>> 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)

(bright music) (crowd talking indistinctly in the background) >> Hey guys, welcome back to Detroit, Michigan. theCUBE is live at KubeCon + CloudNativeCon 2022. You might notice something really unique here. Lisa Martin with our newest co-host of theCUBE, Savannah Peterson! Savannah, it's great to see you. >> It's so good to be here with you (laughs). >> I know, I know. We have a great segment coming up. I always love talking couple things, cars, one, two, with companies that have been around for a hundred plus years and how they've actually transformed. >> Oh yeah. >> Ford is here. You have a great story about how you, about Ford. >> Ford brought me to Detroit the first time. I was here at the North American International Auto Show. Some of you may be familiar, and the fine folks from Ford brought me out to commentate just like this, as they were announcing the Ford Bronco. >> Satish: Oh wow. >> Which I am still lusting after. >> You don't have one yet? >> For the record. No, I don't. My next car's got to be an EV. Although, ironically, there's a Ford EV right behind us here on set today. >> I know, I know. >> Which we were both just contemplating before we went live. >> It's really shiny. >> We're going to have to go check it out. >> I have to check it out. Yep, we'll do that. Yeah. Well, please welcome our two guests from Ford, Satish Puranam, is here, The Technical Leader at Cloud and Rebecca Risk, Principal Architect, developer relations. We are so excited to have you guys on the program. >> Clearly. >> Thanks for joining us. (all laugh) >> Thank you for having us. >> I love you're Ford enthusiasts! Yeah, that's awesome. >> I drive a Ford. >> Oh, awesome! Thank you. >> I can only say that's one car company here. >> That's great. >> Yes, yes. >> Great! Thank you a lot. >> Thank you for your business! >> Absolutely. (all laugh) >> So, Satish, talk to us a little bit about- I mean I think of Cloud as a car company but it seems like it's a technology company that makes cars. >> Yes. Talk to us about Ford as a Cloud first, technology driven company, and then we're going to talk about what you're doing with Red Hat and Boston University. >> Yeah, I'm like everything that all these cars that you're seeing, beautiful right behind us it's all built on, around, and with technology, right? So there's so much code goes into these cars these days, it's probably, it's mind boggling to think that probably your iPhones might be having less code as opposed to these cars. Everything from control systems, everything is code. We don't do any more clay models. Everything is done digital, 3D, virtual reality and all that stuff. So all that takes code, all of that takes technology. And we have been in that journey for the last- since 2016 when we started our first mobile app and all that stuff. And of late we have been like, heavily invested in Google. Moving a lot of these experiences, data acquisition systems AI/ML modeling for like all the autonomous cars. It's all technology and like from the day it is conceived, to the day it is marketed, to the day when you show up for a servicing, and hopefully soon how you can buy and you know, provide feedback to us, is all technology that drives all of this stuff. So it's amazing for us to see everything that we go and immerse ourselves in the technology. There is a real life thing that we can see what we all do for it, right? So- >> Yes, we're only sorry that our audience can't actually see the car, >> Yep. >> but we'll get some B-roll for you later on. Rebecca, talk a little bit about your role. Here we are at KubeCon, Savannah and I and John were talking when we went live this morning, that this is huge. That the show floor is massive, a lot bigger than last year. The collaboration and the spirit of the community is not only alive and well, as we heard in the keynote this morning, it's thriving. >> Yeah. >> Talk about developer relations at Ford and what you are helping to drive in your role. >> Yeah, so my team is all about helping developers work faster with different platforms that my team curates and produces, so that our developers don't have to deal with all of the details of setting up their environments to actually code. And we have really great people, kind of the top software developers in the company, are part of my team to produce those products that other people can use, and accelerate their development. And we have a great relationship with the developers in the company and outside with the different vendor relationships that we have, to make sure that we're always producing the next platform with the next tech stack that our developers will want to continue to use to produce the really great products that we are all about making at Ford. >> Let's dig in there a little bit because I'm curious and I suspect you both had something to do with it. How did you approach your Cloud Native transformation and how do you evaluate new technologies for the team? >> It's sometimes- many a times I would say it's like dogfooding and like experimentation. >> Yeah. Isn't anything in innovation a lot of- >> Yeah, a lot of experimentation. We started our, as I said, the Cloud Native journey back in 2016 with Cloud Foundry and things, technologies around that. Soon realized, that there was like a lot of buzz around that time. Twelve-Factor was a thing, Stateless was a thing. And then all those Stateful needs to drive the Stateless. So where do we do that thing? And the next logical iteration was Kubernetes was bursting upon the scene at that time. So we started doing a lot of experimentation. >> Like the Kool-Aid man, burst on the Kubernetes scene- >> Exactly right. >> Through the wall. >> So, the question is like, why can't we do? I think we were like crazy enough to say that Kubernetes people are talking about our serverless or Twelve-Factor on Kubernetes. We are crazy enough to do Stateful on Kubernetes and we've been doing it successfully for five years. So it's