>> 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)

>> 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)

>> From theCUBE Studios in Palo Alto in Boston, bringing you data driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> Cybersecurity stocks have been sending mixed signals as of late, mostly negative like much of tech, but some such as Palo Alto Networks, despite a tough go of it recently have held up better than most tech names. Others like CrowdStrike, had been out performing Broader Tech in March, but then flipped in May. Okta's performance was pretty much tracking along with CrowdStrike for most of the past several months, a little bit below, but then the Okta hack changed the trajectory of that name. Zscaler has crossed the critical billion dollar ARR revenue milestone, and now sees a path to five billion dollars in revenue, but the company stock fell sharply after its last earnings report and has been on a down trend since last November. Meanwhile, CyberArk's recent beat and raise, was encouraging and the stock acted well after its last report. Security remains the number one initiative priority amongst IT organizations and the spending momentum for many high flying cyber names remain strong. So what gives in cyber security? Hello, and welcome to this week's Wikibon CUBE insights powered by ETR. In this breaking analysis, we focus on security and will update you on the latest data from ETR to try to make sense out of the market and read into what this all means in both the near and long term, for some of our favorite names in cyber. First, the news. There's always something happening in security news cycles. The big recent news is new President Rodrigo Chavez declared a national emergency in Costa Rica due to the preponderance of Russian cyber attacks on the country's critical infrastructure. Such measures are normally reserved for natural disasters like earthquakes, but this move speaks to the nature of today's cyber threats. Of no surprise is modern superpower warfare even for a depleted power like Russia almost certainly involves cyber warfare as we continue to see in Ukraine. Privately held Arctic Wolf Networks hired Dustin Williams as its new CFO. Williams has taken three companies to IPO, including Nutanix in 2016, a very successful IPO for that company. Whether AWN chooses to pull the trigger this year or will wait until markets are less choppy or obviously remains to be seen. But it's a pretty clear sign the company is headed to IPO at some point. Now, big point of discussion this week at Red Hat Summit in Boston and the prior week at Dell technologies world was security. In the case of Red Hat, securing the digital supply chain was the main theme. And from Dell building, many security features into its storage arrays and cyber resilience services into its as a service offering called Apex. And we're seeing a trend where buyers want to reduce the number of bespoke tools they use if they, in fact can. Here's IDC's Jim Mercer, sharing data from a recent survey they conducted on the topic. Play the clip. >> Interestingly, we did a survey, I think around last August or something. And one of the questions was around where do you want your security, right? Where do you want to get your DevSecOps security from? Do you want to get it from individual vendors, right? Or do you want to get it from like your platforms that you're using and deploying changes in Kubernetes? >> Great question. What did they say? >> The majority of them, they're hoping they can get it built into the platform. That's really what they want-- >> Now, whether that's actually achievable is debatable because you have so much innovation and investment going on from the likes of startups and for instance, lace work or sneak and security companies that you see even trying to build platforms, you've got CrowdStrike, Okta, Zscaler and many others, trying to build security platforms and put it all under their umbrella. Now the last point will hit here is there was a lot of buzz in the news about Okta. The reaction to what was a relatively benign hack was pretty severe and probably overblown, but Okta's stock is paying the price of what is generally considered a blown communications plan versus a technical failure. Remember, identity is not an easy thing to rip and replace and Okta remains a best-of-breed player and leader in the space. So we're going to look at some ETR data later in this segment to try and make sense of the recent action in the market and certain names. Speaking of which let's take a look at how some of the names in cybersecurity have fared relative to some of the indices and relative indicators that we like to look at. Here's a Google finance comparison for a number of stocks and names in the bottom there you can see we plot the hack ETF which tracks security stocks. This is a year to date view. And so we don't show it here but the tech heavy NASDAQ is off around 26% year to date whereas the cyber ETF that we're showing is down 18%, okay. So cyber holding up a little bit better than broader tech as we've reported earlier, was actually much better