which one we can move straight through because they're not supposed to be any issues with it, both on the underwriting and the claims side. So that's where every insurer is shooting for right now. But most of them are not there yet. >>Totally. Right. So on the right side of this slide specifically for underwriting, we would, we like to show what types of data generally are being used in use cases around underwriting, in the different faces of maturity and analytics that I just described. So you will see that on the reporting side, in the beginning, we start with rates, information, quotes, information, submission information, bounding information. Um, then if you go to the descriptive phase, we start to add risk engineering information, risk reports, um, schedules of assets on the commercial side, because some are profiles, uh, as a descriptions, move into some sort of an unstructured data environment, um, notes, diaries, claims notes, underwriting notes, risk engineering notes, transcripts of customer service calls, and then totally to the other side of this baseball field looking slide, right? You will see the relatively new data sources that can add tremendous value. >>Um, but I'm not Whitely integrated yet. So I will walk through some use cases around these specifically. So think about sensors, wearables, you know, sensors on people's bodies, sensors, moving assets for transportation, drone images for underwriting. It's not necessary anymore to send, uh, an inspection person and inspector or risk, risk inspector or engineer to every building, you know, be insurers now, fly drones over it, to look at the roofs, et cetera, photos. You know, we see it a lot in claims first notice of loss, but we also see it for underwriting purposes that policies out there. Now that pretty much say sent me pictures of your five most valuable assets in your home and we'll price your home and all its contents for you. So we start seeing more and more movements towards those, as I mentioned earlier, dynamic and bespoke types of underwriting. >>So this is how Cloudera supports those initiatives. So on the left side, you see data coming into your insurance company. There are all sorts of different data. There are, some of them are managed and controlled by you. Some orders you get from third parties, and we'll talk about Della medics in a little bit. It's one of the use cases. They move into the data life cycle, the data journey. So the data is coming into your organization. You collected, you store it, you make it ready for utilization. You plop it either in an operational environment for processing or in an analytical environment for analysis. And then you close on the loop and adjusted from the beginning if necessary, no specifically for insurance, which is if not the most regulated industry in the world it's coming awfully close, and it will come in as a, a very admirable second or third. >>Um, it's critically important that that data is controlled and managed in the correct way on the old, the different regulations that, that we are subject to. So we do that in the cloud era Sharon's data experiment experience, which is where we make sure that the data is accessed by the right people. And that we always can track who did watch to any point in time to that data. Um, and that's all part of the Cloudera data platform. Now that whole environment that we run on premise as well as in the cloud or in multiple clouds or in hybrids, most insurers run hybrid models, which are part of the data on premise and part of the data and use cases and workloads in the clouds. We support enterprise use cases around on the writing in risk selection, individualized pricing, digital submissions, quote processing, the whole quote, quote bound process, digitally fraud and compliance evaluations and network analysis around, um, service providers. So I want to walk you to some of the use cases that we've seen in action recently that showcases how this work in real life. >>First one >>Is to seize that group plus Cloudera, um, uh, full disclosure. This is obviously for the people that know a Dutch health insurer. I did not pick the one because I happen to be dodged is just happens to be a fantastic use case and what they were struggling with as many, many insurance companies is that they had a legacy infrastructure that made it very difficult to combine data sets and get a full view of the customer and its needs. Um, as any insurer, customer demands and needs are rapidly changing competition is changing. So C-SAT decided that they needed to do something about it. And they built a data platform on Cloudera that helps them do a couple of things. It helps them support customers better or proactively. So they got really good in pinging customers on what potential steps they need to take to improve on their health in a preventative way. >>But also they sped up rapidly their, uh, approvals of medical procedures, et cetera. And so that was the original intent, right? It's like serve the customers better or retain the customers, make sure what they have the right access to the right services when they need it in a proactive way. As a side effect of this, um, data platform. They also got much better in, um, preventing and predicting fraud and abuse, which is, um, the topic of the other session we're running today. So it really was a good success and they're very happy with it. And they're actually starting to see a significant uptick in their customer service, KPIs and results. The other one that I wanted to quickly mention is Octo. As most of you know, Optune is a very, very large telemedics provider, telematics data provider globally. It's been with Cloudera for quite some time. >>This one I want to showcase because it showcases what we can do with data in mass amounts. So for Octo, we, um, analyze on Cloudera 5 million connected cars, ongoing with 11 billion data points. And really what they're doing is the creating the algorithms and the models and insurers use to, um, to, um, run, um, tell them insurance, telematics programs made to pay as you drive pay when you drive, pay, how you drive. And this whole telemedics part of insurance is actually growing very fast too, in, in, still in sort of a proof of concept mini projects, kind of initiatives. But, um, what we're succeeding is that companies are starting to offer more and more services around it. So they become preventative and predictive too. So now you got to the program staff being me as a driver saying, Monique, you're hopping in the car for two hours. >>Now, maybe it's time you take a break. Um, we see that there's a Starbucks coming up on the ride or any coffee shop. That's part of a bigger chain. Uh, we know because you have that app on your phone, that you are a Starbucks user. So if you stop there, we'll give you a 50 cents discount on your regular coffee. So we start seeing these types of programs coming through to, again, keep people safe and keep cars safe, but primarily of course the people in it, and those are the types of use cases that we start seeing in that telematic space. >>This looks more complicated than it is. So bear with me for a second. This is a commercial example because we see a data work. A lot of data were going on in commercial insurance. It's not Leah personal insurance thing. Commercial is near and dear to my heart. That's where I started. I actually, for a long time, worked in global energy insurance. So what this one wheelie explains is how we can use sensors on people's outfits and people's clothes to manage risks and underwrite risks better. So there are programs now for manufacturing companies and for oil and gas, where the people that work in those places are having sensors as part of their work outfits. And it does a couple of things. It helps in workers' comp underwriting and claims because you can actually see where people are moving, what they are doing, how long they're working. >>Some of them even tracks some very basic health-related information like blood pressure and heartbeat and stuff like that, temperature. Um, so those are all good things. The other thing that had to us, it helps, um, it helps collect data on the specific risks and exposures. Again, we're getting more and more to individual underwriting or individual risk underwriting, who insurance companies that, that ensure these, these, um, commercial, commercial, um, enterprises. So they started giving discounts if the workers were sensors and ultimately if there is an unfortunate event and it like a big accident or big loss, it helps, uh, first responders very quickly identify where those workers are. And, and, and if, and how they're moving, which is all very important to figure out who to help first in case something bad happens. Right? So these are the type of data that quite often got implements in one specific use case, and then get broadly moved to other use cases or deployed into other use cases to help price risks, betters better, and keep, you know, risks, better control, manage, and provide preventative care. Right? >>So these were some of the use cases that we run in the underwriting space that are very excited to talk about. So as a next step, what we would like you to do is considered opportunities in your own companies to advance risk assessment specific to your individual customer's need. And again, customers can be people they can be enterprises to can be other any, any insurable entity, right? The please physical dera.com solutions insurance, where you will find all our documentation assets and thought leadership around the topic. And if you ever want to chat about this, please give me a call or schedule a meeting with us. I get very passionate about this topic. I'll gladly talk to you forever. If you happen to be based in the us and you ever need somebody to filibuster on insurance, please give me a call. I'll easily fit 24 hours on this one. Um, so please schedule a call with me. I promise to keep it short. So thank you very much for joining this session. And as a last thing, I would like to remind all of you read our blogs, read our tweets. We'd our thought leadership around insurance. And as we all know, insurance is sexy.

(upbeat music) >> Narrator: From around the globe, it's the cube with digital coverage of AWS re:invent 2020, sponsored by Intel, AWS, and our community partners. >> Hey, welcome back, everybody. Jeff Frick here with the cube. Welcome back to our ongoing coverage of AWS re:invent 2020. It's virtual this year, just like everything is virtual this year. But it's still the biggest event in cloud, and we're excited to be back. I'd like to welcome in our next guest, he is Erez Yarkoni, head of cloud and telco technologies for checkpoint software technologies. There it is great to see you. >> Nice to see you, Jeff. Thank you for hosting me this morning. >> Absolutely, so let's jump into it. You've been in the cloud space. For a while I saw a great interview with you, I think like four or five years ago, when I was doing some research, and you're talking about, all the great innovation that's coming from cloud. That was years and years ago. Now, suddenly, we had COVID arrived. And I'm sure you've seen all the social media means who's driving your digital transformation, the CEO, the CMO, or COVID. And we don't know what the answer is. So first off, I'd just love to get your perspective, you've been in this a long time now that we're here in 2020, both in terms of the development of the cloud and the adoption of the cloud, as well as this accelerant that came into our lives in March. >> Hey Jeff, You know I have been lucky that I got to participate in this kind of innovation cycle of IT and technology. Earlier, I was a CIO for an organization, large organization, and we were adopting cloud. At the same time, as an organization, we were selling technologies and networks to our customers, and they were asking to adopt cloud and so on. And these are probably some of the early interviews we looked at. So I got lucky that I had to look at my own organization and understand where cloud is beneficial. And obviously, now I work with cybersecurity and secure in the cloud. So it's all come together. I think that as as cloud technologies came in, it really came in to help many of us address the fundamental need to come to market with business capabilities and functionality faster. For those of us in technology, you know we were probably always the bottleneck of our business counterparts that said. Well, if you could only do this for me, I could grow the business, I could change your business, I can go to other places, I can incrementally bring more customers, revenues, and so on. The cloud platforms have done a tremendous job allowing developers and operators have technology to change the speed in which they service their businesses. But with speed comes security. And I think the cloud platforms disneynow. Specifically, here platforms like AWS build security into into the cloud as well. But there's other needs in it and the pandemic or COVID. All it did is it shifted some of these motions into another gear and then it created some new business needs that can only be service that digital mean, you are now having a collaboration session over a digital channel where otherwise would be probably sitting in the same studio. So definitely collaboration has changed. Commerce have changed, especially for some organizations that never planned to do commerce over digital channels, small businesses and so on. Just think about the food delivery industry and how many new customers have now sole, restaurants that have now signed up for food delivery services that must have exploded. These continuous changes brought continuous needs to address security as well. AWS is allowing people to build some amazing applications. I watched the commercials when I watch football on Sunday. Right? So peloton and zoom in education and many other things. And yeah, so when people build those amazing applications, the next thing they need to do is make sure that the zoom session is secure. And nobody's crashing in if you have a bunch of kids doing zoom for school. >> Erez you talked on so many topics on that. So let's break a few of them down. First off, I just, you know thank goodness for cloud, right? >> Yeah >> If this pandemic had hit 10 years ago, 15 years ago, we would not have been able those of us in the IT industry to shift so easily to cloud based or excuse me to working from home or working from anywhere because of the cloud based applications huge enabler. But it's funny now once on what you just talked about, did you talk about cost savings? And I still find there's a lot of people that are looking at cloud as a way to save costs. You been in it for a while, and you know the truth is all about agility and speed of business, speed of adoption, speed of innovation. You said it in every single one of your answers. But it still seems to be a lag for a lot of people now with with COVID, and, you know securing people work from home, one of the big issues go back to security is increasing attack surface. And we know the increasing sophistication of the bad guys. Now, I'm hearing from some people that they're actually using old techniques that they used to use back in the day because they know people are at home, and maybe things are as locked down. You talk about security needs to bake be baked in all long the way we're using all these, more and more cloud based apps. How do people think about the security perspective? How do you bake it into everything that you do? And how do you respond to the increased attack surfaces that have now suddenly opened up to look like for probably a little while not just going back to the old way, anytime soon? >> Yeah, so you know, you you touched on that, you said that you hear about people using old secure the old attack methods or vectors or so on, coming back, because people are now at home and no longer behind a very secure environment in their office or in the data center, people had to maybe move things that they never thought they would call center operations. That was by definition, you showed up to the call center for certain organizations and moved it out. And they may have not been ready to move those applications so on, so they had to address the security of it. I think that's exactly it, which is now some of the reaction we had to have for just staying in business. We used kind of very older, or, we increased what we know about security about remote access by increasing VPN capacity for the organization or, or those type of methodologies. Now people are looking at what happened to our topology to our architecture, where are people and machines coming in to execute their work over the network? Where are the applications residing? What have we moved to the cloud because we had to know flex for capacity and speed and maybe localize and move it into regions and so on. I don't think it was about cost saving, as you think it was about business agility, especially in this phase. I actually think that at the end of the day, the big benefit from cloud is business agility. Cost has to come with it, we cannot sacrifice costs and everything we do. And we look at overall how we use cloud technologies and other technologies and make sure that the cost fits into what our business demands from a cost structure but it is about business agility. Now, it's also about security agility. So people are building, you know methods and capabilities to match the business agility with security and security was, at least for me, for instance, as as a CIO, security was a bottleneck. So when business demanded the Agile development, you know iterations, sprints, deliver functionality in weeks, and, you know keep pouring it into the environment. One of the inhibitors was security, right, we weren't ready for it, we weren't ready to release it. So we had to find a way to adopt it. And then came in companies like AWS, saying, we built some of that security built into the platform. And companies like checkpoint saying we have cloud security that moves at cloud speed and allows you to integrate into your CICD, environmental or, or processes and allows you to match the speed of the business with the speed of security. >> Yeah, that's great. I mean, again, I agree with you, 100%, it's all about agility, and speed of business. And being able to move faster just always surprises me how people how many people are still kind of stuck on the cost saving piece. And then the other thing, of course, which you're super aware of, if you've ever been to one of kind of the technical keynotes at AWS re:invent the amount of investment that they can make an infrastructure including security, in just, just completely over overshadows anything in an individual company can invest just in terms of the resources and then somebody like you guys can leverage on top of not only using the the massive Amazon, kind of core investments in security at the infrastructure layer, but then all the stuff that you guys can do in terms of securing the enterprise and helping make sure that the right people have access to the right information at the right time, but not a lot more than that. I wonder if you can talk about a new kind of zero trust in some of the evolution within security in terms of the posturing, and how you kind of make assumptions, as we said, it's no longer like a wall anymore, it's no longer talking about having these physical borders, or even logical borders, but it's really about access and breaking down access even to the person in the application and the data etc. >> Yeah, I think you asked specifically about zero trust, and I think that we want to move, maybe want to keep that the the theme here around the application security, I'll get to zero trust at the end. You know, so one of the things that that definitely is thematic, or what we see happening is, in the evolution in the maturity curve of adopting the cloud, the initial adoption was, maybe some lift shift from organizations and the IaaS layer was a big player. But the PaaS layers of the cloud are where all the interesting things happen, where all the exciting services, all the innovation coming from organizations like AWS, all the enablers for a business agility, and capabilities are coming from there. And when you start developing your applications for that PaaS layer, we start leveraging the services, the type of security changes, so you're no longer looking at network security, or maybe northeast, east west, north south, east west type of security on your network, you're now looking at security API's and securing the backplane of the cloud, from those services that they give you, you know you get to encrypt your buckets, you got to make sure your security groups are correct, you want to make sure your serverless functions are not executing anything malicious in them or, or talking to IP addresses, they shouldn't be. Same with your container, you want to make sure that your container code is scanned properly, you didn't download anything in there that's malicious. And obviously, have runtime security, both to make sure you're compliant from a posture perspective, you make compliance may require you to be PCI compliant one of those. So the elevation in which you execute to security changed from the from the stack from a kind of a traditional stack, requires different capabilities and between what AWS has built into the platform and what checkpoint puts together in cloud guard. This is big, the big target, then we get into, okay, so how do you access all these great things that we just built? Right? So we built these, this great application? It's sitting on AWS, it's using some of the great services there. How do you how do you get to it? Who gets to it? How do you get to it? This is where some of these, sassy and zero trusts come in. Because what happened is, you used to come into a lot of enterprise applications from the data center, then we moved some web apps, and you came over the web into the application. So we have some web firewalls and security for that. Now you're getting into every application from the edge of the network, because we are all at home, or we are we used to be traveling but a lot more of us are now at home coming over the edge of the network, we're adding IoT devices coming on via generic and so on, there's a lot more volume coming at you. And you get to find different ways than just VPN authentication of the traffic into so we are coming into the age of having to identify who's coming at the application at the capability at any given time. And that's where you come into the framework of zero trust, I, every time you come in, I'm going to authenticate that is you. And there's different methodologies in there. For instance, one of the things that we just added to our portfolio is the ability to put an agent, let's say in your around your AWS application, and allow remote access with no VPN to your enterprise app aah to an acquisition company we call odo without having to put a VPN so the