a lot about experimentation. I think good chunk of experiments that we do do not yield the results that we get, but many a times, some of them are like Gangbusters. Like, other aspects that we've been doing of late is like partnering with Becky and rest of the organization, right? Because they are the people who are like closest to the developers. We are somewhat behind the scenes doing some things but it is Becky and the rest of the architecture teams who are actually front and center with the customers, right? So it is the collaborative effort that we've been working through past few years that has been really really been useful and coming around and helping us to make some of these products really beautiful. >> Yeah, well you make a lot of beautiful products. I think we've all, I think we've all seen them. Something that I think is really interesting and part of why I was so excited for this interview, and kind of nudged John out, was because you've been- Ford has been investing in technology in a committed way for decades and I don't think most people are aware of that. When I originally came out to Dearborn, I learned that you've had a head of VR who happens to be a female. For what it's worth, Elizabeth, who's been running VR for you for two and a half decades, for 25 years. >> Satish: Yep. >> That is an impressive commitment. What is that like from a culture perspective inside of Ford? What is the attitude around innovation and technology? >> So I've been a long time Ford employee. I just celebrated my 29th year. >> Oh, wow! >> Congratulations! >> Wow, congrats! That's a huge deal. >> Yeah, it's a huge deal. I'm so proud of my career and all that Ford has brought to me and it's just a testament. I have many colleagues like me who've been there for their whole career or have done other things and come to Ford and then spent another 20 years with us because we foster the culture that makes you want to stay. We have development programs to allow you to upscale and change your role and learn new things and play with the new technologies that people are interested in doing and really make an impact to our community of developers at Ford or the company itself and the results that we're delivering. So to have that, you know, culture for so many years that people really love to work. They love to work with the people that they're working with. They love to stay engaged and they love the fact that you can have many different careers within the same umbrella, which we call the "blue oval". And that's really why I've been there for so long. I think I probably had 13 very unique and different jobs along the way. It's as if I left, and you know shopped around my skills elsewhere. But I didn't ever have to leave the company. It's been fabulous. >> The cultural change and adoption of- embracing modern technology- Cloud Native automotive software is impressive because a lot of historied companies, you guys have been there a long time, have challenges with that because it's really hard to get an entire moving, you'll call it the blue oval, to change and adapt- >> Savannah: I love that. >> and be willing to experiment. So that that is impressive. Talk about, you go by Becky, so I'll call you Becky, >> Rebecca/Becky: Yeah. >> The developer culture in terms of the developers really being the center of the nucleus of influencing the direction in which the company's going. I imagine that they probably are fairly influential. >> Yeah, so I had a very- one of the unique positions I held was a culture change for our department, Information Technology in 2016. >> Satish: Yeah. >> As the teacher was involved with moving us to the cloud, I was responsible- >> You are the transformation team! This is beautiful. I love this. We've got the right people on the show. >> Yeah, we do. >> I was responsible for changing the culture to orient our employees to pay attention to what do we want to create for tomorrow? What are the kind of skills we need to trust each other to move quickly. And that was completely unique. >> Satish: Yeah. >> Like I had men in the trenches delivering software before that, and then plucked out because they wanted someone, you know who had authentic experience with our development team to be that voice. And it was such a great investment that Ford continues to do is invest in our culture transformation. Because with each step forward that we do, we have to refine what our priorities are. And you do that through culture transformation and culture management. And that's been, I think really, the key to our successful pivots that we've made over the last six years that we've been able to continue to refine and hone where we really want to go through that culture movement. >> Absolutely. I think if I could add another- >> Please. >> spotlight to it is like the biggest thing about Ford has been among various startup-like culture, right? So the idea is that we encourage people to think outside the box, right? >> Savannah: Or outside the oval? >> Right! (laughs) >> Lisa: Outside the oval, yes! >> Absolutely! Right. >> So the question is like, you can experiment with various things, new technologies and you will get all the leadership support to go along with it. I think that is very important too and like we can be in the trenches and talk about all of these nice little things but who the heck would've thought that, you know Kubernetes was announced in 2015, in late 2016, we have early dev Kubernetes clusters already running. 