(upbeat music) >> Welcome everyone to theCUBE's presentation of the AWS Startup Showcase AI/ML Top Startups Building Foundation Model Infrastructure. This is season three, episode one of our ongoing series covering exciting startups from the AWS ecosystem to talk about data and analytics. I'm your host, Lisa Martin and today we're excited to be joined by two guests from Astronomer. Steven Hillion joins us, it's Chief Data Officer and Jeff Fletcher, it's director of ML. They're here to talk about machine learning and data orchestration. Guys, thank you so much for joining us today. >> Thank you. >> It's great to be here. >> Before we get into machine learning let's give the audience an overview of Astronomer. Talk about what that is, Steven. Talk about what you mean by data orchestration. >> Yeah, let's start with Astronomer. We're the Airflow company basically. The commercial developer behind the open-source project, Apache Airflow. I don't know if you've heard of Airflow. It's sort of de-facto standard these days for orchestrating data pipelines, data engineering pipelines, and as we'll talk about later, machine learning pipelines. It's really is the de-facto standard. I think we're up to about 12 million downloads a month. That's actually as a open-source project. I think at this point it's more popular by some measures than Slack. Airflow was created by Airbnb some years ago to manage all of their data pipelines and manage all of their workflows and now it powers the data ecosystem for organizations as diverse as Electronic Arts, Conde Nast is one of our big customers, a big user of Airflow. And also not to mention the biggest banks on Wall Street use Airflow and Astronomer to power the flow of data throughout their organizations. >> Talk about that a little bit more, Steven, in terms of the business impact. You mentioned some great customer names there. What is the business impact or outcomes that a data orchestration strategy enables businesses to achieve? >> Yeah, I mean, at the heart of it is quite simply, scheduling and managing data pipelines. And so if you have some enormous retailer who's managing the flow of information throughout their organization they may literally have thousands or even tens of thousands of data pipelines that need to execute every day to do things as simple as delivering metrics for the executives to consume at the end of the day, to producing on a weekly basis new machine learning models that can be used to drive product recommendations. One of our customers, for example, is a British food delivery service. And you get those recommendations in your application that says, "Well, maybe you want to have samosas with your curry." That sort of thing is powered by machine learning models that they train on a regular basis to reflect changing conditions in the market. And those are produced through Airflow and through the Astronomer platform, which is essentially a managed platform for running airflow. So at its simplest it really is just scheduling and managing those workflows. But that's easier said than done of course. I mean if you have 10 thousands of those things then you need to make sure that they all run that they all have sufficient compute resources. If things fail, how do you track those down across those 10,000 workflows? How easy is it for an average data scientist or data engineer to contribute their code, their Python notebooks or their SQL code into a production environment? And then you've got reproducibility, governance, auditing, like managing data flows across an organization which we think of as orchestrating them is much more than just scheduling. It becomes really complicated pretty quickly. >> I imagine there's a fair amount of complexity there. Jeff, let's bring you into the conversation. Talk a little bit about Astronomer through your lens, data orchestration and how it applies to MLOps. >> So I come from a machine learning background and for me the interesting part is that machine learning requires the expansion into orchestration. A lot of the same things that you're using to go and develop and build pipelines in a standard data orchestration space applies equally well in a machine learning orchestration space. What you're doing is you're moving data between different locations, between different tools, and then tasking different types of tools to act on that data. So extending it made logical sense from a implementation perspective. And a lot of my focus at Astronomer is really to explain how Airflow can be used well in a machine learning context. It is being used well, it is being used a lot by the customers that we have and also by users of the open source version. But it's really being able to explain to people why it's a natural extension for it and how well it fits into that. And a lot of it is also extending some of the infrastructure capabilities that Astronomer provides to those customers for them to be able to run some of the more platform specific requirements that come with doing machine learning pipelines. >> Let's get into some of the things that make Astronomer unique. Jeff, sticking with you, when you're in customer conversations, what are some of the key differentiators that you articulate to customers? >> So a lot of it is that we are not specific to one cloud provider. So we have the ability to operate across all of the big cloud providers. I know, I'm certain we have the best developers that understand how best practices implementations for data orchestration works. So we spend a lot of time talking to not just the business outcomes and the business users of the product, but also also for the technical people, how to help them better implement things that they may have come across on a Stack Overflow article or not necessarily just grown with how the product has migrated. So it's the ability to run it wherever you need to run it and also our ability to help you, the customer, better implement and understand those workflows that I think are two of the primary differentiators that we have. >> Lisa: Got it. >> I'll add another one if you don't mind. >> You can go ahead, Steven. >> Is lineage and dependencies between workflows. One thing we've done is to augment core Airflow with Lineage services. So using the Open Lineage framework, another open source framework for tracking datasets as they move from one workflow to another one, team to another, one data source to another is a really key component of what we do and we bundle that within the service so that as a developer or as a production engineer, you really don't have to worry about lineage, it just happens. Jeff, may show us some of this later that you can actually see as data flows from source through to a data warehouse out through a Python notebook to produce a predictive model or a dashboard. Can you see how those data products relate to each other? And when something goes wrong, figure out what upstream maybe caused the problem, or if you're about to change something, figure out what the impact is going to be on the rest of the organization. So Lineage is a big deal for us. >> Got it. >> And just to add on to that, the other thing to think about is that traditional Airflow is actually a complicated implementation. It required quite a lot of time spent understanding or was almost a bespoke language that you needed to be able to develop in two write these DAGs, which is like fundamental pipelines. So part of what we are focusing on is tooling that makes it more accessible to say a data analyst or a data scientist who doesn't have or really needs to gain the necessary background in how the semantics of Airflow DAGs works to still be able to get the benefit of what Airflow can do. So there is new features and capabilities built into the astronomer cloud platform that effectively obfuscates and removes the need to understand some of the deep work that goes on. But you can still do it, you still have that capability, but we are expanding it to be able to have orchestrated and repeatable processes accessible to more teams within the business. >> In terms of accessibility to more teams in the business. You talked about data scientists, data analysts, developers. Steven, I want to talk to you, as the chief data officer, are you having more and more conversations with that role and how is it emerging and evolving within your customer base? >> Hmm. That's a good question, and it is evolving because I think if you look historically at the way that Airflow has been used it's often from the ground up. You have individual data engineers or maybe single data engineering teams who adopt Airflow 'cause it's very popular. Lots of people know how to use it and they bring it into an organization and say, "Hey, let's use this to run our data pipelines." But then increasingly as you turn from pure workflow management and job scheduling to the larger topic of orchestration you realize it gets pretty complicated, you want to have coordination across teams, and you want to have standardization for the way that you manage your data pipelines. And so having a managed service for Airflow that exists in the cloud is easy to spin up as you expand usage across the organization. And thinking long term about that in the context of orchestration that's where I think the chief data officer or the head of analytics tends to get involved because they really want to think of this as a strategic investment that they're making. Not just per team individual Airflow deployments, but a network of data orchestrators. >> That network is key. Every company these days has to be a data company. We talk about companies being data driven. It's a common word, but it's true. It's whether it is a grocer or a bank or a hospital, they've got to be data companies. So talk to me a little bit about Astronomer's business model. How is this available? How do customers get their hands on it? >> Jeff, go ahead. >> Yeah, yeah. So we have a managed cloud service and we have two modes of operation. One, you can bring your own cloud infrastructure. So you can say here is an account in say, AWS or Azure and we can go and deploy the necessary infrastructure into that, or alternatively we can host everything for you. So it becomes a full SaaS offering. But we then provide a platform that connects at the backend to your internal IDP process. So however you are authenticating users to make sure that the correct people are accessing the services that they need with role-based access control. From there we are deploying through Kubernetes, the different services and capabilities into either your cloud account or into an account that we host. And from there Airflow does what Airflow does, which is its ability to then reach to different data systems and data platforms and to then run the orchestration. We make sure we do it securely, we have all the necessary compliance certifications required for GDPR in Europe and HIPAA based out of the US, and a whole bunch host of others. So it is a secure platform that can run in a place that you need it to run, but it is a managed Airflow that includes a lot of the extra capabilities like the cloud developer environment and the open lineage services to enhance the overall airflow experience. >> Enhance the overall experience. So Steven, going back to you, if I'm a Conde Nast or another organization, what are some of the key business outcomes that I can expect? As one of the things I think we've learned during the pandemic is access to realtime data is no longer a nice to have for organizations. It's really an imperative. It's that demanding consumer that wants to have that personalized, customized, instant access to a product or a service. So if I'm a Conde Nast or I'm one of your customers, what can I expect my business to be able to achieve as a result of data orchestration? >> Yeah, I think in a nutshell it's about providing a reliable, scalable, and easy to use service for developing and running data workflows. And talking of demanding customers, I mean, I'm actually a customer myself, as you mentioned, I'm the head of data for Astronomer. You won't be surprised to hear that we actually use Astronomer and Airflow to run all of our data pipelines. And so I can actually talk about my experience. When I started I was of course familiar with Airflow, but it always seemed a little bit unapproachable to me if I was introducing that to a new team of data scientists. They don't necessarily want to have to think about learning something new. But I think because of the layers that Astronomer has provided with our Astro service around Airflow it was pretty easy for me to get up and running. Of course I've got an incentive for doing that. I work for the Airflow company, but we went from about, at the beginning of last year, about 500 data tasks that we were running on a daily basis to about 15,000 every day. We run something like a million data operations every month within my team. And so as one outcome, just the ability to spin up new production workflows essentially in a single day you go from an idea in the morning to a new dashboard or a new model in the afternoon, that's really the business outcome is just removing that friction to operationalizing your machine learning and data workflows. >> And I imagine too, oh, go ahead, Jeff. >> Yeah, I think to add to that, one of the things that becomes part of the business cycle is a repeatable capabilities for things like reporting, for things like new machine learning models. And the impediment that has existed is that it's difficult to take that from a team that's an analyst team who then provide that or a data science team that then provide that to the data engineering team who have to work the workflow all the way through. What we're trying to unlock is the ability for those teams to directly get access to scheduling and orchestrating capabilities so that a business analyst can have a new report for C-suite execs that needs to be done once a week, but the time to repeatability for that report is much shorter. So it is then immediately in the hands of the person that needs to see it. It doesn't have to go into a long list of to-dos for a data engineering team that's already overworked that they eventually get it to it in a month's time. So that is also a part of it is that the realizing, orchestration I think is fairly well and a lot of people get the benefit of being able to orchestrate things within a business, but it's having more people be able to do it and shorten the time that that repeatability is there is one of the main benefits from good managed orchestration. >> So a lot of workforce productivity improvements in what you're doing to simplify things, giving more people access to data to be able to make those faster decisions, which ultimately helps the end user on the other end to get that product or the service that they're expecting like that. Jeff, I understand you have a demo that you can share so we can kind of dig into this. >> Yeah, let me take you through a quick look of how the whole thing works. So our starting point is our cloud infrastructure. This is the login. You go to the portal. You can see there's a a bunch of workspaces that are available. Workspaces are like individual places for people to operate in. I'm not going to delve into all the deep technical details here, but starting point for a lot of our data science customers is we have what we call our Cloud IDE, which is a web-based development environment for writing and building out DAGs without actually having to know how the underpinnings of Airflow work. This is an internal one, something that we use. You have a notebook-like interface that lets you write python code and SQL code and a bunch of specific bespoke type of blocks if you want. They all get pulled together and create a workflow. So this is a workflow, which gets compiled to something that looks like a complicated set of Python code, which is the DAG. I then have a CICD process pipeline where I commit this through to my GitHub repo. So this comes to a repo here, which is where these DAGs that I created in the previous step exist. I can then go and say, all right, I want to see how those particular DAGs have been running. We then get to the actual Airflow part. So this is the managed Airflow component. So we add the ability for teams to fairly easily bring up an Airflow instance and write code inside our notebook-like environment to get it into that instance. So you can see it's been running. That same process that we built here that graph ends up here inside this, but you don't need to know how the fundamentals of Airflow work in order to get this going. Then we can run one of these, it runs in the background and we can manage how it goes. And from there, every time this runs, it's emitting to a process underneath, which is the open lineage service, which is the lineage integration that allows me to come in here and have a look and see this was that actual, that same graph that we built, but now it's the historic version. So I know where things started, where things are going, and how it ran. And then I can also do a comparison. So if I want to see how this particular run worked compared to one historically, I can grab one from a previous date and it will show me the comparison between the two. So that combination of managed Airflow, getting Airflow up and running very quickly, but the Cloud IDE that lets you write code and know how to get something into a repeatable format get that into Airflow and have that attached to the lineage process adds what is a complete end-to-end orchestration process for any business looking to get the benefit from orchestration. >> Outstanding. Thank you so much Jeff for digging into that. So one of my last questions, Steven is for you. This is exciting. There's a lot that you guys are enabling organizations to achieve here to really become data-driven companies. So where can folks go to get their hands on this? >> Yeah, just go to astronomer.io and we have plenty of resources. If you're new to Airflow, you can read our documentation, our guides to getting started. We have a CLI that you can download that is really I think the easiest way to get started with Airflow. But you can actually sign up for a trial. You can sign up for a guided trial where our teams, we have a team of experts, really the world experts on getting Airflow up and running. And they'll take you through that trial and allow you to actually kick the tires and see how this works with your data. And I think you'll see pretty quickly that it's very easy to get started with Airflow, whether you're doing that from the command line or doing that in our cloud service. And all of that is available on our website >> astronomer.io. Jeff, last question for you. What are you excited about? There's so much going on here. What are some of the things, maybe you can give us a sneak peek coming down the road here that prospects and existing customers should be excited about? >> I think a lot of the development around the data awareness components, so one of the things that's traditionally been complicated with orchestration is you leave your data in the place that you're operating on and we're starting to have more data processing capability being built into Airflow. And from a Astronomer perspective, we are adding more capabilities around working with larger datasets, doing bigger data manipulation with inside the Airflow process itself. And that lends itself to better machine learning implementation. So as we start to grow and as we start to get better in the machine learning context, well, in the data awareness context, it unlocks a lot more capability to do and implement proper machine learning pipelines. >> Awesome guys. Exciting stuff. Thank you so much for talking to me about Astronomer, machine learning, data orchestration, and really the value in it for your customers. Steve and Jeff, we appreciate your time. >> Thank you. >> My pleasure, thanks. >> And we thank you for watching. This is season three, episode one of our ongoing series covering exciting startups from the AWS ecosystem. I'm your host, Lisa Martin. You're watching theCUBE, the leader in live tech coverage. (upbeat music)

(upbeat intro music) >> Hello everyone. Welcome to theCUBE's coverage of International Women's Day. I'm your host, John Furrier, here in Palo Alto, California. Got a special remote guest coming in. Teresa Carlson, President and Chief Commercial Officer at Flexport, theCUBE alumni, one of the first, let me go back to 2013, Teresa, former AWS. Great to see you. Thanks for coming on. >> Oh my gosh, almost 10 years. That is unbelievable. It's hard to believe so many years of theCUBE. I love it. >> It's been such a great honor to interview you and follow your career. You've had quite the impressive run, executive level woman in tech. You've done such an amazing job, not only in your career, but also helping other women. So I want to give you props to that before we get started. Thank you. >> Thank you, John. I, it's my, it's been my honor and privilege. >> Let's talk about Flexport. Tell us about your new role there and what it's all about. >> Well, I love it. I'm back working with another Amazonian, Dave Clark, who is our CEO of Flexport, and we are about 3,000 people strong globally in over 90 countries. We actually even have, we're represented in over 160 cities and with local governments and places around the world, which I think is super exciting. We have over 100 network partners and growing, and we are about empowering the global supply chain and trade and doing it in a very disruptive way with the use of platform technology that allows our customers to really have visibility and insight to what's going on. And it's a lot of fun. I'm learning new things, but there's a lot of technology in this as well, so I feel right at home. >> You quite have a knack from mastering growth, technology, and building out companies. So congratulations, and scaling them up too with the systems and processes. So I want to get into that. Let's get into your personal background. Then I want to get into the work you've done and are doing for empowering women in tech. What was your journey about, how did it all start? Like, I know you had a, you know, bumped into it, you went Microsoft, AWS. Take us through your career, how you got into tech, how it all happened. >> Well, I do like to give a shout out, John, to my roots and heritage, which was a speech and language pathologist. So I did start out in healthcare right out of, you know, university. I had an undergraduate and a master's degree. And I do tell everyone now, looking back at my career, I think it was super helpful for me because I learned a lot about human communication, and it has done me very well over the years to really try to understand what environments I'm in and what kind of individuals around the world culturally. So I'm really blessed that I had that opportunity to work in healthcare, and by the way, a shout out to all of our healthcare workers that has helped us get through almost three years of COVID and flu and neurovirus and everything else. So started out there and then kind of almost accidentally got into technology. My first small company I worked for was a company called Keyfile Corporation, which did workflow and document management out of Nashua, New Hampshire. And they were a Microsoft goal partner. And that is actually how I got into big tech world. We ran on exchange, for everybody who knows that term exchange, and we were a large small partner, but large in the world of exchange. And those were the days when you would, the late nineties, you would go and be in the same room with Bill Gates and Steve Ballmer. And I really fell in love with Microsoft back then. I thought to myself, wow, if I could work for a big tech company, I got to hear Bill on stage about saving, he would talk about saving the world. And guess what my next step was? I actually got a job at Microsoft, took a pay cut and a job downgrade. I tell this story all the time. Took like three downgrades in my role. I had been a SVP and went to a manager, and it's one of the best moves I ever made. And I shared that because I really didn't know the world of big tech, and I had to start from the ground up and relearn it. I did that, I just really loved that job. I was at Microsoft from 2000 to 2010, where I eventually ran all of the U.S. federal government business, which was a multi-billion dollar business. And then I had the great privilege of meeting an amazing man, Andy Jassy, who I thought was just unbelievable in his insights and knowledge and openness to understanding new markets. And we talked about government and how government needed the same great technology as every startup. And that led to me going to work for Andy in 2010 and starting up our worldwide public sector business. And I pinch myself some days because we went from two people, no offices, to the time I left we had over 10,000 people, billions in revenue, and 172 countries and had done really amazing work. I think changing the way public sector and government globally really thought about their use of technology and Cloud computing in general. And that kind of has been my career. You know, I was there till 2020, 21 and then did a small stint at Splunk, a small stint back at Microsoft doing a couple projects for Microsoft with CEO, Satya Nadella, who is also an another amazing CEO and leader. And then Dave called me, and I'm at Flexport, so I couldn't be more honored, John. I've just had such an amazing career working with amazing individuals. >> Yeah, I got to say the Amazon One well-documented, certainly by theCUBE and our coverage. We watched you rise and scale that thing. And like I said at a time, this will when we look back as a historic run because of the build out. I mean as a zero to massive billions at a historic time where government was transforming, I would say Microsoft had a good run there with Fed, but it was already established stuff. Federal business was like, you know, blocking and tackling. The Amazon was pure build out. So I have to ask you, what was your big learnings? Because one, you're a Seattle big tech company kind of entrepreneurial in the sense of you got, here's some working capital seed finance and go build that thing, and you're in DC and you're a woman. What did you learn? >> I learned that you really have to have a lot of grit. You, my mom and dad, these are kind of more southern roots words, but stick with itness, you know. you can't give up and no's not in your vocabulary. I found no is just another way to get to yes. That you have to figure out what are all the questions people are going to ask you. I learned to be very patient, and I think one of the things John, for us was our secret sauce was we said to ourselves, if we're going to do something super transformative and truly disruptive, like Cloud computing, which the government really had not utilized, we had to be patient. We had to answer all their questions, and we could not judge in any way what they were thinking because if we couldn't answer all those questions and prove out the capabilities of Cloud computing, we were not going to accomplish our goals. And I do give so much credit to all my colleagues there from everybody like Steve Schmidt who was there, who's still there, who's the CISO, and Charlie Bell and Peter DeSantis and the entire team there that just really helped build that business out. Without them, you know, we would've just, it was a team effort. And I think that's the thing I loved about it was it was not just sales, it was product, it was development, it was data center operations, it was legal, finance. Everybody really worked as a team and we were on board that we had to make a lot of changes in the government relations team. We had to go into Capitol Hill. We had to talk to them about the changes that were required and really get them to understand why Cloud computing could be such a transformative game changer for the way government operates globally. >> Well, I think the whole world and the tech world can appreciate your work and thank you later because you broke down those walls asking those questions. So great stuff. Now I got to say, you're in kind of a similar role at Flexport. Again, transformative supply chain, not new. Computing wasn't new when before Cloud came. Supply chain, not a new concept, is undergoing radical change and transformation. Online, software supply chain, hardware supply chain, supply chain in general, shipping. This is a big part of our economy and how life is working. Similar kind of thing going on, build out, growth, scale. >> It is, it's very much like that, John, I would say, it's, it's kind of a, the model with freight forwarding and supply chain is fairly, it's not as, there's a lot of technology utilized in this global supply chain world, but it's not integrated. You don't have a common operating picture of what you're doing in your global supply chain. You don't have easy access to the information and visibility. And that's really, you know, I was at a conference last week in LA, and it was, the themes were so similar about transparency, access to data and information, being able to act quickly, drive change, know what was happening. I was like, wow, this sounds familiar. Data, AI, machine learning, visibility, common operating picture. So it is very much the same kind of themes that you heard even with government. I do believe it's an industry that is going through transformation and Flexport has been a group that's come in and said, look, we have this amazing idea, number one to give access to everyone. We want every small business to every large business to every government around the world to be able to trade their goods, think about supply chain logistics in a very different way with information they need and want at their fingertips. So that's kind of thing one, but to apply that technology in a way that's very usable across all systems from an integration perspective. So it's kind of exciting. I used to tell this story years ago, John, and I don't think Michael Dell would mind that I tell this story. One of our first customers when I was at Keyfile Corporation was we did workflow and document management, and Dell was one of our customers. And I remember going out to visit them, and they had runners and they would run around, you know, they would run around the floor and do their orders, right, to get all those computers out the door. And when I think of global trade, in my mind I still see runners, you know, running around and I think that's moved to a very digital, right, world that all this stuff, you don't need people doing this. You have machines doing this now, and you have access to the information, and you know, we still have issues resulting from COVID where we have either an under-abundance or an over-abundance of our supply chain. We still have clogs in our shipping, in the shipping yards around the world. So we, and the ports, so we need to also, we still have some clearing to do. And that's the reason technology is important and will continue to be very important in this world of global trade. >> Yeah, great, great impact for change. I got to ask you about Flexport's inclusion, diversity, and equity programs. What do you got going on there? That's been a big conversation in the industry around keeping a focus on not making one way more than the other, but clearly every company, if they don't have a strong program, will be at a disadvantage. That's well reported by McKinsey and other top consultants, diverse workforces, inclusive, equitable, all perform better. What's Flexport's strategy and how are you guys supporting that in the workplace? >> Well, let me just start by saying really at the core of who I am, since the day I've started understanding that as an individual and a female leader, that I could have an impact. That the words I used, the actions I took, the information that I pulled together and had knowledge of could be meaningful. And I think each and every one of us is responsible to do what we can to make our workplace and the world a more diverse and inclusive place to live and work. And I've always enjoyed kind of the thought that, that I could help empower women around the world in the tech industry. Now I'm hoping to do my little part, John, in that in the supply chain and global trade business. And I would tell you at Flexport we have some amazing women. I'm so excited to get to know all. I've not been there that long yet, but I'm getting to know we have some, we have a very diverse leadership team between men and women at Dave's level. I have some unbelievable women on my team directly that I'm getting to know more, and I'm so impressed with what they're doing. And this is a very, you know, while this industry is different than the world I live in day to day, it's also has a lot of common themes to it. So, you know, for us, we're trying to approach every day by saying, let's make sure both our interviewing cycles, the jobs we feel, how we recruit people, how we put people out there on the platforms, that we have diversity and inclusion and all of that every day. And I can tell you from the top, from Dave and all of our leaders, we just had an offsite and we had a big conversation about this is something. It's a drum beat that we have to think about and live by every day and really check ourselves on a regular basis. But I do think there's so much more room for women in the world to do great things. And one of the, one of the areas, as you know very well, we lost a lot of women during COVID, who just left the workforce again. So we kind of went back unfortunately. So we have to now move forward and make sure that we are giving women the opportunity to have great jobs, have the