administrator defines what applications are connected to the connector. They define who's the users that are allowed and authenticate them based on the authentication framework, let's say Octo, something like that, and allows them to come in and that that those are the type of capabilities you need in these new frameworks. So, how do you get to these great applications we're building? >> Right, right. And you touched on something really interesting, right, which is, which is the complexity is only going up? As you mentioned edge you mentioned a little bit of IoT, right, so as 5G comes on board, as IoT gets increasing amounts of traction. All these applications are API based there's all types of information flying back and forth, so I wonder if you can share kind of your guys thoughts on, applied machine learning and artificial intelligence to help, you know kind of get through all the all the signal or excuse me all the noise, find the signal, and really, you know bring more automation to help the security experts in the security systems be more effective at their jobs. >> Yeah, so I think a lot of what we talked about, until now was protecting establishing a new perimeter, there's not really a perimeter, right because we talked about the perimeter has grown and it's fuzzy and it's at scale that really doesn't allow you to say I have it for an undersea up to authentic everybody. But like you said, with that speed, and scale, came a lot of data, you got a lot of logs running in there, you're like got a lot of events, you got a lot of things that you can look into. And by looking into them, you can start with machine learning and those type of AI methodologies start looking both to identify things before they happen, or inform organizations and inform about things that are already happened and they're in and potentially remediate them. At checkpoint, for instance, we have something called the threat, the threat cloud, we collect these events from every gateway, every appliance, every virtual appliance, every type of security agent that we have around the world, into the flex cloud that processes and I'm going to throw a number there, that's the closer about 80 billion a day transactions. >> 80 billion with B >> Yeah, and that allows us to, to process to apply machine learning and AI algorithms to find threat, and then inform all these great checkpoint security agents out there of new threats and prevent those threats from ever happening in the in the environment. Right? If you're operating on a on an AWS environment, there's a lot of blood flows happening in your environment, there's a lot of things to collect and look at, right. So in cloud guard, we offer something called logic log.ic, which allows you to harvest those logs, we enrich them and then we allow threat hunting inside those environment, right. So those types of capabilities are definitely kind of the future of advanced security, right. So beyond just establishing, it's like, you establish your security around what you do. And then you have your intelligence unit starting to identify what signals are out there allowing you to both prevent security breaches or any type of threats, but also remediate anything, any, you find the traces of things that happened and remediate them. >> Right, right. Well, there is that's, that's a great illustration of, kind of baking security into the multiple steps of the process and all the steps of the process. That's not just a bolt on anymore. It's got to be, part of everything you do and baked into everything you do. I still, I still wonder how certain companies that that are run by having people click on links that they're not familiar with still happen today. But I guess, I guess they still do. So as I give you the final word, again, you've been in this space for a long time, as we kind of turned to turn the page on 2020. What are some of your priorities we are you excited about for 2021? >> I think the most exciting things for us in cloud security in 2021 is we're releasing more capabilities into into the environment, we're in the maturity curve, of protecting, your network in the cloud, and then protecting your posture in the cloud. We're moving very strongly into predicting your runtime and applications in the cloud, your API's, and working with organizations through that maturity curve and getting them up to all the way up to threat hunting capabilities. And I think that'll be exciting because I hear from customers that they need to move quickly through that maturity curve of cloud security as they have accelerated and continue there to accelerate their move to the cloud. >> Well, that's great. Well, I think, no shortage of job security in the cloud security space. So I'm sure it will be a busy year. Well, it was thanks for sharing your insight. Really appreciate the time and it was great catching up. >> Thank you, Jeff, for your time today. And it was great talking to you. >> Absolutely. All right. Well, he's Erez I'm Jeff. You're watching the cubes, continuous coverage of AWS re:invent 2020 Thanks for watching. I'll see you next time. (upbeat music)

>> Announcer: From around the globe, it's theCUBE with digital coverage of VMworld 2020 brought to you by VMware and its ecosystem partners. >> Hello, welcome back to theCUBE's coverage of VMworld 2020. This is theCUBE virtual with VMworld 2020 virtual. I'm John Furrier, your host of theCUBE with Dave Vellante. It's our 11th year covering VMware. We're not in-person, we're virtual but all the content is flowing. Of course, we're here with Pat Gelsinger, the CEO of VMware who's been on theCUBE, all 11 years. This year virtual of theCUBE as we've been covering VMware from his early days in 2010 when theCUBE started, 11 years later, Pat, it's still changing and still exciting. Great to see you, thanks for taking the time. >> Hey, you guys are great. I love the interactions that we have, the energy, the fun, the intellectual sparring and of course the audiences have loved it now for 11 years, and I look forward to the next 11 that we'll be doing together. >> It's always exciting 'cause we have great conversations, Dave, and I like to drill in and really kind of probe and unpack the content that you're delivering at the keynotes, but also throughout the entire program. It is virtual this year which highlights a lot of the cloud native changes. Just want to get your thoughts on the virtual aspect, VMworld's not in-person, which is one of the best events of the year, everyone loves it, the great community. It's virtual this year but there's a slew of content, what should people take away from this virtual VMworld? >> Well, one aspect of it is that I'm actually excited about is that we're going to be well over 100,000 people which allows us to be bigger, right? You don't have the physical constraints, you also are able to reach places like I've gone to customers and maybe they had 20 people attend in prior years. This year they're having 100. They're able to have much larger teams also like some of the more regulated industries where they can't necessarily send people to events like this, The International Audience. So just being able to spread the audience much more. A digital foundation for an unpredictable world, and man, what an unpredictable world it has been this past year. And then key messages, lots of key products announcements, technology announcements, partnership announcements, and of course in all of the VMworld is that hands-on labs, the interactions that will be delivering a virtual. You come to VMware because the content is so robust and it's being delivered by the world's smartest people. >> Yeah, we've had great conversations over the years and we've talked about hybrid cloud, I think, 2012. A lot of the stuff I look back at a lot of the videos was early on we're picking out all these waves, but there was that moment four years ago or so, maybe even four three, I can't even remember it seems like yesterday. You gave the seminal keynote and you said, this is the way the world's going to happen. And since that keynote, I'll never forget, was in Moscone and since then, you guys have been performing extremely well both on the business front as well as making technology bets and it's paying off. So what's next, you got the cloud, cloud scale, is it Space, is it Cyber? All these things are going on what is next wave that you're watching and what's coming out and what can people extract out of VMworld this year about this next wave? >> Yeah, one of the things I really am excited about and I went to my buddy Jensen, I said, boy, we're doing this work in smart mix we really like to work with you and maybe some things to better generalize the GPU. And Jensen challenged me. Now usually, I'm the one challenging other people with bigger visions. This time Jensen said, "hey Pat, I think you're thinking too small. Let's do the entire AI landscape together, and let's make AI a enterprise class works load from the data center to the cloud and to the Edge. And so I'm going to bring all of my AI resources and make VMware and Tanzu the preferred infrastructure to deliver AI at scale. I need you guys to make the GPUs work like first-class citizens in the vSphere environment because I need them to be truly democratized for the enterprise, so that it's not some specialized AI Development Team, it's everybody being able to do that. And then we're going to connect the whole network together in a new and profound way with our Monterey program as well being able to use the Smart NIC, the DPU, as Jensen likes to call it. So now with CPU, GPU and DPU, all being managed through a distributed architecture of VMware. This is exciting, so this is one in particular that I think we are now re-architecting the data center, the cloud and the Edge. And this partnership is really a central point of that. >> Yeah, the NVIDIA thing's huge and I know Dave probably has some questions on that but I asked you a question because a lot of people ask me, is that just a hardware deal? Talking about SmartNICs, you talk about data processing units. It sounds like a motherboard in the cloud, if you will, but it's not just hardware. Can you talk about the aspect of the software piece? Because again, NVIDIA is known for GPUs, we all know that but we're talking about AI here so it's not just hardware. Can you just expand and share what the software aspect of all this is? >> Yeah well, NVIDIA has been investing in their AI stack and it's one of those where I say, this is Edison at work, right? The harder I work, the luckier I get. And NVIDIA was lucky that their architecture worked much better for the AI workload. But it was built on two decades of hard work in building a parallel data center architecture. And they have built a complete software stack for all the major AI workloads running on their platform. All of that is now coming to vSphere and Tanzu, that is a rich software layer across many vertical industries. And we'll talk about a variety of use cases, one of those that we highlight at VMworld is the University, California, San Francisco partnership, UCSF, one of the world's leading research hospitals. Some of the current vaccine use cases as well, the financial use cases for threat detection and trading benefits. It really is about how we bring that rich software stack. This is a decade and a half of work to the VMware platform, so that now every developer and every enterprise can take advantage of this at scale. That's a lot of software. So in many respects, yeah, there's a piece of hardware in here but the software stack is even more important. >> It's so well we're on the sort of NVIDIA, the arm piece. There's really interesting these alternative processing models, and I wonder if you could comment on the implications for AI inferencing at the Edge. It's not just as well processor implications, it's storage, it's networking, it's really a whole new fundamental paradigm, but how are you thinking about that, Pat? >> Yeah, and we've thought about there's three aspects, what we said, three problems that we're solving. One is the developer problem where we said now you develop once, right? And the developer can now say, "hey I want to have this new AI-centric app and I can develop and it can run in the data center on the cloud or at the Edge." Secondly, my Operations Team can be able to operate this just like I do all of my infrastructure, and now it's VMs containers and AI applications. And third, and this is where your question really comes to bear most significantly, is data gravity. Right, these data sets are big. Some of them need to be very low latency as well, they also have regulatory issues. And if I have to move these large regulated data sets to the cloud, boy, maybe I can't do that generally for my Apps or if I have low latency heavy apps at the Edge, huh, I can't pull it back to the cloud or to my data center. And that's where the uniform architecture and aspects of the Monterey Program where I'm able to take advantage of the network and the SmartNICs that are being built, but also being able to fully represent the data gravity issues of AI applications at scale. 'Cause in many cases, I'll need to do the processing, both the learning and the inference at the Edge as well. So that's a key part of our strategy here with NVIDIA and I do think is going to unlock a new class of apps because when you think about AI and containers, what am I using it for? Well, it's the next generation of applications. A lot of those are going to be Edge, 5G-based, so very critical. >> We've got to talk about security now too. I'm going to pivot a little bit here, John, if it's okay. Years ago, you said security is a do-over, you said that on theCUBE, it stuck with us. But there's been a lot of complacency. It's kind of if it ain't broke, don't fix it, but but COVID kind of broke it. And so you see three mega trends, you've got cloud security, you'll see in Z-scaler rocket, you've got Identity Access Management and Octo which I hope there's I think a customer of yours and then you got Endpoint, you're seeing Crowdstrike explode you guys paid 2.7 billion, I think, for Carbon Black, yet Crowdstrike has this huge valuation. That's a mega opportunity for you guys. What are you seeing there? How are you bringing that all together? You've got NSX components, EUC components, you've got sort of security throughout your entire stack. How should we be thinking about that? >> Well, one of the announcements that I am most excited about at VMworld is the release of Carbon Black workload. 'Cause we said we're going to take those carbon black assets and we're going to combine it with workspace one, we're going to build it in NSX, we're going to make it part of Tanzu, and we're going to make it part of vSphere. And Carbon Black workload is literally the vSphere embodiment of Carbon Black in an agent-less way. So now you don't need to insert new agents or anything, it becomes part of the hypervisor itself. Meaning that there's no attack surface available for the bad guys to pursue. But not only is this an exciting new product capability, but we're going to make it free, right? And what I'm announcing at VMworld and everybody who uses vSphere gets Carbon Black workload for free for an unlimited number of VMs for the next six months. And as I said in the keynote, today is a bad day for cyber criminals. This is what intrinsic security is about, making it part of the platform. Don't add anything on, just click the button and start using what's built into vSphere. And we're doing that same thing with what we're doing at the networking layer, this is the last line acquisition. We're going to bring that same workload kind of characteristic into the container, that's why we did the Octarine acquisition, and we're releasing the integration of workspace one with Carbon Black client and that's going to be the differentiator, and by the way, Crowdstrike is doing well, but guess what? So are we, and right both of us are eliminating the rotting dead carcasses of the traditional AV approach. So there's a huge market for both of us to go pursue here. So a lot of great things in security, and as you said, we're just starting to see that shift of the industry occur that I promised last year in theCUBE. >> So it'd be safe to say that you're a cloud native and a security company these days? >> Yeah well, absolutely. And the bigger picture of us is that we're this critical infrastructure layer for the Edge, for the cloud, for the Telco environment and for the data center from every endpoint, every application, every cloud. >> So, Pat, I want to ask you a virtual question we got from the community. I'm going to throw it out to you because a lot of people look at Amazon and the cloud and they say, okay we didn't see it coming, we saw it coming, we saw it scale all the benefits that are coming out of cloud well documented. The question for you is, what's next after cloud? As people start to rethink especially with COVID highlighting and all the scabs out there as people look at their exposed infrastructure and their software, they want to be modern, they want the modern apps. What's next after cloud, what's your vision? >> Well, with respect to cloud, we are taking customers on the multicloud vision, right, where you truly get to say, oh, this workload I want to be able to run it with Azure, with amazon, I need to bring this one on-premise, I want to run that one hosted. I'm not sure where I'm going to run that application, so develop it and then run it at the best place. And that's what we mean by our hybrid multicloud strategy, is being able for customers to really have cloud flexibility and choice. And even as our preferred relationship with Amazon is going super well, we're seeing a real uptick, we're also happy that the Microsoft Azure VMware service is now GA. So there in Marketplace, are Google, Oracle, IBM and Alibaba partnerships, and the much broader set of VMware Cloud partner programs. So the future is multicloud. Furthermore, it's then how do we do that in the Telco network for the 5G build out? The Telco cloud, and how do we do that for the Edge? And I think that might be sort of the granddaddy of all of these because increasingly in a 5G world, we'll be enabling Edge use cases, we'll be pushing AI to the Edge like we talked about earlier in this conversation, we'll be enabling these high bandwidth low latency use cases at the Edge, and we'll see more and more of the smart embodiment smart city, smart street, smart factory, the autonomous driving, all of those need these type of capabilities. >> Okay. >> So there's hybrid and there's multi, you just talked about multi. So hybrid are data, are data partner ETR they do quarterly surveys. We're seeing big uptick in VMware Cloud on AWS, you guys mentioned that in your call. We're also seeing the VMware Cloud, VMware Cloud Foundation and the other elements, clearly a big uptick. So how should we think about hybrid? It looks like that's an extension of on-prem maybe not incremental, maybe a share shift, whereas multi looks like it's incremental but today multi is really running on multiple clouds, but a vision toward incremental value. How are you thinking about that? >> Yeah, so clearly, the idea of multi is truly multiple clouds. Am I taking advantage of multiple clouds being my private clouds, my hosted clouds and of course my public cloud partners? We believe everybody will be running a great private cloud, picking a primary public cloud and then a secondary public cloud. Hybrid then is saying, which of those infrastructures are identical, so that I can run them without modifying any aspect of my infrastructure operations or applications? And in today's world where people are wanting to accelerate their move to the cloud, a hybrid cloud is spot-on with their needs. Because if I have to refactor my applications, it's a couple million dollars per app and I'll see you in a couple of years. If I can simply migrate my existing application to the hybrid cloud, what we're consistently seeing is the time is 1/4 and the cost is 1/8 or less. Those are powerful numbers. And if I need to exit a data center, I want to be able to move to a cloud environment to be able to access more of those native cloud services, wow, that's powerful. And that's why for seven years now, we've been preaching that hybrid is the future, it is not a way station to the future. And I believe that more fervently today than when I declared it seven years ago. So we are firmly on that path that we're enabling a multi and hybrid cloud future for all of our customers. >> Yeah, you addressed that like Cube 2013, I remember that interview vividly was not a weigh station I got hammered answered. Thank you, Pat, for clarifying that going back seven years. I love the vision, you always got the right wave, it's always great to talk to you but I got to ask you about these initiatives that you're seeing clearly. Last year, a year and a half ago, Project Pacific came out, almost like a guiding directional vision. It then put some meat on the bone Tanzu and now you guys have that whole cloud native initiative, it's starting to flower up, thousands of flowers are blooming. This year, Project Monterey has announced. Same kind of situation, you're showing out the vision. What are the plans to take that to the next level? And take a minute to explain how Project Monterey, what it means and how you see that filling out. I'm assuming it's going to take the same trajectory as Pacific. >> Yeah, Monterey is a big deal. This is re-architecting the core of vSphere and it really is ripping apart the IO stack from the intrinsic operation of vSphere and the SX itself because in many ways, the IO, we've been always leveraging the NIC and essentially virtual NICs, but we never leverage the resources of the network adapters themselves in any fundamental way. And as you think about SmartNICs, these are powerful resources now where they may have four, eight, 16 even 32 cores running in the SmartNIC itself. So how do I utilize that resource, but it also sits in the right place? In the sense that it is the network traffic cop, it is the place to do security acceleration, it is the place that enables IO bandwidth optimization across increasingly rich applications where the workloads, the data, the latency get more important both in the data center and across data centers, to the cloud and to the Edge. So this re-architecting is a big deal, we announced the three partners, Intel, NVIDIA Mellanox and Pensando that we're working with, and we'll begin the deliveries of this as part of the core vSphere offerings beginning next year. So it's a big re-architecting, these are our key partners, we're excited about the work that we're doing with them and then of course our system partners like Dell and Lenovo who've already come forward and says, "Yeah we're going to to be bringing these to market together with VMware." >> Pat, personal question for you. I want to get your personal take, your career going back to Intel, you've seen it