2017, we are live with workloads on Kubernetes! >> Savannah: Early adopters over here. >> Yeah. >> Yeah. >> I'm like all of this thing doesn't happen without lot of foresight and support from the leadership, but it's also the grassroot efforts that is encouraged all along to be on the front end of all of these things and try different things. Some of them may not work >> Savannah: Right. >> But that's okay. But how do we know we are doing something, if you're not failing? We have to fail in order to do something, right? >> Lisa: I always say- >> So I think that's been a great thing that is encouraged very often and otherwise I would not be doing, I've done a whole bunch of stuff at Ford. Without that kind of ability to support and have an appetite for, some of those things would not have been here at all. >> I always say failure is not a bad F-word. >> Satish: Yep. >> Savannah: I love that. >> But what you're talking about there is kind of like driving this hot wheel of experimentation. You have to have the right culture and the mindset- >> Satish: Absolutely. >> to do that. Try fail, move on, learn, iterate, go. >> Satish: Correct. >> You guys have a great partnership with Red Hat and Boston University. You're speaking about that later today. >> Satish: Yes. >> Unpack that for us. What, from a technical perspective, what are you doing and what's it resulting in? >> Yeah, I think the biggest thing is Becky was talking about as during this transformation journey, is lot has changed in very small amount of time. So we traditionally been like, "Hey, here's a spreadsheet of things I need you to deliver for me" to "Here is a catalog of things, you can get it today and be successful with it". That is frightening to several of our developers. The goal, one of the things that we've been working with Q By Example, Red Hat and all the thing, is that how can we lower the bar for the developers, right? Kubernetes is great. It's also a wall of YAML. >> It's extremely complex, number one complaint. >> The question is how can I zero on? I'm like, if we go back think like when we talk about in cars with human-machine interfaces, which parts do I need to know? Here's the steering wheel, here's the gas pedal, or here's the brake. As long as you know these two, three different things you should be fairly be okay to drive those things, right? So the idea of some of the things with enablementing we are trying to do is like reduce that barrier, right? Reduce- lower the bar so that more people can participate in it. >> One of the ways that you did that was Q By Example, right, QBE? >> Satish: Yes, Yes. >> Can you tell us a little bit more about that as you finish this answer? >> Yeah, I think the biggest thing with Q By Example is like Q By Example gives you the small bite-sized things about Kubernetes, right? >> Savannah: Great place to start. >> But what we wanted to do is that we wanted to reinforce that learning by turning into a real world living example app. We took part info, we said, Hey, what does it look like? How do I make sure that it is highly available? How do I make sure that it is secure? Here is an example YAML of it that you can literally verbatim copy and paste into your editor and click run and then you will get an instant gratification feedback loop >> I was going to say, yeah, they feel like you're learning too! >> Yes. Right. So the idea would be is like, and then instead of giving you just a boring prose text to read, we actually drop links to relevant blog posts saying that, hey you can just go there. And that has been inspirational in terms of like and reinforcing the learning. So that has been where we started working with the Boston University, Red Hat and the community around all of that stuff. >> Talk a little bit about, Becky, about some of the business outcomes. You mentioned things like upskilling the workforce which is really nice to hear that there's such a big focus on it. But I imagine too, there's more participation in the community, but also from an end customer perspective. Obviously, everything Ford's doing is to serve the end customers >> Becky: Right. How does this help the end customer have that experience that they really, these days, demand with patience being something that, I think, is gone because of the pandemic? >> Right? Right. So one of the things that my team does is we create the platforms that help Accelerate developers be successful and it helps educate them more quickly on appropriate use of the platforms and helps them by adopting the platforms to be more secure which inherently lead to the better results for our end customers because their data is secure because the products that they have are well created and they're tested thoroughly. So we catch all those things earlier in the cycle by using these platforms that we help curate and produce. And that's really important because, like you had mentioned, this steep learning curve associated with Kubernetes, right? >> Savannah: Yeah. >> So my team is able to kind of help with that abstraction so that we solve kind of the higher complex problems for them so that developers can move faster and then we focus our education on what's important for them. We use things like Q By Example, as a source instead of creating that content ourselves, right? We are able to point them to that. So it's great that there's that community and we're definitely involved with that. But that's so important to help our developers be successful in moving as quickly as they want and not having 20,000 people solve the same problems. >> Satish: (chuckles) Yeah. >> Each individually- >> Savannah: you don't need to! >> and sometimes differently. >> Savannah: We're stronger together, you know? >> Exactly. >> The water level rises together and Ford is definitely a company that illustrates that by example. >> Yeah, I'm like, we can't make a better round wheel right? >> Yeah! So, we have to build upon what we have already been built ahead of us. And I think a lot of it is also about how can we give back and participate in the community, right? So I think that is paramount for us as like, here we are in Detroit so we're trying to recruit and show people that you know, everything that we do is not just old car and sheet metal >> Savannah: Combustion. >> and everything and right? There's a lot of tech goes and sometimes it is really, really cool to do that. And biggest thing for us is like how can we involve our community of developers sooner, earlier, faster without actually encumbering them and saying that, hey here is a book, go