flexibility they need as they build a family, and have a workplace environment that is trusted for them to come into every day. >> There's now clear visibility, at least in today's world, not withstanding some of the setbacks from COVID, that a young girl can look out in a company and see a path from entry level to the boardroom. That's a big change. A lot than even going back 10, 15, 20 years ago. What's your advice to the folks out there that are paying it forward? You see a lot of executive leaderships have a seat at the table. The board still underrepresented by most numbers, but at least you have now kind of this solidarity at the top, but a lot of people doing a lot more now than I've seen at the next levels down. So now you have this leveled approach. Is that something that you're seeing more of? And credit compare and contrast that to 20 years ago when you were, you know, rising through the ranks? What's different? >> Well, one of the main things, and I honestly do not think about it too much, but there were really no women. There were none. When I showed up in the meetings, I literally, it was me or not me at the table, but at the seat behind the table. The women just weren't in the room, and there were so many more barriers that we had to push through, and that has changed a lot. I mean globally that has changed a lot in the U.S. You know, if you look at just our U.S. House of Representatives and our U.S. Senate, we now have the increasing number of women. Even at leadership levels, you're seeing that change. You have a lot more women on boards than we ever thought we would ever represent. While we are not there, more female CEOs that I get an opportunity to see and talk to. Women starting companies, they do not see the barriers. And I will share, John, globally in the U.S. one of the things that I still see that we have that many other countries don't have, which I'm very proud of, women in the U.S. have a spirit about them that they just don't see the barriers in the same way. They believe that they can accomplish anything. I have two sons, I don't have daughters. I have nieces, and I'm hoping someday to have granddaughters. But I know that a lot of my friends who have granddaughters today talk about the boldness, the fortitude, that they believe that there's nothing they can't accomplish. And I think that's what what we have to instill in every little girl out there, that they can accomplish anything they want to. The world is theirs, and we need to not just do that in the U.S., but around the world. And it was always the thing that struck me when I did all my travels at AWS and now with Flexport, I'm traveling again quite a bit, is just the differences you see in the cultures around the world. And I remember even in the Middle East, how I started seeing it change. You've heard me talk a lot on this program about the fact in both Saudi and Bahrain, over 60% of the tech workers were females and most of them held the the hardest jobs, the security, the architecture, the engineering. But many of them did not hold leadership roles. And that is what we've got to change too. To your point, the middle, we want it to get bigger, but the top, we need to get bigger. We need to make sure women globally have opportunities to hold the most precious leadership roles and demonstrate their capabilities at the very top. But that's changed. And I would say the biggest difference is when we show up, we're actually evaluated properly for those kind of roles. We have a ways to go. But again, that part is really changing. >> Can you share, Teresa, first of all, that's great work you've done and I wan to give you props of that as well and all the work you do. I know you champion a lot of, you know, causes in in this area. One question that comes up a lot, I would love to get your opinion 'cause I think you can contribute heavily here is mentoring and sponsorship is huge, comes up all the time. What advice would you share to folks out there who were, I won't say apprehensive, but maybe nervous about how to do the networking and sponsorship and mentoring? It's not just mentoring, it's sponsorship too. What's your best practice? What advice would you give for the best way to handle that? >> Well yeah, and for the women out there, I would say on the mentorship side, I still see mentorship. Like, I don't think you can ever stop having mentorship. And I like to look at my mentors in different parts of my life because if you want to be a well-rounded person, you may have parts of your life every day that you think I'm doing a great job here and I definitely would like to do better there. Whether it's your spiritual life, your physical life, your work life, you know, your leisure life. But I mean there's, and there's parts of my leadership world that I still seek advice from as I try to do new things even in this world. And I tried some new things in between roles. I went out and asked the people that I respected the most. So I just would say for sure have different mentorships and don't be afraid to have that diversity. But if you have mentorships, the second important thing is show up with a real agenda and questions. Don't waste people's time. I'm very sensitive today. If you're, if you want a mentor, you show up and you use your time super effectively and be prepared for that. Sponsorship is a very different thing. And I don't believe we actually do that still in companies. We worked, thank goodness for my great HR team. When I was at AWS, we worked on a few sponsorship programs where for diversity in general, where we would nominate individuals in the company that we felt that weren't, that had a lot of opportunity for growth, but they just weren't getting a seat at the table. And we brought 'em to the table. And we actually kind of had a Chatham House rules where when they came into the meetings, they had a sponsor, not a mentor. They had a sponsor that was with them the full 18 months of this program. We would bring 'em into executive meetings. They would read docs, they could ask questions. We wanted them to be able to open up and ask crazy questions without, you know, feeling wow, I just couldn't answer this question in a normal environment or setting. And then we tried to make sure once they got through the program that we found jobs and support and other special projects that they could go do. But they still had that sponsor and that group of individuals that they'd gone through the program with, John, that they could keep going back to. And I remember sitting there and they asked me what I wanted to get out of the program, and I said two things. I want you to leave this program and say to yourself, I would've never had that experience if I hadn't gone through this program. I learned so much in 18 months. It would probably taken me five years to learn. And that it helped them in their career. The second thing I told them is I wanted them to go out and recruit individuals that look like them. I said, we need diversity, and unless you all feel that we are in an inclusive environment sponsoring all types of individuals to be part of this company, we're not going to get the job done. And they said, okay. And you know, but it was really one, it was very much about them. That we took a group of individuals that had high potential and a very diverse with diverse backgrounds, held 'em up, taught 'em things that gave them access. And two, selfishly I said, I want more of you in my business. Please help me. And I think those kind of things are helpful, and you have to be thoughtful about these kind of programs. And to me that's more sponsorship. I still have people reach out to me from years ago, you know, Microsoft saying, you were so good with me, can you give me a reference now? Can you talk to me about what I should be doing? And I try to, I'm not pray 100%, some things pray fall through the cracks, but I always try to make the time to talk to those individuals because for me, I am where I am today because I got some of the best advice from people like Don Byrne and Linda Zecker and Andy Jassy, who were very honest and upfront with me about my career. >> Awesome. Well, you got a passion for empowering women in tech, paying it forward, but you're quite accomplished and that's why we're so glad to have you on the program here. President and Chief Commercial Officer at Flexport. Obviously storied career and your other jobs, specifically Amazon I think, is historic in my mind. This next chapter looks like it's looking good right now. Final question for you, for the few minutes you have left. Tell us what you're up to at Flexport. What's your goals as President, Chief Commercial Officer? What are you trying to accomplish? Share a little bit, what's on your mind with your current job? >> Well, you kind of said it earlier. I think if I look at my own superpowers, I love customers, I love partners. I get my energy, John, from those interactions. So one is to come in and really help us build even a better world class enterprise global sales and marketing team. Really listen to our customers, think about how we interact with them, build the best executive programs we can, think about new ways that we can offer services to them and create new services. One of my favorite things about my career is I think if you're a business leader, it's your job to come back around and tell your product group and your services org what you're hearing from customers. That's how you can be so much more impactful, that you listen, you learn, and you deliver. So that's one big job. The second job for me, which I am so excited about, is that I have an amazing group called flexport.org under me. And flexport.org is doing amazing things around the world to help those in need. We just announced this new funding program for Tech for Refugees, which brings assistance to millions of people in Ukraine, Pakistan, the horn of Africa, and those who are affected by earthquakes. We just took supplies into Turkey and Syria, and Flexport, recently in fact, just did sent three air shipments to Turkey and Syria for these. And I think we did over a hundred trekking shipments to get earthquake relief. And as you can imagine, it was not easy to get into Syria. But you know, we're very active in the Ukraine, and we are, our goal for flexport.org, John, is to continue to work with our commercial customers and team up with them when they're trying to get supplies in to do that in a very cost effective, easy way, as quickly as we can. So that not-for-profit side of me that I'm so, I'm so happy. And you know, Ryan Peterson, who was our founder, this was his brainchild, and he's really taken this to the next level. So I'm honored to be able to pick that up and look for new ways to have impact around the world. And you know, I've always found that I think if you do things right with a company, you can have a beautiful combination of commercial-ity and giving. And I think Flexport does it in such an amazing and unique way. >> Well, the impact that they have with their system and their technology with logistics and shipping and supply chain is a channel for societal change. And I think that's a huge gift that you have that under your purview. So looking forward to finding out more about flexport.org. I can only imagine all the exciting things around sustainability, and we just had Mobile World Congress for Big Cube Broadcast, 5Gs right around the corner. I'm sure that's going to have a huge impact to your business. >> Well, for sure. And just on gas emissions, that's another thing that we are tracking gas, greenhouse gas emissions. And in fact we've already reduced more than 300,000 tons and supported over 600 organizations doing that. So that's a thing we're also trying to make sure that we're being climate aware and ensuring that we are doing the best job we can at that as well. And that was another thing I was honored to be able to do when we were at AWS, is to really cut out greenhouse gas emissions and really go global with our climate initiatives. >> Well Teresa, it's great to have you on. Security, data, 5G, sustainability, business transformation, AI all coming together to change the game. You're in another hot seat, hot roll, big wave. >> Well, John, it's an honor, and just thank you again for doing this and having women on and really representing us in a big way as we celebrate International Women's Day. >> I really appreciate it, it's super important. And these videos have impact, so we're going to do a lot more. And I appreciate your leadership to the industry and thank you so much for taking the time to contribute to our effort. Thank you, Teresa. >> Thank you. Thanks everybody. >> Teresa Carlson, the President and Chief Commercial Officer of Flexport. I'm John Furrier, host of theCUBE. This is International Women's Day broadcast. Thanks for watching. (upbeat outro music)

(upbeat music) >> Hello and welcome to theCube's coverage of International Women's Day. I'm John Furrier, your host of "theCUBE." We've got great two remote guests coming into our Palo Alto Studios, some tech athletes, as we say, people that've been in the trenches, years of experience, Lena Smart, CISO at MongoDB, Cube alumni, and Tara Hernandez, VP of Developer Productivity at MongoDB as well. Thanks for coming in to this program and supporting our efforts today. Thanks so much. >> Thanks for having us. >> Yeah, everyone talk about the journey in tech, where it all started. Before we get there, talk about what you guys are doing at MongoDB specifically. MongoDB is kind of gone the next level as a platform. You have your own ecosystem, lot of developers, very technical crowd, but it's changing the business transformation. What do you guys do at Mongo? We'll start with you, Lena. >> So I'm the CISO, so all security goes through me. I like to say, well, I don't like to say, I'm described as the ones throat to choke. So anything to do with security basically starts and ends with me. We do have a fantastic Cloud engineering security team and a product security team, and they don't report directly to me, but obviously we have very close relationships. I like to keep that kind of church and state separate and I know I've spoken about that before. And we just recently set up a physical security team with an amazing gentleman who left the FBI and he came to join us after 26 years for the agency. So, really starting to look at the physical aspects of what we offer as well. >> I interviewed a CISO the other day and she said, "Every day is day zero for me." Kind of goofing on the Amazon Day one thing, but Tara, go ahead. Tara, go ahead. What's your role there, developer productivity? What are you focusing on? >> Sure. Developer productivity is kind of the latest description for things that we've described over the years as, you know, DevOps oriented engineering or platform engineering or build and release engineering development infrastructure. It's all part and parcel, which is how do we actually get our code from developer to customer, you know, and all the mechanics that go into that. It's been something I discovered from my first job way back in the early '90s at Borland. And the art has just evolved enormously ever since, so. >> Yeah, this is a very great conversation both of you guys, right in the middle of all the action and data infrastructures changing, exploding, and involving big time AI and data tsunami and security never stops. Well, let's get into, we'll talk about that later, but let's get into what motivated you guys to pursue a career in tech and what were some of the challenges that you faced along the way? >> I'll go first. The fact of the matter was I intended to be a double major in history and literature when I went off to university, but I was informed that I had to do a math or a science degree or else the university would not be paid for. At the time, UC Santa Cruz had a policy that called Open Access Computing. This is, you know, the late '80s, early '90s. And anybody at the university could get an email account and that was unusual at the time if you were, those of us who remember, you used to have to pay for that CompuServe or AOL or, there's another one, I forget what it was called, but if a student at Santa Cruz could have an email account. And because of that email account, I met people who were computer science majors and I'm like, "Okay, I'll try that." That seems good. And it was a little bit of a struggle for me, a lot I won't lie, but I can't complain with how it ended up. And certainly once I found my niche, which was development infrastructure, I found my true love and I've been doing it for almost 30 years now. >> Awesome. Great story. Can't wait to ask a few questions on that. We'll go back to that late '80s, early '90s. Lena, your journey, how you got into it. >> So slightly different start. I did not go to university. I had to leave school when I was 16, got a job, had to help support my family. Worked a bunch of various jobs till I was about 21 and then computers became more, I think, I wouldn't say they were ubiquitous, but they were certainly out there. And I'd also been saving up every penny I could earn to buy my own computer and bought an Amstrad 1640, 20 meg hard drive. It rocked. And kind of took that apart, put it back together again, and thought that could be money in this. And so basically just teaching myself about computers any job that I got. 'Cause most of my jobs were like clerical work and secretary at that point. But any job that had a computer in front of that, I would make it my business to go find the guy who did computing 'cause it was always a guy. And I would say, you know, I want to learn how these work. Let, you know, show me. And, you know, I would take my lunch hour and after work and anytime I could with these people and they were very kind with their time and I just kept learning, so yep. >> Yeah, those early days remind me of the inflection point we're going through now. This major C change coming. Back then, if you had a computer, you had to kind of be your own internal engineer to fix things. Remember back on the systems revolution, late '80s, Tara, when, you know, your career started, those were major inflection points. Now we're seeing a similar wave right now, security, infrastructure. It feels like it's going to a whole nother level. At Mongo, you guys certainly see this as well, with this AI surge coming in. A lot more action is coming in. And so there's a lot of parallels between these inflection points. How do you guys see this next wave of change? Obviously, the AI stuff's blowing everyone away. Oh, new user interface. It's been called the browser moment, the mobile iPhone moment, kind of for this generation. There's a lot of people out there who are watching that are young in their careers, what's your take on this? How would you talk to those folks around how important this wave is? >> It, you know, it's funny, I've been having this conversation quite a bit recently in part because, you know, to me AI in a lot of ways is very similar to, you know, back in the '90s when we were talking about bringing in the worldwide web to the forefront of the world, right. And we tended to think in terms of all the optimistic benefits that would come of it. You know, free passing of information, availability to anyone, anywhere. You just needed an internet connection, which back then of course meant a modem. >> John: Not everyone had though. >> Exactly. But what we found in the subsequent years is that human beings are what they are and we bring ourselves to whatever platforms that are there, right. And so, you know, as much as it was amazing to have this freely available HTML based internet experience, it also meant that the negatives came to the forefront quite quickly. And there were ramifications of that. And so to me, when I look at AI, we're already seeing the ramifications to that. Yes, are there these amazing, optimistic, wonderful things that can be done? Yes. >> Yeah. >> But we're also human and the bad stuff's going to come out too. And how do we- >> Yeah. >> How do we as an industry, as a community, you know, understand and mitigate those ramifications so that we can benefit more from the positive than the negative. So it is interesting that it comes kind of full circle in really interesting ways. >> Yeah. The underbelly takes place first, gets it in the early adopter mode. Normally industries with, you know, money involved arbitrage, no standards. But we've seen this movie before. Is there hope, Lena, that we can have a more secure environment? >> I would hope so. (Lena laughs) Although depressingly, we've been in this well for 30 years now and we're, at the end of the day, still telling people not to click links on emails. So yeah, that kind of still keeps me awake at night a wee bit. The whole thing about AI, I mean, it's, obviously I am not an expert by any stretch of the imagination in AI. I did read (indistinct) book recently about AI and that was kind of interesting. And I'm just trying to teach myself as much as I can about it to the extent of even buying the "Dummies Guide to AI." Just because, it's actually not a dummies guide. It's actually fairly interesting, but I'm always thinking about it from a security standpoint. So it's kind of my worst nightmare and the best thing that could ever happen in the same dream. You know, you've got this technology where I can ask it a question and you know, it spits out generally a reasonable answer. And my team are working on with Mark Porter our CTO and his team on almost like an incubation of AI link. What would it look like from MongoDB? What's the legal ramifications? 'Cause there will be legal ramifications even though it's the wild, wild west just now, I think. Regulation's going to catch up to us pretty quickly, I would think. >> John: Yeah, yeah. >> And so I think, you know, as long as companies have a seat at the table and governments perhaps don't become too dictatorial over this, then hopefully we'll be in a good place. But we'll see. I think it's a really interest, there's that curse, we're living in interesting times. I think that's where we are. >> It's interesting just to stay on this tech trend for a minute. The standards bodies are different now. Back in the old days there were, you know, IEEE standards, ITF standards. >> Tara: TPC. >> The developers are the new standard. I mean, now you're seeing open source completely different where it was in the '90s to here beginning, that was gen one, some say gen two, but I say gen one, now we're exploding with open source. You have kind of developers setting the standards. If developers like it in droves, it becomes defacto, which then kind of rolls into implementation. >> Yeah, I mean I think if you don't have developer input, and this is why I love working with Tara and her team so much is 'cause they get it. If we don't have input from developers, it's not going to get used. There's going to be ways of of working around it, especially when it comes to security. If they don't, you know, if you're a developer and you're sat at your screen and you don't want to do that particular thing, you're going to find a way around it. You're a smart person. >> Yeah. >> So. >> Developers on the front lines now versus, even back in the '90s, they're like, "Okay, consider the dev's, got a QA team." Everything was Waterfall, now it's Cloud, and developers are on the front lines of everything. Tara, I mean, this is where the standards are being met. What's your reaction to that? >> Well, I think it's outstanding. I mean, you know, like I was at Netscape and part of the crowd that released the browser as open source and we founded mozilla.org, right. And that was, you know, in many ways kind of the birth of the modern open source movement beyond what we used to have, what was basically free software foundation was sort of the only game in town. And I think it is so incredibly valuable. I want to emphasize, you know, and pile onto what Lena was saying, it's not just that the developers are having input on a sort of company by company basis. Open source to me is like a checks and balance, where it allows us as a broader community to be able to agree on and enforce certain standards in order to try and keep the technology platforms as accessible as possible. I think Kubernetes is a great example of that, right. If we didn't have Kubernetes, that would've really changed the nature of how we think about container orchestration. But even before that, Linux, right. Linux allowed us as an industry to end the Unix Wars and as someone who was on the front lines of that as well and having to support 42 different operating systems with our product, you know, that was a huge win. And it allowed us to stop arguing about operating systems and start arguing about software or not arguing, but developing it in positive ways. So with, you know, with Kubernetes, with container orchestration, we all agree, okay, that's just how we're going to orchestrate. Now we can build up this huge ecosystem, everybody gets taken along, right. And now it changes the game for what we're defining as business differentials, right. And so when we talk about crypto, that's a little bit harder, but certainly with AI, right, you know, what are the checks and balances that as an industry and as the developers around this, that we can in, you know, enforce to make sure that no one company or no one body is able to overly control how these things are managed, how it's defined. And I think that is only for the benefit in the industry as a whole, particularly when we think about the only other option is it gets regulated in ways that do not involve the people who actually know the details of what they're talking about. >> Regulated and or thrown away or bankrupt or- >> Driven underground. >> Yeah. >> Which would be even worse actually. >> Yeah, that's a really interesting, the checks and balances. I love that call out. And I was just talking with another interview part of the series around women being represented in the 51% ratio. Software is for everybody. So that we believe that open source movement around the collective intelligence of the participants in the industry and independent of gender, this is going to be the next wave. You're starting to see these videos really have impact because there are a lot more leaders now at the table in companies developing software systems and with AI, the aperture increases for applications. And this is the new dynamic. What's your guys view on this dynamic? How does this go forward in a positive way? Is there a certain trajectory you see? For women in the industry? >> I mean, I think some of the states are trying to, again, from the government angle, some of the states are trying to force women into the boardroom, for example, California, which can be no bad thing, but I don't know, sometimes I feel a bit iffy about all this kind of forced- >> John: Yeah. >> You know, making, I don't even know how to say it properly so you can cut this part of the interview. (John laughs) >> Tara: Well, and I think that they're >> I'll say it's not organic. >> No, and I think they're already pulling it out, right. It's already been challenged so they're in the process- >> Well, this is the open source angle, Tara, you are getting at it. The change agent is open, right? So to me, the history of the proven model is openness drives transparency drives progress. >> No, it's- >> If you believe that to be true, this could have another impact. >> Yeah, it's so interesting, right. Because if you look at McKinsey Consulting or Boston Consulting or some of the other, I'm blocking on all of the names. There has been a decade or more of research that shows that a non homogeneous employee base, be it gender or ethnicity or whatever, generates more revenue, right? There's dollar signs that can be attached to this, but it's not enough for all companies to want to invest in that way. And it's not enough for all, you know, venture firms or investment firms to grant that seed money or do those seed rounds. I think it's getting better very slowly, but socialization is a much harder thing to overcome over time. Particularly, when you're not just talking about one country like the United States in our case, but around the world. You know, tech centers now exist all over the world, including places that even 10 years ago we might not have expected like Nairobi, right. Which I think is amazing, but you have to factor in the cultural implications of that as well, right. So yes, the openness is important and we have, it's important that we have those voices, but I don't think it's a panacea solution, right. It's just one more piece. I think honestly that one of the most important opportunities has been with Cloud computing and Cloud's been around for a while. So why would I say that? It's because if you think about like everybody holds up the Steve Jobs, Steve Wozniak, back in the '70s, or Sergey and Larry for Google, you know, you had to have access to enough credit card limit to go to Fry's and buy your servers and then access to somebody like Susan Wojcicki to borrow the garage or whatever. But there was still a certain amount of upfrontness that you had to be able to commit to, whereas now, and we've, I think, seen a really good evidence of this being able to lease server resources by the second and have development platforms that you can do on your phone. I mean, for a while I think Africa, that the majority of development happened on mobile devices because there wasn't a sufficient supply chain of laptops yet. And that's no longer true now as far as I know. But like the power that that enables for people who would otherwise be underrepresented in our industry instantly opens it up, right? And so to me that's I think probably the biggest opportunity that we've seen from an industry on how to make more availability in underrepresented representation for entrepreneurship. >> Yeah. >> Something like AI, I think that's actually going to take us backwards if we're not careful. >> Yeah. >> Because of we're reinforcing that socialization. >> Well, also the bias. A lot of people commenting on the biases of the large language inherently built in are also problem. Lena, I want you to weigh on this too, because I think the skills question comes up here and I've been advocating that you don't need the pedigree, college pedigree, to get into a certain jobs, you mentioned Cloud computing. I mean, it's been around for you think a long time, but not really, really think about it. The ability to level up, okay, if you're going to join something new and half the jobs in cybersecurity are created in the past year, right? So, you have this what used to be a barrier, your degree, your pedigree, your certification would take years, would be a blocker. Now that's gone. >> Lena: Yeah, it's the opposite. >> That's, in fact, psychology. >> I think so, but the people who I, by and large, who I interview for jobs, they have, I think security people and also I work with our compliance folks and I can't forget them, but let's talk about security just now. I've always found a particular kind of mindset with security folks. We're very curious, not very good at following rules a lot of the time, and we'd love to teach others. I mean, that's one of the big things stem from the start of my career. People were always interested in teaching and I was interested in learning. So it was perfect. And I think also having, you know, strong women leaders at MongoDB allows other underrepresented groups to actually apply to the company 'cause they see that we're kind of talking the talk. And that's been important. I think it's really important. You know, you've got Tara and I on here today. There's obviously other senior women at MongoDB that you can talk to as well. There's a bunch of us. There's not a whole ton of us, but there's a bunch of us. And it's good. It's definitely growing. I've been there for four years now and I've seen a growth in women in senior leadership positions. And I think having that kind of track record of getting really good quality underrepresented candidates to not just interview, but come and join us, it's seen. And it's seen in the industry and people take notice and they're like, "Oh, okay, well if that person's working, you know, if Tara Hernandez is working there, I'm going to apply for that." And that in itself I think can really, you know, reap the rewards. But it's getting started. It's like how do you get your first strong female into that position or your first strong underrepresented person into that position? It's hard. I get it. If it was easy, we would've sold already. >> It's like anything. I want to see people like me, my friends in there. Am I going to be alone? Am I going to be of a group? It's a group psychology. Why wouldn't? So getting it out there is key. Is there skills that you think that people should pay attention to? One's come up as curiosity, learning. What are some of the best practices for folks trying to get into the tech field or that's in the tech field and advancing through? What advice are you guys- >> I mean, yeah, definitely, what I say to my team is within my budget, we try and give every at least one training course a year. And there's so much free stuff out there as well. But, you know, keep learning. And even if it's not right in your wheelhouse, don't pick about it. Don't, you know, take a look at what else could be out there that could interest you and then go for it. You know, what does it take you few minutes each night to read a book on something that might change your entire career? You know, be enthusiastic about the opportunities out there. And there's so many opportunities in security. Just so many. >> Tara, what's your advice for folks out there? Tons of