all but the shift is consumer to enterprise and you look at just recently Snowflake IPO, the biggest ever in the history of Wall Street. It's an enterprise data company, and the enterprise is now relevant. The consumer enterprise feels consumery, we talked about consumerization of IT years and years ago. But now more than ever the hottest financial IPO enterprise, you guys are enterprise. You did enterprise at Intel (laughing), you know the enterprise, you're doing it here at VMware. The enterprise is the consumer now with cloud and all this new landscape. What is your view on this because you've seen the waves, have you seen the historical perspective? It was consumer, was the big thing now it's enterprise, what's your take on all this? How do you make sense of it because it's now mainstream, what's your view on this? >> Well, first I do want to say congratulations to my friend, Frank and the extraordinary Snowflake IPO. And by the way they use VMware, so I not only do I feel a sense of ownership 'cause Frank used to work for me for a period of time, but they're also a customer of ours so go Frank, go Snowflake. We're excited about that. But there is this episodic to the industry where for a period of time, it is consumer-driven and CES used to be the hottest ticket in the industry for technology trends. But as you say, it has now shifted to be more business-centric, and I've said this very firmly, for instance, in the case of 5G where I do not see consumer. A faster video or a better Facebook isn't going to be why I buy 5G. It's going to be driven by more business use cases where the latency, the security and the bandwidth will have radically differentiated views of the new applications that will be the case. So we do think that we're in a period of time and I expect that it's probably at least the next five years where business will be the technology drivers in the industry. And then probably, hey there'll be a wave of consumer innovation, and I'll have to get my black turtlenecks out again and start trying to be cool but I've always been more of an enterprise guy so I like the next five to 10 years better. I'm not cool enough to be a consumer guy and maybe my age is now starting to conspire against me as well. >> Hey, Pat I know you got to go but a quick question. So you guys, you gave guidance, pretty good guidance actually. I wonder, have you and Zane come up with a new algorithm to deal with all this uncertainty or is it kind of back to old school gut feel? >> (laughing) Well, I think as we thought about the year, as we came into the year, and obviously, COVID smacked everybody, we laid out a model, we looked at various industry analysts, what we call the Swoosh Model, right? Q2, Q3 and Q4 recovery, Q1 more so, Q2 more so. And basically, we built our own theories behind that, we tested against many analyst perspectives and we had Vs and we had Ws and we had Ls and so on. We picked what we thought was really sort of grounded in the best data that we could, put our own analysis which we have substantial data of our own customers' usage, et cetera and picked the model. And like any model, you put a touch of conservatism against it, and we've been pretty accurate. And I think there's a lot of things we've been able to sort of with good data, good thoughtfulness, take a view and then just consistently manage against it and everything that we said when we did that back in March has sort of proven out incrementally to be more accurate. And some are saying, "Hey things are coming back more quickly" and then, "Oh, we're starting to see the fall numbers climb up a little bit." Hey, we don't think this goes away quickly, there's still a lot of secondary things to get flushed through, the various economies as stimulus starts tailoring off, small businesses are more impacted, and we still don't have a widely deployed vaccine and I don't expect we will have one until second half of next year. Now there's the silver lining to that, as we said, which means that these changes, these faster to the future shifts in how we learn, how we work, how we educate, how we care for, how we worship, how we live, they will get more and more sedimented into the new normal, relying more and more on the digital foundation. And we think ultimately, that has extremely good upsides for us long-term, even as it's very difficult to navigate in the near term. And that's why we are just raving optimists for the long-term benefits of a more and more digital foundation for the future of every industry, every human, every workforce, every hospital, every educator, they are going to become more digital and that's why I think, going back to the last question this is a business-driven cycle, we're well positioned and we're thrilled for all of those who are participating with Vmworld 2020. This is a seminal moment for us and our industry. >> Pat, thank you so much for taking the time. It's an enabling model, it's what platforms are all about, you get that. My final parting question for you is whether you're a VC investing in startups or a large enterprise who's trying to get through COVID with a growth plan for that future. What does a modern app look like, and what does a modern company look like in your view? >> Well, a modern company would be that instead of having a lot of people looking down at infrastructure, the bulk of my IT resources are looking up at building apps, those apps are using modern CICD data pipeline approaches built for a multicloud embodiment, right, and of course VMware is the best partner that you possibly could have. So if you want to be modern cool on the front end, come and talk to us. >> All right, Pat Gelsinger, the CEO of VMware here on theCUBE for VMworld 2020 virtual, here with theCUBE virtual great to see you virtually, Pat, thanks for coming on, thanks for your time. >> Hey, thank you so much, love to see you in person soon enough but this is pretty good. >> Yeah. >> Thank you Dave. Thank you so much. >> Okay, you're watching theCUBE virtual here for VMworld 2020, I'm John Furrier, Dave Vellante with Pat Gelsinger, thanks for watching. (gentle music)

from the cube studios in Palo Alto in Boston connecting with thought leaders all around the world this is a cube conversation you know for years marketers marketers have been pushing for more digital especially with their big conferences I heard forward-thinking CMO say the war will be won in digital but the sales teams love the belly-to-belly interaction so every year once or even sometimes more often big corporations have hosted gatherings of thousands or even tens of thousands of attendees these events were like rock concerts they had DJs in the hallway thumping music giant screens beautiful pitches highly produced videos thing a technical breakouts Food lines private dinners etc all come on it culminating in a customer appreciation event with a big-name band physical events are expensive but they generate tons of leads for the host companies and their partner ecosystems well then BOOM coronavirus hits and the marketing teams got what they wished for right overnight virtual events became a mandate if you don't have a solution you were in big trouble because your leads from these large events just dried up hello everyone this is Dave Allen day and welcome to this week's cube insights powered by ETR ETR is entering its quiet period and I won't be able to share any new data for a couple of weeks so rather than look back at the April survey in this breaking analysis we thought we'd take a pause and really talk about the virtual event landscape and just a few of the things that we've learned in the past 120 days now this isn't meant to be an exhaustive list but we do want to call out a few important items that we see is critical in this new digital world in the isolation economy every company scrambled they took one of three paths first companies either postpone their events to buy some time think like Dell technology world Google cloud next cube convey my MIT CBO event etc or to some companies flat-out canceled their events for the year until next year like snowflake and uipath forth number three they scrambled to deploy a virtual event and they went forward IBM think did this HPE discover Susac on AWS summits docker convey Monde a peggle world Vertica big data conference octane sa P sapphire and hundreds of others pushed forward so when this braking analysis I want to share some data from the cube what we've learned not only in the last hundred and twenty days but in ten years of doing events mostly physical and we want to share the new rules of events and event marketing and beyond so let's get right into it everyone knows events events have gone virtual and there are tons of people who could give you advice on approving your digital events including us and and I will in this segment but the first thing that everyone found out is they're going to attract far more people online with a free virtual event than they do with a paid physical event so removing time timing in the expensive travel dramatically increases the participation Tam the total available market here's a tweet from docker CEO Scott Johnson he says that he's looking forward to welcoming 50,000 people to his event this is based on registration data somewhere around 30,000 people logged into the live event so docker got 60% of the pre event registrants to actually log in which is outstanding but there's a lot more to this story I'll share some other stats that are worth mentioning by the way I got permission from docker to to share these numbers not surprising because the event was it was a huge success for such a small company in the end they got nearly 83,000 registrations and they continue to come in weeks after the event which was held in late May now marketers generally will cite 2 to 3 minutes as a respect-- respectable time on site for a web property docker logged in users averaged almost four and a half minutes on site that's the average the bell curve sauce superfans like this guy who was binge watching so this brings me to rule number one it's actually really easy to get people to sign up for free online events but it's not so easy to keep them there now I could talk all day about what docker did right and I'm gonna bring some examples in during this except this segment but the one thing docker did was they did a call for papers or a call for sessions and that's a lot of work but if you look at the docket on speaker list the content is all community driven not all but mostly community driven talker had to break some eggs and reject some folks but it also had a sponsor track so it gave folks another avenue to participate so big success for docker they definitely did it right which brings us to new rule number two attention is precious you got to create high-quality content and realize that you have much less time with participants than if they were in person now unfortunately the doctor docker example is a bit of an outlier it hasn't always been this pretty remember that scene in the social network the movie when a duardo pulled the funding on the servers just to get marks attention remember how Jesse Eisenberg the actor who played Zuckerberg reacted everybody else we don't crash ever if the server's are down for even a day our entire reputation is irreversibly destroyed the whole point well some of the big tech companies crashed their servers and they say there's no such thing as bad press but look at look what happened to s AP and s AP apologized publicly and its CEO told people that they made a mistake in outsourcing their event platform so this brings us to new rule number three don't crash now I come back to Dhaka Khan for a second here's a tweet from a developer who shared the network traffic profile of his network before and during docker con you can see no glitches I mean I don't mean to pick on sa P they they owned the problem and look s AP had a huge attention attendance at its digital event more than 200,000 people and over a million views so Wow you'll kill me with that problem but it underscores the importance of scaling and s AP you have to say was not alone there have been lots of fails from much smaller events here's an example that was really frustrating you try to log in at 7:59 but the event doesn't start until 8:00 sharp really come on back in 60 seconds and in another example there was a slide failure I mean many of these virtual events are glorified webinars so if you're going to rely on slide where make sure the slides will render its scale you maybe embed them into the video you know but at least this company had a back-up plan here's another example and I've redacted the email because I'm not here to throw anyone under the bus well you know kind of but but no reason to name names you know who they are but in this case an old legacy webinar platform failed and they had to move to WebEx and again at least there was a back-up plan so you know it's been tough in a lot of these cases here's a tweet from Jason Reed it kind of summed sums it up now what does he mean by vendors are not getting the job done not enough creativity well not only were platforms failing they weren't performing adequately but the virtual experience is leaving many users unenthused they're they're just one alt-tab away from something better if the virtual event fails to engage them so new rule number four is virtual events that look like webinars actually our webinar webinars I mean in fairness you know the industry had to pivot with no notice but this is why I always tell people start with the outcome that you want and work backwards that'll inform you as to the content strategy the new roles you need to assign and make no mistakes there are new rules you know there's no site inspection virtual and then you got to figure out what you want to use your experience to be there's a whole lot to figure out and this next next one is a bit of a throwaway because yeah it's so obvious and everyone talks about it but I want to bring it up because it's important because I'm amazed at how many virtual event speakers really haven't thought through their setup you can look good you know or at least less bad get those things called books and raise up the laptop figure out some better audio your better yet get a good kit send it to their home with a nice camera and a solid mic maybe you know a clearer IFB comms for the ear spend some money to look good just as you might go and buy a nice outfit even if you're a developer put on a clean t-shirt so rule number five don't cheap out on production value get your guests a good set up and coach them up it doesn't have to be over the top no just a bit thought out okay one of the biggest mistakes I've seen is event organisers they become enamored with a platform and the features of that platform that really don't support their objectives kind of feature creep or they have so many competing objectives and masters that they're serving that they lose sight of the user experience and then the event becomes a buffet of unused features rather than a buffet of engaging content now many have told me that Dave these virtual events are too long there's too much content now I don't necessarily agree I really think if you have something to say you should say it as long as you do it right and you keep people engaged so I want to talk a little bit about a to of the meteor events that we attended one was octane twenty20 hosted by octo the identity management security player and then IBM think 2020 they called it the the think digital event experience and they both had multi day events with lots of content they both organized sessions by topic and made it pretty easy to find stuff and all assessing sessions had a reasonably consistent look and feel to them which kind of helped the production value IBM had content organized and categorized which made things easy to find and they both had good search and with IBM you could go directly from the list of topics right into the videos which I really liked very easy and intuitive and as you can see here in this octane video they had a nice and very ambitious agenda that was really quite well organized and things were pretty easy to find as you can see with this crisp filtering on the left hand side and in really nice search but one of the things that has been frustrating with most of the events that I've watched is you can't get to the sessions directly from the agenda you got to go back out for some linear path and find the content and it's somewhat confusing so I want to come back to the docker count example because I think there were two things that I found interesting and useful with docker con you know this got George nailed it when he said this is how you display a virtual conference what's relevant about this picture is you have multiple simultaneous sessions running live and concurrently and you can pop in and out of them you can easily see the sessions and this tile and there's a red line this linear clock that's running in real time to show you where you are in the event agenda versus in a time of day so I felt like with docker that as a user user you're really connected to the event you come to the site and there's a hero video very easy to find the content and in fact you can't miss it it's not a sales pitch to get to the content and then I really liked what what George change was talking about in terms of the agenda and the tile layout you can see they ran simultaneous sessions and at one point up to seven at once and they gave their sponsors a track on the agenda which is very easy to navigate but what I really like as well is when you click on a tile it takes you directly to the session video and you can see the chat which docker preserved in the PO event mode and you have this easy-to-follow agenda and again you can go directly to the session video and in the chat from the agenda so many paths to find the content I mean something so simple is navigating directly from the agenda to the session most events haven't done that they make you back out and then what I call this linear manner and then go forward and find the sessions that you want and then dive in now maybe they're trying to simulate walking to a session in a Las Vegas Convention Center because it takes about that long to figure out where most of these events in these sessions live so rule number six is make it easy to discover and consume content sounds so simple why is it not happening in most events okay I'm running out of time so I want to encapsulate a number of items in one idea that we talk about all the time at the cube I ran a little survey of the day and someone asked does it really make sense to cram educational content product content partner content customer content rally content and leadership content into the constrain confines of an arbitrary one or two-day window I thought that was an interesting comment now it doesn't necessarily mean shorten up the virtual event which a lot of people think should happen people complain that these things are too long well let me leave you with this it's actually not just about events what do I mean by that well you know how everyone says that all companies are software companies or every company is a SAS company well guess what we believe that every company is a media company in 2004 at the low point of its reputation Microsoft launched channel 9 it was named after the United Airlines channel 9 that lets you listen in to the pilots and their unfiltered conversations kind of cool Microsoft understood that having an authentic voice with which to communicate to developers and serve its community was a smart thing to do and that is the key point channel 9 is about community it's not about audience metrics or lead generation both important things but Microsoft they launched this site understanding the leverage it gets out of its community of developers and instead of treating them like leads they created a site to help developers learn so rule number seven is get your best media mojo on one of the biggest failures I see with physical events and it's clearly carrying over to digital is the failure to optimize the post-event opportunity and experience so just like physical events when the event is over I see companies and their employees they're so burnt out after a virtual event because they feel like they've just given birth and what do they do now after the event they take some time off they got to recharge and when they come back they're swamped and so they're on to the next project it might be another event it might be a webinar series or some regional summits or whatever now it's interesting it feels like all tech companies talk about these days is breaking down silos but most of these parent and child events are disconnected silos sure maybe the data around the events is consolidated into a marketing cloud maybe so that you can nurture leads okay that's fine but what about the community kovat has given us a great opportunity to reimagine how we serve communities and one thing I'm certain about is that physical events they're going to come back at some point in some form but when they do there's gonna be a stronger digital component attached to them hybrids will emerge and some will serve communities better than others and in our opinion the ones that do the best job in digital and serving their communities are gonna win the marketing Wars so ask yourself how are you serving your community are you serving the best way that you can is a lead conversion your number one metric that's okay there's nothing wrong with that but how are your content consumption metrics looking what are you measuring what does your Arc of content look like what's your content and an organic media strategy what does your media stack look like media stack you ask what do you mean Dave well you nailed physical and then you were forced to do virtual overnight eventually there's going to be a hybrid that emerges so there's physical at the bottom and then there's a virtual layer and then you get this hybrid layer at some point on top of that at the very top of the stack you got apps social media you got corporate content you got TV like channel 9 you have video library's website you have tools for agile media you got media production and distribution tooling remember customers will be entering from any one of these layers of that stack and they'll be looking to you for guidance inspiration learning vision product knowledge how to's etc and you'd be delivering that primarily through content so your media stack should be designed to serve your community events software yeah sure but it's much more than that we believe that this stack will emerge not as a monolithic beast but rather as a set of scalable cloud services and api's think of paths for media that you can skin yes of course but also one that you can control add value to integrate with other platforms and fit your business as your community demands and remember new roles are emerging as a result of this pandemic and the pivot to digital the things are different really mostly from from most physical events is that it's very important to think about these roles and one of the important roles is this designer or UX developer that can actually do some coding and API integration think of it as a DevOps for digital organizations that's emerging organizations like yours will want self-service and sometimes out-of-the-box functionality and features for sure no question but we believe that as a media producer you will want to customize your media experience for your community and this work will require new skills that you haven't really prioritized in the past what what do you think what's your vision as to how this will all play out and unfold do you buy that all companies must become media companies or at least media savvy not in the sense of Corp comms but really as an organic media producer tweet me at devonté or email me at David Galante at Silicon angle comm or comment on my LinkedIn post who would react next week with some data from et our survey sphere thanks for watching this wiki bond cube insights powered by ETR this is Dave Volante we'll see you next time [Music]