master it. We'll talk two months later. So I think that has been another journey. I think that has been a biggest uphill challenge for us is that how can we actually democratize all of these things for everybody. >> Yeah. Well no one better to try than you I would suspect. >> We can only try and hope everything turns out well, right? >> You know, as long as there's room for the bumpers on the lane for if you fail. >> Exactly. >> It sounds like you're driving the program in the right direction. Closing question for you, what's next? Is electric the future? Is Kubernetes the future? What's Ford all in on right now, looking forward? (crowd murmuring in the background) >> Data is the king, right? >> Savannah: Oh, okay, yes! >> Data is a new currency. We use that for several things to improve the cars improve the quality of autonomous driving Is Level 5 driving here? Maybe will be here soon, we'll see. But we are all working towards it, right? So machine learning, AI feedback. How do you actually post sale experience for example? So all of these are all areas that we are working to. We are, may not be getting like Kubernetes in a car but we are putting Kubernetes in plants. Like you order a Marquis or you order a Bronco, you see that here. Here's where in the assembly line your car is. It's taking pictures. It's actually taking pictures on Kubernetes platform. >> That's pretty cool. >> And it is tweeting for you on the Twitter and the social media platform. So there's a lot of that. So it is real and we are doing it. We need more help. A lot of the community efforts that we are seeing and a lot of the innovation that is happening on the floor here, it's phenomenal. The question is how we can incorporate those things into our workflows. >> Yeah, well you have the right audience for that here. You also have the right attitude, >> Exactly. >> the right appetite, and the right foundation. Becky, last question for you. Top three takeaways from your talk today. If you're talking to the developer community you want to inspire: Come work for us! What would you say? >> If you're ready to invest in yourself and upskill and be part of something that is pretty remarkable, come work for us! We have many, many different technical career paths that you can follow. We invest in our employees. When you master something, it's time for you to move on. We have career growth for you. It's been a wonderful gift to me and my family and I encourage everyone to check us out careers.ford.com or stop by our booth if you're happen to be here in person. >> Satish: Absolutely! >> We have our curated job openings that are specific for this community, available. >> Satish: Absolutely. >> Love it. Perfect close. Nailed pitch there. I'm sure you're all going to check out their job page. (all laugh) >> Exactly! And what you talked about, the developer experience, the customer experience are inextricably linked and you guys are really focused on that. Congratulations on all the work that you've done. We got to go get a selfie with that car girl. >> Yes, we do. >> Absolutely. >> We got to show them, we got to show the audience what it looks like on the inside too. We'll do a little IG video. (Lisa laughs) >> Absolutely. >> We will show you that for our guests and my cohost, Savannah Peterson. Lisa Martin here live in Detroit with theCUBE at KubeCon and CloudNativeCon 2022. The one and only John Furrier, who you know gets FOMO, is going to be back with me next. So stick around. (all laugh) (bright music)

>>live from Las Vegas. It's the Cube covering Splunk dot com. 19. Brought to you by spunk. >>Welcome back to the Cube, everyone. I'm John Ferrier with an angle on the Cube here in Las Vegas for Splunk dot com. 19. It's there 10 years of their customer main event. All the top customers and partners were here and, of course, accuse. Been covering dot com for seven years at a great guests from a censure. Mike Heinlein. Ecosystem Adventures. Global Analytics Plays and offerings lead a century Now. First of all, welcome to the Q. Thank you, John says. You're always has >>long titles. It's a very long title. Your lead. That's a mouthful. Offerings. Yeah, this >>meanings to these titles of the century. This, like >>Esso, I'm part of the Ecosystem Adventures Group, which helps to incubate our various different channel partners. And Dr Service is with those partners and then within the splint partnership. I'm focused on driving analytics offerings with various different practices that are already considering analytics and taking those >>to market. So you guys have a relation with spunk is evolving pretty quickly. >>It is >>what's the future look like? What's the current path >>Well, as you may be aware, we recently renewed our partnership with Bronco back in February. After two and 1/2 years, we had achieved most of our goals. And where we were starting to see is that where our initial objective was to help our clients to get Maur costs takeout and risk associated with their I T and Security operations way also learned a few things along the way, which is the Splunk Analyze politics engine can also be used outside of I t and Security and we can start to take it into industry verticals. And so one of the exciting things that we're doing is we brought our digital practice into the tent with us. We renewed in February, way have a couple of years. We're looking into the future, and we're gonna not only double down in i t and Security, but we're also going to start to build business analytics and io ti type solutions on top of within the vertical industries that were focused on one >>of those industries. Can you share them? >>Yeah. Yeah, so? So it would be things like energy utilities where power line analytics to reduce the amount of vegetation that might take out power lines cause fires cause outages. Patient flow, which would be how to help accelerate getting patients through the e. R and also increase throughput. Four Hospitals within supply Chain We're doing number of different things way have