stuff to taste, taste test, try things. >> Absolutely. I mean, I always say, you know, my primary qualifications for people, I'm looking for them to be smart and motivated, right. Because the industry changes so quickly. What we're doing now versus what we did even last year versus five years ago, you know, is completely different though themes are certainly the same. You know, we still have to code and we still have to compile that code or package the code and ship the code so, you know, how well can we adapt to these new things instead of creating floppy disks, which was my first job. Five and a quarters, even. The big ones. >> That's old school, OG. There it is. Well done. >> And now it's, you know, containers, you know, (indistinct) image containers. And so, you know, I've gotten a lot of really great success hiring boot campers, you know, career transitioners. Because they bring a lot experience in addition to the technical skills. I think the most important thing is to experiment and figuring out what do you like, because, you know, maybe you are really into security or maybe you're really into like deep level coding and you want to go back, you know, try to go to school to get a degree where you would actually want that level of learning. Or maybe you're a front end engineer, you want to be full stacked. Like there's so many different things, data science, right. Maybe you want to go learn R right. You know, I think it's like figure out what you like because once you find that, that in turn is going to energize you 'cause you're going to feel motivated. I think the worst thing you could do is try to force yourself to learn something that you really could not care less about. That's just the worst. You're going in handicapped. >> Yeah and there's choices now versus when we were breaking into the business. It was like, okay, you software engineer. They call it software engineering, that's all it was. You were that or you were in sales. Like, you know, some sort of systems engineer or sales and now it's,- >> I had never heard of my job when I was in school, right. I didn't even know it was a possibility. But there's so many different types of technical roles, you know, absolutely. >> It's so exciting. I wish I was young again. >> One of the- >> Me too. (Lena laughs) >> I don't. I like the age I am. So one of the things that I did to kind of harness that curiosity is we've set up a security champions programs. About 120, I guess, volunteers globally. And these are people from all different backgrounds and all genders, diversity groups, underrepresented groups, we feel are now represented within this champions program. And people basically give up about an hour or two of their time each week, with their supervisors permission, and we basically teach them different things about security. And we've now had seven full-time people move from different areas within MongoDB into my team as a result of that program. So, you know, monetarily and time, yeah, saved us both. But also we're showing people that there is a path, you know, if you start off in Tara's team, for example, doing X, you join the champions program, you're like, "You know, I'd really like to get into red teaming. That would be so cool." If it fits, then we make that happen. And that has been really important for me, especially to give, you know, the women in the underrepresented groups within MongoDB just that window into something they might never have seen otherwise. >> That's a great common fit is fit matters. Also that getting access to what you fit is also access to either mentoring or sponsorship or some sort of, at least some navigation. Like what's out there and not being afraid to like, you know, just ask. >> Yeah, we just actually kicked off our big mentor program last week, so I'm the executive sponsor of that. I know Tara is part of it, which is fantastic. >> We'll put a plug in for it. Go ahead. >> Yeah, no, it's amazing. There's, gosh, I don't even know the numbers anymore, but there's a lot of people involved in this and so much so that we've had to set up mentoring groups rather than one-on-one. And I think it was 45% of the mentors are actually male, which is quite incredible for a program called Mentor Her. And then what we want to do in the future is actually create a program called Mentor Them so that it's not, you know, not just on the female and so that we can live other groups represented and, you know, kind of break down those groups a wee bit more and have some more granularity in the offering. >> Tara, talk about mentoring and sponsorship. Open source has been there for a long time. People help each other. It's community-oriented. What's your view of how to work with mentors and sponsors if someone's moving through ranks? >> You know, one of the things that was really interesting, unfortunately, in some of the earliest open source communities is there was a lot of pervasive misogyny to be perfectly honest. >> Yeah. >> And one of the important adaptations that we made as an open source community was the idea, an introduction of code of conducts. And so when I'm talking to women who are thinking about expanding their skills, I encourage them to join open source communities to have opportunity, even if they're not getting paid for it, you know, to develop their skills to work with people to get those code reviews, right. I'm like, "Whatever you join, make sure they have a code of conduct and a good leadership team. It's very important." And there are plenty, right. And then that idea has come into, you know, conferences now. So now conferences have codes of contact, if there are any good, and maybe not all of them, but most of them, right. And the ideas of expanding that idea of intentional healthy culture. >> John: Yeah. >> As a business goal and business differentiator. I mean, I won't lie, when I was recruited to come to MongoDB, the culture that I was able to discern through talking to people, in addition to seeing that there was actually women in senior leadership roles like Lena, like Kayla Nelson, that was a huge win. And so it just builds on momentum. And so now, you know, those of us who are in that are now representing. And so that kind of reinforces, but it's all ties together, right. As the open source world goes, particularly for a company like MongoDB, which has an open source product, you know, and our community builds. You know, it's a good thing to be mindful of for us, how we interact with the community and you know, because that could also become an opportunity for recruiting. >> John: Yeah. >> Right. So we, in addition to people who might become advocates on Mongo's behalf in their own company as a solution for themselves, so. >> You guys had great successful company and great leadership there. I mean, I can't tell you how many times someone's told me "MongoDB doesn't scale. It's going to be dead next year." I mean, I was going back 10 years. It's like, just keeps getting better and better. You guys do a great job. So it's so fun to see the success of developers. Really appreciate you guys coming on the program. Final question, what are you guys excited about to end the segment? We'll give you guys the last word. Lena will start with you and Tara, you can wrap us up. What are you excited about? >> I'm excited to see what this year brings. I think with ChatGPT and its copycats, I think it'll be a very interesting year when it comes to AI and always in the lookout for the authentic deep fakes that we see coming out. So just trying to make people aware that this is a real thing. It's not just pretend. And then of course, our old friend ransomware, let's see where that's going to go. >> John: Yeah. >> And let's see where we get to and just genuine hygiene and housekeeping when it comes to security. >> Excellent. Tara. >> Ah, well for us, you know, we're always constantly trying to up our game from a security perspective in the software development life cycle. But also, you know, what can we do? You know, one interesting application of AI that maybe Google doesn't like to talk about is it is really cool as an addendum to search and you know, how we might incorporate that as far as our learning environment and developer productivity, and how can we enable our developers to be more efficient, productive in their day-to-day work. So, I don't know, there's all kinds of opportunities that we're looking at for how we might improve that process here at MongoDB and then maybe be able to share it with the world. One of the things I love about working at MongoDB is we get to use our own products, right. And so being able to have this interesting document database in order to put information and then maybe apply some sort of AI to get it out again, is something that we may well be looking at, if not this year, then certainly in the coming year. >> Awesome. Lena Smart, the chief information security officer. Tara Hernandez, vice president developer of productivity from MongoDB. Thank you so much for sharing here on International Women's Day. We're going to do this quarterly every year. We're going to do it and then we're going to do quarterly updates. Thank you so much for being part of this program. >> Thank you. >> Thanks for having us. >> Okay, this is theCube's coverage of International Women's Day. I'm John Furrier, your host. Thanks for watching. (upbeat music)

(gentle music) >> Hello, and welcome to theCUBE's coverage of International Women's Day. I'm John Furrier, host of theCUBE. I've got a great guest here, CUBE alumni and very impressive, inspiring, Rachel Mushahwar Skaff, who's a managing director and general manager at AWS. Rachel, great to see you. Thanks for coming on. >> Thank you so much. It's always a pleasure to be here. You all make such a tremendous impact with reporting out what's happening in the tech space, and frankly, investing in topics like this, so thank you. >> It's our pleasure. Your career has been really impressive. You worked at Intel for almost a decade, and that company is very tech, very focused on Moore's law, cadence of technology power in the industry. Now at AWS, powering next-generation cloud. What inspired you to get into tech? How did you get here and how have you approached your career journey, because it's quite a track record? >> Wow, how long do we have? (Rachel and John laugh) >> John: We can go as long as you want. (laughs) It's great. >> You know, all joking aside, I think at the end of the day, it's about this simple statement. If you don't get goosebumps every single morning that you're waking up to do your job, it's not good enough. And that's a bit about how I've made all of the different career transitions that I have. You know, everything from building out data centers around the world, to leading network and engineering teams, to leading applications teams, to going and working for, you know, the largest semiconductor in the world, and now at AWS, every single one of those opportunities gave me goosebumps. And I was really focused on how do I surround myself with humans that are better than I am, smarter than I am, companies that plan in decades, but live in moments, companies that invest in their employees and create like artists? And frankly, for me, being part of a company where people know that life is finite, but they want to make an infinite impact, that's a bit about my career journey in a nutshell. >> Yeah. What's interesting is that, you know, over the years, a lot's changed, and a theme that we're hearing from leaders now that are heading up large teams and running companies, they have, you know, they have 20-plus years of experience under their belt and they look back and they say, "Wow, "things have changed and it's changing faster now, "hopefully faster to get change." But they all talk about confidence and they talk about curiosity and building. When did you know that this was going to be something that you got the goosebumps? And were there blockers in your way and how did you handle that? (Rachel laughs) >> There's always blockers in our way, and I think a lot of people don't actually talk about the blockers. I think they make it sound like, hey, I had this plan from day one, and every decision I've made has been perfect. And for me, I'll tell you, right, there are moments in your life that mark a differentiation and those moments that you realize nothing will be the same. And time is kind of divided into two parts, right, before this moment and after this moment. And that's everything from, before I had kids, that's a pretty big moment in people's lives, to after I had kids, and how do you work through some of those opportunities? Before I got married, before I got divorced. Before I went to this company, after I left this company. And I think the key for all of those is just having an insatiable curiosity around how do you continue to do better, create better and make better? And I'll tell you, those blockers, they exist. Coming back from maternity leave, hard. Coming back from a medical leave, hard. Coming back from caring for a sick parent or a sick friend, hard. But all of those things start to help craft who you are as a human being, not as a leader, but as a human being, and allows you to have some empathy with the people that you surround yourself with, right? And for me, it's, (sighs) you can think about these blockers in one of two ways. You can think about it as, you know, every single time that you're tempted to react in the same way to a blocker, you can be a prisoner of your past, or you can change how you react and be a pioneer of the future. It's not a blocker when you think about it in those terms. >> Mindset matters, and that's really a great point. You brought up something that's interesting, I want to bring this up. Some of the challenges in different stages of our lives. You know, one thing that's come out of this set of interviews, this, of day and in conversations is, that I haven't heard before, is the result of COVID, working at home brought empathy about people's personal lives to the table. That came up in a couple interviews. What's your reaction to that? Because that highlights that we're human, to your point of view. >> It does. It does. And I'm so thankful that you don't ask about balance because that is a pet peeve of mine, because there is no such thing as balance. If you're in perfect balance, you are not moving and you're not changing. But when you think about, you know, the impact of COVID and how the world has changed since that, it has allowed all of us to really think about, you know, what do we want to do versus what do we have to do? And I think so many times, in both our professional lives and our personal lives, we get caught up in doing what we think we have to do to get ahead versus taking a step back and saying, "Hey, what do I want to do? "And how do I become a, you know, "a better human?" And many times, John, I'm asked, "Hey, "how do you define success or achievement?" And, you know, my answer is really, for me, the greatest results that I've achieved, both personally and professionally, is when I eliminate the word success and balance from my vocabulary, and replace them with two words: What's my contribution and what's my impact? Those things make a difference, regardless of gender. And I'll tell you, none of it is easy, ever. I think all of us have been broken, we've been stretched, we've been burnt out. But I also think what we have to talk about as leaders in the industry is how we've also found endurance and resilience. And when we felt unsteady, we've continued to go forward, right? When we can't decide, the best answer is do what's uncomfortable. And all of those things really stemmed from a part of what happened with COVID. >> Yeah, yeah, I love the uncomfortable and the balance highlight. You mentioned being off balance. That means you're growing, you're not standing still. I want to get your thoughts on this because one thing that has come out again this year, and last year as well, is having a team with you when you do it. So if you're off balance and you're going to stretch, if you have a good team with you, that's where people help each other. Not just pick them up, but like maybe get 'em back on track again. So, but if you're solo, you fall, (laughs) you fall harder. So what's your reaction to that? 'Cause this has come up, and this comes up in team building, workforce formation, goal setting, contribution. What's your reaction to that? >> So my reaction to that that is pretty simple. Nobody gets there on their own at all, right? Passion and ambition can only take you so far. You've got to have people and teams that are supporting you. And here's the funny thing about people, and frankly, about being a leader that I think is really important: People don't follow for you. People follow for who you help them become. Think about that for a second. And when you think about all the amazing things that companies and teams are able to do, it's because of those people. And it's because you have leaders that are out there, inspiring them to take what they believe is impossible and turn it into the possible. That's the power of teams. >> Can you give an example of your approach on how you do that? How do you build your teams? How do you grow them? How do you lead them effectively and also make 'em inclusive, diverse and equitable? >> Whew. I'll give you a great example of some work that we're doing at AWS. This year at re:Invent, for the first time in its history, we've launched an initiative with theCUBE called Women of the Cloud. And part of Women of the Cloud is highlighting the business impact that so many of our partners, our customers and our employees have had on the social, on the economic and on the financials of many companies. They just haven't had the opportunity to tell their story. And at Amazon, right, it is absolutely integral to us to highlight those examples and continue to extend that ethos to our partners and our customers. And I think one of the things that I shared with you at re:Invent was, you know, as U2's Bono put it, (John laughs) "We'll build it better than we did before "and we are the people "that we've been waiting for." So if we're not out there, advocating and highlighting all the amazing things that other women are doing in the ecosystem, who will? >> Well, I've got to say, I want to give you props for that program. Not only was it groundbreaking, it's still running strong. And I saw some things on LinkedIn that were really impressive in its network effect. And I met at least half a dozen new people I never would have met before through some of that content interaction and engagement. And this is like the power of the current world. I mean, getting the voices out there creates momentum. And it's good for Amazon. It's not just personal brand building for my next job or whatever, you know, reason. It's sharing and it's attracting others, and it's causing people to connect and meet each other in that world. So it's still going strong. (laughs) And this program we did last year was part of Rachel Thornton, who's now at MessageBird, and Mary Camarata. They were the sponsors for this International Women's Day. They're not there anymore, so we decided we're going to do it again because the impact is so significant. We had the Amazon Education group on. It's amazing and it's free, and we've got to get the word out. I mean, talk about leveling up fast. You get in and you get trained and get certified, and there's a zillion jobs out (laughs) there in cloud, right, and partners. So this kind of leadership is really important. What was the key learnings that you've taken away and how do you extend this opportunity to nurture the talent out there in the field? Because when you throw the content out there from great leaders and practitioners and developers, it attracts other people. >> It does. It does. So look, I think there's two types of people, people that are focused on being and people who are focused on doing. And let me give you an example, right? When we think about labels of, hey, Rachel's a female executive who launched Women of the Cloud, that label really limits me. I'd rather just be a great executive. Or, hey, there's a great entrepreneur. Let's not be a great entrepreneur. Just go build something and sell it. And that's part of this whole Women of the cloud, is I don't want people focused on what their label is. I want people sharing their stories about what they're doing, and that's where the lasting impact happens, right? I think about something that my grandmother used to tell me, and she used to tell me, "Rachel, how successful "you are, doesn't matter. "The lasting impact that you have "is your legacy in this very finite time "that you have on Earth. "Leave a legacy." And that's what Women of the Cloud is about. So that people can start to say, "Oh, geez, "I didn't know that that was possible. "I didn't think about my career in that way." And, you know, all of those different types of stories that you're hearing out there. >> And I want to highlight something you said. We had another Amazonian on the program for this day earlier and she coined a term, 'cause inside Amazon, you have common language. One of them is bar raising. Raise the bar, that's an Amazonian (Rachel laughs) term. It means contribute and improve and raise the bar of capability. She said, "Bar raising is gender neutral. "The bar is a bar." And I'm like, wow, that was amazing. Now, that means your contribution angle there highlights that. What's the biggest challenge to get that mindset set in culture, in these- >> Oh. >> 'Cause it's that simple, contribution is neutral. >> It absolutely is neutral, but it's like I said earlier, I think so many times, people are focused on success and being a great leader versus what's the contribution I'm making and how am I doing as a leader, you know? And when it comes to a lot of the leadership principles that Amazon has, including bar raising, which means insisting on the highest standards, and then those standards continue to raise every single time. And what that is all about is having all of our employees figure out, how do I get better every single day, right? That's what it's about. It's not about being better than the peer next to you. It's about how do I become a better leader, a better human being than I was yesterday? >> Awesome. >> You know, I read this really cute quote and I think it really resonates. "You meditate to upgrade your software "and you work out to upgrade your hardware." And while it's important that we're all ourselves at work, we can't deny that a lot of times, ourselves still need that meditation or that workout. >> Well, I hope I don't have any zero days in my software out there, so, but I'm going to definitely work on that. I love that quote. I'm going to use that. Thank you very much. That was awesome. I got to ask you, I know you're really passionate about, and we've talked about this, around, so you're a great leader but you're also focused on what's behind you in the generation, pipelining women leaders, okay? Seats at the table, mentoring and sponsorship. What can we do to build a strong pipeline of leaders in technology and business? And where do you see the biggest opportunity to nurture the talent in these fields? >> Hmm, you know, that's great, great question. And, you know, I just read a "Forbes" article by another Amazonian, Tanuja Randery, who talked about, you know, some really interesting stats. And one of the stats that she shared was, you know, by 2030, less than 25% of tech specialists will be female, less than 25%. That's only a 6% growth from where we are in 2023, so in seven years. That's alarming. So we've really got to figure out what are the kinds of things that we're going to go do from an Amazon perspective to impact that? And one of the obvious starting points is showcasing tech careers to girls and young women, and talking openly about what a technology career looks like. So specifically at Amazon, we've got an AWS Git IT program that helps schools and educators bring in tech role models to show them what potential careers look like in tech. I think that's one great way that we can help build the pipeline, but once we get the pipeline, we also have to figure out how we don't let that pipeline leak. Meaning how do we keep women and, you know, young women on their tech career? And I think big part of that, John, is really talking about how hard it is, but it's also greater than you can ever imagine. And letting them see executives that are very authentic and will talk about, geez, you know, the challenges of COVID were a time of crisis and accelerated change, and here's what it meant to me personally and here's what we were able to solve professionally. These younger generations are all about social impact, they're about economic impact and they're about financial impact. And if we're not talking about all three of those, both from how AWS is leading from the front, but how its executives are also taking that into their personal lives, they're not going to want to go into tech. >> Yeah, and I think one of the things you mentioned there about getting people that get IT, good call out there, but also, Amazon's going to train 30 million people, put hundreds of millions of dollars into education. And not only are they making it easier to get in to get trained, but once you're in, even savvy folks that are in there still have to accelerate. And there's more ways to level up, more things are happening, but there's a big trend around people changing careers either in their late 20s, early 30s, or even those moments you talk about, where it's before and after, even later in the careers, 40s, 50s. Leaders like, well, good experience, good training, who were in another discipline who re-skilled. So you have, you know, more certifications coming in. So there's still other pivot points in the pipeline. It's not just down here. And that, I find that interesting. Are you seeing that same leadership opportunities coming in where someone can come into tech older? >> Absolutely. You know, we've got some amazing programs, like Amazon Returnity, that really focuses on how do we get other, you know, how do we get women that have taken some time off of work to get back into the workforce? And here's the other thing about switching careers. If I look back on my career, I started out as a civil engineer, heavy highway construction. And now I lead a sales team at the largest cloud company in the world. And there were, you know, twists and turns around there. I've always focused on how do we change and how do we continue to evolve? So it's not just focused on, you know, young women in the pipeline. It's focused on all gender and all diverse types throughout their career, and making sure that we're providing an inclusive environment for them to bring in their unique skillsets. >> Yeah, a building has good steel. It's well structured. Roads have great foundations. You know, you got the builder in you there. >> Yes. >> So I have to ask you, what's on your mind as a tech athlete, as an executive at AWS? You know, you got your huge team, big goals, the economy's got a little bit of a headwind, but still, cloud's transforming, edge is exploding. What's your outlook as you look out in the tech landscape these days and how are you thinking about it? What your plans? Can you share a little bit about what's on your mind? >> Sure. So, geez, there's so many trends that are top of mind right now. Everything from zero trust to artificial intelligence to security. We have more access to data now than ever before. So the opportunities are limitless when we think about how we can apply technology to solve some really difficult customer problems, right? Innovation sometimes feels like it's happening at a rapid pace. And I also say, you know, there are years when nothing happens, and then there's years when centuries happen. And I feel like we're kind of in those years where centuries are happening. Cloud technologies are refining sports as we know them now. There's a surge of innovation in smart energy. Everyone's supply chain is looking to transform. Custom silicon is going mainstream. And frankly, AWS's customers and partners are expecting us to come to them with a point of view on trends and on opportunities. And that's what differentiates us. (John laughs) That's what gives me goosebumps- >> I was just going to ask you that. Does that give you goosebumps? How could you not love technology with that excitement? I mean, AI, throw in AI, too. I just talked to Swami, who heads up the AI and database, and we just talked about the past 24 months, the change. And that is a century moment happening. The large language models, computer vision, more compute. Compute's booming than ever before. Who thought that was going to happen, is still happening? Massive change. So, I mean, if you're in tech, how can you not love tech? >> I know, even if you're not in tech, I think you've got to start to love tech because it gives you access to things you've never had before. And frankly, right, change is the only constant. And if you don't like change, you're going to like being irrelevant even less than you like change. So we've got to be nimble, we've got to adapt. And here's the great thing, once we figure it out, it changes all over again. And it's not something that's easy for any of us to operate. It's hard, right? It's hard learning new technology, it's hard figuring out what do I do next? But here's the secret. I think it's hard because we're doing it right. It's not hard because we're doing it wrong. It's just hard to be human and it's hard to figure out how we apply all this different technology in a way that positively impacts us, you know, economically, financially, environmentally and socially. >> And everyone's different, too. So you got to live those (mumbles). I want to get one more question in before we, my last question, which is about you and your impact. When you talk to your team, your sales, you got a large sales team, North America. And Tanuja, who you mentioned, is in EMEA, we're going to speak with her as well. You guys lead the front lines, helping customers, but also delivering the revenue to the company, which has been fantastic, by the way. So what's your message to the troops and the team out there? When you say, "Take that hill," like what is the motivational pitch, in a few sentences? What's the main North Star message in today's marketplace when you're doing that big team meeting? >> I don't know if it's just limited to a team meeting. I think this is a universal message, and the universal message for me is find your edge, whatever that may be. Whether it is the edge of what you know about artificial intelligence and neural networks or it's the edge of how do we migrate our applications to the cloud more quickly. Or it's the edge of, oh, my gosh, how do I be a better parent and still be great at work, right? Find your edge, and then sharpen it. Go to the brink of what you think is possible, and then force yourself to jump. Get involved. The world is run by the people that show up, professionally and personally. (John laughs) So show up and get started. >> Yeah as Steve Jobs once said, "The future "that everyone looks at was created "by people no smarter than you." And I love that quote. That's really there. Final question for you. I know we're tight on time, but I want to get this in. When you think about your impact on your company, AWS, and the industry, what's something you want people to remember? >> Oh, geez. I think what I want people to remember the most is it's not about what you've said, and this is a Maya Angelou quote. "It's not about what you've said to people "or what you've done, "it's about how you've made them feel." And we can all think back on leaders or we can all think back on personal moments in our lives where we felt like we belonged, where we felt like we did something amazing, where we felt loved. And those are the moments that sit with us for the rest of our lives. I want people to remember how they felt when they were part of something bigger. I want people to belong. It shouldn't be uncommon to talk about feelings at work. So I want people to feel. >> Rachel, thank you for your time. I know you're really busy and we stretched you a little bit there. Thank you so much for contributing to this wonderful day of great leaders sharing their stories. And you're an inspiration. Thanks for everything you do. We appreciate you. >> Thank you. And let's go do some more Women of the Cloud videos. >> We (laughs) got more coming. Bring those stories on. Back up the story truck. We're ready to go. Thanks so much. >> That's good. >> Thank you. >> Okay, this is theCUBE's coverage of International Women's Day. It's not just going to be March 8th. That's the big celebration day. It's going to be every quarter, more stories coming. Stay tuned at siliconangle.com and thecube.net here, with bringing all the stories. I'm John Furrier, your host. Thanks for watching. (gentle music)