and still seems to be a gap there, but the data are mixed. You can see Okta is way off relative to its peers. That's a combination of the breach that we talked about but also the run up in the stock since COVID. CrowdStrike was actually faring better but broke this month, we'll see how it's upcoming earnings announcements are received when it announces on June 2nd after the close. Palo Alto in the light blue has done better than most and until recently was holding up quite well. And of course, Sailpoint is another identity specialist, it is kind of off the charts here because it's going private with the acquisition by Thoma Bravo at nearly seven billion dollars. So you see some mixed signals in cyber these past several months and weeks. And so we're trying to understand what that all means. So let's take a look at the survey data and see how spending momentum is holding up. As we've reported IT spending forecast, at the macro level, they've come off their 8% highs from the end of the year, the ETRS December survey, but robust tech spending is still there. It's expected at nearly seven percent and this is amongst 1200 ETR respondents. Here's a picture from the ETR survey of the cybersecurity landscape. That y-axis that's net score or a measure of spending momentum and that horizontal access is overlap. We used to talk about it as a market share which is a measure of pervasiveness in the data set. That dotted red line at 40% indicates an elevated spending momentum level on the vertical axis and we filter the names and limited to only those with a hundred or more responses in the ETR survey. Then the pictures still pretty crowded as you can see. You got lots of companies above the red dotted line, including Microsoft which is up into the right, they're so far off the chart, it's just amazing. But also Palo Alto and Okta, Auth0, which of course is now owned by Okta, Zscaler, CyberArk is making moves. Sailpoint and Cloudflare, they're all above that magic 40% line. Now, you look at Cisco, it shows a very large presence in the horizontal axis in the data set. And it's got pretty respectable momentum and you see Splunk doing okay, no before and tenable just below that 40% line and a lot of names in the very respectable 20% zone. And we've included some legacy names just for context that fall below the zero percent line with a negative net score. And that means a larger proportion, that negative net score means a larger proportion of their customers in the survey are spending less than those that are spending more. Now, typically for these legacy names you're going to have a huge proportion of customers who have flat spending that kind of fat middle and that's why they sort of don't have that highly elevated score, but they're still viable as they get the recurring revenue each year. But the bottom line is that spending remains robust for some of the top names that we've talked about earlier despite their rocky stock performance. Now, let's filter this data a bit more to make it a little bit easier to read. So to do that, we take out Microsoft because they're just so dominant and we cherry pick some names to make the data more consumable and scannable. The other data point we've added is Okta's net score breakdown, the multicolored rows there, that row in the bottom right. Net score, it measures the percent of customers that are adding the platform new, that's the lime green, at 18% for Okta. The forest green is at 42%. That's the percent of customers in the survey that are spending six percent or more. The gray is flat spending. That's 32% for Okta, this past survey. The pink is customers that are spending less, that's three percent. They're spending six percent or worse in the survey, so only three percent for Okta. And the bright red at three percent is decommissioning the platform. You subtract the reds from the greens and you get a net score, well, into the 50s for Okta and you can see. We highlight Okta here because it's a name that we've been following for quite some time and customers have given us really solid feedback on the technology and up until the hack, they're affinity to Okta, but that seems to be continuing. We'll talk more about that. This recent breach to Okta has caused us to take a closer look. And you may recall, we reported with our ETR colleague, Eric Bradley. The breach was announced right in the middle of ETR collecting data in the last survey. And while we did see a noticeable downtick right after the announcement, the exposure of the hack and Okta's net score just after the breach was disclosed, you can see the combination of Okta and Auth0 remains very strong. I asked Eric Bradley this morning what he thought about Okta, and he pointed out that you can't evaluate this company on its price to earnings ratio. But it's forward sales multiple is now below 7X. And while attractive, these high flyers at some point, Eric says, they got to start making a profit. So you going to hold that thought, we'll come back to that. Now, another cut of the ETR data to look at our four star security names here. A while back we developed a methodology to try