four different offerings that focus on technology, telecom, retail, consumer goods and manufacturing. So, like industrial type clients, >>so pretty much standard vertical industry that we normally see that's cracking in the business. Yeah, so I'll get your thoughts on this. One of the observations I want to share with you and get your reaction is is that with cloud and with data, it's interesting these day. There's a really key part of all this you mentioned. I I t and Security. Obviously, it's pretty straightforward. You see, that way started adding machine learning and a I and the things that domain expertise of these verticals become the pacing item the ke ke i t, if you will with scale of that what's going on? That's right level. Are you seeing that this is a fertile ground for opportunities that how you guys see it? Can you >>you Absolutely I think I think where it centuries strong is in our industry, Ackerman not just to 19 security, but within different industry verticals on. Then you take our digital practice, which is where our data science is live, where they're developing advanced analytics models and essentially working with a lot of the open source modeling tools like python that integrates very well a Splunk. It gives us the opportunity to take that data that could be bundled up. It could be data rest, maybe three years of sales data, and we create a forecast with it and do that on top of spunk. Or maybe something where within a supply chain or a flow within a hospital, were able to use machine learning to start to move some of the computer and thought from human beings to machines >>were some of the innovative service is you guys have built on top of Splunk because they're enabling platform. So again, opportunities. What are you guys doing in the >>soles? So both in the retail and in the technology space, we've created a couple of punishment engines. When you think of a supply chain, I need to know what my forecast is. What do I plan to sell? How many items. Do I need to have an inventory in the warehouse and in the store? And then how am I gonna get those items? And then how many should I order the next day? So we're using Splint to figure all of that out. >>What sort of surprise? Learnings You've got a deal with flunk because has always seems to be a new revelation when people get data and they start playing with insights. Beyond that, some sort of business breakthroughs are weird. Things happen when you start playing with data. Any anecdotal surprises, their learnings. You've seen >>a, well, a tremendous number. And in fact, what what happens is when you start to open up the silos. So most of our clients are stuck with a lot of legacy technologies that they've acquired over the last two or three decades. Splunk enables to open that Optimus get insights that we couldn't before. So it could be it could be. I could get a patient through a particular process, you know, twice as fast is what historically had been able to do. Or maybe for examples, something that Doug Merit mentioned yesterday, which is where we're partying very closely with Splunk for human trafficking. We've created an offering where split it already gone out created Data Lake of a lot of data from educational entities. Ngo's government agencies we took that builds a machine learning on top of it and able to identify high value targets or establishments that have a high risk of human trafficking, which is already starting to get results. In Florida, >>you mentioned health care no multiple times, someone of your key verticals. >>It is one that's emerging is very exciting. And it's kind of evidence of where we're working really well, a sponge. A lot of cases we've developed things that we take into Splunk, and we go to market together. In this particular case, Splunk created patient flow, took it to us. And now we're working to identify about a dozen different hospitals where we're gonna go meet with their CEOs and talk to him about what we can do to help them increased profit and patient satisfaction at the same time. >>What some of those conversations, like when you go and knock on the doors and say, Hey, I got a new secret weapon to solve your problems because this is its new things that people have these problems that couldn't have attacked before in the past. Now they have potential capabilities. What are some of those conversations? Take out there like Come on in, educate me. I want to buy right away or door slammed in your face and get his attention. >>Well, so way just had a really exciting meeting with a very large brochure in the Midwest. And as was explaining the different things that we could do a Splunk she actually the head of supply chain. Excuse me. It almost seems like fairy dust to me. In other words, the hardest challenge that I have sometimes is able to say, Look, you're used to doing this 24 months, maybe 36 months. I think I could do it free in less than six, and that's just so hard for them to absorb. So So a lot of cases it's it's transitioning to Well, let us figure out how we could prove that to you. Doing some kind of a concept or a pilot. >>You know, it's interesting is that you know, when you see people get set up with data platform, it's kind of editor of stage. Let's set the foundation. Let's make sure things flowing in you well. And then they started getting some discoveries here and there, and then they get business value, and then it kind of goes to another level. I think this is where things I see you guys doing well and others here in the ecosystem floor, and that is that It's a workflow optimization issue, I think. Wait a minute, way have all this data. Well, let's go do this. That's a little bit more of a ballistic business process or some sort of. >>That's right. Your >>challenge. Is that how >>you Yes. So I would say you always have a business process, at least in the industry verticals, and you have a lot of data that silo on. Then you crack those silos open on, then it's really basically intersection of what we would call