>> Announcer: From San Francisco, it's theCUBE. Covering VMware Radio 2019. Brought to you by VMware. >> Hi, welcome to theCUBE's exclusive coverage of VMware Radio 2019. Lisa Martin with John Furrier, in San Francisco. This is an internal R&D innovation off site that VMware does, lots of innovation going on here from engineers from all over the globe. We're pleased to welcome Joe Baguley, the CTO from EMEA, from VMware. Joe, welcome to theCUBE. >> Hi. >> So we've been having some great conversations this morning about this tremendous amount of innovation, I mean the potential is massive. Not just from Radio, but from all the other innovation programs that VMware has, really speaks very strongly to the culture of innovation that VMware has had. But of course all this innovation has to be able to be harnessed to deliver what customers need. Talk to us about that, you're in the field, field CTO. What is that connection with the innovation that happens within VMware? How do customers help influence that and vice versa? >> Yeah, I think we're very unique in the structure that we've put around that to drive that innovation over the years. So my job as field CTO is, I call it sort of 50, 50. So 50% is Chief Technology Officer, which is this kind of stuff for Radio and 50% is Chief Talking Officer, which is out with our customers and presenting at conferences, et cetera. But the general remit is connecting R&D in the field. And so for eight years now I've been connecting R&D in the field at VMware, I actually did at my previous company as well. And what we've done is, we've built a series of programs over the years to do that, and one of the biggest ones is the CTO Ambassadors. And so that was, you know, you get to a point, you get to a growth size, I've been here eight years, and suddenly you need someone else to help you because I can't be everywhere. And the original role was, back in the day I was hired to scale Steve Herrod, because Steve Herrod couldn't be in Europe all the time, I was like mini Steve Herrod that could be there when needed. But then eventually I can't be in every European country and our major regions as we get bigger and bigger, and we've grown dramatically. So the CTO Ambassadors is to support that. And that's really, we've got 140 of our top customer facing techies from around the globe in this program called the Ambassadors. And they have to be customer facing, and they have to be individual contributors, so like a pre-sales manager or something doesn't count. They're a massively active community, there's a whole bunch of them here at Radio as well. And their job is really that conduit, that source of information, and also a sounding board, a much shorter range sounding board for R&D. So if R&D want to get a feel of what's going on, they don't have to ask everyone they can bounce off the Ambassadors, which is part of what we do, and that makes it easier. >> So like a filter too, they're also also filtering input from the field, packaging it up for R&D. >> Totally. Yeah, and when you're at an organization of our scale, filtering is really important. Because obviously, you can't have every customer directly talking to every engineer, it's never going to work. (laughs) >> I mean another radio project stay right there, a machine learning based champion CTO to go through all the feedback. >> Yeah, so I started my career, with my previous company doing that, I was the filter. So I'd get a hundred questions a day from various people in the field, and 99 of those I'd bounce right back because I knew the answer. But there was the one that I was like, uh. Then I'd turn around to R&D and ask them. But the great thing was that R&D knew that if I was asking then it was a real question, it wasn't the 99. So the CTO Ambassadors, and what we do in Octo Global field is really a method of scaling that. >> I want to ask you about that because that's a great example of here reputation comes in. Because your reputation is on the line if you go back and pull the fire alarm, if you will, send too many lame requests back, you're going to be lame. So you've got to kind of check, balance there. So that begs the question, how do you do the filtering for the champions that work for you? Is there a high bar? Is there a certain line? Like being a kid, you've got to be this tall to ride the roller coaster. Is there criteria? Is there certification? Take us through the filtering there. >> The Ambassador program is a rotating nomination system. So essentially there's a two year tenure. So what happens is, if you're in the field and you want to be an ambassador, which is a really prestigious thing, then you nominate yourself or get nominated and then people vote on you and you put forward your case, et cetera. Essentially it's a democratic process based on your peers and other people in the company. And then after you're allowed a maximum of two years. Sorry, two tenures so you get four years, if that makes sense, I'm not confusing you. >> John: So term limits? >> Yeah there's term limits, right, we have term limits. And after two terms you have to go out for a year to give someone else a chance because otherwise it will just glub- >> It'll turn into the US government. (laughs) >> But no, it's important to maintain freshness, maintain diversity and all those kind of things. And so it comes back to that filter piece we were talking about before. The reputation is massive, of the CTO Ambassadors. I mean when we started this six years ago as a program, most of R&D were like, who are these Ambassador guys? What value are they going to add? Now, if you're in R&D, one of the best things you can say, if you want to get something done, is what the CTO Ambassador said. I mean, literally it is, you can go and we have- >> John: The routine approach to that. Talk about how you guys add in a new category. So, for instance kubernetes, we saw this years ago when KubeCon was started, theCUBE was there present at the creation of that trend we kind of got it right away. Now Gelsinger and the team sees this as a massive traction layer. So that would be an example, where we need an Ambassador. So do you like just create one or how does that work? >> They create themselves, that's the best thing. So we have an annual conference which is in February, held in Paolo Alto where we all get together along with all the chief technologists, which is the level below me. And the principles, which the most senior field people. So literally the best of the best get together. It's about 200 plus get together for a week. And we are an hour and a half on on one with Pat for example, so Pat's there with all of us in a room. But one of the sessions we do is the shark tank, and there's two of them. One of them is, come up with your really cool, crazy, wacky ideas, and the other one is the acquisition shark tank. So there we get the MNA team, include our E-staff sit in, and the Ambassadors, as teams, will come in and present. We think we should acquire, uh because that's making a big difference. The great thing is, not nine times out of 10 but probably seven times out of 10, the E-staff are going, yeah we know about that, when actually we can't really tell you what's going on but yeah we know about them. But there's the two or three times out of 10 that people are like, oh yeah, so tell me more about them. And it might be a company that's just coming up, it might be 2013 and there's this company called Docker that no one's heard of, but the Ambassadors are shouting about Docker, and saying it's a big, you know. So there's that- >> So white space is too emerging you can see it's a telemetry, literally feedback from the field to direct management on business strategy. >> And our customers are pushing our field in directions faster than maybe R&D get pushed if you know what I mean. >> You guys deserve a lot of credit because Pat Gelsinger was just on this morning with Lisa and me, and we were talking about that. He just came back from the Sales President's club cruise, and one of the comments he said was the sales executive said, hey, who does strategy? Because everything's fitting together beautifully. Which kind of highlights how radiance this all progresses, not like magic, there's a process here, and this kind of points to your job is to fit that pieces in, is that correct? >> Yeah. People always say, as a CTO do you all sit down once a week and talk about strategy? And that's not what you do. There's a hive mind, there's a continual interaction, there's conference calls, there's phone calls, there's meetings, there's get togethers of various different types, groups, and levels. And what happens is there's themes that emerge over that. And so my role specifically, as the EMEA CTO is to represent Europe, Middle East, and Africa's voice in those conversations. And maybe the nuances that we might have around particular product requirements or whatever, to remind people that maybe sit in a bubble in Silicon Valley. >> John: I'm sure you raised your hand on privacy and GDPR? (laughs) >> Just a couple of times, yeah. Yeah, now and again. >> The canary in the coal mine is a really big point that helps companies, if they're not listening to the signals coming in. >> Well you do, and you see a lot. There's a lot of the tech companies that I see, it's often defined as the three bubbles, or your Massimo Re Ferrè, who's now at Amazon. When he was here, did this fantastic blog post talking about the first bubble is Silicon Valley, and the second bubble is North America, and the third bubble is everywhere else. And so you kind of watch these things emerge. And my job is to jump over that pop into the Silicon Valley bubble before something happens and say, no you should be thinking about X, you should think about Y. At an event like Radio I've got a force multiplier because I've got 40 plus Ambassadors with me all popping up at all these little booths you see behind you, and the shows, and the talks. >> And the goal here is not to be a bubble, but to be completely one hive mind. >> And the diversity at VMware just blows my mind, it really does. I think a lot of people comment on it quite often, and in fact I've been asked to be a non-exec director of other companies, to help them advise on their culture. Which is not in tech, in culture, which is quite interesting. And so the diversity that we have here is really infusing people to innovate in a way that they've not done before. It's that diverse set of opinions really helps. >> Well it does. And this, from what we've heard, Radio is a very, there's a lot of internal competition, it's like a badge of honor to be able to respond to the call for papers, let alone get selected. Touch on the synergies, the symbiosis that I feel like I'm hearing between the things that are presented here, the CTO Ambassadors and the customers. Like maybe a favorite example of a product or service that came from, maybe a CTO Ambassador, to Radio, to market. >> Yeah, I'm just trying to think of any one specific one. There are always bits and pieces, and things here and there. I think I should have thought of that before I came on really. I think what you're looking at here is, it's much more about an informed conversation and so it's those ideas around the fact. And also, quite often someone will have a cool idea, and they'll go to the Ambassadors, can you find me five customers that want to try this? Bang, we've got it. So if you're out there on a customer, and someone comes to you as an ambassador and says, I've got a really cool thing I'd like you to try. It might be before, we have a thing called Fling, so it might even be before it's made a fling. You probably heard from Morney how that process goes. Then engage fast, because you're probably getting that conduit direct into the core of R&D. So a lot of the features that people see and functions and products et cetera, that people see. A lot of the work you see, we're doing with the next version if you realized our management platform, a lot of that has been driven by work that's been done by Ambassadors in the field, and what we're doing there. All the stuff you'll see, I've got my jacket over there with NANO EDGE written on it. A lot of the EDGE stuff that you see, a lot of the stuff around ESXi on Arm, a lot of the stuff around that is driven specifically around a particular product range. So a really good example is, a few years ago, probably around four, myself and Ray sat down and had a meeting in VMware Barcelona, with a retail customer, and the retail customer was talking about could we get them an STDC, but small enough to fit in every store. They didn't say that at the time, but that's how we kind of got to it. So that started off a whole process in our minds, and then I went back and we, the easiest actual way for me to do it was to then get a bunch of the Ambassadors to present that as one of their innovation ideas, which became NANO EDGE. I originally called it VX Nook, because we were going to do it on intel Nooks. (laughs) Unfortunately the naming committee wouldn't allow VX Nook, so it became NANO EDGE. And that drove a whole change within the company, I think within R&D. So if you think up until that point, four years ago, most of what we were doing was, how do we run things bigger and faster? It was all like Monster VM, remember that? All those kinds of things, right? How do we get these SAP HANA 12 terabyte VMs running? And really NANO EDGE was not necessarily a product, per se but it was more of a movement driven by a particular individual, Simon Richardson, who had got promoted to Principle as a result, through the Ambassador program. That was driven through our R&D to get them to think small as well as big, you know. So next time you're building that thing, how small can you run your SX, how small can we get an SX? >> John: Small, at scale. Which is EDGE, right? >> And, you know, so get small, at scale, which was EDGE. And so suddenly everyone starts talking about EDGE, and I'm like, hang on I've been talking about this for a while now, but we just didn't really call it that. And then along comes technology like Kubernetes, which is how do you manage thousands of small things. And it's kind of, these things come together. But yes, totally, you can almost say our EDGE strategy, and a lot of the early EDGE work was done and driven out of stuff that was done from CTO Ambassadors. It's just one of the examples. >> What are some of the Kubernetes service mesh? Because one of the things we heard from Pat, and we've heard this before, but most recently at Dell Technologies World, in the last couple of weeks, was don't look down, look up. Which basically means we're automating the infrastructure. I get that, I've covered ad nauseam. But looking up the stack means you're talking about kubernetes app developers, you've got cloud native, you've got services meshes, microservices, new kinds of challenges around instrumentation. How are you guys inside Radio looking at that trend? Because there's some commercial impact, You've got Heptio, you've got Craig and the team, some of the original guys. >> Yeah, yeah. >> As well as you have a future state coming out, with state, pun intended, data, stateless. (laughs) These are new dynamics. >> Yeah, yeah. >> What's the R&D take on this? >> So there's two ways that I really talk to people about this. The first one is, I've got a concept that I talk about called application chromatography. Which sounds mental, but you remember from high school probably, chromatography was where you had that really special paper and you put the dot of liquid on and it spread it to all it's constituent parts. That's actually what's happening with our applications right now. So, we've gone through a history of re-platform. You know, mainframe, blah blah blah blah blah. So then when we got to x86, everything's on x86, along comes cloud, and as you know John, for the last 10 years it's been everything's going to cloud because we think that's the next platform. It's not, but then everything's not going to SAS, it's not all going to paths, it's not all going to Functions, it's not all going to containers. What you're seeing is those applications are coming off that one big server, and they're spreading themselves out to the right places. So I talk to customers now and they say, okay, well actually I need a management plan, and a strategy and an architecture for infrastructure as a service, containers as a service, functions as a service platform as a service and SAS, and I need a structure for that on premises and off premises. So that's truly driving R&D thinking is not how do we help our customers get from one of those to the other? They're going to all of them. >> It sounds like a green screen for media. >> It is, and then the other side of that is I've just had a conversation with some of the best, you know, what these events are like? Some of the best conversations in the water cooler, in the- >> In the hallway, yup exactly. >> I've just had a fascinating conversation with one of our guys has been talking about, oh it's really cool if we got kubernetes cause I could use it right down at the edge. I could use it to manage thousands as a tiny EDGE things. And as I'm talking to him and sort of saying, you know what he's doing, I suddenly went, hang on a second, how does a developer talk to that? He's like, well I've not really thought about that. I said, well that's your problem. We need to stop thinking about things from how can that framework help me? But how can I extend that framework? And so a lot of that- >> Moving beyond just standing up kubernetes, for what purpose? Or is that what you know, the why, what? >> So if the developers there, it shouldn't be all. I'm going to use this new framework to solve my problem or the EDGE if an R&D person would, but people like myself are there to drive them to think of the bigger picture. So ultimately at some point a developer in the future is going to want to sit there and through an API, push out software SQL server, a bit of Mongo over here, some stuff on AWS, go and use the service on our Azure at the same time pushing stuff into their own data center and maybe push a container to every store if they're a retailer and they want to do that through one place. That's what we're building. And you know, driving that, all these bits and pieces you see behind you pulling those all together into this sort of consistent operations model. As I'm sure you've heard many of- >> And it's dynamics not static, so it's not like provisioning the old way. You got to track what's being turned on and off because how do you log off? What goes turns on? What services get turned on? Turned off, turned on. >> If you don't get a theme of really, I suppose not only Radio, but our industry of the last few years, people have always said if that cliche change is constant, right? Oh, change is constant. Yet still architects build systems that are static, right? You guys that just, I'm designing an architect in this new system for the next three years. I'm like, that's stupid. What you need to do is design a system that you know is going to change before you've even finished starting it. More or less started going half way through it. So actually, as I see, I was in a fantastic session yesterday with the Architects around ESXi and VCenter, which might be boring to most, but where we architecting that for scale at a huge way. >> Well, I think that's the key thing I mean this is, first of all, we'd love this conversation because, if you can make it programmable with API and have data available, that's the architecture because it's programmable, it's not static. So you let it morph into however the application, because I think I mentioned green screen, you know chroma keys as we have those concepts here, but that's what you're saying. The apps are going to have this notion of, I need an app right now and then it goes away. Services are going to be provisioning and turning on and off. >> There is a transience, there's a transience to infrastructure, there's a transience to applications, there's a transience to components that traditional mechanisms aren't built to do. So if you look at actually, what are we building here? And what's that sort of hive mind message? It's how do we provide that platform going forward that supports transience? that allows customers to come, I mean people used to use the term agile, but it's been over years and it's not right. It's the fact that literally it's a situation of constant change. And what your deploying onto, it's constantly changing and what you're deploying is constantly changing. So we're trying to work out how do we put that piece in the middle, that is also changing but allows you some kind of constancy in what you're doing, right? So we can plug new things in the bottom, a new cloud here, a new piece of software there, a new piece of hardware there or whatever. And at the same time, there's new ways of doing architecture coming on top. That's the challenge of this, the software defined data centers, almost like an operating system for clouds or the future operating system for all apps on all clouds and all of- >> It's a systems thinking for sure, absolutely. >> Let's put your Chief Talking Officer hat on for a second as we look- >> I thought I've been doing that for the last fifteen minutes. (laughs) >> At VMWorld 2019, which is just around the corner. Any cool ANEA customers that are going to be on stage that we should be excited to hear about it? >> Actually, I was having a meeting yesterday morning about that, so I can't really say, but there's some exciting stuff we're lining up right now. We're obviously now is the time we start thinking about the keynotes, now at the time you start thinking about who's on stage. Myself and a few others are responsible for what those demos are, you know the cool demos you see on stage every year. So we literally had the meeting yesterday morning at Radio to discuss what's going to be the wow at VMWorld this year. So I'm not going to give anything away to you. I'll just say make sure you're there to watch it because it's going to be good. And we're also making sure there's a big difference between what we're doing in Moscone now and what we're going to be doing it in Barcelona when we- >> And when expand theCUBE outside of the United States certainly, we'd love to have you guys plug in and localize some of these unique challenges. Like you said, I agree bubble now the west of the world has different challenges content different. >> Definitely, I think to that end, multicloud is probably more of a thing in Europe than it was necessarily in, in North America for a longer time because those privacy laws you talked about before, people have always been looking at the fact that maybe they had to use a local cloud for some things. You know, a German cloud run by German people in a German data center and they could use another cloud like Amazon for other things. And you know, we have UK cloud who provide a specific government based cloud, et cetera. Whereas in America there was, you could use an American cloud and that was fine. So I think actually in Europe we've already been at the forefront of that multicloud thinking for a while. So it's worth watching. >> It is worth watching, I wish we had more time to, so you're just going to have to come back. >> Definitely, anytime tell me when. >> We look forward to seeing you at VMWorld. We thank you for sharing some insights with John and me on theCUBE today. >> Cool, thank you. >> For John Ferrier, I'm Lisa Martin. You're watching theCUBE's exclusive coverage of VMware Radio 2019, thanks for watching. (upbeat music)