and cut through the noise of the crowded security sector using the ETR data to evaluate two key metrics; net score and shared N. Net score again is, spending momentum, the latter is an indicator of presence in the data set which is a proxy for market presence. Okay, we assigned those companies that cracked the top 10 in both net score and shared N, we give them four stars, okay, if they make the top 10. This chart here shows the April survey data for those companies with an N that's greater than, equal to a hundred responses. So again, we're filtering on those with a hundred or more responses. The table on the left that you see there, that's sorted by net score, okay. So we're sorting by spending momentum. And then the one on the right is sorted by shared N, so their presence in the data set. Seven companies hit the top 10 for both categories; Palo Alto Network, Splunk, CrowdStrike Okta, Proofpoint, Fortinet and Zscaler. Now, remember, take a look, Okta excludes Auth0, in this little methodology that we came up with. Auth0 didn't make the cuts but it hits the top 10 for net score. So if you add in Auth0's 112 N there that you see on the right. You add that into Okta, we put Okta in the number two spot in the survey on the right most table with the shared N of 354. Only Cisco has a higher presence in the data set. And you can see Cisco in the left lands just below that red dotted line. That's the top 10 in security. So if we were to combine Okta and Auth0 as one, Cisco would make the cut and earn four stars. Now, some other notables are CyberArk, which is just below the red line on the right most chart with an impressive 177 shared N. Again, if you combine Auth0 and Okta, CyberArk makes the four star grade because it's in the top 10 for net score on the left. And Sailpoint is another notable with a net score above 50% and it's got a shared N of 122, which is respectable. So despite the market's choppy waters, we're seeing some positive signs in the survey data for some of the more prominent names that we've been following for the last couple of years. So what does this mean for the markets going forward? As always, when we see these confusing signs we like to reach out to the network and one of the sharpest traders out there is Chip Simonton. We've quoted him before and we like to share some of his insights. And so we're going to highlight some of that here. So technically, almost every good tech stock is oversold. And as such, he suggested we might see a bounce here. We certainly are seeing that on this Friday, the 13th. But the right call tactically has been to sell into the rally these past several months, so we'll see what happens on Monday. The key issue with the name like Okta and some other momentum names like CrowdStrike and Zscaler is that when money comes back into tech, it's likely going to go to the FAANG stocks, the Facebook, Apple, Amazon, Netflix, Google, and of course, you put Microsoft in there as well. And we'll see about Amazon, by the way, it's kind of out of favor right now, as everyone's focused on the retail side of the business meanwhile it's cloud business is booming and that's where all the profit is. We think that should be the real focus for Amazon. But the point is, for these momentum names in cybersecurity that don't make money, they face real headwinds, as growth is slowing overall and interest rates rise, that makes the net present value of these investments much less attractive. We've talked about that before. But longer term, we agree with Chip Simonton that these are excellent companies and they will weather the storm and we think they're going to lead their respective markets. And in cyber, we would expect continued M&A activity, which could act as a booster shot in the arms of these names. Now in 2019, we saw the ETR data, it pointed to CrowdStrike, Zscaler, Okta and others in the security space. Some of those names that really looked to us like they were moving forward and the pandemic just created a surge in these names and admittedly they got out over their skis. But the data suggests that these leading companies have continued momentum and the potential for stay in power. Unlike the SolarWinds hack, it seems at this point anyway that Okta will recover in the market. For the reasons that we cited, investors, they might stay away for some time but longer term, there's a shift in CSO security strategies that appear to be permanent. They're really valuing cloud-based modern platforms, these platforms will likely continue to gain share and carry their momentum forward. Okay, that's it for now, thanks to Stephanie Chan, who helps with the background research and with social, Kristen Martin and Cheryl Knight help get the word out and do some great work as well. Alex Morrison is on production and handles all of our podcast. Alex, thank you. And Rob Hof is our Editor in Chief at SiliconANGLE. Remember, all these episodes, they're available as podcast, you can pop in the headphones and listen, just search "Breaking Analysis Podcast." I publish each week on wikibon.com and SiliconANGLE.com. Don't forget to check out etr.ai, best in the business for real customer data. It's an awesome platform. You can reach me at dave.vellante@siliconangle.com or @dvellante. You can comment on our LinkedIn posts. This is Dave Vellante for the CUBEinsights powered by ETR. Thanks for watching. And we'll see you next time. (bright upbeat music)