planning and execution, which is, for example, maybe I have on oil rig and I have a ship that is taking materials and people back and forth. But now I know that I have actual things. Head into that port where if I send this ship now, I'm gonna have to come back in the next 24 hours. If I hold that ship off for two or three hours, then I can get more materials and people on board, and I don't have to come back for another 48 hours. So now I've just reduced greatly my operating costs. >>And I think that's interesting. Is that you think about what you just said, Yeah, go back 15 years. What's the data base scheming and make that happen. Date is over there, it's over. They're gonna write a query that Leighton see. It never happens. >>It's Jackie, right? So we're kind of out of the business of trying to fit square pegs into relational round holes, which takes the better part of maybe 50% of a lot of projects to implement those solutions. And so, with spunk, you're basically dumping the date end and you're layering your scheme on top of it, which enables you to accelerate delivery. And additionally, I don't have to cobble together and stitched together multiple technologies to do ingestion analytic storage visualization so I could mobilize teams much more quickly. Then it would traditional solutions. >>You know, Mike, I'd love your thoughts on the center's transformation because looking at you. What you guys have done is a company. It's been interesting, a lot of successes. But firm's been around for a while, right? So impressed. Different names don't back the old school back minicomputers. You know, rolling out projects had long arises. Multiyear. Now the speedy a name has completely changed clouds. Here you got data. How has the Splunk on these Modern technology has changed the centers engagement practices. >>I think you're touching on what we would probably call agile delivery, right or continuous delivery, where our clients don't want to push off from shore into a big bang project where they don't get to see the results for 12 to 24 months. That's a lot of risk for them. So what's book enables us to do, really is to do a delivery and deliver value in Angel's sprints in three 12 you know, 16 weeks sprints where we're literally be giving them value. We also don't have to understand all of the data. If you're using relational databases, you pretty much have to understand everything before you push off from shore with spunk. I can no minimal amount and start and deliver value, and then as I go, I'm learning more about my data. I could deliver more use cases and more value. >>It's interesting, you know, go back to the old enterprise sales model. You know, you do a pilot or a POC poc that a pilot with pilots, a date and that's what months and then Then the decision makes. And then you got to start over for the time that it'll happen in about months. A year. Yeah, technology changes. >>That's right. >>You guys are doing essentially agile sprints that are kind of like a little Mini p O sees. That's that's correct. Docs are actually really work. >>That's right. That's >>the new seems like the new sales model is that >>Well, I would say it's something that, with the rapid prototyping capability, like a sponge that gives us that flexibility todo depending on what we're doing, we may not have that flexibility. We may be limited by the technology. >>How would you describe the strength of censure Splunk partnership? >>It's a very strong So like I mentioned before, we way started to a nap three years ago. Way just renewed that relationship in February, and we've added more practices from within Accenture like digital practice. So now we have strategy, digital technology and security. We're focusing in doubling down and security in our I T markets, but also then starting to explore new industry verticals in Business analytics and Io Ti. As I explained earlier, we're bringing things to Splunk in there helping us cell, and they're bringing things to Austin. We're helping themselves, and there's a lot of excitement. I mean, I think it's really a combination of the right people with the right industry knowledge at the right time with the right technology. >>Final question in the industry For a while, you see the waves pretty big wave run now. Lot of confluence coming together. Multiple different Durant cloud data scale, everything speed. What's exciting you these days? What's the big story that people should pay attention to right now? Well, in this space, I >>think it really dovetails into Doug Steam, and I don't mean Thio, really, you know, piggyback on that. But it's true, and that is that so many of our clients, you know, still have a lot of technical debt from decades ago, and we get to come in there and say, Look in a matter of weeks and months, we could help You make sense of this way, can help you capture revenue you couldn't capture before Dr Out costs that you couldn't drive out before and reduce risk that you couldn't reduce before. So I mean, it's it's probably the best time of my entire career. >>Frankly, Cooper, daddies and certainly containers helps. Yeah, make those legacy workloads somewhat compatible with modern infrastructure. When you have those technical debt conversations with customers kind of realizing like I'm on the verge of bankruptcy, what do I do it? Is it more advisor? You guys come in, more counseling slash get developed? >>Yeah, yeah, A lot of times it's It's helping them to come in and assess what their situation is. Help them build a road map into the future. Sometimes it's rationalizing some of the technical debt. Sometimes it's how can we augment what you already have? And then and then in the future is that reaches end of life. We almost just turn it off. But you're up and running, you know, on this other platform that we've augmented into that ecosystem >>So tech flow positive. >>There you go. >>Yeah, cash flow positive take from technical debt from checked bag. Mike. Thanks for coming up. Appreciate it. Thanks for the knights. Thanks for having me. Great insights. You get all the data and the insights here. Workflow is rocking the cube. Second day of three days. I'm John Barrymore coverage after this short break.