>> Female Voice: From San Francisco, it's theCUBE, covering VMware RADIO 2019, brought to you by VMware. >> Welcome to theCUBE's exclusive coverage of VMware RADIO 2019, Lisa Martin with John Furrier in San Francisco, talking all sorts of innovation in this innovation long history culture at VMware, welcoming back to theCUBE, Mornay Van Der Walt, VP of R&D in the Explorer Group. Mornay, thank you for joining John and me on theCUBE today. >> Thank you for having me. >> So, I got to start with Explorer Group. Super cool name. >> Yeah. >> What is that within R&D? >> So the origins of the Explorer Group. I've had many roles at VMware, and I've been fortunate enough to do a little bit of everything. Technical marketing; product development; business development; one of the big things I did before the Explorer group was created was actually EVO:RAIL. I was the founder of that, pitched that idea. Raghu and Ray and Pat were very supportive. We took that to market, took it to (inaudible), handed that off to Dell EMC, the rest is history, right? And then was, "what's next?" So Ray and me look at some special projects, go and look at IoT, go and look at Telemetry, and did some orders for them, and then said "Alright, why don't you look at all our innovation programs." Because beyond RADIO, we actually have four other programs. And everyone, was -- RADIO gets a lot of airtime and press, but it's really the collective. It's the power of those other four programs that support RADIO that allow us to take an idea from inception to an impactful outcome. So hence the name, the Explorer Group. We're going out there, we're exploring for new ideas, new technologies, what's happening in the market. >> Talk about the R&D management style. You've actually got all these-- RADIO's one-- kind of a celebration, it's kind of the best of the best come together, with papers and submissions. Kind of a symposium meets kind of a, you know, successive end for all the top engineers. There's more, as you've mentioned. How does all of it work? Because, in this modern era of distributed teams, decentralization, decisions around business, decisions on allocating to the portfolio, what gets invested, money, spend, how do you organize? Give a quick minute to explain how R&D is structured. >> So, obviously, we have the BUs structured-- well there's PCS, Raghu and Rajeev head that up. And then we've got the OCTO organization, which Ray O'Farrell heads up. And the business, you know, it's innovating every day to get products out the door, right, and that's something that we've got to be mindful of because, I mean, that's ultimately what's allowing us to get products into the hands of our customers, solving tough problems. But then in addition to that, we want to give our engineers an avenue to go and explore, and, you know, tinker on something that's maybe related to their day job, or completely off, unrelated to their day job. The other thing that's important is, we also want to give, because we're such a global R&D, you know, our setup globally, we want to give teams the opportunity to work together, collaborate together, get that diversity of thought going, and so a lot of times, if we do a Hackathon, which we call a Borathon, we actually give bonus points if teams pull from outside of their business units. So you've got an idea, well, let's make it a diverse idea in terms of thought and perspective. If you're from the storage business unit, bring in folks from the network business unit. Bring in folks from the cloud business unit. Maybe you've partnered with some folks that are in IT. It's very, you know, sometimes engineers will go, "Ah, it's just R&D that's innovating." But in reality, there's great innovation coming out of our IT department. There's great innovation coming out of our global support organization. Our SEs that are on the front lines, sometimes are seeing the customers' pain points firsthand, and then they bring that back, and some of that makes it into the product. >> How much of R&D is applied R&D, which is kind of business unit aligned, or somewhat aligned, versus the wacky, crazy ideas: "Go solve a big, hairy problem", that's out there, that's not, kind of, related to the current product sets? >> Ah, that's tough to put an actual number on it, >> John: Well ballpark, I mean. >> But if I just say, like, if I had to just think about budgets and that, it's probably ten to fifteen percent is the wacky stuff, that's, you know, not tied to a roadmap, that's why we call it "off-road innovation", and the five programs that my Explorer Group ultimately leads is all about driving that off-road innovation. And eventually you want to find an on-ramp, >> Yeah. >> to a roadmap, you know, that's aligned to a business unit, or a new emerging, you know, technology. >> How does someone come up with an idea and say, "Hey, you know, I want to do this"? Do they submit, like, a form? Is there a proposal? Who approves it? I mean, do you get involved? How does that process work? >> So that's a good question. It really depends on the engineer, right? You take someone who's just a new college grad, straight out of, you know, college. That's why we have these five programs. Because some of these folks, they've got a good idea, but they don't really know how to frame it, pitch it. And so if you've got a good idea, and let's say, this is your first rodeo, so to speak, We have a program called TechTalks where it allows you to actually go and pitch your idea; get some feedback. And that's sometimes where you get the best feedback, because you go and, you know, present your idea, and somebody will come back and say, "Well, you know, have you met, you know, Johnny and Sue over there, in this group? They're actually working on something similar. You should go and talk to them, maybe you guys can bring your ideas together." Folks that are, you know, more seasoned, you know, longer tenure, sometimes they just come up, and-- "I'm going to pitch an idea to xLabs," and for xLabs, for example --that's an internal incubator-- there is, like, a submissions process. We want to obviously make sure, that, you know, your idea's timing in the market's correct, we've got limited funding there so we're going to make sure we're really investing on the right, you know, type of ideas. But if you don't want to go and pitch your idea and get feedback, go and do a Borathon. Turn an idea into a little prototype. And we see a lot of that happening, and some of the greatest ideas are coming from our Borathons, you know? And it's also about tracking the journey. So, we have RADIO here today, we have mentioned xLabs, TechTalks, we have another program called Flings. Some of our engineers are shipping product, and they've got an idea to augment the product. They put it out as a Fling, and our customers and the ecosystem download these, and it augments the product. And then we get great feedback. And then that makes it back into the product roadmap. So there's a lot of different ways to do it, and RADIO, the process for RADIO, there's a lot of rigor in it. It's, like, it's run as a research program. >> Lisa: It's a call for papers, right? >> Call for papers, you know, there's a strict format, it's got to be, you know, this many pages; if you go over about one line, you're sort of, disqualified, so to speak. And then once you've got those papers, like this year we had 560 papers be submitted, out of those 560, 31 made it onto mainstage, and another 61 made it as posters, as you can see in the room we're sitting in. >> I have an idea. Machine learning should get all those papers. (laughs) I mean, that's-- >> Funny you say that. We actually have, one of our engineers, Josh Simons, is actually using machine learning to go back in time and look at all the submissions. So idea harvesting is something we're paying a lot of attention to, because you submit an idea, >> Interesting. >> the market may not be right for it, or reality is, I just don't have a budget to fund it if it's an xLab. >> John: So it's like a Google search for your, kind of, the indexing all those workers. >> Internally, yeah, and sometimes it's-- there's a great idea here, you merge that with another idea from another group or another geo, and then you can actually go and fund something. >> Well, that's important because timing is critical, in these early-- most stuff can be early in just incubation, gestation period for that tech or concept, could be in play because the computer-- all the new things, right? >> Correct. And, do you actually have the time? You're an engineer working on a release, the priority is getting that release out the door, right? >> (laughs) >> So, put the idea on the back burner, come off the release, and then, you know, get a couple of colleagues together and maybe there's a Borathon being held and you go and move that idea forward that way. Or, it's time for RADIO submissions, get a couple of colleagues together and submit a RADIO paper. So we want to have different platforms for our engineers to submit ideas outside of their day job. >> And it sounds like, the different programs that you're talking about: Flings, xLab, Borathon, RADIO, what it sounds like is, there isn't necessarily a hierarchy that ideas have to go through. It really depends on the teams that have the ideas, that are collaborating, and they can put them forward to any of these programs, >> Correct, yeah. >> and one might get, say, rejected for RADIO, but might be great for a Borathon or a Fling? >> Correct. >> So they've got options there, and there's multiple committees, I imagine? Is that spearheaded out of Ray's OCTO group, >> Yep. >> that's helping to make the selections? Tell us a little bit about that process. >> Sure, so. That's a great point, right? To get an idea out the door, you don't always have to take the same pathway. And so one thing we started tracking was these innovation journeys that all take different pathways. We just published an impact report on innovation for FY19, and we've got the vSAN story in there, right? It was an idea. A group of engineers had an idea, like, in 2009, and they worked on their idea a little bit-- it first made it to RADIO in 2011. And then they came back in 2013, and, sort of, the rest is history, you know. vSAN launched in 2014. We had a press release this week for Carbon Avoidance Meter. It was an idea that actually started as a calculator many years ago. Was used, and then sort of died on the vine, so to speak? One of our SEs said, "You know, this is a good idea. I want to evolve this a little bit further." Came and pitched an xLabs idea, and we said, "Alright, we're going to fund this as an xLabs Lite. Three to six months project, limited funding, work on one objective --you're still doing your day job-- move the project forward a little bit." Then Nicola Acutt, our Sustainability VP, got involved, wanted to move the idea a little bit further along, came back for another round of funding through an xLabs Lite, and then GSS, with their Skyline platform, picked it up, and that's going to be integrated in the coming months into Skyline, and we're going to be able to give our customers a carbon, sort of, readout of their data center. And then they'll be able to, you know, map that, and get a bigger picture, because obviously, it's not just the servers that are virtualized, there's cooling in the data center plants, and all these other factors that you've got to, you know, take into account when you want to look at your carbon footprint for your facility. So, we have lots of examples of how these innovation pathways take different turns, and sometimes it's Team A starting with an idea, Team B joins in, and then there's this convergence at a particular point, and then it goes nowhere for a couple of months, and then, a business unit picks it up. >> One of the things that's come out-- Pat Gelsinger mentioned that a theme outside of the normal product stuff is how people do work. There's been some actual R&D around it, because you guys have a lot of distributed, decentralized operations in R&D because of the global nature. >> Yeah. >> How should companies and R&D be run when the reality is that developers could be anywhere? They could be at a coffee shop, they could be overseas, they could be in any geography, how do you create an environment where you have that kind of innovation? Can you just share some of the best practices that you guys have found? >> I'm not sure if there's 'best practices', per se, but to make sure that the programs are open and inclusive to everybody on the planet. So, I'll give you some stats. For example, when RADIO started in the early days, we were founded in Palo Alto. It was a very Palo Alto-centric company. And for the first few years, if you looked at the percentage of attendees, it was probably over 75% were coming from Palo Alto. We've now over the years shifted that, to where Palo Alto probably represents about 44%, 16% is the rest of North America, and then the balance is from across the globe. And so that shift has been deliberate, obviously that impacts the budget a little bit, but in our programs, like a Borathon, you can hack from anywhere. We've got a lot of folks that are remote office workers, using, you know, collaborative tools, they can be part of a team. If the Borathon's happening in China, it doesn't stop somebody in Palo Alto or in Israel or in Bulgaria, participating. And, you know, that's the beautiful nature of being global, right? If you think about how products get out of the door, sometimes you've got teams and you are literally following the sun, and you're doing handoff, you know, from Team A to B to C, but at the end of the day you're delivering one product. And so that's just part of our culture, I mean, everybody's open to that, we don't say, "Oh, we can't work with those guys because they're in that geo-location." It's pretty open. >> This is also, really, an essential driver, and I think I saw last year's RADIO, there were participants from 25+ countries. But this is an essential-- not only is VMware a global company, but many of your customers are as well, and they have very similar operating models. So that thought diversity, to be able to build that into the R&D process is critical. >> Absolutely. And also, think about, you know, when you're going to Europe. Smaller borders, countries, you deploy technology differently. And so, you want to have that diversity in thought as well, because you don't just want to be thinking, "Alright, we're going to deploy a disaster recovery product in North America where they can fail over from, you know, East Coast to West Coast. You go to Europe, and typically you're failing over from, you know, site A to site B, and they're literally three or four miles apart. And so, just having that perspective as well, is very important. And we see that, you know, when we release certain products, you'll get, you know, better uptick in a certain geo, and then, "Why is it stalling over here?" well it's, sometimes it's cultural, right? How do you deploy that technology? Just because it works in the US, doesn't mean it's going to work in Europe or in APJ. >> How was your team involved in the commercialization? You mentioned vSAN and the history of that, but I'm just wondering, looking at it from an investment standpoint of deciding which projects to invest in, and then there's also the-- if they're ready to go to market, the balance of "How much do we need to invest in sales and marketing to be able to get this great idea-- because if we can't market it and sell it, you know, then there's obviously no point." So what's that balance like, within your organization, about, "how do we commercialize this effectively, at scale"? >> So that is ultimately not the responsibility of my group. We'll incubate ideas, like, for example, through an xLabs project. And, you know, sometimes we'll get to a point and we'll work, collaborate with a business unit, and we'll say, "Alright, we feel this project's probably a 24 months project", if it's an xLabs Full. So these folks are truly giving up their day job. But at the end of the day, you want to have an exit and when we say exit, what does that exit mean? Is that an exit into a business unit? Are you exiting the xLabs project because we're now out of funding? You know, think about a VC, I'm going to fund you to, you know, to a particular point; if there is no market traction, >> Right. >> we may, you know, sunset the project. And, you know, so our goal is to get these ideas, select which ones we want to invest in, and then find a sort of off-ramp into a business unit. And sometimes there'll be an off-ramp into a business unit, and the project goes on for a couple of months, and then we make a decision, right? And it's not a personal decision, it's like, "Well we funded that as an xLabs; we're now going to shut it down because, you know, we're going to go and make an acquisition in this space. And with the talent that's going to come onboard, the talent that was working on this xLab project, we can push the agenda forward." >> John: You have a lot of action going on so you move people around. >> Exactly. >> Kind of like the cloud, elastic resource, yeah? (laughs) >> So, then, some of these things, because xLabs is only a two-year-old, you know, we haven't had things exit yet that are, you know, running within a business unit that we're seeing this material impact. You know, from a revenue point of view. So that's why tracking the journeys is very important. And, you know, stay tuned, maybe in about three or four years we'll have this, similar, you know, interview, and I'll be able to say, "Yeah, you know, that started as an xLab, and now it's three years into the market, and look at the run rate. >> So there's 31-- last question for you-- there's 31 projects that were presented on mainstage. Are there any that you could kind of see, early on, "ooh", you know, those top five? Anything that really kind of sticks out-- you don't have to explain it in detail, but I'm just curious, can you see some of that opportunity in advance? >> Absolutely. There's been some great papers up on mainstage. And covering, you know, things on the networking side, there's a lot of innovation going in on the storage side. If you think about data, right, the explosion of data because of edge computing, how are you going to manage that data? How are you going to take, you know, make informed decisions on that data? How can you manipulate that data? What are you going to have to do from a dedupe point of view, or a replication point of view, because you want to get that to many locations, quickly? So, I saw some really good papers on data orchestration, manipulation, get it out to many places, it can take an informed decision. I saw great-- there was a great paper on, you know, you want to go and put something in AWS. There's a bull that you get at the end of the month, right? Sometimes those bulls can be a little bit frightening, right? You know, what can you do to make sure that you manage those bulls correctly? And sometimes, the innovation has got nothing to do with the product per se, but it has to do with how we're going to develop. So we have some innovation on the floor here where an engineer has looked at a different way of, basically, creating an application. And so, there's a ton of these ideas, so after RADIO, it doesn't stop there. Now the idea harvesting starts, right? So yes, there were 31 papers that made it onto mainstage, 61 that are posters here. During that review process, and you asked that question earlier and I apologize, I didn't answer it-- you know, when we look at the papers, there's a team of over 100 folks from across the globe that are reviewing these papers. During that review process, they'll flag things like "This is not going to make it onto mainstage, but the idea here is very novel; we should send this off to our IP team," you know. So this year at RADIO, there were 250 papers that were flagged for further followup with our IP team, so, do we go and then file an IDF, Invention Disclosure Form, do those then become patents, you know? So if we look at the data last year, it was 210. Out of those 210, 74 patents were filed. So there's a lot of work that now will happen post-RADIO. Some of these papers come in, they don't make it onto mainstage; they might become a poster. But at the same time they're getting flagged for a business unit. So from last year, there were 39 ideas that were submitted that are now being mapped to roadmap across the BUs. Some of these papers are great for academic research programs, so David Tennenhouse's research group will take these papers and then, you know, evolve them a little bit more, and then go and present them at academic conferences around the world. So there's a lot of, like, the "what's next?" aspect of RADIO has become a really big deal for us. >> The potential is massive. Well, Mornay, thank you so much for joining John and me, >> Thank you. >> and I've got to follow xLabs, there's just a lot of >> (laughs) >> really, really, innovative things that are so collaborative, coming forward. We thank you for your time. >> Thank you. >> For John Furrier, I'm Lisa Martin; you're watching theCUBE, exclusive coverage of VMware RADIO 2019, from San Francisco. Thanks for watching.