(calm music) >> Okay, welcome back everyone to theCUBE's live coverage here on the floor at Moscone south in San Francisco California for AWS summit, 2022. This is part of their summit conferences, not re:Invent it's kind of like becoming like regional satellite, mini re:Invents, but it's all part of education developers. Of course theCUBE's here. We're going to be at the AWS summit in New York city, only two this year. And this summer check us out. Of course, re:MARS is another event we're going to be going to so check us out there as well. And of course re:Invent at the end of the year and re:Inforce the security conference in Boston. So, Sarbjeet Johal, our next guest here. CUBE alumni, CUBE influencer, influencer in the cloud industry. Sarbjeet great to see you. Thanks for coming on. Oh, by the way, we'll be at Boston re:Inforce, re:Invent in December, re:MARS which is the robotics AI show, and of course the summit here in San Francisco and New York city, the hot areas. >> That's cool. >> Great to see you. >> Good to see you too. >> Okay. I got a lot of data to report. You've been on the floor talking to people. What are you finding out? What's the report? >> The report is actually, I spoke to three people from AWS earlier. As said one higher up guy from the doctor, Casey Tan. He works on French SaaS chips and he gave me a low down on how that thing works. And there's a systolic arrays TPUs, and like a lot of insider stuff >> Like deep Silicon chip stuff. >> Yes. And that they're doing some great stuff there. And of course that works for us at scale and for cloud guys it's all about scale. If you're saving pennies at that scale, you're saving millions and maybe hundreds of millions at some point. Right? So that was one. And I also spoke to the analytics guys and they gave me some low-down on the Glue announcements. How the big data processing is happening at AWS and how they are now giving you the ability where your infrastructure hugs your demand. So you're not wasting any sources. So that was a number one complaint with the Glue from AWS. So that was one. And then I did the DeepRacing race and my timings were like number 78. So. >> You got some work to do. You download your machine learning module. >> No, I will do that and then play with it. Yes. I will train one. >> You like a simulation too? >> Yeah. Yeah. I will do that simulation, yes. >> What else? Anything jump off the page for you. What's the highlight if you could point at something? Did anything pop up at you in this event with AWS? Was there any aha moment or something that just jumps off the page? >> I think it was mainly sort of incremental to be honest with you. And the one thing-- >> Nothing earth shattering >> Nothing earth shattering and that at the summit it's like that, you know, like it but they are doing new announcements of like almost every day with new services. So I would go home and read on that but there are some patterns that we are seeing emerging and there are some folks very active on Twitter. Mark in recent just did very controversial kind of tweet couple of days back. That was, that was hard. >> Was he shit posting again? >> Shit posting. Yeah. He was shit posting actually, according to actually I saw Corey as well on the floor, Corey and Rodrigo. And, and-- >> Did you see Corey's interview with me? We were talking about shit posting 'cause he wrote in this newsletter. Mark and recently Elon Musk, they're all kind of like they're really kind of active on Twitter with a lot of highly intelligent snarkiness. >> They're super intelligent and they know the patterns, they know the economics and technology. Super smart guys and yeah. Who is in control, there was a move from the middle seat and social media kind of side of things where people are controlling the narratives and who controls the narrative. Is it billionaires? Is it government? We see that. >> Well I mean, it's interesting seeing the power. I mean, I call it the revenge of the nerds. You got the billionaires who are looking at the political screw-ups that Facebook and others have done. And by not being clear and it's hard, it's a hard problem to solve. I don't really want to be in their seat. Even Andy Jassy is the CEO of AWS. What is he? I mean, he's dealing with problems that for some people would be their worst part of like they could ever dream of scenario. He's dealing with that at breakfast. And then throughout his day, he's got all kinds of Amazon's so big and Apple and you got Google and you got the fan companies. So, you know, at some point tech is now so part of society, it's not just the nerds from California. It's tech is in everything now. So it's a societal impact. And so there's consequences for stuff. And so you're starting to see this force for good that's come from the sustainability angle. You're