(upbeat music) >> Announcer: Live from Las Vegas it's theCube covering AWS re:Invent 2017 presented by AWS, Intel and our ecosystem of partners. >> Well welcome back here on theCube we are live at re:Invent, AWS's big show, and I mean big show here in Las Vegas spanning some four hotels hundreds of thousands of exhibit space and nearly 50,000 attendees gonna be a great 3 days and we're glad you're with us here on theCube. I'm John Walls, along with Lisa Martin again, glad to have you here and we're now joined by Paul Beavers who is VP of products he specializes on the RND and the product management side of the house of BMC and Paul, glad to have you with us. Say, A Cube first-timer, right? >> Yes I am, nice to meet you, glad to be here. >> John: Well go easy on ya. >> Okay, good. >> John: And a Bronco >> Yeah >> John: UCO, Central Oklahoma >> Yes, absolutely >> I'm an old Tulsa guy >> Oh, are you? >> So I know a lot about UCO My wife's a UT grad >> Alright good, we'll keep it all in the house here First, tell us about BMC first, company's been around for nearly, what, almost some 40 years, so you've gone through multiple iterations, so how'd you get to the point to where you are now and what are you doing now? >> You know, the way that I like to think about BMC is while the technology, the underlying technology has changed a lot over the years we started off with our roots in mainframe. We supported many different Unix platforms, Linux platforms different types of databases, but the one thing that has always been the same is, BMC had one overarching goal which is to help our customers succeed with IT, regardless of what the platform is. So as the industry is transitioned, I've been in the industry about 30 years and over the last 30 years as the industry's transitioned it, there has always been a need for our large enterprises, insurance companies, finance companies to be successful with their IT. And there's always a gap to be filed around making IT better and making IT functional making it perform and most importantly making sure that it's supporting the business and the business is continuing. >> And that kind of previews a question that I wanted to ask you, is as you've seen massive technology shifts since 1981, what are some of the trends that you are seeing that the business is really leading with? The business outcomes that IT has to facilitate. >> I think the, obviously there's been lots of different transitions in the business and the technology over the years since 81. I think the last five years have been the most pivotal. And the reason is because, not because there is a change in deity or the technology but because of all of the different technology and opportunities that are out there, businesses are now leveraging IT to be the business as opposed to support the business. Right, so if you take things like Uber, Netflix, Airbnb even banks today, the IT is the business, right. So if you think back about five or ten years ago, IT, a mobile app for the bank was a convenience now if you're a member of a bank and the mobile app doesn't work, you're gonna find a new bank. That's all there is to it, it is now critical. It's what digital transformation really means, it's not a buzzword, it's real and all the businesses that surround us we're at Amazon's event, right, Amazon, one of the most, the biggest digital businesses there is. All of those businesses have a new dependency on, on IT. So that change has created opportunities for companies like BMC to ensure that IT works because then we ensure that the digital businesses are working. >> And you say, you know, not a buzz word, a reality but yet there's still a lot of people on the other side of that fence, right, and they haven't made that transformation yet or they're in the process, that's what you're all about right, facilitating that, so what do you, talking to those who may be a little bit of a foot dragger, you might say, and they've got to make some different decisions now, so how do you, how are you coaxing those folks along and what's your primary messaging on that? >> There's kind of two different aspects on that. So one is from a business perspective we really want to see, if they don't digitally transform, they won't exist in five years. And I think they know that, so, I think the situation's becoming more and more dire or urgent for them. One of the things that has helped them is things like AWS, Amazon web services, in the cloud, makes it much easier to digitally transform, right. Because it's so readily available and actually there's whole businesses that are growing up on AWS. So what we do at BMC is help those customers that are the edge, they're about to make a decision around cloud. We help them ensure that they're going to be okay when they go to the cloud, right. An example would be, we've been with them now, some of these companies, large insurance company in the Midwest, we've been with them for 30 years as customer and we're still going to be there and we're still going to help them on their cloud journey. And that story gets repeated time and time again across our customer base. >> Lisa: One of the interesting things that was in the news, John Furrier wrote a great article that was published on Forbes the other day. He did an exclusive interview with Andy Jassy, the CEO of AWS, who talked about the, AWS 18 billion dollar run rate 42% growth a year, he said, you know, we haven't here by working with startups alone. We're at the precipices of this mass enterprise migration. You guys have been a partner with AWS for a while you're an ISV, what are some of the new things that you really hear at AWS re:Invent to reinforce with respect to your strategic partnership with AWS? >> You know, when, I can break that down into kinda three simple, three simple ways, right. So when you think about