>> Announcer: theCUBE's live coverage is made possible by funding from Dell Technologies creating technologies that drive human progress. (upbeat music) >> Hey everyone, welcome back to theCube's first day of coverage of MWC 23 from Barcelona, Spain. Lisa Martin here with Dave Vellante and Dave Nicholson. I'm literally in between two Daves. We've had a great first day of coverage of the event. There's been lots of conversations, Dave, on disaggregation, on the change of mobility. I want to be able to get your perspectives from both of you on what you saw on the show floor, what you saw and heard from our guests today. So we'll start with you, Dave V. What were some of the things that were our takeaways from day one for you? >> Well, the big takeaway is the event itself. On day one, you get a feel for what this show is like. Now that we're back, face-to-face kind of pretty much full face-to-face. A lot of excitement here. 2000 plus exhibitors, I mean, planes, trains, automobiles, VR, AI, servers, software, I mean everything. I mean, everybody is here. So it's a really comprehensive show. It's not just about mobile. That's why they changed the name from Mobile World Congress. I think the other thing is from the keynotes this morning, I mean, you heard, there's a lot of, you know, action around the telcos and the transformation, but in a lot of ways they're sort of protecting their existing past from the future. And so they have to be careful about how fast they move. But at the same time if they don't move fast, they're going to get disrupted. We heard some complaints, essentially, you know, veiled complaints that the over the top guys aren't paying their fair share and Telco should be able to charge them more. We heard the chairman of Ericsson talk about how we can't let the OTTs do that again. We're going to charge directly for access through APIs to our network, to our data. We heard from Chris Lewis. Yeah. They've only got, or maybe it was San Ji Choha, how they've only got eight APIs. So, you know the developers are the ones who are going to actually build out the innovation at the edge. The telcos are going to provide the connectivity and the infrastructure companies like Dell as well. But it's really to me all about the developers. And that's where the action's going to be. And it's going to be interesting to see how the developers respond to, you know, the gun to the head. If you want access, you're going to have to pay for it. Now maybe there's so much money to be made that they'll go for it, but I feel like there's maybe a different model. And I think some of the emerging telcos are going to say, you know what, here developers, here's a platform, have at it. We're not going to charge you for all the data until you succeed. Then we're going to figure out a monetization model. >> Right. A lot of opportunity for the developer. That skillset is certainly one that's in demand here. And certainly the transformation of the telecom industry is, there's a lot of conundrums that I was hearing going on today, kind of chicken and egg scenarios. But Dave, you had a chance to walk around the show floor. We were here interviewing all day. What were some of the things that you saw that really stuck out to you? >> I think I was struck by how much attention was being paid to private 5G networks. You sort of read between the lines and it appears as though people kind of accept that the big incumbent telecom players are going to be slower to move. And this idea of things like open RAN where you're leveraging open protocols in a stack to deliver more agility and more value. So it sort of goes back to the generalized IT discussion of moving to cloud for agility. It appears as though a lot of players realize that the wild wild west, the real opportunity, is in the private sphere. So it's really interesting to see how that works, how 5G implemented into an environment with wifi how that actually works. It's really interesting. >> So it's, obviously when you talk to companies like Dell, I haven't hit HPE yet. I'm going to go over there and check out their booth. They got an analyst thing going on but it's really early days for them. I mean, they started in this business by taking an X86 box, putting a name on it, you know, that sounded like it was edged, throwing it over, you know, the wall. That's sort of how they all started in this business. And now they're, you know, but they knew they had to form partnerships. They had to build purpose-built systems. Now with 16 G out, you're seeing that. And so it's still really early days, talking about O RAN, open RAN, the open RAN alliance. You know, it's just, I mean, not even, the game hasn't even barely started yet but we heard from Dish today. They're trying to roll out a massive 5G network. Rakuten is really focused on sort of open RAN that's more reliable, you know, or as reliable as the existing networks but not as nearly as huge a scale as Dish. So it's going to take a decade for this to evolve. >> Which is surprising to the average consumer to hear that. Because as far as we know 5G has been around for a long time. We've been talking about 5G, implementing 5G, you sort of assume it's ubiquitous but the reality is it is just the beginning. >> Yeah. And you know, it's got a fake 5G too, right? I mean you see it on your phone and you're like, what's the difference here? And it's, you know, just, >> Dave N.: What does it really mean? >> Right. And so I think your point about private is interesting, the conversation Dave that we had earlier, I had throughout, hey I don't think it's a replacement for wifi. And you said, "well, why not?" I guess it comes down to economics. I mean if you can get the private network priced close enough then you're right. Why wouldn't it replace wifi? Now you got wifi six coming in. So that's a, you know, and WiFi's flexible, it's cheap, it's good for homes, good for offices, but these private networks are going to be like kickass, right? They're going to be designed to run whatever, warehouses and robots, and energy drilling facilities. And so, you know the economics I don't think are there today but maybe they can be at volume. >> Maybe at some point you sort of think of today's science experiment becoming the enterprise-grade solution in the future. I had a chance to have some conversations with folks around the show. And I think, and what I was surprised by was I was reminded, frankly, I wasn't surprised. I was reminded that when we start talking about 5G, we're talking about spectrum that is managed by government entities. Of course all broadcast, all spectrum, is managed in one way or another. But in particular, you can't simply put a SIM in every device now because there are a lot of regulatory hurdles that have to take place. So typically what these things look like today is 5G backhaul to the network, communication from that box to wifi. That's a huge improvement already. So yeah, my question about whether, you know, why not put a SIM in everything? Maybe eventually, but I think, but there are other things that I was not aware of that are standing in the way. >> Your point about spectrum's an interesting one though because private networks, you're going to be able to leverage that spectrum in different ways, and tune it essentially, use different parts of the spectrum, make it programmable so that you can apply it to that specific use case, right? So it's going to be a lot more flexible, you know, because I presume the needs spectrum needs of a hospital are going to be different than, you know, an agribusiness are going to be different than a drilling, you know, unit, offshore drilling unit. And so the ability to have the flexibility to use the spectrum in different ways and apply it to that use case, I think is going to be powerful. But I suspect it's going to be expensive initially. I think the other thing we talked about is public policy and regulation, and it's San Ji Choha brought up the point, is telcos have been highly regulated. They don't just do something and ask for permission, you know, they have to work within the confines of that regulated environment. And there's a lot of these greenfield companies and private networks that don't necessarily have to follow those rules. So that's a potential disruptive force. So at the same time, the telcos are spending what'd we hear, a billion, a trillion and a half over the next seven years? Building out 5G networks. So they got to figure out, you know how to get a payback on that. They'll get it I think on connectivity, 'cause they have a monopoly but they want more. They're greedy. They see the over, they see the Netflixes of the world and the Googles and the Amazons mopping up services and they want a piece of that action but they've never really been good at it. >> Well, I've got a question for both of you. I mean, what do you think the odds are that by the time the Shangri La of fully deployed 5G happens that we have so much data going through it that effectively it feels exactly the same as 3G? What are the odds? >> That's a good point. Well, the thing that gets me about 5G is there's so much of it on, if I go to the consumer side when we're all consumers in our daily lives so much of it's marketing hype. And, you know all the messaging about that, when it's really early innings yet they're talking about 6G. What does actual fully deployed 5G look like? What is that going to enable a hospital to achieve or an oil refinery out in the middle of the ocean? That's something that interests me is what's next for that? Are we going to hear that at this event? >> I mean, walking around, you see a fair amount of discussion of, you know, the internet of things. Edge devices, the increase in connectivity. And again, what I was surprised by was that there's very little talk about a sim card in every one of those devices at this point. It's like, no, no, no, we got wifi to handle all that but aggregating it back into a central network that's leveraging 5G. That's really interesting. That's really interesting. >> I think you, the odds of your, to go back to your question, I think the odds are even money, that by the time it's all built out there's going to be so much data and so much new capability it's going to work similarly at similar speeds as we see in the networks today. You're just going to be able to do so many more things. You know, and your video's going to look better, the graphics are going to look better. But I think over the course of history, this is what's happening. I mean, even when you go back to dial up, if you were in an AOL chat room in 1996, it was, you know, yeah it took a while. You're like, (screeches) (Lisa laughs) the modem and everything else, but once you were in there- >> Once you're there, 2400 baud. >> It was basically real time. And so you could talk to your friends and, you know, little chat room but that's all you could do. You know, if you wanted to watch a video, forget it, right? And then, you know, early days of streaming video, stop, start, stop, start, you know, look at Amazon Prime when it first started, Prime Video was not that great. It's sort of catching up to Netflix. But, so I think your point, that question is really prescient because more data, more capability, more apps means same speed. >> Well, you know, you've used the phrase over the top. And so just just so we're clear so we're talking about the same thing. Typically we're talking about, you've got, you have network providers. Outside of that, you know, Netflix, internet connection, I don't need Comcast, right? Perfect example. Well, what about the over the top that's coming from direct satellite communications with devices. There are times when I don't have a signal on my, happens to be an Apple iPhone, when I get a little SOS satellite logo because I can communicate under very limited circumstances now directly to the satellite for very limited text messaging purposes. Here at the show, I think it might be a Motorola device. It's a dongle that allows any mobile device to leverage direct satellite communication. Again, for texting back to the 2,400 baud modem, you know, days, 1200 even, 300 even, go back far enough. What's that going to look like? Is that too far in the future to think that eventually it's all going to be over the top? It's all going to be handset to satellite and we don't need these RANs anymore. It's all going to be satellite networks. >> Dave V.: I think you're going to see- >> Little too science fiction-y? (laughs) >> No, I, no, I think it's a good question and I think you're going to see fragments. I think you're going to see fragmentation of private networks. I think you're going to see fragmentation of satellites. I think you're going to see legacy incumbents kind of hanging on, you know, the cable companies. I think that's coming. I think by 2030 it'll, the picture will be much more clear. The question is, and I think it's come down to the innovation on top, which platform is going to be the most developer friendly? Right, and you know, I've not heard anything from the big carriers that they're going to be developer friendly. I've heard "we have proprietary data that we're going to charge access for and developers are going to have to pay for that." But I haven't heard them saying "Developers, developers, developers!" You know, Steve Bomber running around, like bend over backwards for developers, they're asking the developers to bend over. And so if a network can, let's say the satellite network is more developer friendly, you know, you're going to see more innovation there potentially. You know, or if a dish network says, "You know what? We're going after developers, we're going after innovation. We're not going to gouge them for all this network data. Rather we're going to make the platform open or maybe we're going to do an app store-like model where we take a piece of the action after they succeed." You know, take it out of the backend, like a Silicon Valley VC as opposed to an East Coast VC. They're not going to get you in the front end. (Lisa laughs) >> Well, you can see the sort of disruptive forces at play between open RAN and the legacy, call it proprietary stack, right? But what is the, you know, if that's sort of a horizontal disruptive model, what's the vertically disruptive model? Is it private networks coming in? Is it a private 5G network that comes in that says, "We're starting from the ground up, everything is containerized. We're going to go find people at KubeCon who are, who understand how to orchestrate with Kubernetes and use containers in microservices, and we're going to have this little 5G network that's going to deliver capabilities that you can't get from the big boys." Is there a way to monetize that? Is there a way for them to be disrupted, be disruptive, or are these private 5G networks that everybody's talking about just relegated to industrial use cases where you're just squeezing better economics out of wireless communication amongst all your devices in your factory? >> That's an interesting question. I mean, there are a lot of those smart factory industrial use cases. I mean, it's basically industry 4.0 use cases. But yeah, I don't count the cloud guys out. You know, everybody says, "oh, the narrative is, well, the latency of the cloud." Well, not if the cloud is at the edge. If you take a local zone and put storage, compute, and data right next to each other and the cloud model with the cloud APIs, and then you got an asynchronous, you know, connection back. I think that's a reasonable model. I think the cloud guys figured out developers, right? Pretty well. Certainly Microsoft and, and Amazon and Google, they know developers. I don't see any reason why they can't bring their model to the edge. So, and that's really disruptive to the legacy telco guys, you know? So they have to be careful. >> One step closer to my dream of eliminating the word "cloud" from IT lexicon. (Lisa laughs) I contend that it has always been IT, and it will always be IT. And this whole idea of cloud, what is cloud? If AWS, for example, is delivering hardware to the edge where it needs to be, is that cloud? Do we go back to the idea that cloud is an operational model and not a question of physical location? I hope we get to that point. >> Well, what's Apex and GreenLake? Apex is, you know, Dell's as a service. GreenLake is- >> HPE. >> HPE's as a service. That's outposts. >> Dave N.: Right. >> Yeah. >> That's their outpost. >> Yeah. >> Well AWS's position used to be, you know, to use them as a proxy for hyperscale cloud. We'll just, we'll grow in a very straight trajectory forever on the back of net new stuff. Forget about the old stuff. As James T. Kirk said of the Klingons, "let them die." (Lisa laughs) As far as the cloud providers were concerned just, yeah, let, let that old stuff go away. Well then they found out, there came a point in time where they realized there's a lot of friction and stickiness associated with that. So they had to deal with the reality of hybridity, if that's the word, the hybrid nature of things. So what are they doing? They're pushing stuff out to the edge, so... >> With the same operating model. >> With the same operating model. >> Similar. I mean, it's limited, right? >> So you see- >> You can't run a lot of database on outpost, you can run RES- >> You see this clash of Titans where some may have written off traditional IT infrastructure vendors, might have been written off as part of the past. Whereas hyperscale cloud providers represent the future. It seems here at this show they're coming head to head and competing evenly. >> And this is where I think a company like Dell or HPE or Cisco has some advantages in that they're not going to compete with the telcos, but the hyperscalers will. >> Lisa: Right. >> Right. You know, and they're already, Google's, how much undersea cable does Google own? A lot. Probably more than anybody. >> Well, we heard from Google and Microsoft this morning in the keynote. It'd be interesting to see if we hear from AWS and then over the next couple of days. But guys, clearly there is, this is a great wrap of day one. And the crazy thing is this is only day one. We've got three more days of coverage, more news, more information to break down and unpack on theCUBE. Look forward to doing that with you guys over the next three days. Thank you for sharing what you saw on the show floor, what you heard from our guests today as we had about 10 interviews. Appreciate your insights and your perspectives and can't wait for tomorrow. >> Right on. >> All right. For Dave Vellante and Dave Nicholson, I'm Lisa Martin. You're watching theCUBE's day one wrap from MWC 23. We'll see you tomorrow. (relaxing music)

(gentle music) >> Okay, welcome back to Supercloud 2, live here in Palo Alto, California for our live stage performance. Supercloud 2 is our second Supercloud event. We're going to get these out as fast as we can every couple months. It's our second one, you'll see two and three this year. I'm John Furrier, my co-host, Dave Vellante. A panel here to break down the Supercloud momentum, the wave, and the developer impact that we bringing back Vittorio Viarengo, who's a VP for Cross-Cloud Services at VMware. Sarbjeet Johal, industry influencer and Analyst at StackPayne, his company, Cube alumni and Influencer. Sarbjeet, great to see you. Vittorio, thanks for coming back. >> Nice to be here. >> My pleasure. >> Vittorio, you just gave a keynote where we unpacked the cross-cloud services, what VMware is doing, how you guys see it, not just from VMware's perspective, but VMware looking out broadly at the industry and developers came up and you were like, "Developers, developer, developers", kind of a goof on the Steve Ballmer famous meme that everyone's seen. This is a huge star, sorry, I mean a big piece of it. The developers are the canary in the coal mines. They're the ones who are being asked to code the digital transformation, which is fully business transformation and with the market the way it is right now in terms of the accelerated technology, every enterprise grade business model's changing. The technology is evolving, the builders are kind of, they want go faster. I'm saying they're stuck in a way, but that's my opinion, but there's a lot of growth. >> Yeah. >> The impact, they got to get released up and let it go. Those developers need to accelerate faster. It's been a big part of productivity, and the conversations we've had. So developer impact is huge in Supercloud. What's your, what do you guys think about this? We'll start with you, Sarbjeet. >> Yeah, actually, developers are the masons of the digital empires I call 'em, right? They lay every brick and build all these big empires. On the left side of the SDLC, or the, you know, when you look at the system operations, developer is number one cost from economic side of things, and from technology side of things, they are tech hungry people. They are developers for that reason because developer nights are long, hours are long, they forget about when to eat, you know, like, I've been a developer, I still code. So you want to keep them happy, you want to hug your developers. We always say that, right? Vittorio said that right earlier. The key is to, in this context, in the Supercloud context, is that developers don't mind mucking around with platforms or APIs or new languages, but they hate the infrastructure part. That's a fact. They don't want to muck around with servers. It's friction for them, it is like they don't want to muck around even with the VMs. So they want the programmability to the nth degree. They want to automate everything, so that's how they think and cloud is the programmable infrastructure, industrialization of infrastructure in many ways. So they are happy with where we are going, and we need more abstraction layers for some developers. By the way, I have this sort of thinking frame for last year or so, not all developers are same, right? So if you are a developer at an ISV, you behave differently. If you are a developer at a typical enterprise, you behave differently or you are forced to behave differently because you're not writing software.- >> Well, developers, developers have changed, I mean, Vittorio, you and I were talking earlier on the keynote, and this is kind of the key point is what is a developer these days? If everything is software enabled, I mean, even hardware interviews we do with Nvidia, and Amazon and other people building silicon, they all say the same thing, "It's software on a chip." So you're seeing the role of software up and down the stack and the role of the stack is changing. The old days of full stack developer, what does that even mean? I mean, the cloud is a half a stack kind of right there. So, you know, developers are certainly more agile, but cloud native, I mean VMware is epitome of operations, IT operations, and the Tan Zoo initiative, you guys started, you went after the developers to look at them, and ask them questions, "What do you need?", "How do you transform the Ops from virtualization?" Again, back to your point, so this hardware abstraction, what is software, what is cloud native? It's kind of messy equation these days. How do you guys grokel with that? >> I would argue that developers don't want the Supercloud. I dropped that up there, so, >> Dave: Why not? >> Because developers, they, once they get comfortable in AWS or Google, because they're doing some AI stuff, which is, you know, very trendy right now, or they are in IBM, any of the IPA scaler, professional developers, system developers, they love that stuff, right? Yeah, they don't, the infrastructure gets in the way, but they're just, the problem is, and I think the Supercloud should be driven by the operators because as we discussed, the operators have been left behind because they're busy with day-to-day jobs, and in most cases IT is centralized, developers are in the business units. >> John: Yeah. >> Right? So they get the mandate from the top, say, "Our bank, they're competing against". They gave teenagers or like young people the ability to do all these new things online, and Venmo and all this integration, where are we? "Oh yeah, we can do it", and then build it, and then deploy it, "Okay, we caught up." but now the operators are back in the private cloud trying to keep the backend system running and so I think the Supercloud is needed for the primarily, initially, for the operators to get in front of the developers, fit in the workflow, but lay the foundation so it is secure.- >> So, so I love this thinking because I love the rift, because the rift points to what is the target audience for the value proposition and if you're a developer, Supercloud enables you so you shouldn't have to deal with Supercloud. >> Exactly. >> What you're saying is get the operating environment or operating system done properly, whether it's architecture, building the platform, this comes back to architecture platform conversations. What is the future platform? Is it a vendor supplied or is it customer created platform? >> Dave: So developers want best to breed, is what you just said. >> Vittorio: Yeah. >> Right and operators, they, 'cause developers don't want to deal with governance, they don't want to deal with security, >> No. >> They don't want to deal with spinning up infrastructure. That's the role of the operator, but that's where Supercloud enables, to John's point, the developer, so to your question, is it a platform where the platform vendor is responsible for the architecture, or there is it an architectural standard that spans multiple clouds that has to emerge? Based on what you just presented earlier, Vittorio, you are the determinant of the architecture. It's got to be open, but you guys determine that, whereas the nirvana is, "Oh no, it's all open, and it just kind of works." >> Yeah, so first of all, let's all level set on one thing. You cannot tell developers what to do. >> Dave: Right, great >> At least great developers, right? Cannot tell them what to do. >> Dave: So that's what, that's the way I want to sort of, >> You can tell 'em what's possible. >> There's a bottle on that >> If you tell 'em what's possible, they'll test it, they'll look at it, but if you try to jam it down their throat, >> Yeah. >> Dave: You can't tell 'em how to do it, just like your point >> Let me answer your answer the question. >> Yeah, yeah. >> So I think we need to build an architect, help them build an architecture, but it cannot be proprietary, has to be built on what works in the cloud and so what works in the cloud today is Kubernetes, is you know, number of different open source project that you need to enable and then provide, use this, but when I first got exposed to Kubernetes, I said, "Hallelujah!" We had a runtime that works the same everywhere only to realize there are 12 different distributions. So that's where we come in, right? And other vendors come in to say, "Hey, no, we can make them all look the same. So you still use Kubernetes, but we give you a place to build, to set those operation policy once so that you don't create friction for the developers because that's the last thing you want to do." >> Yeah, actually, coming back to the same point, not all developers are same, right? So if you're ISV developer, you want to go to the lowest sort of level of the infrastructure and you want to shave off the milliseconds from to get that performance, right? If you're working at AWS, you are doing that. If you're working at scale at Facebook, you're doing that. At Twitter, you're doing that, but when you go to DMV and Kansas City, you're not doing that, right? So your developers are different in nature. They are given certain parameters to work with, certain sort of constraints on the budget side. They are educated at a different level as well. Like they don't go to that end of the degree of sort of automation, if you will. So you cannot have the broad stroking of developers. We are talking about a citizen developer these days. That's a extreme low, >> You mean Low-Code. >> Yeah, Low-Code, No-code, yeah, on the extreme side. On one side, that's citizen developers. On the left side is the professional developers, when you say developers, your mind goes to the professional developers, like the hardcore developers, they love the flexibility, you know, >> John: Well app, developers too, I mean. >> App developers, yeah. >> You're right a lot of, >> Sarbjeet: Infrastructure platform developers, app developers, yes. >> But there are a lot of customers, its a spectrum, you're saying. >> Yes, it's a spectrum >> There's a lot of customers don't want deal with that muck. >> Yeah. >> You know, like you said, AWS, Twitter, the sophisticated developers do, but there's a whole suite of developers out there >> Yeah >> That just want tools that are abstracted. >> Within a company, within a company. Like how I see the Supercloud is there shouldn't be anything which blocks the developers, like their view of the world, of the future. Like if you're blocked as a developer, like something comes in front of you, you are not developer anymore, believe me, (John laughing) so you'll go somewhere else >> John: First of all, I'm, >> You'll leave the company by the way. >> Dave: Yeah, you got to quit >> Yeah, you will quit, you will go where the action is, where there's no sort of blockage there. So like if you put in front of them like a huge amount of a distraction, they don't like it, so they don't, >> Well, the idea of a developer, >> Coming back to that >> Let's get into 'cause you mentioned platform. Get year in the term platform engineering now. >> Yeah. >> Platform developer. You know, I remember back in, and I think there's still a term used today, but when I graduated my computer science degree, we were called "Software engineers," right? Do people use that term "Software engineering", or is it "Software development", or they the same, are they different? >> Well, >> I think there's a, >> So, who's engineering what? Are they engineering or are they developing? Or both? Well, I think it the, you made a great point. There is a factor of, I had the, I was blessed to work with Adam Bosworth, that is the guy that created some of the abstraction layer, like Visual Basic and Microsoft Access and he had so, he made his whole career thinking about this layer, and he always talk about the professional developers, the developers that, you know, give him a user manual, maybe just go at the APIs, he'll build anything, right, from system engine, go down there, and then through obstruction, you get the more the procedural logic type of engineers, the people that used to be able to write procedural logic and visual basic and so on and so forth. I think those developers right now are a little cut out of the picture. There's some No-code, Low-Code environment that are maybe gain some traction, I caught up with Adam Bosworth two weeks ago in New York and I asked him "What's happening to this higher level developers?" and you know what he is told me, and he is always a little bit out there, so I'm going to use his thought process here. He says, "ChapGPT", I mean, they will get to a point where this high level procedural logic will be written by, >> John: Computers. >> Computers, and so we may not need as many at the high level, but we still need the engineers down there. The point is the operation needs to get in front of them >> But, wait, wait, you seen the ChatGPT meme, I dunno if it's a Dilbert thing where it's like, "Time to tic" >> Yeah, yeah, yeah, I did that >> "Time to develop the code >> Five minutes, time to decode", you know, to debug the codes like five hours. So you know, the whole equation >> Well, this ChatGPT is a hot wave, everyone's been talking about it because I think it illustrates something that's NextGen, feels NextGen, and it's just getting started so it's going to get better. I mean people are throwing stones at it, but I think it's amazing. It's the equivalent of me seeing the browser for the first time, you know, like, "Wow, this is really compelling." This is game-changing, it's not just keyword chat bots. It's like this is real, this is next level, and I think the Supercloud wave that people are getting behind points to that and I think the question of Ops and Dev comes up because I think if you limit the infrastructure opportunity for a developer, I think they're going to be handicapped. I mean that's a general, my opinion, the thesis is you give more aperture to developers, more choice, more capabilities, more good things could happen, policy, and that's why you're seeing the convergence of networking people, virtualization talent, operational talent, get into the conversation because I think it's an infrastructure engineering opportunity. I think this is a seminal moment in a new stack that's emerging from an infrastructure, software virtualization, low-code, no-code layer that will be completely programmable by things like the next Chat GPT or something different, but yet still the mechanics and the plumbing will still need engineering. >> Sarbjeet: Oh yeah. >> So there's still going to be more stuff coming on. >> Yeah, we have, with the cloud, we have made the infrastructure programmable and you give the programmability to the programmer, they will be very creative with that and so we are being very creative with our infrastructure now and on top of that, we are being very creative with the silicone now, right? So we talk about that. That's part of it, by the way. So you write the code to the particle's silicone now, and on the flip side, the silicone is built for certain use cases for AI Inference and all that. >> You saw this at CES? >> Yeah, I saw at CES, the scenario is this, the Bosch, I spoke to Bosch, I spoke to John Deere, I spoke to AWS guys, >> Yeah. >> They were showcasing their technology there and I was spoke to Azure guys as well. So the Bosch is a good example. So they are building, they are right now using AWS. I have that interview on camera, I will put it some sometime later on there online. So they're using AWS on the back end now, but Bosch is the number one, number one or number two depending on what day it is of the year, supplier of the componentry to the auto industry, and they are creating a platform for our auto industry, so is Qualcomm actually by the way, with the Snapdragon. So they told me that customers, their customers, BMW, Audi, all the manufacturers, they demand the diversity of the backend. Like they don't want all, they, all of them don't want to go to AWS. So they want the choice on the backend. So whatever they cook in the middle has to work, they have to sprinkle the data for the data sovereign side because they have Chinese car makers as well, and for, you know, for other reasons, competitive reasons and like use. >> People don't go to, aw, people don't go to AWS either for political reasons or like competitive reasons or specific use cases, but for the most part, generally, I haven't met anyone who hasn't gone first choice with either, but that's me personally. >> No, but they're building. >> Point is the developer wants choice at the back end is what I'm hearing, but then finish that thought. >> Their developers want the choice, they want the choice on the back end, number one, because the customers are asking for, in this case, the customers are asking for it, right? But the customers requirements actually drive, their economics drives that decision making, right? So in the middle they have to, they're forced to cook up some solution which is vendor neutral on the backend or multicloud in nature. So >> Yeah, >> Every >> I mean I think that's nirvana. I don't think, I personally don't see that happening right now. I mean, I don't see the parody with clouds. So I think that's a challenge. I mean, >> Yeah, true. >> I mean the fact of the matter is if the development teams get fragmented, we had this chat with Kit Colbert last time, I think he's going to come on and I think he's going to talk about his keynote in a few, in an hour or so, development teams is this, the cloud is heterogenous, which is great. It's complex, which is challenging. You need skilled engineering to manage these clouds. So if you're a CIO and you go all in on AWS, it's hard. Then to then go out and say, "I want to be completely multi-vendor neutral" that's a tall order on many levels and this is the multicloud challenge, right? So, the question is, what's the strategy for me, the CIO or CISO, what do I do? I mean, to me, I would go all in on one and start getting hedges and start playing and then look at some >> Crystal clear. Crystal clear to me. >> Go ahead. >> If you're a CIO today, you have to build a platform engineering team, no question. 