>> live from Las Vegas. It's the queue covering Dell Technologies. World twenty nineteen. Brought to you by Dell Technologies and its ecosystem partners. >> The one Welcome to the Special Cube Live coverage here in Las Vegas with Dell Technologies World 2019. I'm John Furrier with Dave Vellante breaking down day one of three days of wall the wall Coverage - 2 Cube sets. Uh, big news today and dropping here. Dell Technology World's series of announcements Cloud ability, unified work spaces and then multi cloud with, uh, watershed announced with Microsoft support for VMware with Azure are guests here theCUBE alumni that Seo, senior leader of'Em Where Sanjay *** and such a great to see you, >> John and Dave always a pleasure to be on your show. >> So before we get into the hard core news around Microsoft because you and Satya have a relationship, you also know Andy Jassy very well. You've been following the Clouds game in a big way, but also as a senior leader in the industry and leading BM where, um, the evolution of the end user computing kind of genre,  that whole area is just completely transformed with mobility and cloud kind of coming together with data and all this new kinds of applications. The modern applications are different. It's changing the game on how end users, employees, normal people use computing because some announcement here on their What's your take on the ever changing role of cloud and user software? >> Yeah, John, I think that our vision , as  you know, it was the first job I came to do at VMware almost six years ago, to run and use a computing. And the vision we had at that time was that you should be able to work at the speed of life, right? You and I happen to be on a plane at the same time  yesterday coming here, we should be able to pick our amps up on our devices. You often have Internet now even up at thirty thousand feet. In the consumer world, you don't lug around your CDs, your music, your movies come to you. So the vision of any app on any device was what we articulated with the digital workspace We. had Apple and Google very well figured out. IOS later on Mac,  Android,  later on chrome . The Microsoft relationship in end use the computing was contentious because we overlapped. They had a product, PMS and in tune. But we always dreamed of a day. I tweeted out this morning that for five and a half years I competed with these guys. It was always my dream to partner with the With Microsoft. Um, you know, a wonderful person, whom I respect there, Brad Anderson. He's a friend, but we were like LeBron and Steph Curry. We were competing against each other. Today everything changed. We are now partners. Uh, Brad and I we're friends, we'll still be friends were actually partners  now why? Because we want to bring the best of the digital workspace solution VMware brings workspace one to the best of what Microsoft brings in Microsoft 365 , active directory, E3 capabilities around E. M. S and into it and combined those together to help customers get the best for any device. Apple, Google and Microsoft that's a game changer. >> Tell about the impact of the real issue of Microsoft on this one point, because is there overlap is their gaps, as Joe Tucci used to say, You can't have any. There's no there's no overlap if you have overlapped. That's not a >> better to have overlapped and seems right. A gaps. >> So where's the gaps? Where this words the overlapping cloud. Next, in the end user world, >> there is a little bit of overlap. But the much bigger picture is the complementarity. We are, for example, not trying to be a directory in the Cloud That's azure active directory, which is the sequel to Active Directory. So if we have an identity access solution that connect to active directory, we're gonna compliment that we've done that already. With Octo. Why not do that? Also inactive Directory Boom that's clear. Ignored. You overlap. Look at the much bigger picture. There's a little bit of overlap between in tune and air Watch capabilities, but that's not the big picture. The big picture is combining workspace one with E. M s. to allow Office 365 customers to get conditional access. That's a game, so I think in any partnership you have to look past, I call it sort of these Berlin Wall moments. If the U. S and Soviet Union will fighting over like East Germany, vs West Germany, you wouldn't have had that Berlin wall moment. You have to look past the overlaps. Look at the much bigger picture and I find the way by which the customer wins. When the customer wins, both sides are happy. >> Tearing down the access wall, letting you get seamless. Access the data. All right, Cloud computing housely Multi cloud announcement was azure something to tell on stage, which was a surprise no one knew was coming. No one was briefed on this. It was kind of the hush hush, the big news Michael Delll, Pat Girl singer and it's nothing to tell up there. Um, Safia did a great job and really shows the commitment of Microsoft with the M wear and Dell Technologies. What is this announcement? First, give us your take an analysis of what they announced. And what does it mean? Impact the customers? >> Yeah, listen, you know, for us, it's a further That's what, like the chess pieces lining up of'Em wars vision that we laid up many years for a hybrid cloud world where it's not all public cloud, it isn't all on premise. It's a mixture. We coined that Tom hybrid loud, and we're beginning to see that realize So we had four thousand cloud providers starting to build a stack on VM, where we announced IBM Cloud and eight of us. And they're very special relationships. But customers, some customers of azure, some of the retailers, for example, like Wal Mart was quoted in the press, released Kroger's and some others so they would ask us, Listen, we're gonna have a way by which we can host BMO Workloads in there. So, through a partnership now with Virtue Stream that's owned by Dell on DH er, we will be able to allow we, um, where were close to run in Virtue Stream. Microsoft will sell that solution as what's called Azure V M, where solutions and customers now get the benefit of GMO workloads being able to migrate there if they want to. Or my great back on the on premise. We want to be the best cloud infrastructure for that multi cloud world. >> So you've got IBM eight of us Google last month, you know, knock down now Azure Ali Baba and trying you. Last November, you announced Ali Baba, but not a solution. Right >> now, it's a very similar solutions of easy solution. There's similar what's announced with IBM and Nash >> So is it like your kids where you loved them all equally or what? You just mentioned it that Microsoft will sell the VM wear on Azure. You actually sell the eight of us, >> so there is a distinction. So let me make that clear because everything on the surface might look similar. We have built a solution that is first and preferred for us. Called were MacLeod on a W s. It's a V m er manage solution where the Cloud Foundation stack compute storage networking runs on a ws bare metal, and V. Ember manages that our reps sell that often lead with that. And that's a solution that's, you know, we announced you were three years ago. It's a very special relationship. We have now customer attraction. We announce some big deals in queue, for that's going great, and we want it even grow faster and listen. Eight of us is number one in the market, but there are the customers who have azure and for customers, one azure very similar. You should think of this A similar to the IBM ah cloud relationship where the V C P. V Partners host VM where, and they sell a solution and we get a subscription revenue result out of that, that's exactly what Microsoft is doing. Our reps will get compensated when they sell at a particular customer, but it's not a solution that's managed by BM. Where >> am I correct? You've announced that I think a twenty million dollars deal last quarter via MacLeod and A W. And that's that's an entire deal. Or is that the video >> was Oh, that was an entirely with a customer who was making a big shift to the cloud. When I talked to that customer about the types of workloads, they said that they're going to move hundreds off their APs okay on premise onto via MacLeod. And it appears, so that's, you know, that's the type of cloud transformation were doing. And now with this announcement, there will be other customers. We gave an example of few that Well, then you're seeing certain verticals that are picking as yours. We want those two also be happy. Our goal is to be the undisputed cloud infrastructure for any cloud, any cloud, any AP any device. >> I want to get your thoughts. I was just in the analysts presentation with Dell technology CFO and looking at the numbers, the performance numbers on the revenue side Don Gabin gap our earnings as well as market share. Dell. That scales because Michael Delll, when we interviewed many years ago when it was all going down, hinted that look at this benefits that scale and not everyone's seeing the obvious that we now know what the Amazon scale winds so scale is a huge advantage. Um, bm Where has scale Amazon's got scale as your Microsoft have scales scales Now the new table stakes just as an industry executive and leader as you look at the mark landscape, it's a having have not world you'd have scale. You don't If you don't have scale, you're either ecosystem partner. You're in a white space. How do companies compete in this market? Sanjay, what's your thoughts on I thinkit's >> Jonah's? You said there is a benefit to scale Dell, now at about ninety billion in revenue, has gone public on their stock prices. Done where Dellvin, since the ideal thing, the leader >> and sir, is that point >> leader in storage leader inclined computing peces with Vienna and many other assets like pivotal leaders and others. So that scale VM, Where about a ten billion dollar company, fifth largest software company doing verywell leader in the softer to find infrastructure leader, then use a computing leader and softer, defined networking. I think you need the combination of scale and speed, uh, just scale on its own. You could become a dinosaur, right? And what's the fear that every big company should have that you become ossified? And I think what we've been able to show the world is that V M wear and L can move with scale and speed. It's like having the combination of an elephant and a cheetah and won and that to me special. And for companies like us that do have scaled, we've to constantly ask ourselves, How do we disrupt ourselves? How do we move faster? How do we partner together? How do we look past these blind spots? How do we pardon with big companies, small companies and the winner is the customer. That's the way we think. And we could keep doing that, you'll say so. For example, five, six years ago, nobody thought of VMware--this is going before Dell or EMC--in the world of networking, quietly with ten thousand customers, a two million dollar run rate, NSX has become the undisputed leader and software-defined networking. So now we've got a combination of server, storage and a networking story and Dell VMware, where that's very strong And that's because we moved with speed and with scale. >> So of course, that came to an acquisition with Nice Sarah. Give us updates on the recent acquisitions. Hep C e o of Vela Cloud. What's happening there? >> Yeah, we've done three. That, I think very exciting to kind of walk through them in chronological order about eighteen months ago was Velo Cloud. We're really excited about that. It's sort of like the name, velocity and cloud fast. Simple Cloud based. It is the best solution. Ston. How do we come to deciding that we went to talk to our partners like t other service providers? They were telling us this is the best solution in town. It connects to the data center story to the cloud story and allows our virtual cloud network to be the best softer. To find out what you can, you have your existing Mpls you might have your land infrastructure but there's nobody who does softer to find when, like Philip, they're excited about that cloud health. We're very excited about that because that brings a multi cloud management like, sort of think of it like an e r P system on top of a w eso azure to allow you to manage your costs and resource What ASAP do it allows you to manage? Resource is for materials world manufacturing world. In this world, you've got resources that are sitting on a ws or azure. Uh, cloud held does it better than anybody else. Hefty. Oh, now takes a Cuban eighty story that we'd already begun with pivotal and with Google is you remember at at PM world two years ago. And that's that because the founders of Cuban eighties left Google and started FTO. So we're bringing that DNA we've become now one of the top two three contributors to communities, and we want to continue to become the de facto platform for containers. If you go to some of the airports in San Francisco, New York, I think Keilani and Heathrow to you'LL see these ads that are called container where okay, where do you think the Ware comes from Vienna, where, OK, and our goal is to make containers as container where you know, come to you from the company that made vmc possible of'Em where So if we popularized PM's, why not also popularised the best enterprise contain a platform? That's what helped you will help us do >> talk about Coburn at ease for a minute because you have an interesting bridge between end user computing and their cloud. The service is micro. Services that are coming on are going to be powering all these APS with either data and or these dynamic services. Cooper, Nettie sees me the heart of that. We've been covering it like a blanket. Um, I'm gonna get your take on how important that is. Because back Nelson, you're setting the keynote at the Emerald last year. Who burn it eases the dial tone. Is Cooper Netease at odds with having a virtual machine or they complimentary? How does that evolving? Is it a hedge? What's the thoughts there? >> Yeah, First off, Listen, I think the world has begun to realize it is a world of containers and V ems. If you looked at the company that's done the most with containers. Google. They run their containers in V EMS in their cloud platform, so it's not one or the other. It's vote. There may be a world where some parts of containers run a bare metal, but the bulk of containers today run and Beyonce And then I would say, Secondly, you know, five. Six years ago, people all thought that Doctor was going to obliterate VM where, But what happened was doctors become a very good container format, but the orchestration layer from that has not become daugher. In fact, Cuban Eddie's is kind of taking a little of the head and steam off Dr Swarm and Dr Enterprise, and it is Cooper Navy took the steam completely away. So Senses Way waited for the right time to embrace containers because the obvious choice initially would have been some part of the doctor stack. We waited as Borg became communities. You know, the story of how that came on Google. We've embraced that big time, and we've stated a very important ball hefty on All these moves are all part of our goal to become the undisputed enterprise container platform, and we think in a multi cloud world that's ours to lose. Who else can do multi cloud better than VM? Where may be the only company that could have done that was Red Hat. Not so much now, inside IBM, I think we have the best chance of doing that relative. Anybody else >> Sanjay was talking about on our intro this morning? Keynote analysis. Talking about the stock price of Dell Technologies, comparing the stock price of'Em where clearly the analysis shows that the end was a big part of the Dell technologies value. How would you summarize what v m where is today? Because on the Kino there was a Bank of America customers. She said she was the CTO ran, she says, Never mind. How we got here is how we go floors the end wars in a similar situation where you've got so much success, you always fighting for that edge. But as you go forward as a company, there's all these new opportunities you outlined some of them. What should people know about the VM? We're going forward. What is the vision in your words? What if what is VM where >> I think packed myself and all of the key people among the twenty five thousand employees of'Em are trying to create the best infrastructure company of all time for twenty one years. Young. OK, and I think we have an opportunity to create an incredible brand. We just have to his use point on the begins show create platforms. The V's fear was a platform. Innocent is a platform workspace. One is a platform V san, and the hyper convert stack of weeks right becomes a platform that we keep doing. That Carbonetti stuff will become a platform. Then you get platforms upon platforms. One platforms you create that foundation. Stone now is released. ADelle. I think it's a better together message. You take VX rail. We should be together. The best option relative to smaller companies like Nutanix If you take, you know Veum Where together with workspace one and laptops now put Microsoft in the next. There's nobody else. They're small companies like Citrix Mobile. I'm trying to do it. We should be better than them in a multi cloud world. They maybe got the companies like Red Hat. We should have bet on them. That said, the end. Where needs toe also have a focus when customers don't have Dale infrastructure. Some people may have HP servers and emcee storage or Dell Silvers and netapp storage or neither. Dellery emcee in that case, usually via where, And that's the way we roll. We want to be relevant to a multi cloud, multi server, multi storage, any hardware, any cloud. Any AP any device >> I got. I gotta go back to the red hat. Calm in a couple of go. I could see you like this side of IBM, right? So So it looks like a two horse race here. I mean, you guys going hard after multi cloud coming at it from infrastructure, IBM coming at it with red hat from a pass layer. I mean, if I were IBM, I had learned from VM where leave it alone, Let it blossom. I mean, we have >> a very good partisan baby. Let me first say that IBM Global Services GTS is one about top sai partners. We do a ton of really good work with them. Uh, I'm software re partner number different areas. Yeah, we do compete with red hat with the part of their portfolios. Relate to contain us. Not with Lennox. Eighty percent plus of their businesses. Lennox, They've got parts of J Boss and Open Stack that I kind of, you know, not doing so well. But we do compete with open ship. That's okay, but we don't know when we can walk and chew gum so we can compete with Red Hat. And yet partner with IBM. That's okay. Way just need to be the best at doing containing platform is better than open shifter. Anybody, anything that red hat has were still partner with IBM. We have to be able to look at a world that's not black and white. And this partnership with Microsoft is a good example. >> It's not a zero sum game, and it's a huge market in its early days. Talk >> about what's up for you now. What's next? What's your main focus? What's your priorities? >> Listen, we're getting ready for VM World now. You know in August we want to continue to build momentum on make many of these solutions platforms. So I tell our sales reps, take the number of customers you have and add a zero behind that. OK, so if you've got ten thousand customers of NSX, how do we get one hundred thousand customers of insects. You have nineteen thousand customers of Visa, which, by the way, significantly head of Nutanix. How do we have make one hundred ninety thousand customers? And we have that base? Because we have V sphere and we have the Delll base. We have other partners. We have, I think, eighty thousand customers off and use of computing tens of millions of devices. How do we make sure that we are workspace? One is on billion. Device is very much possible. That's the vision. >> I think that I think what's resonating for me when I hear you guys, when you hear you talk when we have conversations also in Pat on stage talks about it, the simplification message is a good one and the consistency of operating across multiple environments because it sounds great that if you can achieve that, that's a good thing. How you guys get into how you making it simple to run I T. And consistent operating environment. It's all about keeping the customer in the middle of this. And when we listen to customs, all of these announcements the partnership's when there was eight of us, Microsoft, anything that we've done, it's about keeping the customer first, and the customer is basically guiding up out there. And often when I sit down with customers, I had the privilege of talking hundreds of thousands of them. Many of these CEOs the S and P five hundred I've known for years from S athe of'Em were they'LL Call me or text me. They want us to be a trusted advisor to help them understand where and how they should move in their digital transformation and compared their journey to somebody else's. So when we can bring the best off, for example, of developer and operations infrastructure together, what's called DEV Ops customers are wrestling threw that in there cloud journey when we can bring a multi device world with additional workspace. Customers are wrestling that without journey there, trying to figure out how much they keep on premise how much they move in the cloud. They're thinking about vertical specific applications. All of these places where if there's one lesson I've learned in my last ten twenty years of it has become a trusted advisor to your customers. Lean on them and they will lean on you on when you do that. I mean the beautiful world of technology is there's always stuff to innovate. >> Well, they have to lean on you because they can't mess around with all this infrastructure. They'LL never get their digital transformation game and act together, right? Actually, >>= it's great to see you. We'Ll see you at PM, >> Rollo. Well, well, come on, we gotta talk hoops. All right, All right, All right, big. You're a big warriors fan, right? We're Celtics fan. Would be our dream, for both of you are also Manny's themselves have a privileged to go up against the great Warriors. But what's your prediction this year? I mean, I don't know, and I >> really listen. I love the warriors. It's ah, so in some senses, a little bit of a tougher one. Now the DeMarcus cousins is out for, I don't know, maybe all the playoffs, but I love stuff. I love Katie. I love Clay, you know, and many of those guys is gonna be a couple of guys going free agents, so I want to do >> it again. Joy. Well, last because I don't see anybody stopping a Celtics may be a good final. That would be fun if they don't make it through the rafters, though. That's right. Well, I Leonard, it's tough to make it all right. That sounds great. >> Come on. Sanjay Putin, CEO of BM Wear Inside the Cube, Breaking down his commentary of you on the landscape of the industry and the big news with Microsoft there. Other partner's bringing you all the action here Day one of three days of coverage here in the Cubicle two sets a canon of cube coverage out there. We're back with more after this short break.