going to start to see force for good with technology as it relates to people's lives. And we had Mapbox on the CUBE and they provide all this navigation and Gareth the guy who runs that division, he talks about dark kitchens, dark stores. So just they're re-engineering the supply chain of delivery. So we all been to restaurants and seen people there from picking up food delivery. Why are they going to the retail? So dark kitchens are just basically depots for supplying the 10 menus that everyone orders from. That's a change of a structural change in the industry. So that's jumped out at me, Matt Wood spoke to me about serverless impact to the analytics team. And again, structural changes, technical and culture. Right? So, so you're starting to see to me more and more of the two themes of some technology change, architectural change, system change and culture thinking. And you know, we had a 20 year old guest on here who was first worked at Amazon web services when he was 16. >> Wow. >> Graduated high school early and went into Amazon. He's like, I love tools. So people love tools. Hardware is coming back. Right? So I mean Sarbjeet this is crazy. >> It's crazy. >> What's going on. >> It's crazy actually. Remember the nine year old kid at re:Invent 2019. Karthick was the name if I remember, but I spoke to him and he was crazy. He was AWS certified and kids are playing with this technology in their high schools. >> It's awesome. >> And even in their elementary schools now. >> They can get their hands on it quicker. They don't need to go in full class for a year. They can self-teach, they can do side projects they can launch a side hustle, they can stand up a headless retail outlet, who knows what they can do if you got the Lego blocks. This is what I love about the cloud, you can really show something fast and then abandon it. >> Actually, I think it is all enabled through cloud. Like the accessibility of technology has gone like exponentially, like wildfire. Like once you have access to the cloud just all you need is connection to the internet. After that you have the VMs. and you have the serverless, there's zero cost to you. And things are thrown at you. Somebody who was saying that earlier here like we have said that many times it's like that's how the drug dealer, you know, sell the drug. Like sniff it, it's free, >> First is free. >> So they're doing it. Yes. >> We say that about theCUBE. >> And from the, I see cloud from two different angles, like we all do. And like, I try to sort of force myself to look at it from the both angles. There's the supplier side and the buyer side or the consumer side on the other side. Right? So from the supplier side, it's a race for talent to build it, number one, then number two is race for talent to train them. So we saw the numbers and millions being shown today at the keynote again. And Google is showing those numbers as well. Like how many millions they are training like 25 to 30 million people within next two, three years. It's crazy numbers. >> Sarbjeet I got to say so if I have to look at what jumped off the page for me on this event, was couple things and this is kind of weird nuanced stuff but I'll just try to explain it as best I can. Number one, we're going to see more managed services like DevOps managed services. As DevOps teams grow, talent is a problem. And Kubernetes obviously is growing and got to get that right. It's not easy to be a Kubernetes, you know slinging clusters around with Kubernetes. It's hard. I think that's got to get easier. So I think the path to easy is going to be some sort of abstraction service layer. And I think the smart people are going to have this layer will manage it and then provide that as a service, number one. Number two is this notion of a systems design thinking around elements, whether it's storage or maps for like Mapbox and around these elements they have to have a systematic effect of other things. You can't just, if it changes, it's going to have consequences that's what systems do. So, tooling being built around these elements and they have to have hardened APIs that is clear. People who are trying to be "cloud native" need to get this right. And you have to have the tooling in and around the the element and then have APIs to connect and then glue up. So it's interesting. Clearly those things are happening and multiple conversations, people were teasing that out. And then obviously the super cloud was coming in. >> Is there. >> Mapbox is basically a super cloud. They're like what snowflake is for data analytics. They are for-- >> MongoDB is another one. >> MongoDB's got Atlas. I mean, MongoDB was criticized for years. Doesn't scale. Remember the old lamp stack days, they were preferred. They're document, they nailed it with document. The document aspects of data, but they were always getting criticized. They can't scale. And they just keep scaling. But now with Atlas, they're on AWS. It's just, auto scale. So that's killer for MongoDB. So I think their stock price is undervalued my opinion but you know, I don't give legal advice. >> I think that the whole notion