'Cause if we agree that we cannot tell the great developers what to do, we have to create a platform engineering team that using pieces of the Supercloud can build, and let's make this very pragmatic and give examples. First you need to be able to lay down the run time, okay? So you need a way to deploy multiple different Kubernetes environment in depending on the cloud. Okay, now we got that. The second part >> That's like table stakes. >> That are table stake, right? But now what is the advantage of having a Supercloud service to do that is that now you can put a policy in one place and it gets distributed everywhere consistently. So for example, you want to say, "If anybody in this organization across all these different buildings, all these developers don't even know, build a PCI compliant microservice, They can only talk to PCI compliant microservice." Now, I sleep tight. The developers still do that. Of course they're going to get their hands slapped if they don't encrypt some messages and say, "Oh, that should have been encrypted." So number one. The second thing I want to be able to say, "This service that this developer built over there better satisfy this SLA." So if the SLA is not satisfied, boom, I automatically spin up multiple instances to certify the SLA. Developers unencumbered, they don't even know. So this for me is like, CIO build a platform engineering team using one of the many Supercloud services that allow you to do that and lay down. >> And part of that is that the vendor behavior is such, 'cause the incentive is that they don't necessarily always work together. (John chuckling) I'll give you an example, we're going to hear today from Western Union. They're AWS shop, but they want to go to Google, they want to use some of Google's AI tools 'cause they're good and maybe they're even arguably better, but they're also a Snowflake customer and what you'll hear from them is Amazon and Snowflake are working together so that SageMaker can be integrated with Snowflake but Google said, "No, you want to use our AI tools, you got to use BigQuery." >> Yeah. >> Okay. So they say, "Ah, forget it." So if you have a platform engineering team, you can maybe solve some of that vendor friction and get competitive advantage. >> I think that the future proximity concept that I talk about is like, when you're doing one thing, you want to do another thing. Where do you go to get that thing, right? So that is very important. Like your question, John, is that your point is that AWS is ahead of the pack, which is true, right? They have the >> breadth of >> Infrastructure by a lot >> infrastructure service, right? They breadth of services, right? So, how do you, When do you bring in other cloud providers, right? So I believe that you should standardize on one cloud provider, like that's your primary, and for others, bring them in on as needed basis, in the subsection or sub portfolio of your applications or your platforms, what ever you can. >> So yeah, the Google AI example >> Yeah, I mean, >> Or the Microsoft collaboration software example. I mean there's always or the M and A. >> Yeah, but- >> You're going to get to run Windows, you can run Windows on Amazon, so. >> By the way, Supercloud doesn't mean that you cannot do that. So the perfect example is say that you're using Azure because you have a SQL server intensive workload. >> Yep >> And you're using Google for ML, great. If you are using some differentiated feature of this cloud, you'll have to go somewhere and configure this widget, but what you can abstract with the Supercloud is the lifecycle manage of the service that runs on top, right? So how does the service get deployed, right? How do you monitor performance? How do you lifecycle it? How you secure it that you can abstract and that's the value and eventually value will win. So the customers will find what is the values, obstructing in making it uniform or going deeper? >> How about identity? Like take identity for instance, you know, that's an opportunity to abstract. Whether I use Microsoft Identity or Okta, and I can abstract that. >> Yeah, and then we have APIs and standards that we can use so eventually I think where there is enough pain, the right open source will emerge to solve that problem. >> Dave: Yeah, I can use abstract things like object store, right? That's pretty simple. >> But back to the engineering question though, is that developers, developers, developers, one thing about developers psychology is if something's not right, they say, "Go get fixing. I'm not touching it until you fix it." They're very sticky about, if something's not working, they're not going to do it again, right? So you got to get it right for developers. I mean, they'll maybe tolerate something new, but is the "juice worth the squeeze" as they say, right? So you can't go to direct say, "Hey, it's, what's a work in progress? We're going to get our infrastructure together and the world's going to be great for you, but just hang tight." They're going to be like, "Get your shit together then talk to me." So I think that to me is the question. It's an Ops question, but where's that value for the developer in Supercloud where the capabilities are there, there's less friction, it's simpler, it solves the complexity problem. I don't need these high skilled labor to manage Amazon. I got services exposed. >> That's what we talked about earlier. It's like the Walmart example. They basically, they took away from the developer the need to spin up infrastructure and worry about all the governance. I mean, it's not completely there yet. So the developer could focus on what he or she wanted to do. >> But there's a big, like in our industry, there's a big sort of flaw or the contention between developers and operators. Developers want to be on the cutting edge, right? And operators want to be on the stability, you know, like we want governance. >> Yeah, totally. >> Right, so they want to control, developers are like these little bratty kids, right? And they want Legos, like they want toys, right? Some of them want toys by way. They want Legos, they want to build there and they want make a mess out of it. So you got to make sure. My number one advice in this context is that do it up your application portfolio and, or your platform portfolio if you are an ISV, right? So if you are ISV you most probably, you're building a platform these days, do it up in a way that you can say this portion of our applications and our platform will adhere to what you are saying, standardization, you know, like Kubernetes, like slam dunk, you know, it works across clouds and in your data center hybrid, you know, whole nine yards, but there is some subset on the next door systems of innovation. Everybody has, it doesn't matter if you're DMV of Kansas or you are, you know, metaverse, right? Or Meta company, right, which is Facebook, they have it, they are building something new. For that, give them some freedom to choose different things like play with non-standard things. So that is the mantra for moving forward, for any enterprise. >> Do you think developers are happy with the infrastructure now or are they wanting people to get their act together? I mean, what's your reaction, or you think. >> Developers are happy as long as they can do their stuff, which is running code. They want to write code and innovate. So to me, when Ballmer said, "Developer, develop, Developer, what he meant was, all you other people get your act together so these developers can do their thing, and to me the Supercloud is the way for IT to get there and let developer be creative and go fast. Why not, without getting in trouble. >> Okay, let's wrap up this segment with a super clip. Okay, we're going to do a sound bite that we're going to make into a short video for each of you >> All right >> On you guys summarizing why Supercloud's important, why this next wave is relevant for the practitioners, for the industry and we'll turn this into an Instagram reel, YouTube short. So we'll call it a "Super clip. >> Alright, >> Sarbjeet, you want, you want some time to think about it? You want to go first? Vittorio, you want. >> I just didn't mind. (all laughing) >> No, okay, okay. >> I'll do it again. >> Go back. No, we got a fresh one. We'll going to already got that one in the can. >> I'll go. >> Sarbjeet, you go first. >> I'll go >> What's your super clip? >> In software systems, abstraction is your friend. I always say that. Abstraction is your friend, even if you're super professional developer, abstraction is your friend. We saw from the MFC library from C++ days till today. Abstract, use abstraction. Do not try to reinvent what's already being invented. Leverage cloud, leverage the platform side of the cloud. Not just infrastructure service, but platform as a service side of the cloud as well, and Supercloud is a meta platform built on top of these infrastructure services from three or four or five cloud providers. So use that and embrace the programmability, embrace the abstraction layer. That's the key actually, and developers who are true developers or professional developers as you said, they know that. >> Awesome. Great super clip. Vittorio, another shot at the plate here for super clip. Go. >> Multicloud is awesome. There's a reason why multicloud happened, is because gave our developers the ability to innovate fast and ever before. So if you are embarking on a digital transformation journey, which I call a survival journey, if you're not innovating and transforming, you're not going to be around in business three, five years from now. You have to adopt the Supercloud so the developer can be developer and keep building great, innovating digital experiences for your customers and IT can get in front of it and not get in trouble together. >> Building those super apps with Supercloud. That was a great super clip. Vittorio, thank you for sharing. >> Thanks guys. >> Sarbjeet, thanks for coming on talking about the developer impact Supercloud 2. On our next segment, coming up right now, we're going to hear from Walmart enterprise architect, how they are building and they are continuing to innovate, to build their own Supercloud. Really informative, instructive from a practitioner doing it in real time. Be right back with Walmart here in Palo Alto. Thanks for watching. (gentle music)

>> John: Hello and welcome to this cube conversation here in Palo Alto, California. I'm John Furrier, host of theCUBE. We got a great conversation on making machine learning easier and more affordable in an era where everybody wants more machine learning and AI. We're featuring Neural Magic with the CEO is also Cube alumni, Brian Steve. CEO, Great to see you Brian. Thanks for coming on this cube conversation. Talk about machine learning. >> Brian: Hey John, happy to be here again. >> John: What a buzz that's going on right now? Machine learning, one of the hottest topics, AI front and center, kind of going mainstream. We're seeing the success of the, of the kind of NextGen capabilities in the enterprise and in apps. It's a really exciting time. So perfect timing. Great, great to have this conversation. Let's start with taking a minute to explain what you guys are doing over there at Neural Magic. I know there's some history there, neural networks, MIT. But the, the convergence of what's going on, this big wave hitting, it's an exciting time for you guys. Take a minute to explain the company and your mission. >> Brian: Sure, sure, sure. So, as you said, the company's Neural Magic and spun out at MIT four plus years ago, along with some people and, and some intellectual property. And you summarize it better than I can cause you said, we're just trying to make, you know, AI that much easier. And so, but like another level of specificity around it is. You know, in the world you have a lot of like data scientists really focusing on making AI work for whatever their use case is. And then the next phase of that, then they're looking at optimizing the models that they built. And then it's not good enough just to work on models. You got to put 'em into production. So, what we do is we make it easier to optimize the models that have been developed and trained and then trying to make it super simple when it comes time to deploying those in production and managing them. >> Brian: You know, we've seen this movie before with the cloud. You start to see abstractions come out. Data science we saw like was like the, the secret art of being like a data scientist now democratization of data. You're kind of seeing a similar wave with machine learning models, foundational models, some call it developers are getting involved. Model complexity's still there, but, but it's getting easier. There's almost like the democratization happening. You got complexity, you got deployment, it's challenges, cost, you got developers involved. So it's like how do you grow it? How do you get more horsepower? And then how do you make developers productive, right? So like, this seems to be the thread. So, so where, where do you see this going? Because there's going to be a massive demand for, I want to do more with my machine learning. But what's the data source? What's the formatting? This kind of a stack develop, what, what are you guys doing to address this? Can you take us through and demystify this, this wave that's hitting, that everyone's seeing? >> Brian: Yeah. Now like you said, like, you know, the democratization of all of it. And that brings me all the way back to like the roots of open source, right? When you think about like, like back in the day you had to build your own tech stack yourself. A lot of people probably probably don't remember that. And then you went, you're building, you're always starting on a body of code or a module that was out there with open source. And I think that's what I equate to where AI has gotten to with what you were talking about the foundational models that didn't really exist years ago. So you really were like putting the layers of your models together in the formulas and it was a lot of heavy lifting. And so there was so much time spent on development. With far too few success cases, you know, to get into production to solve like a business stereo technical need. But as these, what's happening is as these models are becoming foundational. It's meaning people don't have to start from scratch. They're actually able to, you know, the avant-garde now is start with existing model that almost does what you want, but then applying your data set to it. So it's, you know, it's really the industry moving forward. And then we, you know, and, and the best thing about it is open source plays a new dimension, but this time, you know, in the, in the realm of AI. And so to us though, like, you know, I've been like, I spent a career focusing on, I think on like the, not just the technical side, but the consumption of the technology and how it's still way too hard for somebody to actually like, operationalize technology that all those vendors throw at them. So I've always been like empathetic the user around like, you know what their job is once you give them great technology. And so it's still too difficult even with the foundational models because what happens is there's really this impedance mismatch between the development of the model and then where, where the model has to live and run and be deployed and the life cycle of the model, if you will. And so what we've done in our research is we've developed techniques to introduce what's known as sparsity into a machine learning model. It's already been developed and trained. And what that sparsity does is that unlocks by making that model so much smaller. So in many cases we can make a model 90 to 95% smaller, even smaller than that in research. So, and, and so by doing that, we do that in a way that preserves all the accuracy out of the foundational model as you talked about. So now all of a sudden you get this much smaller model just as accurate. And then the even more exciting part about it is we developed a software-based engine called Deep Source. And what that, what the Inference Runtime does is takes that now sparsified model and it runs it, but because you sparsified it, it only needs a fraction of the compute that it, that it would've needed otherwise. So what we've done is make these models much faster, much smaller, and then by pairing that with an inference runtime, you now can actually deploy that model anywhere you want on commodity hardware, right? So X 86 in the cloud, X 86 in the data center arm at the edge, it's like this massive unlock that happens because you get the, the state-of-the-art models, but you get 'em, you know, on the IT assets and the commodity infrastructure. That is where all the applications are running today. >> John: I want to get into the inference piece and the deep sparse you mentioned, but I first have to ask, you mentioned open source, Dave and I with some fellow cube alumnis. We're having a chat about, you know, the iPhone and Android moment where you got proprietary versus open source. You got a similar thing happening with some of these machine learning modules where there's a lot of proprietary things happening and there's open source movement is growing. So is there a balance there? Are they all trying to do the same thing? Is it more like a chip, you know, silicons involved, all kinds of things going on that are really fascinating from a science. What's your, what's your reaction to that? >> Brian: I think it's like anything that, you know, the way we talk about AI you think had been around for decades, but the reality is it's been some of the deep learning models. When we first, when we first started taking models that the brain team was working on at Google and billing APIs around them on Google Cloud where the first cloud to even have AI services was 2015, 2016. So when you think about it, it's really been what, 6 years since like this thing is even getting lift off. So I think with that, everybody's throwing everything at it. You know, there's tons of funded hardware thrown at specialty for training or inference new companies. There's legacy companies that are getting into like AI now and whether it's a, you know, a CPU company that's now building specialized ASEX for training. There's new tech stacks proprietary software and there's a ton of asset service. So it really is, you know, what's gone from nascent 8 years ago is the wild, wild west out there. So there's a, there's a little bit of everything right now and I think that makes sense because at the early part of any industry it really becomes really specialized. And that's the, you know, showing my age of like, you know, the early pilot of the two thousands, you know, red Hat people weren't running X 86 in enterprise back then and they thought it was a toy and they certainly weren't running open source, but you really, and it made sense that they weren't because it didn't deliver what they needed to at that time. So they needed specialty stacks, they needed expensive, they needed expensive hardware that did what an Oracle database needed to do. They needed proprietary software. But what happens is that commoditizes through both hardware and through open source and the same thing's really just starting with with AI. >> John: Yeah. And I think that's a great point before we to call that out because in any industry timing's everything, right? I mean I remember back in the 80s, late 80s and 90s, AI, you know, stuff was going on and it just wasn't, there wasn't enough horsepower, there wasn't enough tech. >> Brian: Yep. >> John: You mentioned some of the processing. So AI is this industry that has all these experts who have been itch scratching that itch for decades. And now with cloud and custom silicon. The tech fundamental at the lower end of the stack, if you will, on the performance side is significantly more performant. It's there you got more capabilities. >> Brian: Yeah. >> John: Now you're kicking into more software, faster software. So it just seems like we're at a tipping point where finally it's here, like that AI moment or machine learning and now data is, is involved. So this is where organizations I see really jumping in with the CEO mandate. Hey team, make ML work for us. Go figure it out. It's got to be an advantage for us. >> Brian: Yeah. >> John: So now they go, okay boss, we will. So what, what do they do? What's the steps does an enterprise take to get machine learning into their organizations? Cause you know, it's coming down from the boards, you know, how does this work for rob? >> Brian: Yeah. Like the, you know, the, what we're seeing is it's like anything, like it's, whether that was source adoption or whether that was cloud adoption, it always starts usually with one person. And increasingly it is the CEO, which realizes they're getting further behind the competition because they're not leaning in, you know, faster. But typically it really comes down to like a really strong practitioner that's inside the organization, right? And, that realizes that the number one goal isn't doing more and just training more models and and necessarily being proprietary about it. It's really around understanding the art of the possible. Something that's grounded in the art of the possible, what, what deep learning can do today and what business outcomes you can deliver, you know, if you can employ. And then there's well proven paths through that. It's just that because of where it's been, it's not that industrialized today. It's very much, you know, you see ML project by ML project is very snowflakey, right? And that was kind of the early days of open source as well. And so, we're just starting to get to the point where it's getting easier, it's getting more industrialized, there's less steps, there's less burdensome on developers, there's less burdensome on, on the deployment side. And we're trying to bring that, that whole last mile by saying, you know what? Deploying deep learning and AI models should be as easy as the as to deploy your application, right? You shouldn't have to take an extra step to deploy an AI model. It shouldn't have to require a new hardware, it shouldn't require a new process, a new DevOps model. It should be as simple as what you're already doing. >> John: What is the best practice for companies to effectively bring an acceptable level of machine learning and performance into their organizations? >> Brian: Yeah, I think like the, the number one start is like what you hinted at before is they, they have to know the use case. They have to, in most cases, you're going to find across every industry you know, that that problem's been tackled by some company, right? And then you have to have the best practice around fine-tuning the models already exist. So fine tuning that existing model. That foundational model on your unique dataset. You, you know, if you are in medical instruments, it's not good enough to identify that it's a medical instrument in the picture. You got to know what type of medical instrument. So there's always a fine tuning step. And so we've created open source tools that make it easy for you to do two things at once. You can fine tune that existing foundational model, whether that's in the language space or whether that's in the vision space. You can fine tune that on your dataset. And at the same time you get an optimized model that comes out the other end. So you get kind of both things. So you, you no longer have to worry about you're, we're freeing you from worrying about the complexity of that transfer learning, if you will. And we're freeing you from worrying about, well where am I going to deploy the model? Where does it need to be? Does it need to be on a device, an edge, a data center, a cloud edge? What kind of hardware is it? Is there enough hardware there? We're liberating you from all of that. Because what you want, what you can count on is there'll always be commodity capability, commodity CPUs where you want to deploy in abundance cause that's where your application is. And so all of a sudden we're just freeing you of that, of that whole step. >> John: Okay. Let's get into deep sparse because you mentioned that earlier. What inspired the creation of deep sparse and how does it differ from any other solutions in the market that are out there? >> Brian: Sure. So, so where unique is it? It starts by, by two things. One is what the industry's pretty good at from the optimization side is they're good at like this thing called quantization, which turns like, you know, big numbers into small numbers, lower precision. So a 32 bit representation of a, of AI weight into a bit. And they're good at like cutting out layers, which also takes away accuracy. What we've figured out is to take those, the industry techniques for those that are best practice, but we combined it with unstructured varsity. So by reducing that model by 90 to 95% in size, that's great because it's made it smaller. But we've taken that when it's the deep sparse engine, when you deploy it that looks at that model and says, because it's so much smaller, I no longer have to run the part of the model that's been essentially sparsified. So what that's done is, it's meant that you no longer need a supercomputer to run models because there's not nearly as much math and processing as there was before the model was optimized. So now what happens is, every CPU platform out there has, has an enormous amount of compute because we've sparsified the rest of it away. So you can pick a, you can pick your, your laptop and you have enough compute to run state-of-the-art models. The second thing that, and you need a software engine to do that cause it ignores the parts of the models. It doesn't need to run, which is what like specialized hardware can't do. The second part is it's then turned into a memory efficiency problem. So it's really around just getting memory, getting the models loaded into the cash of the computer and keeping it there. Never having to go back out to memory. So, so our techniques are both, we reduce the model size and then we only run the part of the model that matters and then we keep it all in cash. And so what that does is it gets us to like these, these low, low latency faster and we're able to increase, you know, the CPU processing by an order magnitude. >> John: Yeah. That low latency is key. And you got developers, you know, co coding super fast. We'll get to the developer angle in a second. I want to just follow up on this, this motivation behind the, the deep sparse because you know, as we were talking earlier before we came on camera about the old days, I mean, not too long ago, virtualization and VMware abstracted away the os from, from the hardware rights and the server virtualization changed the game. >> Brian: Yeah. >> John: And that basically invented cloud computing as we know it today. So, so we see that abstraction. >> Brian: Yeah. >> John: There seems to be a motivation behind abstracting the way the machine learning models away from the hardware. And that seems to be bringing advantages to the AI growth. Can you elaborate on, is that true? And it's, what's your comment? >> Brian: It's true. I think it's true for us. I don't think the industry's there yet, honestly. Cause I think the industry still is of that mindset that if I took, if it took these expensive GPUs to train my model, then I want to run my model on those same expensive GPUs. Because there's often like not a separation between the people that are developing AI and the people that have to manage and deploy at where you need it. So the reality is, is that that's everything that we're after. Like, do we decrease the cost? Yes. Do we make the models smaller? Yes. Do we make them faster? A yes. But I think the most amazing power is that we've turned AI into a docker based microservice. And so like who in the industry wants to deploy their apps the old way on a os without virtualization, without docker, without Kubernetes, without microservices, without service mesh without serverless. You want all those tools for your apps by converting AI models. So they can be run inside a docker container with no apologies around latency and performance cause it's faster. You get the best of that whole world that you just talked about, which is, you know, what we're calling, you know, software delivered AI. So now the AI lives in the same world. Organizations that have gone through that digital cloud transformation with their app infrastructure. AI fits into that world. >> John: And this is where the abstraction concepts matter. When you have these inflection points, the convergence of compute data, machine learning that powers AI, it really becomes a developer opportunity. Because now applications and businesses, when they actually go through the digital transformation, their businesses are completely transformed. There is no IT. Developers are the application. They are the company, right? So AI will be part of whatever business or app will be out there. So there is a application developer angle here. Brian, can you explain >> Brian: Oh completely. >> John: how they're going to use this? Because you mentioned docker container microservice, I mean this really is an insane flipping of the script for developers. >> Brian: Yeah. >> John: So what's that look like? >> Brian: Well speak, it's because like AI's kind of, I mean, again, like it's come so fast. So you figure there's my app team and here's my AI team, right? And they're in different places and the AI team is dragging in specialized infrastructure in support of that as well. And that's not how app developers think. Like they've ran on fungible infrastructure that subtracted and virtualized forever, right? And so what we've done is we've, in addition to fitting into that world that they, that they like, we've also made it simple for them for they don't have to be a machine learning engineer to be able to experiment with these foundational models and transfer learning 'em. We've done that. So they can do that in a couple of commands and it has a simple API that they can either link to their application directly as a library to make difference calls or they can stand it up as a standalone, you know, scale up, scale out inference server. They get two choices. But it really fits into that, you know, you know that world that the modern developer, whether they're just using Python or C or otherwise, we made it just simple. So as opposed to like Go learn something else, they kind of don't have to. So in a way though, it's made it. It's almost made it hard because people expect when we talk to 'em for the first time to be the old way. Like, how do you look like a piece of hardware? Are you compatible with my existing hardware that runs ML? Like, no, we're, we're not. Because you don't need that stack anymore. All you need is a library called to make your prediction and that's it. That's it. >> John: Well, I mean, we were joking on Twitter the other day with someone saying, is AI a pet or a cattle? Right? Because they love their, their AI bots right now. So, so I'd say pet there. But you look at a lot of, there's going to be a lot of AI. So on a more serious note, you mentioned in microservices, will deep sparse have an API for developers? And how does that look like? What do I do? >> Brian: Yeah. >> John: tell me what my, as a developer, what's the roadmap look like? What's the >> Brian: Yeah, it, it really looks, it really can go in both modes. It can go in a standalone server mode where it handles, you know, rest API and it can scale out with ES as the