(energetic music) >> [Narrator] From San Francisco, it's theCUBE, covering Radio 2018. Brought to you by VMware. >> Hello everyone. Welcome to the special CUBE coverage here in San Francisco, California for VMware's Radio 2018 event. This is their R&D big event kickoff. It's like a sales kickoff for engineers, as Steve Herrod said on stage. Out next guest is Mornay Van Der Walt, VP of the Explore Group, Office of the CTO. Also, program chair of the Event Today Conference, working for the collective of people within VMware on a rigorous selection committee for a high bar here at your event. Welcome to theCUBE. Thanks for joining me. >> Thank you. >> Talk about the event, because I know a lot of work went into it. Congratulations, the talks were amazing. I see the schedule. We have Pat Gelsinger coming on later today. We just had Ray O'Farrell on. This is like the, I don't want to say, Burning Man of Vmware, but this is really a recognition, but also really important innovation. Take a minute to talk about the process that you go through to put this together. It's a fantastic event. The smartest minds, the cream rises to the top. It's hard, it's challenging, it's a team effort, but yet you gotta ride the right waves. >> Right. So, RADIO: R&D Innovation Offsite. And as you said, it is tough because we've got this huge R&D community and they've all got amazing ideas. So they get the opportunity to submit ideas. I think this this year we have over 1,700 ideas submitted, and at the end of the day we're only going to showcase 226 of those ideas across research programs, posters, breakout sessions, Just-In-Time BOFs, Birds Of a Feather. You know, so, the bar is high. we've got a finite amount of time, but what's amazing is we take these ideas, and we don't just showcase them at RADIO. We have four other programs that give us the ability to take those ideas to the next level. So when we think about the innovation programs that come out of OCTO, this is really to drive what we call "Off-Road Map Innovation." So Raghu and Rajiv, with our Product Cloud Services Division, are driving road map, zero to three years out the stuff that you can buy from sales, >> [Furrier] Customer centric? >> Customer centric, yeah. OCTO is providing an innovation program structure, these five programs: Tech Talks, Flings, Borathons, RADIO, and xLabs, and as a collective, they are focused on off-road map innovation. Maybe something that's-- >> Give me an example of what that means, Off-Road Map. >> Sure. So last year at RADIO we did a paper that was showcased on functions as a service. So you think of AWS Lambda, right. [Furrier] Yep, yep >> VM was uniquely positioned, with the substrate, to manage and orchestrate VM's containers and whynot functions. So this radio paper was submitted, I then, as the xLabs group, said we're going to fund this, but given where we are in this market, we said, "Alright, we'll fund this for 12 months." So, we're incubating functions as a service. In July/August time frame, that'll actually exit xLabs into the Cloud Native business. >> It's a real rapid innovation. >> Very rapid. >> Within a 12 month period, we're gonna get something into a BU that they can take it to market. >> Yeah, and also I would say that this also I've seen from the talks here, there's also off-road map hard problems that need to kind of get the concepts, building blocks, or architecture... >> [Van Der Walt] Correct. >> With the confluence of hitting, whatever, its IOT or whatever, blockchains, seeing things like that. >> [Van Der Walt] Yeah. Correct. >> Is that also accurate too? >> Very true. And, you know, Ray had a great slide in his keynote this morning, you know, we spoke about how we started in 2003, when he joined the company, it was all about computer virtualization. Fast-forward 15 years, and you look at our strategy today, it's any Cloud, any device, any app, right? Then, you gotta look to the future, beyond there, what we're doing today, what are the next twenty years going to look like? Obviously, there's things like, you know, blockchain, VR, edge computing, you know, AIML... >> [Furrier] Service meshes? >> Services meshes, adaptive security. And, you know, people say, "Oh, AIML, that's a hot topic right now, but if you look back at VM ware, we've been doing that since 2006. Distributed resource scheduler: a great example of something that, at the core of the product, was already using ML techniques, you know, to load-balance a data center. And now, you can load-balance across Clouds. >> It's interesting how buzzwords can become industry verticals. We saw that with Hadoop; it didn't really happen, although it became important in big data as it integrates in. I mean, I find that you guys, really from the ecosystem we look at, you guys have a really interesting challenge. You started out as "inside the box," if you will. I saw your old t-shirt there from the 14 year history you guys have been doing this event. Great collection of t-shirts behind me if you can't see it. It's really cool. But infrastructures, on premise, you buy, it's data center, growth, all that stuff happened. Cloud comes in. Big data comes in. Now you got blockchain. These are big markers now, but the intersection of all these are all kind of touching each other. >> [Van Der Walt] Correct. >> IOT...so it's really that integration. I also find that you guys do a great job of fostering innovation, and always amazed at the VM world with some great either bechmarks or labs that show the good stuff. How do you do it? Walk me through the steps because you have this Explorer program, which is working. >> [Van Der Walt] Yeah >> It's almost a ladder, or a reverse ladder. Start with tech talks, get it out to the marketplace... >> [Van Der Walt] Do a hackathon. >> Hackathon. Take us through the process. So there's four things: tech talks, borathons, which is the meaning behind the name, flings, and xLabs. >> Correct >> Take us through that progression. >> ... and RADIO, of course. >> And RADIO, of course, the big tent event. Bring it all together. >> So, I'm an engineer. I have a great idea. I wanna socialize it; I wanna get some feedback. So, at VMWare, we offer a tech talk platform. You come, you present your idea. It's live. There'll be engineers in the audience. We also record those, and then those get replayed, and engineers will say, "You know, have you thought about this?" or "Have you met up with Johnny and Mary?" They're actually working on something very similar. Why don't you go and, you know, compare ideas? I can actually make that very real. I was in India in November, and we were doing a shark tank for our xLabs incubator, and this one team presented an idea on an augmented reality desktop. We went over to another office, actually the air watch office, and we did another shark tank there. Another team pitched the exact same idea, so I looked at my host, and I said, "Do these two teams know each other?" and the guy goes, "Absolutely not," so what did we do? We made the connection point. Their ideas were virtually identical. They were 25 kilometers apart. Never met. >> [Furrier] Wow. >> You know, so when, that's one of the challenges when your company becomes so big, you've got this vast R&D organization that's truly global, in one country 25 kilometers apart, you had two teams with the same idea that had never met. So part of the challenge is also bringing these ideas together because, you know, the sum of the parts makes for a greater whole. >> And they can then collectively come together then present to RADIO one single paper or idea. >> [Van Der Walt] Absolutely, or go ahead and say, you know what, let's take this to the next step, which would be a borathon, so borathons are heckathons. >> Explain the name because borathon sounds like heckathon, so it is, but there's a meaning behind the name borathon. What is the meaning? >> Sure. So, our very first build repository was named after Bora Bora, and so we paid homage to that, and so, instead of saying a heckathon, we called it a borathon. And one of our senior engineers apparently came up with that name, and it stuck, and it's great. >> So it's got history, okay. So, borathons is like ... okay, so you do tech talks, you collaborate, you socialize the idea via verbal or presentation that gets the seeds of innovation kinda planted. Borathon is okay, lets attack it. >> Turn it into a prototype. >> Prototype. >> And it gets judged, so then you get even more feedback from your most senior engineers. In fact ... >> And there's a process for all this that you guys run? >> Yeah, so the Explorer groups run these five innovation programs. We just recently, in Palo Alto, did a theme borathon. Our fellows and PE's came together. Decided the theme should be sustainability, and we mixed it up a little bit. So, normally, at a borathon, teams come with ideas that they've already been developing. For this one, the teams had no idea what the theme was going to be, so we announced the theme. Then, they showed up on the day to learn what the five challenges were going to be, and some of those challenges, one of them was quite interesting. It was using distributed ledger to manage microgrids, and that's a ... >> A blockchain limitation >> Well, it's a project that's, you know, is near and dear to us at VMWare. We're actually going to be setting up a microgrid on campus, and if you think about microgrids, and Nicola Acutt can talk more to this, we're gonna be looking at, you know, how can we give power back to the city of Palo Alto? Well, imagine that becoming a mesh network. >> [Furrier] With token economics. >> How do you start tracking this, right? A blockchain would be a perfect way to do this, right? So, then, you take your ideas at a borathon, get them into a prototype, get some more feedback, and now you might have enough critical mass to say, "Alright, I'm going to present a RADIO paper next year." So, then, you work as a team; get that into the system. >> [Furrier] And, certainly, in India and these third-world countries now becoming large, growing middle-class, these are important technologies to build on top of, say, mobile... >> [Van Der Walt] Absolutely. >> And with solar and power coming in, it's a natural evolution, so that's good use case. Okay, so, now I do the borathon. I've got a product. Flings? >> It's a prototype, right, so now ... >> You can socialize it, you have a fling, you throw it out there, you fling it out there What happens? >> Yeah, so, I've done something at a borathon. It's like, I want to get some actual feedback from the ecosystem: our customers and partners. That example I used with vSAN. You know, vSAN launched. We wanted to get some health analytics. The release managers were doing their job. The products got a ship on the state. Senior engineers on the team got a health analytics tool out as a fling. It got incredible feedback from the community. Made it into the next release. We did the same with the HTML clients, right? And that's been in the press lately because, you know, we've got Rotoflex. Now, there's HTML, but that actually started - two teams started working on that. One team just did HTML >> a very small portion of the HTML client, presented a RADIO paper. Two years later, another team, started the work, and now we have a full-fledged HTML client that's embedded into the VIS via product. >> [Furrier] So, the fling brings in a community dynamic, it brings in new ideas, or diversity, if you will. All kinds of diverse ideas melting together. Now, xLabs, I'm assuming that's an incubator. That brings it together. What is xLabs? Is that an incubator? You fund it? What happens there? >> So with an xLabs, the real way to think about it, it's truly an incubator. I don't want to use the word "start-up" there because you've clearly got the protection of the larger VMware organization, so you're not being a scrappy start-up, but you've got a great idea, we see there's merit ... >> [Furrier] Go build a real product. >> We see it more being on the disruptive side, and so we offer two tracks in the xLabs. There's a light track, which typically runs three to six months, and you're still doing your day job. You know, so you're basically doing two jobs. You know, we fund you with a level of funding that allows you to bring on extra contracting, resources, developers, etc., and you're typically delivering one objective. The larger xLab is the full-track, so functions as a service. Full-track, we showcased it as a RADIO paper last year. We said, "Alright, we're going to fund this. We're going to give it 12 months worth of funding, and then it needs to exit into a business unit," and we got lucky with that one because we were already doing a lot of work with containers, the PKS, the pivotal. >> [Furrier] Do the people have to quit their day job, not quit their day job, but move their resource over? >> [Van Der Walt] Absolutely. >> The full-track is go for it, green light >> Yep >> Run as fast as you can, take it to this business unit. Is the business unit known as the end point in time? Is it kind of tracked there, or is it more flexible still. >> Not all the time. You know so sometimes, with functions it was easier, right? So, we know we've got pull for zone heading up Cloud native apps. The Cloud native business unit is doing all the partnerships with PKS. That one makes sense. >> [Furrier] Yeah. >> We're actually doing one right now, another xLabs full, called network slicing, and it's going to play into the Telco space. We've obviously got NFV being led by Shekar and team, but we don't know if network slicing, when it exits, and this one is probably going to have a longer time arise and probably 24-36 months. Does it go into the NFV business unit, or does it become its own business unit. >> [Furrier] That's awesome. So, you got great tracks, end to end, so you have a good process. I gotta ask you the question that's on my mind. I think everyone would look at this, and some people might look at Vmware as, and most people do, at least I do, as kind of a cutting-edge tier one company. You guys always are a great place to work. Voted as, get awards for that, but you take seriously innovation and organic growth in community and engineering. Engineering and community are two really important things. How do you bring the foster culture because engineers can be really pissed off. "Oh my god! They're idiots that make the selection!" because you don't want engineers to be pissed cuz they're proud, and they're inventing. >> Yep, yep. >> So, how to manage the team approach? What's the cultural secret in the DNA that makes this so successful over 14 years? >> So, before I answer that question, I think it's important to take a step back. So, when we think about innovation, we call this thing the Vmware "innovation engine." It's really three parts to it, right? If you think about innovation at its core: sustaining, disruptive, internal, external, And, so, we've got product Cloud Services group, Raghu and Rajiv, we've got OCTO, headed up by Ray, we've got corp dev headed up by Shekar. Think of it as it's a three-legged stool. You take one of those legs away, the stool falls over. So, it's a balancing act, right? And we need to be collaborating. >> [Furrier] And they're talking to each other all the time. >> We're talking to each other all the time, right? Build or buy? Are we gonna do something internal, or we gonna go external, right? You think something about acquisitions like Nicira, right? We didn't build that; we bought it. You think about Airwatch, right? Airwatch put us into the top right quadrant from Gartner, right? So, these are very strategic decision that get made. Petchist presented at Dell emc world, Dell Technologies world. He had a slide on there that showed, it was the Nicira acquisition, and then it sort of was this arc leading all the way up to VeloCloud, and when you saw it on one slide, it made perfect sense. As an outsider looking in, you might have thought, "Why were they doing all these things? Why was that acquisition made? But there's always a plan, and that plan involves us all talking across. >> [Furrier] Strategic plan around what to move faster on. >> Correct >> Because there's always the challenge on M&A, if they're not talking to each other, is the buy/build is, you kinda, may miss a core competency. They always ... what's the core competency of the company? And should you outsource a core competency, or should you build it internally? Sometimes, you might even accelerate that, so I think Airwatch and Nicira, I would say, was kinda on the edges of core competency, but together with the synergies ... >> [Van Der Walt] Helped us accelerate. >> And I think that's your message. >> [Van Der Walt] Yep. >> Okay, so that's the culture. How do you make, what's the secret sauce of making all this work? I mean, cuz you have to kinda create an open, collaborative, but it's competitive. >> [Van Der Walt] Absolutely. >> So how do you balance that? >> You know, so clearly, there's a ton of innovation going on within the prior Cloud services division. The stuff that's on the truck that our customers can buy today, alright? We also know we gotta look ahead, and we gotta start looking at solving problems that aren't on the truck today, alright? And, so, having these five programs and the collective is really what allows us to do that. But at the same time, we need to have open channels of communication back into corp dev as well. I can give you examples of, you know, Shekar and his team might be looking at Company X. We're doing some exploratory work, IOT, I did an ordered foray. IOT is gonna be massive; everybody knows that, but you know what's going to be even more massive is all the data at the edge, and what do you do with that data? How do you turn that data into something actionable, right? So, if you think about a jet engine on a big plane, right? When it's operating correctly, you know what all the good levels are, the metrics, the telemetry coming off it. Why do I need to collect that and throw it away? You're interested in the anomalies, right? As we start thinking about IOT, and we start thinking all this data at the edge, we're going to need a different type of analytics engine that can do real-time analytics but not looking at the norm, looking at the deviations, and report back on that, so you can take action on that, you know? So, we started identifying some companies like PubNub, Mulesoft, too, just got acquired, right? Shekar and his team were looking at the same companies, and was like, "These companies are interesting because they're starting to attack the problem in a different way. We do that at Vmware all the time. You think about Appdefense. We've taken a completely different approach to security. You know what the good state is, but if you have a deviation, attack that, you know? And then you can use things like ... >> It's re-imagining, almost flipping everything upside-down. >> Yeah, challenging the status quo. >> Yeah, great stuff, great program. I gotta ask you a final question since it's your show here. Great content program, by the way. Got the competition, got the papers, which is deep, technical coolness, but the show is great content, great event. Thanks for inviting us. What's trending? What's rising up? Have you heard or kind of point at something you see getting some buzz, that you thought might get buzz, or it didn't get buzz? What's rising of the topics of interest here? What's kind of popping out for you; what's trending if I had to a Twitter feed, not Twitter feed, but like top three trending items here. >> Well, I'll take it back to that last borathon that we did on sustainability. We set out the five challenges. The challenge that got the most attention was the blockchain microgrid. So, blockchain is definitely trending, and, you know, the challenge we have with blockchain today is it's not ready for the enterprise. So, David Tennenhouse and his research group is actually looking at how do you make blockchain enterprise ready? And that is a difficult problem to solve. So, there's a ton of interest in watching ... >> [Furrier] Well, we have an opinion. Don't use the public block chain. (both laugh) >> So, you know, that's one that's definitely trending. We have a great program called Propel, where we basically attract the brightest of the brightest, you know, new college grads coming into the company, and they actually come through OCTO first and do a sort of onboarding process. What are they interested in? They're not really interested in working for a particular BU, but, you know, when we share with them, "You're gonna have the ability to work on blockchain, AI, VR, augmented reality, distributed systems, new ways of doing analytics >> that's what attracts them. >> [Furrier] And they have the options to go test and put the toe in the water or jump in deep with xLabs. >> Absolutely >> So, I mean, this is like catnip for engineers. It draws a lot of people in. >> Absolutely, and, you know, we need to do that to be competitive in the valley. I mean, it's a very hard marketplace. >> Great place to work. >> You guys have a great engineering team. >> Congratulations for a great event, Mornay, and thanks for coming on theCUBE. We're here in San Francisco for theCUBE coverage of RADIO 2018. I'm John Furrier. Be back with more coverage after this break. Thanks for watching. (upbeat techno music)