of-- >> Or financial advice. >> The multicloud, right? So for a multicloud to kill that complexity of multicloud, we have to go to the what Dave Vellante and you guys say super cloud, right? Another level of abstraction on top of infrastructure provider by AWS, Google cloud, Azure. So that's where we're going. >> Well, Dave and I debate this right, he bundles multi-cloud in there and most people think that's what he's saying but I'm saying multi-cloud is a reality. I mean, multi-cloud means you're going to have multiple clouds. They're just not you're not sharing workloads across those clouds. It's like not the same workload. That's not going to yet happen. I run Azure because I have 365, that's it. I run Amazon for everything else. That's kind of the use case. But to me, super cloud is building on top of AWS or Azure where you leverage their CapEx and create differentiated value. It's your own cloud without all the CapEx but it's got to be like super integrated and the benefit's got to be so good that it seems like pennies to your point earlier. >> Yeah. >> And the economics to the applications in it are just so obvious and they got to be they got to be so big for the application developer. So that's to me is super cloud. And then of course having the connected tissue to manage the transit around multiple clouds. >> Yeah. I think they have it too. I totally agree with you. But another thing is from having the developer background I think the backward compatibility is a huge issue in cloud. >> Yeah. I agree. >> It's a lot of technical debt being built and I hear that, I'm hearing that more and more. I think that we have to solve as industry as like these three main players have to solve that problem. So that's one big thing, actually. I'm very like after, you know, like to talk about it and all that stuff. So yeah. It's another thing is another pattern actually to all the cloud naysayers out there, right? Is that those are the people who come from the hardware background. So I've seen another pattern out there. So I'm trying to synthesize, who are these people who bash cloud all the time? I'm pro-cloud of course everybody knows that. >> We know you're pro, we're all pro cloud. We're totally biased. We love cloud >> Actually. No, I've seen both sides. I've seen both sides. I've worked at EMC, VMware, I worked at Oracle cloud as well. And then, and before that I have written a lot of software. A software developer is pro-cloud. A typical hardware ops guy or girl, they are pro on-prem or pro hybrid and all that. Like they try to keep it there. >> I think first of all, I have opinion on this. I think, I think you're right. But how hardware is coming back, if you look at how cloud is enabling hardware, it's retro, it's designed for the cloud. So hardware's going to offload, either accelerate stuff and offload stuff from the software guide. So look at DeepRacer it's hardware. Now it's a car. You've got the silicon and the chips. So the chips you're talking about. Those aren't chips for service and the data center. They're just chips to make the software in the cloud run better. >> Sarbjeet: Well scale. >> So scaling. And so I think we're going to see a Renaissance in hardware. It's going to look different. It's going to act different. So we're watching this. I mean, you brought up the idea of having a CUBE hardware box. >> Yeah. It's a great idea. >> It's a good idea. DM me and tell me it's a bad idea or good idea. I'll blame Sarbjeet for that. But what else have you learned? >> What else have learnt actually it's basically boils down to economics at the end of the day. It's about moving fast. It's about having developer productivity, again going back the cloud naysayers. It's like, why did you build a bike? Remember Steve Job used to say that, "computer is the bicycle for the human minds." >> Yes. >> Right. So cloud is the bicycle for the enterprises. They makes them move faster. 'So I think that's-- >> All right. We're closing down. We're going to hold on until they pull the plug on theCUBE literally. Sarbjeet great to see you on there. Check 'em out on Twitter. Great event. Good to see you, great report. Thank for sharing. Sarbjeet Johal here on theCUBE, taking over our community site I hear, right? Now you going to work-- >> I'm there. I'm always there. >> Great to have you on. I'm going to work on some new things with theCUBE. Really appreciate working with us. Thanks a lot. >> I really appreciate you guys giving me this platform. It's an amazing platform. Thank you very much. >> That's all right. We'll be back. That's it for our coverage of AWS summit 2020 here live on the floor. Events are back. Hybrid's back. We get theCUBE studios in Palo Alto in Boston. Re:invent at the end of the year but we're going to the summit in New York city. In the summer, we got re:Inforce in Boston the security conference. Re:MARS which is the robotics IML conference. And of course the big summit New York and San Francisco we're there of course. Share thecube.net for all the action. I'm John for your host with Sarbjeet here. Closing out the show. Thanks for watching. (Calm music)