workload comes up and scale back and like try to make hardware do that. Hardware may scale back, but it's just sitting there dormant, you know, so with this, it scales the same way your application needs to. And then for a developer, they basically just, they just, the PIP install de sparse, you know, has one commanded to do an install, and then they do two calls, really. The first call is a library call that the app makes to create the model. And models really already trained, but they, it's called a model create call. And the second command they do is they make a call to do a prediction. And it's as simple as that. So it's, it's AI's as simple as using any other library that the developers are already using, which I, which sounds hard to fathom because it is just so simplified. >> John: Software delivered AI. Okay, that's a cool thing. I believe in it personally. I think that's the way to go. I think there's going to be plenty of hardware options if you look at the advances of cloud players that got more silicon coming out. Yeah. More GPU. I mean, there's more instance, I mean, everything's out there right now. So the question is how does that evolve in your mind? Because that's seems to be key. You have open source projects emerging. What, what path does this take? Is there a parallel mental model that you see, Brian, that is similar? You mentioned open source earlier. Is it more like a VMware virtualization thing or is it more of a cloud thing? Is there Yeah. Is it going to evolve in a, in a trajectory that looks similar to what we might've seen in the past? >> Brian: Yeah, we're, you know, when I, when when I got involved with the company, what I, when I thought about it and I was reasoning about it, like, do you, you know, you want to, like, we all do when you want to join something full-time. I thought about it and said, where will the industry eventually get to? Right? To fully realize the value of, of deep learning and what's plausible as it evolves. And to me, like I, I know it's the old adage of, you know, you know, software, its hardware, cloudy software. But it truly was like, you know, we can solve these problems in software. Like there's nothing special that's happening at the hardware layer and the processing AI. The reality is that it's just early in the industry. So the view that that we had was like, this is eventually the best place where the industry will be, is the liberation of being able to run AI anywhere. Like you're really not democratizing, you democratize the model. But if you can't run the model anywhere you want because these models are getting bigger and bigger with these large language models, then you're kind of not democratizing. And if you got to go and like by a cluster to run this thing on. So the democratization comes by if all of a sudden that model can be consumed anywhere on demand without planning, without provisioning, wherever infrastructure is. And so I think that's with or without Neural Magic, that's where the industry will go and will get to. I think we're the leaders, leaders in getting it there. It's right because we're more advanced on these techniques. >> John: Yeah. And your background too. You've seen OpenStack, pre-cloud, you saw open source grow and still exponentially growing. And so you have the same similar dynamic with machine learning models growing. And they're also segmenting into almost a, an ML stack or foundational model as we talk about. So you're starting to see the formation of tooling inference. So a lot of components coming. It's almost a stack, it's almost a, it literally is like an operating system problem space, you know? How do you run things, how do you link things? How do you bring things together? Is that what's going on here? Is this like a data modeling operating environment kind of red hat type thing going on? Like. >> Brian: Yeah. Yeah. Like I think there is, you know, I thought about that too. And I think there is the role of like distribution, because the industrialization not happening fast enough of this. Like, can I go back to like every customers, every, every user does it in their own kind of way. Like it's not, everyone's a little bit of a snowflake. And I think that's okay. There's definitely plenty of companies that want to come in and say, well, this is the way it's going to be and we industrialize it as long as you do it our way. The reality is technology doesn't get industrialized by one company just saying, do it our way. And so that's why like we've taken the approach through open source by saying like, Hey, you haven't really industrialized it if you said. We made it simple, but you always got to run AI here. Yeah, right. You only like really industrialize it if you break it down into components that are simple to use and they work integrated in the stack the way you want them to. And so to me, that first principles was getting thing into microservices and dockers that could be run on VMware, OpenShare on the cloud in the edge. And so that's the, that's the real part that we're happening with. The other part, like I do agree, like I think it's going to quickly move into less about the model. Less about the training of the model and the transfer learning, you know, the data set of the model. We're taking away the complexity of optimization. Giving liberating deployment to be anywhere. And I think the last mile, John is going to be around the ML ops around that. Because it's easy to think of like soft now that it's just a software problem, we've turned it into a software problem. So it's easy to think of software as like kind of a point release, but that's not the reality, right? It's a life cycle. And it's, and so I think ML very much brings in the what is the lifecycle of that deployment? And, you know, you get into more interesting conversations, to be honest than like, once you've deployed in a docking container is around like model drift and accuracy and the dataset changes and the user changes is how do you become from an ML perspective of where of that sending signal back retraining. And, and that's where I think a lot of the, in more of the innovation's going to start to move there. >> John: Yeah. And software also, the software problem, the software opportunity as well is developer focused. And if you look at the cloud native landscape now, similar stacks developing a lot of components. A lot of things to, to stitch together a lot of things that are automating under the hood. A lot of developer productivity conversations. I think this is going to go down that same road. I want to get your thoughts because developers will set the pace. And this is something that's clear in this next wave developer productivity. They're the defacto standards bodies. They will decide what microservices check, API check. Now, skill gap is going to be a problem because it's relatively new. So model sprawl, model sizes, proprietary versus open. There has to be a way to kind of crunch that down into a, like a DevOps, like just make it, get the developer out of the, the muck. So what's your view? Are we early days like that? Or what's the young kid in college studying CS or whatever degree who comes into this with, with both feet? What are they doing? >> Brian: I'll probably say like the, the non-popular answer to that. A little bit is it's happening so fast that it's going to get kind of boring fast. Meaning like, yeah, you could go to school and go to MIT, right? Sorry. Like, and you could get a hold through end like becoming a model architect, like inventing the next model, right? And the layers and combining 'em and et cetera, et cetera. And then what operators and, and building a model that's bigger than the last one and trains faster, right? And there will be those people, right? That actually, like they're building the engines the same way. You know, I grew up as an infrastructure software developer. There's not a lot of companies that hire those anymore because they're all sitting inside of three big clouds. Yeah. Right? So you better be a good app developer, but I think what you're going to see is before you had to be everything, you had to be the, if you were going to use infrastructure, you had to know how to build infrastructure. And I think the same thing's true around is quickly exiting ML is to be able to use ML in your company, you better be like, great at every aspect of ML, including every intricacy inside of the model and every operation's doing, that's quickly changing. Like, you're going to start with a starting point. You know, in the future you're not going to be like cracking open these GPT models, you're going to just be pulling them off the shelf, fine tuning 'em and go. You don't have to invent it. You don't have to understand it. And I think that's going to be a pivot point, you know, in the industry between, you know, what's the future? What's, what's the future of a, a data scientist? ML engineer researcher look like? >> John: I think that's, the outcome's going to be determined. I mean, you mentioned, you know, doing it yourself what an SRE is for a Google with the servers scale's huge. So yeah, it might have to, at the beginning get boring, you get obsolete quickly, but that means it's progressing. So, The scale becomes huge. And that's where I think it's going to be interesting when we see that scale. >> Brian: Yep. Yeah, I think that's right. I think that's right. And we always, and, and what I've always said, and much the, again, the distribute into my ML team is that I want every developer to be as adept at being able take advantage of ML as non ML engineer, right? It's got to be that simple. And I think, I think it's getting there. I really do. >> John: Well, Brian, great, great to have you on theCUBE here on this cube conversation. As part of the startup showcase that's coming up. You're going to be featured. Or your company would featured on the upcoming ABRA startup showcase on making machine learning easier and more affordable as more machine learning models come in. You guys got deep sparse and some great technology. We're going to dig into that next time. I'll give you the final word right now. What do you see for the company? What are you guys looking for? Give a plug for the company right now. >> Brian: Oh, give a plug that I haven't already doubled in as the plug. >> John: You're hiring engineers, I assume from MIT and other places. >> Brian: Yep. I think like the, the biggest thing is like, like we're on the developer side. We're here to make this easy. The majority of inference today is, is on CPUs already, believe it or not, as much as kind of, we like to talk about hardware and specialized hardware. The majority is already on CPUs. We're basically bringing 95% cost savings to CPUs through this acceleration. So, but we're trying to do it in a way that makes it community first. So I think the, the shout out would be come find the Neural Magic community and engage with us and you'll find, you know, a thousand other like-minded people in Slack that are willing to help you as well as our engineers. And, and let's, let's go take on some successful AI deployments. >> John: Exciting times. This is, I think one of the pivotal moments, NextGen data, machine learning, and now starting to see AI not be that chat bot, just, you know, customer support or some basic natural language processing thing. You're starting to see real innovation. Brian Stevens, CEO of Neural Magic, bringing the magic here. Thanks for the time. Great conversation. >> Brian: Thanks John. >> John: Thanks for joining me. >> Brian: Cheers. Thank you. >> John: Okay. I'm John Furrier, host of theCUBE here in Palo Alto, California for this cube conversation with Brian Stevens. Thanks for watching.

>> Hey everyone. Welcome back to theCUBE's coverage day two of CloudNative Security CON 23. Lisa Martin here in studio in Palo Alto with John Furrier. John, we've had some great conversations. I've had a global event. This was a global event. We had Germany on yesterday. We had the Boston Studio. We had folks on the ground in Seattle. Lot of great conversations, a lot of great momentum at this event. What is your number one takeaway with this inaugural event? >> Well, first of all, our coverage with our CUBE alumni experts coming in remotely this remote event for us, I think this event as an inaugural event stood out because one, it was done very carefully and methodically from the CNCF. I think they didn't want to overplay their hand relative to breaking out from CUBE CON So Kubernetes success and CloudNative development has been such a success and that event and ecosystem is booming, right? So that's the big story is they have the breakout event and the question was, was it a good call? Was it successful? Was it going to, would the dog hunt as they say, in this case, I think the big takeaway is that it was successful by all measures. One, people enthusiastic and confident that this has the ability to stand on its own and still contribute without taking away from the benefits and growth of Kubernetes CUBE CON and CloudNative console. So that was the key. Hallway conversations, the sessions all curated and developed properly to be different and focused for that reason. So I think the big takeaway is that the CNCF did a good job on how they rolled this out. Again, it was very intimate event small reminds me of first CUBE CON in Seattle, kind of let's test it out. Let's see how it goes. Again, clearly it was people successful and they understood why they're doing it. And as we commented out in our earlier segments this is not something new. Amazon Web Services has re:Invent and re:Inforce So a lot of parallels there. I see there. So I think good call. CNCF did the right thing. I think this has legs. And then as Dave pointed out, Dave Vellante, on our last keynote analysis was the business model of the hackers is better than the business model of the industry. They're making more money, it costs less so, you know, they're playing offense and the industry playing defense. That has to change. And as Dave pointed out we have to make the cost of hacking and breaches and cybersecurity higher so that the business model crashes. And I think that's the strategic imperative. So I think the combination of the realities of the market globally and open source has to go faster. It's good to kind of decouple and be highly cohesive in the focus. So to me that's the big takeaway. And then the other one is, is that there's a lot more security problems still unresolved. The emphasis on developers productivity is at risk here, if not solved. You saw supply chain software, again, front and center and then down in the weeds outside of Kubernetes, things like BIND and DNS were brought up. You're seeing the Linux kernel. Really important things got to be paid attention to. So I think very good call, very good focus. >> I would love if for us to be able to, as the months go on talk to some of the practitioners that actually got to attend. There were 72 sessions, that's a lot of content for a small event. Obviously to your point, very well curated. We did hear from some folks yesterday who were just excited to get the community back together in person. To your point, having this dedicated focus on CloudNativesecurity is incredibly important. You talked about, you know, the offense defense, the fact that right now the industry needs to be able to pivot from being on defense to being on offense. This is a challenging thing because it is so lucrative for hackers. But this seems to be from what we've heard in the last couple days, the right community with the right focus to be able to make that pivot. >> Yeah, and I think if you look at the success of Kubernetes, 'cause again we were there at theCUBE first one CUBE CON, the end user stories really drove end user participation. Drove the birth of Kubernetes. Left some of these CloudNative early adopters early pioneers that were using cloud hyperscale really set the table for CloudNative CON. I think you're seeing that here with this CloudNative SecurityCON where I think we're see a lot more end user stories because of the security, the hairs on fire as we heard from Madrona Ventures, you know, as they as an investor you have a lot of use cases out there where customers are leaning in with getting the rolling up their sleeves, working with open source. This has to be the driver. So I'm expecting to see the next level of SecurityCON to be end user focused. Much more than vendor focused. Where CUBECON was very end user focused and then attracted all the vendors in that grew the industry. I expect the similar pattern here where end user action will be very high at the beginning and that will essentially be the rising tide for the vendors to be then participating. So I expect almost a similar trajectory to CUBECON. >> That's a good path that it needs to all be about all the end users. One of the things I'm curious if what you heard was what are some of the key factors that are going to move CloudNative Security forward? What did you hear the last two days? >> I heard that there's a lot of security problems and no one wants to kind of brag about this but there's a lot of under the hood stuff that needs to get taken care of. So if automation scales, and we heard that from one of the startups we've just interviewed. If automation and scale continues to happen and with the business model of the hackers still booming, security has to be refactored quickly and there's going to be an opportunity structurally to use the cloud for that. So I think it's a good opportunity now to get dedicated focus on fixing things like the DNS stuff old school under the hood, plumbing, networking protocols. You're going to start to see this super cloud-like environment emerge where data's involved, everything's happening and so security has to be re imagined. And I think there's a do over opportunity for the security industry with CloudNative driving that. And I think this is the big thing that I see as an opportunity to, from a story standpoint from a coverage standpoint is that it's a do-over for security. >> One of the things that we heard yesterday is that there's a lot of it, it's a pretty high percentage of organizations that either don't have a SOCK or have a very primitive SOCK. Which kind of surprised me that at this day and age the risks are there. We talked about that today's focus and the keynote was a lot about the software supply chain and what's going on there. What did you hear in terms of the appetite for organizations through the voice of the practitioner to say, you know what guys, we got to get going because there's going to be the hackers are they're here. >> I didn't hear much about that in the coverage 'cause we weren't in the hallways. But from reading the tea leaves and talking to the folks on the ground, I think there's an implied like there's an unlimited money from customers. So it's a very robust from the data infrastructure stack building we cover with the angel investor Kane you're seeing data infrastructure's going to be part of the solution here 'cause data and security go hand in hand. So everyone's got basically checkbook wide open everyone wants to have the answer. And we commented that the co-founder of Palo Alto you had on our coverage yesterday was saying that you know, there's no real platform, there's a lot of tools out there. People will buy anything. So there's still a huge appetite and spend in security but the answer's not going to more tool sprawling. It's going to more platform auto, something that enables automation, fix some of the underlying mechanisms involved and fix it fast. So to me I think it's going to be a robust monetary opportunity because of the demand on the business side. So I don't see that changing at all and I think it's going to accelerate. >> It's a great point in terms of the demand for the business side because as we know as we said yesterday, the next Log4j is out there. It's not a matter of if this happens again it's when, it's the extent, it's how frequent we know that. So organizations all the way up to the board have to be concerned about brand reputation. Nobody wants to be the next big headline in terms of breaches and customer data being given to hackers and hackers making all this money on that. That has to go all the way up to the board and there needs to be alignment between the board and the executives at the organization in terms of how they're going to deal with security, and now. This is not a conversation that can wait. Yeah, I mean I think the five C's we talked about yesterday the culture of companies, the cloud is an enabler, you've got clusters of servers and capabilities, Kubernetes clusters, you've got code and you've got all kinds of, you know, things going on there. Each one has elements that are at risk for hacking, right? So that to me is something that's super important. I think that's why the focus on security's different and important, but it's not going to fork the main event. So that's why I think the spin out was, spinout, or the new event is a good call by the CNCF. >> One of the things today that struck me they're talking a lot about software supply chain and that's been in the headlines for quite a while now. And a stat that was shared this morning during the keynote just blew my brains that there was a 742% increase in the software supply chain attacks occurring over the last three years. It's during Covid times, that is a massive increase. The threat landscape is just growing so amorphously but organizations need to help dial that down because their success and the health of the individuals and the end users is at risk. Well, Covid is an environment where everyone's kind of working at home. So there was some disruption to infrastructure. Also, when you have change like that, there's opportunities for hackers, they'll arbitrage that big time. But I think general the landscape is changing. There's no perimeter anymore. It's CloudNative, this is where it is and people who are moving from old IT to CloudNative, they're at risk. That's why there's tons of ransomware. That's why there's tons of risk. There's just hygiene, from hygiene to architecture and like Nick said from Palo Alto, the co-founder, there's not a lot of architecture in security. So yeah, people have bulked up their security teams but you're going to start to see much more holistic thinking around redoing security. I think that's the opportunity to propel CloudNative, and I think you'll see a lot more coming out of this. >> Did you hear any specific information on some of the CloudNative projects going on that really excite you in terms of these are the right people going after the right challenges to solve in the right direction? >> Well I saw the sessions and what jumped out to me at the sessions was it's a lot of extensions of what we heard at CUBECON and I think what they want to do is take out the big items and break 'em out in security. Kubescape was one we just covered. They want to get more sandbox type stuff into the security side that's very security focused but also plays well with CUBECON. So we'll hear more about how this plays out when we're in Amsterdam coming up in April for CUBECON to hear how that ecosystem, because I think it'll be kind of a relief to kind of decouple security 'cause that gives more focus to the stakeholders in CUBECON. There's a lot of issues going on there and you know service meshes and whatnot. So it's a lot of good stuff happening. >> A lot of good stuff happening. One of the things that'll be great about CUBECON is that we always get the voice of the customer. We get vendors coming on with the voice of the customer talking about and you know in that case how they're using Kubernetes to drive the business forward. But it'll be great to be able to pull in some of the security conversations that spin out of CloudNative Security CON to understand how those end users are embracing the technology. You brought up I think Nir Zuk from Palo Alto Networks, one of the themes there when Dave and I did their Ignite event in December was, of 22, was really consolidation. There are so many tools out there that organizations have to wrap their heads around and they need to be able to have the right enablement content which this event probably delivered to figure out how do we consolidate security tools effectively, efficiently in a way that helps dial down our risk profile because the risks just seem to keep growing. >> Yeah, and I love the technical nature of all that and I think this is going to be the continued focus. Chris Aniszczyk who's the CTO listed like E and BPF we covered with Liz Rice is one of the most three important points of the conference and it's just, it's very nerdy and that's what's needed. I mean it's technical. And again, there's no real standards bodies anymore. The old days developers I think are super important to be the arbiters here. And again, what I love about the CNCF is that they're developer focused and we heard developer first even in security. So you know, this is a sea change and I think, you know, developers' choice will be the standards bodies. >> Lisa: Yeah, yeah. >> They decide the future. >> Yeah. >> And I think having the sandboxing and bringing this out will hopefully accelerate more developer choice and self-service. >> You've been talking about kind of putting the developers in the driver's seat as really being the key decision makers for a while. Did you hear information over the last couple of days that validates that? >> Yeah, absolutely. It's clearly the fact that they did this was one. The other one is, is that engineering teams and dev teams and script teams, they're blending together. It's not just separate silos and the ones that are changing their team dynamics, again, back to the culture are winning. And I think this has to happen. Security has to be embedded everywhere in making it frictionless and to provide kind of the guardrail so developers don't slow down. And I think where security has become a drag or an anchor or a blocker has been just configuration of how the organization's handling it. So I think when people recognize that the developers are in charge and they're should be driving the application development you got to make sure that's secure. And so that's always going to be friction and I think whoever does it, whoever unlocks that for the developer to go faster will win. >> Right. Oh, that's what I'm sure magic to a developer's ear is the ability to go faster and be able to focus on co-development in a secure fashion. What are some of the things that you're excited about for CUBECON. Here we are in February, 2023 and CUBECON is just around the corner in April. What are some of the things that you're excited about based on the groundswell momentum that this first inaugural CloudNative Security CON is generating from a community, a culture perspective? >> I think this year's going to be very interesting 'cause we have an economic challenge globally. There's all kinds of geopolitical things happening. I think there's going to be very entrepreneurial activity this year more than ever. I think you're going to see a lot more innovative projects ideas hitting the table. I think it's going to be a lot more entrepreneurial just because the cycle we're in. And also I think the acceleration of mainstream deployments of out of the CNCF's main event CUBECON will happen. You'll see a lot more successes, scale, more clarity on where the security holes are or aren't. Where the benefits are. I think containers and microservices are continuing to surge. I think the Cloud scale hyperscale as Amazon, Azure, Google will be more aggressive. I think AI will be a big theme this year. I think you can see how data is going to infect some of the innovation thinking. I'm really excited about the data infrastructure because it powers a lot of things in the Cloud. So I think the Amazon Web Services, Azure next level gen clouds will impact what happens in the CloudNative foundation. >> Did you have any conversations yesterday or today with respect to AI and security? Was that a focus of anybody's? Talk to me about that. >> Well, I didn't hear any sessions on AI but we saw some demos on stage. But they're teasing out that this is an augmentation to their mission, right? So I think a lot of people are looking at AI as, again, like I always said there's the naysayers who think it's kind of a gimmick or nothing to see here, and then some are just going to blown away. I think the people who are alpha geeks and the industry connect the dots and understand that AI is going to be an accelerant to a lot of heavy lifting that was either manual, you know, hard to do things that was boring or muck as they say. I think that's going to be where you'll see the AI stories where it's going to accelerate either ways to make security better or make developers more confident and productive. >> Or both. >> Yeah. So definitely AI will be part of it. Yeah, definitely. One of the things too that I'm wondering if, you know, we talk about CloudNative and the goal of it, the importance of it. Do you think that this event, in terms of what we were able to see, obviously being remote the event going on in Seattle, us being here in Palo Alto and Boston and guests on from Seattle and Germany and all over, did you hear the really the validation for why CloudNative Security why CloudNative is important for organizations whether it's a bank or a hospital or a retailer? Is that validation clear and present? >> Yeah, absolutely. I think it was implied. I don't think there was like anyone's trying to debate that. I think this conference was more of it's assumed and they were really trying to push the ability to make security less defensive, more offensive and more accelerated into the solving the problems with the businesses that are out there. So clearly the CloudNative community understands where the security challenges are and where they're emerging. So having a dedicated event will help address that. And they've got great co-chairs too that put it together. So I think that's very positive. >> Yeah. Do you think, is it possible, I mean, like you said several times today so eloquently the industry's on the defense when it comes to security and the hackers are on the offense. Is it really possible to make that switch or obviously get some balances. As technology advances and industry gets to take advantage of that, so do the hackers, is that balance achievable? >> Absolutely. I mean, I think totally achievable. The question's going to be what's the environment going to be like? And I remember as context to understanding whether it's viable or not, is to look at, just go back 13 years ago, I remember in 2010 Amazon was viewed as an unsecure environment. Everyone's saying, "Oh, the cloud is not secure." And I remember interviewing Steve Schmidt at AWS and we discussed specifically how Amazon Cloud was being leveraged by hackers. They made it more complex for the hackers. And he said, "This is just the beginning." It's kind of like barbed wire on a fence. It's yeah, you're not going to climb it so people can get over it. And so since then what's happened is the Cloud has become more secure than on premises for a lot of either you know, personnel reasons, culture reasons, not updating, you know, from patches to just being insecure to be more insecure. So that to me means that the flip the script can be flipped. >> Yeah. And I think with CloudNative they can build in automation and code to solve some of these problems and make it more complex for the hacker. >> Lisa: Yes. >> And increase the cost. >> Yeah, exactly. Make it more complex. Increase the cost. That'll be in interesting journey to follow. So John, here we are early February, 2023 theCUBE starting out strong as always. What year are we in, 12? Year 12? >> 13th year >> 13! What's next for theCUBE? What's coming up that excites you? >> Well, we're going to do a lot more events. We got the theCUBE in studio that I call theCUBE Center as kind of internal code word, but like, this is more about getting the word out that we can cover events remotely as events are starting to change with hybrid, digital is going to be a big part of that. So I think you're going to see a lot more CUBE on location. We're going to do, still do theCUBE and have theCUBE cover events from the studio to get deeper perspective because we can then bring people in remote through our our studio team. We can bring our CUBE alumni in. We have a corpus of content and experts to bring to table. So I think the coverage will be increased. The expertise and data will be flowing through theCUBE and so Cube Center, CUBE CUBE Studio. >> Lisa: Love it. >> Will be a integral part of our coverage. >> I love that. And we have such great conversations with guests in person, but also virtually, digitally as well. We still get the voices of the practitioners and the customers and the vendors and the partner ecosystem really kind of lauded loud and clear through theCUBE megaphone as I would say. >> And of course getting the clips out there, getting the highlights. >> Yeah. >> Getting more stories. No stories too small for theCUBE. We can make it easy to get the best content. >> The best content. John, it's been fun covering CloudNative security CON with you with you. And Dave and our guests, thank you so much for the opportunity and looking forward to the next event. >> John: All right. We'll see you at Amsterdam. >> Yeah, I'll be there. We want to thank you so much for watching TheCUBES's two day coverage of CloudNative Security CON 23. We're live in Palo Alto. You are live wherever you are and we appreciate your time and your view of this event. For John Furrier, Dave Vellante, I'm Lisa Martin. Thanks for watching guys. We'll see you at the next show.