live from Las Vegas Nevada it's the cute covering knowledge 15 brought to you by service now okay welcome back everyone we are live in Las Vegas this is SiliconANGLE Mookie bonds to cube our footage and event coverage would go out to the event started sitteth on the noise i'm john furrier likos day volante our next guest is Jen Stroud senior director and general manager of the HR applications within service now a former customer now general manager welcome to the cube thank you great I get the service now shirt on the jersey of the number everything right I'm official how does it feel so give us a quick you know Darkseid is always a dark side but I won't say which one it is is they always say with the VCS you join the dark side when entrepreneurs join the VC ranks but in this case service now pumping on all cylinders just like a well-oiled machine with the fast side yeah fasten what's it like give us the perspective it's been tremendous that I've been to two knowledge events before but as a customer very different perspective on this side and it's been it's been fabulous very fast you move fast here you have to keep up but it's been wonderful for me to engage with the partners and the customers here to see all the great things that customers are doing with the platform and with our product and also understanding where they want to see us take the the product going forward as a culture like its service now as a company you're in there ask you there for profit yeah kid jittery revenue from customers and I have a product they bring to the customers to get paid for that what's it like internally was the culture like what's the people like it's it's been incredible to be a part of this culture and a little I wasn't what I expected I knew it was going to be very fast-paced but coming in and being able to rely on everyone to make sure you're successful everybody is interested in everybody being successful and I think that starts from Frank on down he's created that culture and so that's what it's about everyone is staring in the same direction and we're I've always said in Silicon Valley you know people you know high fliers come goes a lot of love you come in and out but building a sustainable business is really haha yeah so you gotta give props to Frank's loop and talk about what you've learned Massey HR managers are out struggling this is in the press now small medium-sized businesses you see all kinds of certainly in Silicon Valley where I live you know eight lawsuits coming from just not keeping your eye on the ball little things like yeah Oh someone's offended in a meeting boom lawsuit I've been discriminating against so there's all kinds of stuff happening just by having shot eh our practices so talk about what that means why that's happening is it just because they're lazy or the games change the technologies change what's going on with in the HR application space I think some other people have said it in my colleague Eric hammer who's a solution consultant now leads the enterprise practice said it HR is kind of a 10 to 15 well five to ten years behind IT they're finally understanding that you can't manage with spreadsheets and email anymore and we're seeing it I don't care the the size of the organization or what their annual revenues are there are many organizations struggling with the same thing how do they provide a better experience for their employees and how do they do it in a consistent way and so that's we're seeing it out there the opportunities large and small with with customers it's very consistent Frank Frank mitch is a real time piece what's your perspective on that I mean being real time means service and complaints and managing that I'm sorry Dave I know oh absolutely i mean that's you want to be able to support your employees in a way that they're used to being supported in interacting outside of work right and yet especially the younger generation they come in and they want to work with a company that understands how to how to do that not you know managing through emails and so they want to come in with a hit company that you know gets it so service now is able to provide that type of experience so the state of Technology in HR is changing quite dramatically we were talking I was talking earlier guys from KPMG you know peoplesoft gets acquired by oracle it sets off this chain reaction taleo success factors work day comes into the market space and so the tech base is changing and then all of a sudden service now starts to play and people are confused people asked you yesterday yeah alist me who are you competing with with work day and of course no although you know but we've been asked eight or nine times already I'm just two days you'll continue to be asked you know and then you said something just recently to John that people they can't you know manage effectively with spreadsheets and the like so there's a lot of confusion because there's a lot of ton of technology that's begin going into a human humble management for decades there's some new cool cloud texts coming out technologies work days just you know one example successfactors many others and then and then service now with service management tied to the HRP so what's happening on the technology substrate how would you describe the changes that are going on it's it's amazing I mean they're the companies are understanding very quickly and you look at companies that have done results from their 2014 surveys of large leading HR organizations they understand that they have to to change and to leverage SAS technology in order to be able to to keep up so you like you were indicating we don't have any plan to compete with the workdays or the essay peas or PeopleSoft out there are our whole philosophy is let's figure out how we complement what they do and give like Frank said yesterday and I love what he said let's give let's give our customers choices let's give them good choices that they can they can have a good choice what they want to do ok so you're an HR pro so that's the many people in our audience have the same question that you've been asked nine times today yep you're not competing with the the transaction component that is work day you don't go to service now to to change my you know data about my self but we could if you want to though okay so we could be that front end so I mean again that's Ultima you start there you say yes sir then that make sense yeah go through service now so every request but we're not going to store that we're not we're not the system of Ragnar the system of record there that's the difference mm-hmm right okay but now love flip it so you're not going to go compete with with work day no but if I'm work day and I'm saying wow this company's service now is doing really well they grow in a 50 plus percent a year they got this great market cap maybe I should start doing some of that stuff now they could yeah but they're not going to do the other things it's hell's force like Frank said the other day well hey I talked to penny off all the time you know we're birds of a feather in a lot of ways we're developing apps they're developing absolutely a company like service now with a market tam of 40-plus billion you're playing in a lot of places especially when I have a platform that can do anything that's right now where do you see that all going well I mean in my view when I look at what I want to provide HR leaders I want to provide them out of the box a product that meets the majority of their needs and delivering services to their employees I and I want it to continue to and will expand on this and future releases look and feel the great user interface because it's all about the employee experience with HR IT doesn't care about the employee experience HR cares about the employee experience so really really working on that user interface and that experience and and the workflows for me the the possibilities are limitless what is it you and the work days of comprehensive system but optimizing workflows is interesting because there's so many different workflows in HR so there's that kind that stands like the strategy just picking it's almost like I Tina sends pick a few critical workflows could be trendy hey we got this new law comes out or longboarding of course is the big one that everybody's talking yeah so what is those use cases what are the key ones you guys are well I mean you have leave of absence as a big use case every HR organization and and it's it's one that can be very sticky it can also bleed into legal and other areas of the business so leave leave of absence managing those leave of absence requests some basic ones that are easy to ition reimbursement employment verification really standard that we that we will be offering out of the box too to our customers a pto request managing time off those are all yes you're lying fruit to use automation automation the other ones are just more yeah it's rewire or something or you know could be exposure that's right yep what percent of companies in your experience do performance reviews I just want to ask you as an HR pro ah too many too many too many do you think it's a I reproductive I think the so this is another probably great reason why I joined this organization is in Frank's and Shelley's philosophy on performance reviews and it's not formal the way we consider it formal or HR many HR organizations do with you know the whole performance review and setting goals he really believes that that that whole responsibility lives with the manager and HR is there to support the manager and I love that philosophy but we have to as a as we're developing our product understand that unfortunately this organization don't share Frank's philosophy ok so you're saying that many organizations have the HR oh they do the performance I feel like a neophyte I didn't know that what that's insane absolutely would you have the HR department it is performing well and i and i don't necessarily i don't i don't agree with it but it absolutely i would majority of organizations HR still manages the whole performance whether the sense that they sent a syntax they had the structure and process yeah which controls the behaviors of Manokotak attendance it's a whole they don't do the review submitted yourself they don't do their reviews but they they set the schedule and you must have your reviews done by this time and you must miss assurance icon the dentist makes your teeth pulled yeah basically and then they're constantly pounding on managers when they don't get it done to get it done get it done get it done i mean that's that's the way it was in my previous company no no offense but it just does it's not it doesn't work well what does frank with what what what Frank's philosophy and Shelley's philosophy is here and that is managers are responsible for the performance of their team and you reward people for their performance and then comes in the last place already no prize for you yeah so I want to ask question about systems of engagement versus a record this comes up a lot and that I look at it a little bit differently as I don't look it from the HR perspective mother from the day big data side what's your view of it from an HR perspective what is the definitions of those systems of engagement systems of record I can also imagine so I look at it and this from this is the my philosophy when I was on the customer side I wanted to create that one stop shop where my employees could come where they knew exactly i took all the guesswork out for them here's where you come to do everything now ultimately they may be the they may be interacting and engaging with a form and service now and that was going to feed being an integration to our hrs is system which was oracle that's fine but they don't need to know that for them I wanted to create that standard look and feel standard system of engagement that was predictable for them easy to use and that's really what you want to provide employees you want to make it easy that's an employee that's the app that's user interface user experience that's right flows and clicks yep click stream where all the information is ultimately stored is a whole different matter and not necessarily important to me other than I want to be able to integrate with those systems so bad you I bed ux taking that to the next level means you don't get the data you need for the systems records so the engagement date is pretty critical engagement is is absolutely critical if you want your your employees to use it if it if it is a bad you I if it isn't a good experience they're going to go I'm not going to use this and they're going to they're going to the employees make themselves heard very loudly so they'll let you know if it's a bad experience so that creating that great system of engagement where it's easy to use and they know how to use it that's important about mobile as it relates specifically an HR context that's the conversation we're having are you happy with where you are with mobile is there a lot more work to do there very happy with where we are but as with everything I think we can continue to enhance what we offer it's absolutely a necessity in HR as you think about where many of the employees make their benefit decisions it's not at the office on their lunch break it's at home with their with their families and so they may be you know looking for information and the knowledge base or making a benefit selection on their mobile device at home not at the office so being able to provide that capability on a mobile or you know iPad device is very critical she has talked a lot about you know the affinity with work day of course I know an eel and Frank you know birds of a feather and friendly but there's a lot of other HR platforms out there oracle SI p many others what about those we also so right now we're focusing just because the market there's a lot of shift to an interest in work days Oh cloud its cloud yeah and but other the other ones are also coming up with they have cloud as well as record yeah yeah so so with the Geneva will have a two-way integration with worth work day to make that easier for customers but then we'll be focusing on additional out-of-the-box integrations with those other hris systems as well so does it have to be cloud-based I mean everybody's cloud now everybody is just like it better because you're why it's this is part of the mantra it's easier it's easier for you it's easier for the customers it doesn't action okay yeah this is a big so what's your goal now you're in there get your running shoes on three feet in a cloud of dust making things happen to get some teammates to support you servicenow yeah what's next what's what are you gonna work on what's your plan well we just don't we're still not known enough in the HR industry as a trusted platform in HR so we've got our work cut out for us there and so you know it is about what we're building in the product that's going to help us but it's also going to help us getting out at HR tech that's coming here mandalay bay and octo we'll be here other events working with analysts as well to help them understand what we're doing and really it's going to be about creating more success and a great customer base so that you know this time next year I hope to you know be able to say you know we really are one of those vendors that HR looks to first and not you know us trying to get in there to have the because I think once they do and once they look at what we have to offer it's it's it's very intriguing for them but we really want to be you know on top of their mind it sounds like your strategy then is to say hey you know what you big pickle the big decisions we're going to come in create some value pretty nimble pretty agile land and expand and if that grows it grows and not really mutually exclusive to some other platform no and in we absolutely are concentrating right now on where we are very successful so we have a lot of great customers already on the IT side so they all have HR departments so we're absolutely focused there in 2015 but beyond we really want to expand and be first okay Jamie keep a track and we'll be following you if you need any help let us know we go stroll at the cube to HR tech con and in October it's the cube we are live here at Las Vegas extracting the scene from the noise shared that with you I'm genre Dave vellante we'll be right back after this short break of the next guest stay tuned off