a cloud migration customers are typically looking, looking to do three different things, right, they're either looking to save money by lifting and shifting existing workloads and putting them into the cloud. And Amazon, that's a sweet spot for them they've been doing that for a while. But, that's kind of the entry level what we're seeing is leveraging the native services that AWS provides, not only make it cheaper for the customer but it makes it, it makes it much faster to develop apps and to succeed with digital transformation. Matter of fact, the application development within enterprises are now becoming more integrators of different cloud services and technologies as opposed to building applications from scratch. So it becomes an arms race, if you will, for the different vendors, right, the first bank to get to a mobile app, the first insurance company to do everything online. All of these different needs and capibilites around digital transformation AWS facilitates that. And they do it, they do it, they have some competition, but they're really leading, they're really leading the path. >> And in speaking of that leadership that we, I was talking about their growth rate earlier and they are in the clear lead. And they have a very consistent message coming from Andy Jassy, we're not lookin in the rear view mirror. I'm curious, you've mentioned application development a minute ago, how are, how's your conversation with in organizations, whether it's a bank or an insurance company, AWS has done a great job of attracting developers. Are you seeing the shift, in terms of your conversations, up the chain of command to the CEO, the corporate board? >> I'll answer that in two different ways. So, first of all, if you think about IT operations, right, so IT operations are the guys within these enterprises that typically make sure that IT runs. It's all about monitoring and provisioning, the work that to make IT run. That is BMC's sweet spot. And what you find in these companies is they get, they start small with a cloud strategy and then at some point they reach critical mass and the CEOs and the CIOs get nervous about okay, what if the cloud breaks, right? And so they want to manage that with the rigor and disipline that they manage typical IT operations. That's a real sweet spot for BMC. Because we can manage AWS and monitor all the applications running AWS and give those CEOs and CIOs and CFOs the comfort that their applications are going to be there when they need to, and as we already said earlier, those applications now are their businesses so the cost of an outage is way more significant that it was even five years ago. >> John: You mentioned, you know, four, five year trend this has been going on for little bit now. So just as capabilities have changed, I'm sure the questions coming in are changing too, right? So what's kind of leap frog to the head of the pack in terms of when people come to you and say, hey, I need help, but this is what's worrying me today as opposed to what was answered yesterday. >> You know, the way that I would answer that is scalability, right, so when applications go outside the enterprise, out into the consumer world, right, everybody's got the app on their mobile phone, you go from tens of thousands of users to millions of users. And so the performance metrics and the data that you generate goes into very, very large amounts of data. In order to understand performance, you have to have a new technique. And so understanding performance in modern times is really the problem at hand and that's where you start to hear about things like, big data and the ability to store petabytes of data and the ability to search and analyze that data very quickly. Leveraging machine learning and analytics that's where the big need is today. And that's where companies like BMC are rotating to be able to support that massive scale, that volume of information. Because it's no longer about a thousand users of an internal app it's about, I've got a loyal, we were talking to a grocery store the other day, they have a loyalty app with two and a half million users and by the way, if the loyalty app doesn't work they go to a different grocery store. So it's a completely different model but it's really, I would say the number one concern right now is the scale and second to that is, in order to achieve scale enterprises are leveraging much more modern technology both in the cloud and on the premises but that modern technology, you have to be able to monitor and understand the performance of that modern technology. >> One more question for you Paul. What are you most excited to hear from AWS this week? We've seen a couple of announcements that hit the wire Monday morning at midnight about AI for example. What are some of the things that you and BMC are excited to hear from your partner AWS? >> You know, I actually today, I was in the partner, key note summit. I'm excited about the way that AWS is rotating from a DevOps motion to enterprise. So they announced this week that there's actually going to be the ability for ISV's like BMC to sell product in the AWS marketplace but do it in a way that you can price it and consume it as an enterprise. So they're literally, that's actually news to me at this event, is that they're really uplifting this approach around sort of smaller groups and targeting big enterprises and for us at BMC selfishly, giving us the ability to deliver on AWS to very, very large enterprises which is our customer base, we support the global 2000. >> John: That's why you're licking your chops this week >> Exactly, absolutely Absolutely (John laughs) >> Paul, thanks for the time >> No problem, thank you >> Glad to have you on theCube and look forward to the next time down the road too. >> Paul: Absolutely, anytime. >> John: Alright, Paul Beavers, joining us from BMC >> Very nice to meet both of you >> Back with more, we're here at re:Invent we're live in Las Vegas and you are watching our coverage here on theCube. (upbeat music)