>> Welcome back to SuperCloud2. This is Dave Vellante, and we're here with Jack Greenfield. He's the Vice President of Enterprise Architecture and the Chief Architect for the global technology platform at Walmart. Jack, I want to thank you for coming on the program. Really appreciate your time. >> Glad to be here, Dave. Thanks for inviting me and appreciate the opportunity to chat with you. >> Yeah, it's our pleasure. Now we call what you've built a SuperCloud. That's our term, not yours, but how would you describe the Walmart Cloud Native Platform? >> So WCNP, as the acronym goes, is essentially an implementation of Kubernetes for the Walmart ecosystem. And what that means is that we've taken Kubernetes off the shelf as open source, and we have integrated it with a number of foundational services that provide other aspects of our computational environment. So Kubernetes off the shelf doesn't do everything. It does a lot. In particular the orchestration of containers, but it delegates through API a lot of key functions. So for example, secret management, traffic management, there's a need for telemetry and observability at a scale beyond what you get from raw Kubernetes. That is to say, harvesting the metrics that are coming out of Kubernetes and processing them, storing them in time series databases, dashboarding them, and so on. There's also an angle to Kubernetes that gets a lot of attention in the daily DevOps routine, that's not really part of the open source deliverable itself, and that is the DevOps sort of CICD pipeline-oriented lifecycle. And that is something else that we've added and integrated nicely. And then one more piece of this picture is that within a Kubernetes cluster, there's a function that is critical to allowing services to discover each other and integrate with each other securely and with proper configuration provided by the concept of a service mesh. So Istio, Linkerd, these are examples of service mesh technologies. And we have gone ahead and integrated actually those two. There's more than those two, but we've integrated those two with Kubernetes. So the net effect is that when a developer within Walmart is going to build an application, they don't have to think about all those other capabilities where they come from or how they're provided. Those are already present, and the way the CICD pipelines are set up, it's already sort of in the picture, and there are configuration points that they can take advantage of in the primary YAML and a couple of other pieces of config that we supply where they can tune it. But at the end of the day, it offloads an awful lot of work for them, having to stand up and operate those services, fail them over properly, and make them robust. All of that's provided for. >> Yeah, you know, developers often complain they spend too much time wrangling and doing things that aren't productive. So I wonder if you could talk about the high level business goals of the initiative in terms of the hardcore benefits. Was the real impetus to tap into best of breed cloud services? Were you trying to cut costs? Maybe gain negotiating leverage with the cloud guys? Resiliency, you know, I know was a major theme. Maybe you could give us a sense of kind of the anatomy of the decision making process that went in. >> Sure, and in the course of answering your question, I think I'm going to introduce the concept of our triplet architecture which we haven't yet touched on in the interview here. First off, just to sort of wrap up the motivation for WCNP itself which is kind of orthogonal to the triplet architecture. It can exist with or without it. Currently does exist with it, which is key, and I'll get to that in a moment. The key drivers, business drivers for WCNP were developer productivity by offloading the kinds of concerns that we've just discussed. Number two, improving resiliency, that is to say reducing opportunity for human error. One of the challenges you tend to run into in a large enterprise is what we call snowflakes, lots of gratuitously different workloads, projects, configurations to the extent that by developing and using WCNP and continuing to evolve it as we have, we end up with cookie cutter like consistency across our workloads which is super valuable when it comes to building tools or building services to automate operations that would otherwise be manual. When everything is pretty much done the same way, that becomes much simpler. Another key motivation for WCNP was the ability to abstract from the underlying cloud provider. And this is going to lead to a discussion of our triplet architecture. At the end of the day, when one works directly with an underlying cloud provider, one ends up taking a lot of dependencies on that particular cloud provider. Those dependencies can be valuable. For example, there are best of breed services like say Cloud Spanner offered by Google or say Cosmos DB offered by Microsoft that one wants to use and one is willing to take the dependency on the cloud provider to get that functionality because it's unique and valuable. On the other hand, one doesn't want to take dependencies on a cloud provider that don't add a lot of value. And with Kubernetes, we have the opportunity, and this is a large part of how Kubernetes was designed and why it is the way it is, we have the opportunity to sort of abstract from the underlying cloud provider for stateless workloads on compute. And so what this lets us do is build container-based applications that can run without change on different cloud provider infrastructure. So the same applications can run on WCNP over Azure, WCNP over GCP, or WCNP over the Walmart private cloud. And we have a private cloud. Our private cloud is OpenStack based and it gives us some significant cost advantages as well as control advantages. So to your point, in terms of business motivation, there's a key cost driver here, which is that we can use our own private cloud when it's advantageous and then use the public cloud provider capabilities when we need to. A key place with this comes into play is with elasticity. So while the private cloud is much more cost effective for us to run and use, it isn't as elastic as what the cloud providers offer, right? We don't have essentially unlimited scale. We have large scale, but the public cloud providers are elastic in the extreme which is a very powerful capability. So what we're able to do is burst, and we use this term bursting workloads into the public cloud from the private cloud to take advantage of the elasticity they offer and then fall back into the private cloud when the traffic load diminishes to the point where we don't need that elastic capability, elastic capacity at low cost. And this is a very important paradigm that I think is going to be very commonplace ultimately as the industry evolves. Private cloud is easier to operate and less expensive, and yet the public cloud provider capabilities are difficult to match. >> And the triplet, the tri is your on-prem private cloud and the two public clouds that you mentioned, is that right? >> That is correct. And we actually have an architecture in which we operate all three of those cloud platforms in close proximity with one another in three different major regions in the US. So we have east, west, and central. And in each of those regions, we have all three cloud providers. And the way it's configured, those data centers are within 10 milliseconds of each other, meaning that it's of negligible cost to interact between them. And this allows us to be fairly agnostic to where a particular workload is running. >> Does a human make that decision, Jack or is there some intelligence in the system that determines that? >> That's a really great question, Dave. And it's a great question because we're at the cusp of that transition. So currently humans make that decision. Humans choose to deploy workloads into a particular region and a particular provider within that region. That said, we're actively developing patterns and practices that will allow us to automate the placement of the workloads for a variety of criteria. For example, if in a particular region, a particular provider is heavily overloaded and is unable to provide the level of service that's expected through our SLAs, we could choose to fail workloads over from that cloud provider to a different one within the same region. But that's manual today. We do that, but people do it. Okay, we'd like to get to where that happens automatically. In the same way, we'd like to be able to automate the failovers, both for high availability and sort of the heavier disaster recovery model between, within a region between providers and even within a provider between the availability zones that are there, but also between regions for the sort of heavier disaster recovery or maintenance driven realignment of workload placement. Today, that's all manual. So we have people moving workloads from region A to region B or data center A to data center B. It's clean because of the abstraction. The workloads don't have to know or care, but there are latency considerations that come into play, and the humans have to be cognizant of those. And automating that can help ensure that we get the best performance and the best reliability. >> But you're developing the dataset to actually, I would imagine, be able to make those decisions in an automated fashion over time anyway. Is that a fair assumption? >> It is, and that's what we're actively developing right now. So if you were to look at us today, we have these nice abstractions and APIs in place, but people run that machine, if you will, moving toward a world where that machine is fully automated. >> What exactly are you abstracting? Is it sort of the deployment model or, you know, are you able to abstract, I'm just making this up like Azure functions and GCP functions so that you can sort of run them, you know, with a consistent experience. What exactly are you abstracting and how difficult was it to achieve that objective technically? >> that's a good question. What we're abstracting is the Kubernetes node construct. That is to say a cluster of Kubernetes nodes which are typically VMs, although they can run bare metal in certain contexts, is something that typically to stand up requires knowledge of the underlying cloud provider. So for example, with GCP, you would use GKE to set up a Kubernetes cluster, and in Azure, you'd use AKS. We are actually abstracting that aspect of things so that the developers standing up applications don't have to know what the underlying cluster management provider is. They don't have to know if it's GCP, AKS or our own Walmart private cloud. Now, in terms of functions like Azure functions that you've mentioned there, we haven't done that yet. That's another piece that we have sort of on our radar screen that, we'd like to get to is serverless approach, and the Knative work from Google and the Azure functions, those are things that we see good opportunity to use for a whole variety of use cases. But right now we're not doing much with that. We're strictly container based right now, and we do have some VMs that are running in sort of more of a traditional model. So our stateful workloads are primarily VM based, but for serverless, that's an opportunity for us to take some of these stateless workloads and turn them into cloud functions. >> Well, and that's another cost lever that you can pull down the road that's going to drop right to the bottom line. Do you see a day or maybe you're doing it today, but I'd be surprised, but where you build applications that actually span multiple clouds or is there, in your view, always going to be a direct one-to-one mapping between where an application runs and the specific cloud platform? >> That's a really great question. Well, yes and no. So today, application development teams choose a cloud provider to deploy to and a location to deploy to, and they have to get involved in moving an application like we talked about today. That said, the bursting capability that I mentioned previously is something that is a step in the direction of automatic migration. That is to say we're migrating workload to different locations automatically. Currently, the prototypes we've been developing and that we think are going to eventually make their way into production are leveraging Istio to assess the load incoming on a particular cluster and start shedding that load into a different location. Right now, the configuration of that is still manual, but there's another opportunity for automation there. And I think a key piece of this is that down the road, well, that's a, sort of a small step in the direction of an application being multi provider. We expect to see really an abstraction of the fact that there is a triplet even. So the workloads are moving around according to whatever the control plane decides is necessary based on a whole variety of inputs. And at that point, you will have true multi-cloud applications, applications that are distributed across the different providers and in a way that application developers don't have to think about. >> So Walmart's been a leader, Jack, in using data for competitive advantages for decades. It's kind of been a poster child for that. You've got a mountain of IP in the form of data, tools, applications best practices that until the cloud came out was all On Prem. But I'm really interested in this idea of building a Walmart ecosystem, which obviously you have. Do you see a day or maybe you're even doing it today where you take what we call the Walmart SuperCloud, WCNP in your words, and point or turn that toward an external world or your ecosystem, you know, supporting those partners or customers that could drive new revenue streams, you know directly from the platform? >> Great question, Steve. So there's really two things to say here. The first is that with respect to data, our data workloads are primarily VM basis. I've mentioned before some VMware, some straight open stack. But the key here is that WCNP and Kubernetes are very powerful for stateless workloads, but for stateful workloads tend to be still climbing a bit of a growth curve in the industry. So our data workloads are not primarily based on WCNP. They're VM based. Now that said, there is opportunity to make some progress there, and we are looking at ways to move things into containers that are currently running in VMs which are stateful. The other question you asked is related to how we expose data to third parties and also functionality. Right now we do have in-house, for our own use, a very robust data architecture, and we have followed the sort of domain-oriented data architecture guidance from Martin Fowler. And we have data lakes in which we collect data from all the transactional systems and which we can then use and do use to build models which are then used in our applications. But right now we're not exposing the data directly to customers as a product. That's an interesting direction that's been talked about and may happen at some point, but right now that's internal. What we are exposing to customers is applications. So we're offering our global integrated fulfillment capabilities, our order picking and curbside pickup capabilities, and our cloud powered checkout capabilities to third parties. And this means we're standing up our own internal applications as externally facing SaaS applications which can serve our partners' customers. >> Yeah, of course, Martin Fowler really first introduced to the world Zhamak Dehghani's data mesh concept and this whole idea of data products and domain oriented thinking. Zhamak Dehghani, by the way, is a speaker at our event as well. Last question I had is edge, and how you think about the edge? You know, the stores are an edge. Are you putting resources there that sort of mirror this this triplet model? Or is it better to consolidate things in the cloud? I know there are trade-offs in terms of latency. How are you thinking about that? >> All really good questions. It's a challenging area as you can imagine because edges are subject to disconnection, right? Or reduced connection. So we do place the same architecture at the edge. So WCNP runs at the edge, and an application that's designed to run at WCNP can run at the edge. That said, there are a number of very specific considerations that come up when running at the edge, such as the possibility of disconnection or degraded connectivity. And so one of the challenges we have faced and have grappled with and done a good job of I think is dealing with the fact that applications go offline and come back online and have to reconnect and resynchronize, the sort of online offline capability is something that can be quite challenging. And we have a couple of application architectures that sort of form the two core sets of patterns that we use. One is an offline/online synchronization architecture where we discover that we've come back online, and we understand the differences between the online dataset and the offline dataset and how they have to be reconciled. The other is a message-based architecture. And here in our health and wellness domain, we've developed applications that are queue based. So they're essentially business processes that consist of multiple steps where each step has its own queue. And what that allows us to do is devote whatever bandwidth we do have to those pieces of the process that are most latency sensitive and allow the queue lengths to increase in parts of the process that are not latency sensitive, knowing that they will eventually catch up when the bandwidth is restored. And to put that in a little bit of context, we have fiber lengths to all of our locations, and we have I'll just use a round number, 10-ish thousand locations. It's larger than that, but that's the ballpark, and we have fiber to all of them, but when the fiber is disconnected, and it does get disconnected on a regular basis. In fact, I forget the exact number, but some several dozen locations get disconnected daily just by virtue of the fact that there's construction going on and things are happening in the real world. When the disconnection happens, we're able to fall back to 5G and to Starlink. Starlink is preferred. It's a higher bandwidth. 5G if that fails. But in each of those cases, the bandwidth drops significantly. And so the applications have to be intelligent about throttling back the traffic that isn't essential, so that it can push the essential traffic in those lower bandwidth scenarios. >> So much technology to support this amazing business which started in the early 1960s. Jack, unfortunately, we're out of time. I would love to have you back or some members of your team and drill into how you're using open source, but really thank you so much for explaining the approach that you've taken and participating in SuperCloud2. >> You're very welcome, Dave, and we're happy to come back and talk about other aspects of what we do. For example, we could talk more about the data lakes and the data mesh that we have in place. We could talk more about the directions we might go with serverless. So please look us up again. Happy to chat. >> I'm going to take you up on that, Jack. All right. This is Dave Vellante for John Furrier and the Cube community. Keep it right there for more action from SuperCloud2. (upbeat music)

(upbeat music) >> Good morning everybody. Welcome back to Las Vegas. This is day four of theCUBE's wall-to-wall coverage of our Super Bowl, aka AWS re:Invent 2022. I'm here with my co-host, Paul Gillin. My name is Dave Vellante. Sanjay Poonen is in the house, CEO and president of Cohesity. He's sitting in as our guest market watcher, market analyst, you know, deep expertise, new to the job at Cohesity. He was kind enough to sit in, and help us break down what's happening at re:Invent. But Paul, first thing, this morning we heard from Werner Vogels. He was basically given a masterclass on system design. It reminded me of mainframes years ago. When we used to, you know, bury through those IBM blue books and red books. You remember those Sanjay? That's how we- learned back then. >> Oh God, I remember those, Yeah. >> But it made me think, wow, now you know IBM's more of a systems design, nobody talks about IBM anymore. Everybody talks about Amazon. So you wonder, 20 years from now, you know what it's going to be. But >> Well- >> Werner's amazing. >> He pulled out a 24 year old document. >> Yup. >> That he had written early in Amazon's evolution about synchronous design or about essentially distributed architectures that turned out to be prophetic. >> His big thing was nature is asynchronous. So systems are asynchronous. Synchronous is an illusion. It's an abstraction. It's kind of interesting. But, you know- >> Yeah, I mean I've had synonyms for things. Timeless architecture. Werner's an absolute legend. I mean, when you think about folks who've had, you know, impact on technology, you think of people like Jony Ive in design. >> Dave: Yeah. >> You got to think about people like Werner in architecture and just the fact that Andy and the team have been able to keep him engaged that long... I pay attention to his keynote. Peter DeSantis has obviously been very, very influential. And then of course, you know, Adam did a good job, you know, watching from, you know, having watched since I was at the first AWS re:Invent conference, at time was President SAP and there was only a thousand people at this event, okay? Andy had me on stage. I think I was one of the first guest of any tech company in 2011. And to see now this become like, it's a mecca. It's a mother of all IT events, and watch sort of even the transition from Andy to Adam is very special. I got to catch some of Ruba's keynote. So while there's some new people in the mix here, this has become a force of nature. And the last time I was here was 2019, before Covid, watched the last two ones online. But it feels like, I don't know 'about what you guys think, it feels like it's back to 2019 levels. >> I was here in 2019. I feel like this was bigger than 2019 but some people have said that it's about the same. >> I think it was 60,000 versus 50,000. >> Yes. So close. >> It was a little bigger in 2019. But it feels like it's more active. >> And then last year, Sanjay, you weren't here but it was 25,000, which was amazing 'cause it was right in that little space between Omicron, before Omicron hit. But you know, let me ask you a question and this is really more of a question about Amazon's maturity and I know you've been following them since early days. But the way I get the question, number one question I get from people is how is Amazon AWS going to be different under Adam than it was under Andy? What do you think? >> I mean, Adam's not new because he was here before. In some senses he knows the Amazon culture from prior, when he was running sales and marketing prior. But then he took the time off and came back. I mean, this will always be, I think, somewhat Andy's baby, right? Because he was the... I, you know, sent him a text, "You should be really proud of what you accomplished", but you know, I think he also, I asked him when I saw him a few weeks ago "Are you going to come to re:Invent?" And he says, "No, I want to leave this to be Adam's show." And Adam's going to have a slightly different view. His keynotes are probably half the time. It's a little bit more vision. There was a lot more customer stories at the beginning of it. Taking you back to the inspirational pieces of it. I think you're going to see them probably pulling up the stack and not just focused in infrastructure. Many of their platform services are evolved. Many of their, even application services. I'm surprised when I talk to customers. Like Amazon Connect, their sort of call center type technologies, an app layer. It's getting a lot. I mean, I've talked to a couple of Fortune 500 companies that are moving off Ayer to Connect. I mean, it's happening and I did not know that. So it's, you know, I think as they move up the stack, the platform's gotten more... The data centric stack has gotten, and you know, in the area we're working with Cohesity, security, data protection, they're an investor in our company. So this is an important, you know, both... I think tech player and a partner for many companies like us. >> I wonder the, you know, the marketplace... there's been a big push on the marketplace by all the cloud companies last couple of years. Do you see that disrupting the way softwares, enterprise software is sold? >> Oh, for sure. I mean, you have to be a ostrich with your head in the sand to not see this wave happening. I mean, what's it? $150 billion worth of revenue. Even though the growth rates dipped a little bit the last quarter or so, it's still aggregatively between Amazon and Azure and Google, you know, 30% growth. And I think we're still in the second or third inning off a grand 1 trillion or 2 trillion of IT, shifting not all of it to the cloud, but significantly faster. So if you add up all of the big things of the on-premise world, they're, you know, they got to a certain size, their growth is stable, but stalling. These guys are growing significantly faster. And then if you add on top of them, platform companies the data companies, Snowflake, MongoDB, Databricks, you know, Datadog, and then apps companies on top of that. I think the move to the Cloud is inevitable. In SaaS companies, I don't know why you would ever implement a CRM solution on-prem. It's all gone to the Cloud. >> Oh, it is. >> That happened 15 years ago. I mean, begin within three, five years of the advent of Salesforce. And the same thing in HR. Why would you deploy a HR solution now? You've got Workday, you've got, you know, others that are so some of those apps markets are are just never coming back to an on-prem capability. >> Sanjay, I want to ask you, you built a reputation for being able to, you know, forecast accurately, hit your plan, you know, you hit your numbers, you're awesome operator. Even though you have a, you know, technology degree, which you know, that's a two-tool star, multi-tool star. But I call it the slingshot economy. This is like, I mean I've seen probably more downturns than anybody in here, you know, given... Well maybe, maybe- >> Maybe me. >> You and I both. I've never seen anything like this, where where visibility is so unpredictable. The economy is sling-shotting. It's like, oh, hurry up, go Covid, go, go go build, build, build supply, then pull back. And now going forward, now pulling back. Slootman said, you know, on the call, "Hey the guide, is the guide." He said, "we put it out there, We do our best to hit it." But you had CrowdStrike had issues you know, mid-market, ServiceNow. I saw McDermott on the other day on the, on the TV. I just want to pay, you know, buy from the guy. He's so (indistinct) >> But mixed, mixed results, Salesforce, you know, Octa now pre-announcing, hey, they're going to be, or announcing, you know, better visibility, forward guide. Elastic kind of got hit really hard. HPE and Dell actually doing really well in the enterprise. >> Yep. >> 'Course Dell getting killed in the client. But so what are you seeing out there? How, as an executive, do you deal with such poor visibility? >> I think, listen, what the last two or three years have taught us is, you know, with the supply chain crisis, with the surge that people thought you may need of, you know, spending potentially in the pandemic, you have to start off with your tech platform being 10 x better than everybody else. And differentiate, differentiate. 'Cause in a crowded market, but even in a market that's getting tougher, if you're not differentiating constantly through technology innovation, you're going to get left behind. So you named a few places, they're all technology innovators, but even if some of them are having challenges, and then I think you're constantly asking yourselves, how do you move from being a point product to a platform with more and more services where you're getting, you know, many of them moving really fast. In the case of Roe, I like him a lot. He's probably one of the most savvy operators, also that I respect. He calls these speedboats, and you know, his core platform started off with the firewall network security. But he's built now a very credible cloud security, cloud AI security business. And I think that's how you need to be thinking as a tech executive. I mean, if you got core, your core beachhead 10 x better than everybody else. And as you move to adjacencies in these new platforms, have you got now speedboats that are getting to a point where they are competitive advantage? Then as you think of the go-to-market perspective, it really depends on where you are as a company. For a company like our size, we need partners a lot more. Because if we're going to, you know, stand on the shoulders of giants like Isaac Newton said, "I see clearly because I stand on the shoulders giants." I need to really go and cultivate Amazon so they become our lead partner in cloud. And then appropriately Microsoft and Google where I need to. And security. Part of what we announced last week was, last month, yeah, last couple of weeks ago, was the data security alliance with the biggest security players. What was I trying to do with that? First time ever done in my industry was get Palo Alto, CrowdStrike, Wallace, Tenable, CyberArk, Splunk, all to build an alliance with me so I could stand on their shoulders with them helping me. If you're a bigger company, you're constantly asking yourself "how do you make sure you're getting your, like Amazon, their top hundred customers spending more with that?" So I think the the playbook evolves, and I'm watching some of these best companies through this time navigate through this. And I think leadership is going to be tested in enormously interesting ways. >> I'll say. I mean, Snowflake is really interesting because they... 67% growth, which is, I mean, that's best in class for a company that's $2 billion. And, but their guide was still, you know, pretty aggressive. You know, so it's like, do you, you know, when it when it's good times you go, "hey, we can we can guide conservatively and know we can beat it." But when you're not certain, you can't dial down too far 'cause your investors start to bail on you. It's a really tricky- >> But Dave, I think listen, at the end of the day, I mean every CEO should not be worried about the short term up and down in the stock price. You're building a long-term multi-billion dollar company. In the case of Frank, he has, I think I shot to a $10 billion, you know, analytics data warehousing data management company on the back of that platform, because he's eyeing the market that, not just Teradata occupies today, but now Oracle occupies or other databases, right? So his tam as it grows bigger, you're going to have some of these things, but that market's big. I think same with Palo Alto. I mean Datadog's another company, 75% growth. >> Yeah. >> At 20% margins, like almost rule of 95. >> Amazing. >> When they're going after, not just the observability market, they're eating up the sim market, security analytics, the APM market. So I think, you know, that's, you look at these case studies of companies who are going from point product to platforms and are steadily able to grow into new tams. You know, to me that's very inspiring. >> I get it. >> Sanjay: That's what I seek to do at our com. >> I get that it's a marathon, but you know, when you're at VMware, weren't you looking at the stock price every day just out of curiosity? I mean listen, you weren't micromanaging it. >> You do, but at the end of the day, and you certainly look at the days of earnings and so on so forth. >> Yeah. >> Because you want to create shareholder value. >> Yeah. >> I'm not saying that you should not but I think in obsession with that, you know, in a short term, >> Going to kill ya. >> Makes you, you know, sort of myopically focused on what may not be the right thing in the long term. Now in the long arc of time, if you're not creating shareholder value... Look at what happened to Steve Bomber. You needed Satya to come in to change things and he's created a lot of value. >> Dave: Yeah, big time. >> But I think in the short term, my comments were really on the quarter to quarter, but over a four a 12 quarter, if companies are growing and creating profitable growth, they're going to get the valuation they deserve. >> Dave: Yeah. >> Do you the... I want to ask you about something Arvind Krishna said in the previous IBM earnings call, that IT is deflationary and therefore it is resistant to the macroeconomic headwinds. So IT spending should actually thrive in a deflation, in a adverse economic climate. Do you think that's true? >> Not all forms of IT. I pay very close attention to surveys from, whether it's the industry analysts or the Morgan Stanleys, or Goldman Sachs. The financial analysts. And I think there's a gluc in certain sectors that will get pulled back. Traditional view is when the economies are growing people spend on the top line, front office stuff, sales, marketing. If you go and look at just the cloud 100 companies, which are the hottest private companies, and maybe with the public market companies, there's way too many companies focused on sales and marketing. Way too many. I think during a downsizing and recession, that's going to probably shrink some, because they were all built for the 2009 to 2021 era, where it was all about the top line. Okay, maybe there's now a proposition for companies who are focused on cost optimization, supply chain visibility. Security's been intangible, that I think is going to continue to an investment. So I tell, listen, if you are a tech investor or if you're an operator, pay attention to CIO priorities. And right now, in our business at Cohesity, part of the reason we've embraced things like ransomware protection, there is a big focus on security. And you know, by intelligently being a management and a security company around data, I do believe we'll continue to be extremely relevant to CIO budgets. There's a ransomware, 20 ransomware attempts every second. So things of that kind make you relevant in a bank. You have to stay relevant to a buying pattern or else you lose momentum. >> But I think what's happening now is actually IT spending's pretty good. I mean, I track this stuff pretty closely. It's just that expectations were so high and now you're seeing earnings estimates come down and so, okay, and then you, yeah, you've got the, you know the inflationary factors and your discounted cash flows but the market's actually pretty good. >> Yeah. >> You know, relative to other downturns that if this is not a... We're not actually not in a downturn. >> Yeah. >> Not yet anyway. It may be. >> There's a valuation there. >> You have to prepare. >> Not sales. >> Yeah, that's right. >> When I was on CNBC, I said "listen, it's a little bit like that story of Joseph. Seven years of feast, seven years of famine." You have to prepare for potentially your worst. And if it's not the worst, you're in good shape. So will it be a recession 2023? Maybe. You know, high interest rates, inflation, war in Russia, Ukraine, maybe things do get bad. But if you belt tightening, if you're focused in operational excellence, if it's not a recession, you're pleasantly surprised. If it is one, you're prepared for it. >> All right. I'm going to put you in the spot and ask you for predictions. Expert analysis on the World Cup. What do you think? Give us the breakdown. (group laughs) >> As my... I wish India was in the World Cup, but you can't get enough Indians at all to play soccer well enough, but we're not, >> You play cricket, though. >> I'm a US man first. I would love to see one of Brazil, or Argentina. And as a Messi person, I don't know if you'll get that, but it would be really special for Messi to lead, to end his career like Maradonna winning a World Cup. I don't know if that'll happen. I'm probably going to go one of the Latin American countries, if the US doesn't make it far enough. But first loyalty to the US team, and then after one of the Latin American countries. >> And you think one of the Latin American countries is best bet to win or? >> I don't know. It's hard to tell. They're all... What happens now at this stage >> So close, right? >> is anybody could win. >> Yeah. You just have lots of shots of gold. I'm a big soccer fan. It could, I mean, I don't know if the US is favored to win, but if they get far enough, you get to the finals, anybody could win. >> I think they get Netherlands next, right? >> That's tough. >> Really tough. >> But... The European teams are good too, but I would like to see US go far enough, and then I'd like to see Latin America with team one of Argentina, or Brazil. That's my prediction. >> I know you're a big Cricket fan. Are you able to follow Cricket the way you like? >> At god unearthly times the night because they're in Australia, right? >> Oh yeah. >> Yeah. >> I watched the T-20 World Cup, select games of it. Yeah, you know, I'm not rapidly following every single game but the World Cup games, I catch you. >> Yeah, it's good. >> It's good. I mean, I love every sport. American football, soccer. >> That's great. >> You get into basketball now, I mean, I hope the Warriors come back strong. Hey, how about the Warriors Celtics? What do we think? We do it again? >> Well- >> This year. >> I'll tell you what- >> As a Boston Celtics- >> I would love that. I actually still, I have to pay off some folks from Palo Alto office with some bets still. We are seeing unprecedented NBA performance this year. >> Yeah. >> It's amazing. You look at the stats, it's like nothing. I know it's early. Like nothing we've ever seen before. So it's exciting. >> Well, always a pleasure talking to you guys. >> Great to have you on. >> Thanks for having me. >> Thank you. Love the expert analysis. >> Sanjay Poonen. Dave Vellante. Keep it right there. re:Invent 2022, day four. We're winding up in Las Vegas. We'll be right back. You're watching theCUBE, the leader in enterprise and emerging tech coverage. (lighthearted soft music)

(gentle music) >> Good morning, fellow cloud nerds, and welcome back to day four of AWS re:Invent. We are here in fabulous Las Vegas, Nevada. I'm joined by my cohost Paul Gillin. I'm Savannah Peterson. We're on theCUBE. Paul, how you doing? You doing well? >> We're staggering to the conclusion. >> (laughing) It's almost the end then. >> And I say that only talking about my feet. This event is still going strong. The great keynote this morning by Werner Vogels about system architecture and really teaching 70,000 people how to design systems. AWS really taking advantage of this event to educate its customer base and- >> So much education here. >> Yeah, and that was a fantastic sort of cap to the keynotes we've seen this week. >> Yeah, I'm impressed Paul, our first AWS re:Invent. I think we're doing pretty good all things considered. >> Well, we're still alive. >> And our next guest actually looks like he's been sleeping this week, which is remarkable. Please welcome Ayal to the show. Ayal, how you doing today? >> I'm good, I'm good. Thank you for having me. >> It's our pleasure. You're with Anjuna. >> Yes. >> Just in case the audience isn't familiar, what's Anjuna? >> Anjuna is an enterprise security company. We focus in the space of confidential computing. And essentially we enable people to run anything they want in any environment with complete security and privacy. >> Which is a top priority for pretty much every single person here. >> Ayal: That is true. >> Now, confidential computing, I keep hearing that term. >> Yeah, let's go there. >> Is it, I mean, is there a trademark associated with it? Is there a certification? Is the concept or is it actually a set of principles and frameworks? >> Savannah: Give us the scoop. >> Yeah, so confidential computing is essentially a set of technologies that were added to the hardware itself, to the CPU, and now to GPUs by the hardware vendors. So Intel, AMD, Arm, Nvidia AWS with their own hardware solution for this. And essentially what it allows you to do is to run workloads on top of the CPU and the GPU in a way that even if somebody gets full access to the infrastructure, you know, root access, physical access, they're not going to have any access to the data and the code running on top of it. And as you can imagine in cloud environments, this is extremely, extremely (indistinct). >> And this done through encryption? >> It involves encryption. If you go one step deeper, it involves protecting the data while it's running, data and memory, when the application is processing it. Which is always been the missing piece in terms of where you protect data. >> So I got excited when I looked at the show notes because you are serving some of the most notoriously security strict customers in the market. Can you tell us about the Israeli Ministry of Defense? >> Sure. So essentially what we do with the Israel Ministry of Defense and other customers, especially on the on the government side, one of the challenges government has is that they have to, if they want security and privacy in the cloud, they have to use something like a gov cloud. And sometimes that makes sense, but sometimes either the gov cloud is not ready because of legal battles or just it takes time to set it up. In some countries, it's just not going to make financial sense for the clouds to create a gov cloud. So what we do is we enable them to run in the commercial cloud with the security and privacy of a gov cloud. >> Was that, I can imagine, so you took them to the public cloud, correct? >> Ayal: Yes. >> Was that a challenging process? When I think of national security, I can imagine a business transformation like that would be a little nerve-wracking. >> Oh, definitely. It was a long process and they went like, "This is probably one of the best security experts on the planet." And they went extremely deep in making sure that this aligns with what they would be able to do to actually move sensitive data to the commercial cloud. Which, obviously, that the requirements are higher than anything I've ever seen from anybody else. And the fact that they were willing to publicly talk about this and be a public reference for us shows the level of confidence that they have in the underlying technology, in the security and privacy that this allows them to achieve. >> We still hear reservations, particularly from heavily regulated industries, about moving into the cloud. Concerns about security, data ownership, shared responsibility. >> Ayal: Yes. >> Are those real, are those valid? Or is the technology foundation now strong enough that they should not be worried about those things? >> Yeah, this is an excellent question, because the the shared responsibility model, is exactly sort of the core of what this is about. The shared responsibility model essentially means the cloud's, sort of by definition, the cloud is somebody else managing the infrastructure for you, right? And if somebody's managing the infrastructure for you they have full access to what you do on top of that infrastructure. That's almost the definition. And that's always been sort of one of the core security problems that was never solved. Confidential computing solves this. It means that you can use the cloud without the clouds having any access to what you do on top of their infrastructure. And that means that if the clouds get hacked, your data is safe. If an employee of the cloud decides to get access to your data, they can't. They just don't have any access. Or if the government comes to the cloud with a subpoena, the clouds can't give them access to your data, which is obviously very important for European customers and other customers outside of the US. So this is essentially what confidential computing does and it allows to break that shared responsibility model, where you as the customer get full control of your data back. >> Now, do you need the hardware foundation to do that? Or are you solving this problem in software? >> No. So we do need a hardware foundation for this which is now available in every cloud. And it's part of every server CPU that Intel ship, that AMD ship. This is part of almost every data center in AWS. But what we bring to the table at Anjuna, is every time there was a fundamental shift in computer architecture, you needed a software stack on top of it to essentially make it usable. And I think the best last example was VMware, right? But virtualization was extremely powerful technology that nobody was using until VMware built a software stack to make it super simple to virtualize anything. And to some extent that was the birth of the public cloud. We would never have a public cloud without virtualization. We're seeing the same level of shift now with confidential computing on the hardware side. And all the large players are behind this. They're all part of the confidential computing consortium that pushes this. But the challenge customers are running into, is for them to go use this they have to go refactor and rebuild every application. >> Why? >> And nobody's going to go do that. And that's exactly what we help them with. >> Yeah. >> In terms of why, as part of confidential computing, what it essentially means is that the operating system is outside the cross cycle. You, you don't want to cross the operating system because you don't want somebody with root access to have any access to your data. And what this means is every application obviously communicates with the operating system pretty often, right? To send something to the network or some, you know, save something to the file system, which means you have to re-architect your application and break it into two: a confidential piece and a piece that's communicating with the operating system and build some channel for the two sides to communicate. Nobody's going to go do that for every application. We allow you to essentially do something like Anjuna run application and it just runs in a confidential computing environment. No changes. >> Let's talk a little bit more about that. So when we're thinking about, I think we've talked a little bit about it, but I think there's a myth of control when we're talking about on-prem. Everybody thinks that things are more secure. >> Right. >> It's not the case. Tell us how enterprise security changes once when a customer has adopted Anjuna. >> Yeah, so I think you're absolutely right. I think the clouds can put a lot more effort and expertise into bringing security than the data center. But you definitely have this sort of more sense of security in your data center because you own the full stack, right? It's your people, it's your servers, it's your networks in the cloud >> Savannah: It's in your house, so to speak. Yeah. >> Exactly. And the cloud is the third party managing all that for you. And people get very concerned about that, and to some extent for a good reason. Because if a breach happens regardless of whose fault it is, the customer's going to be the one sort of left holding the bag and dealing with the aftermath of the breach. So they're right to be concerned. In terms of what we do, once you run things in confidential computing, you sort of solve the core problem of security. One of the core problems of security has always been when somebody gets access to the infrastructure especially root access to the infrastructure, it's game over. They have access to everything. And a lot of how security's been built is almost like these bandaid solutions to try to solve. Like perimeter security is how do I make sure nobody gets access to the infrastructure if they don't need to, right? All these detection solutions is once they're in the infrastructure, how do I detect that they've done something they shouldn't have? A lot of the vulnerability management is how do I make sure everything is patched? Because if somebody gets access how do I make sure they don't get root access? And then they really get access to everything. And conversation computing solves all of that. It solves the root cause, the root problem. So even if somebody gets root access, even if somebody has full access to the infrastructure, they don't have access to anything, which allows you to one, essentially move anything you want to the public cloud regardless, of the sensitivity of it, but also get rid of a lot of these other sort of bandaid solutions that you use today to try to stop people from getting that access because it doesn't matter anymore. >> Okay. So cyber security is a one and a half trillion dollar industry, growing at over 10% a year. Are you saying that if organizations were to adopt confidential computing universally that industry would not be necessary? >> No, I think a lot of it will have to change with confidential computing. Exactly, like the computer industry changed with virtualization. If you had asked when VMware just got started if the data centers are going to like, "Oh, this is going to happen," I don't think anybody could have foreseen this. But this is exactly what virtualization did. Confidential computing will change the the security industry in a massive way, but it doesn't solve every security problem. What it essentially does is it moves the perimeter from the machine itself, which used to be sort of the smallest atom, to be around the workload. And what happens in the machine doesn't matter anymore. You still need to make sure that your workload is protected. So companies that make sure that you write secure code are still going to be needed. Plus you're going to need security for things like denial of service. Because if somebody runs, you know, gets access to their infrastructure, they can stop you from running but your data is going to be protected. You're not going to need any of these data protection solutions around the box anymore. >> Let's hang out there for a second. Where do you see, I mean what an exciting time to be you, quite frankly, and congratulations on all of your success so far. Where are we going in the next two to five years? >> Yeah, I think with confidential computing the first thing that this is going to enable is essentially moving everything to the public cloud. I think the number one concern with the cloud kind of like you mentioned, is security and privacy. >> Savannah: Right. >> And this essentially eliminates that need. And that's why the clouds are so excited about this. That's why AWS talks about it. And I think Steve Schmidt, the of CISO of Amazon, used to be the CISO of AWS, talks about confidential computing as the future of data security and privacy. And there's a reason why he does that. We've seen other clouds talk about this and push this. That's why the clouds are so excited about this. But even more so again, I think over time this will allow you to essentially remove a lot of the security tools that exist there, kind of reimagine security in a better way. >> Savannah: Clean it up a little bit. Yeah. >> Exactly. And over time, I think it's going to change the world of compute even more because one of the things this allows you to do is the closer you get to the edge, the more security and privacy problems you have. >> Savannah: Right. And so many variables. >> Exactly. And it's basically out there in the wild, and people can get physical access. >> Quite literally a lot of the time, yeah. >> Exactly. And what confidential computing does, it provides that complete security and privacy regardless of even if somebody has physical access, which will allow you to move workloads much closer to the edge or to the edge itself instead of sending everything back to your backend to process things. >> We have interviewed a number of security companies here during this event, and I have to say, confidential computing has never come up. They don't talk about it. Why is that? Is there an awareness problem? >> Savannah: Are they threatened? >> Yeah, so I think the biggest, and to some extent, this is exactly like I kept bringing up VMware. Like VMware's, you can think of Salesforce, when they talked about SaaS, they sort of embedded the concept of SaaS. No other company on the planet was talking about SaaS. They created a new category and now almost everything is SaaS. VMware with virtualization, right? Nobody was using it, and now, almost everything is virtualized. Confidential computing is a new way of doing things. It's basically a kind have to shift the way of how you think about security and how you think about privacy. And this is exactly what we're seeing. I don't expect other security companies to talk about this. And to some extent, one of the things I've realized that we're almost more of an infrastructure company than a security company, because we bake security to be part of the infrastructure. But we're seeing more and more the clouds talk about this. The CPU vendors talk about this. We talk to customers more and more. Like almost every large bank I talk to now has a confidential computing strategy for 2023. This is now becoming part of the mainstream. And yeah, security companies will have to adopt or die if they don't fit into that new world that it is going to create >> This is the new world order, baby, get on the train or get left behind. >> Ayal: Exactly. >> I love it. This is a really fascinating conversation and honestly what you're doing makes so much sense. Yeah, you don't need me to validate your business model, but I will, just for the sake of that. >> Thank you. >> We have a new challenge here at re:Invent on theCUBE where we are looking for your 30 second Instagram reel hot take, thought leadership. What's the biggest theme, key takeaway from the show or experience this year for you? >> Yeah, so for me, obviously focusing on confidential computing. I think this is just going to be similar to how no network was encrypted 10 years ago and today every network is encrypted with TLS and HTTPS. And how five years ago no disc was encrypted, and today every disc is encrypted with disc encryption. The one missing piece is memory. Memory is where data is exposed now. I think within a few years all memory is going to be encrypted and it's just going to change two industries: the security industry as well as the computer industry. >> Paul: Does that include cache memory? >> What's that? >> Does that include cache memory? >> That is encrypting the RAM essentially. So everything, this is the one last place where data is not encrypted, and that's exactly what confidential computing brings to the table. >> Are there any performance concerns with encrypting memory? >> That's a phenomenal question. One of the really nice things about confidential computing is that the heavy lifting is done by the hardware vendors themselves as part of the hardware and not part of the critical path in the CPU. It's very similar to the TLS acceleration cards, if you remember those, which allows us to be extremely, extremely performant. And that's why I think this is going to be for everything. Because every time we had a security solution that had no performance impact and was super simple to use it just became the default, because why wouldn't you use it for everything? >> Ayal, this has been absolutely fascinating. We could talk to you all day. Unfortunately, we're out of time. But really thank you so much for coming on the show. Now, we feel more confident in terms of our confidential computing knowledge and definitely learned a lot. Thank all of you for tuning in to our fantastic four day live stream at AWS re:Invent here in Sin City with Paul Gillin. I'm Savannah Peterson. You're watching theCUBE, the leader in high tech coverage. (gentle music)

(upbeat music) >> Good morning and welcome back to fabulous Las Vegas, Nevada. We're here at AWS re:Invent with wall-to-wall coverage all day long on theCUBE. My name is Savannah Peterson and I am joined this morning by the beautiful Lisa Martin. Lisa, good morning. >> Good morning. Good. >> How you feeling day three? >> Day three is we are going to be shot out of a cannon today. The amount of content coming at you from theCUBE today- >> Get ready, you all. >> Us two gals, is a lot. We're going to have some great conversations. >> And we're starting with a really great one with a Cube Alumni to the max. You've been on the show multiple times. >> John: Yeah. >> Very excited to welcome John, the CMO of Couchbase. Welcome. How you doing this morning? >> Thanks. I'm doing great. Great to be here with you. >> How do you feel about the show so far? What's your pulse? >> The show has been great. I say the energy is great. The traffic at our booth, the conversations that we're having, both with prospective customers and even just partners, right? They're all here. The ecosystem is here >> And everyone's finally back in person and it feels so good. >> John: It does. >> So, we're going to dig in a little bit but just in case the audience isn't familiar, tell us about Couchbase. >> Sure. Couchbase is a publicly traded database company. We have a cloud database platform called Capella which is hosted on AWS and GCP. It is used for building mission-critical applications. So, we have great customers, we're building apps that really matter and are using to drive their business. So, we're very excited about that. 30% of the Fortune 100 are Couchbase customers. >> Nice. Talk a little bit about the AWS relationship. >> Mm-hm. Yeah, so we have a great AWS relationship. In fact, yesterday we announced a deepening of that relationship, a strategic collaboration agreement. We're very excited. It's a multi-year agreement. It's focused on go-to market, from a sales and marketing standpoint. We're going to target, you know, various verticals and, you know, really generate joint business between the two of us. So, it's a deepening of a already strong relationship and we're really excited about that. >> Savannah: Yeah. Go ahead. >> What are some of the industry verticals that you're going to be tackling together? >> Well, gaming for one, right? Manufacturing, the workloads that Couchbase is good for are these mission-critical workloads are ones that are really suited for us to be used with AWS. So, we've done some work with them already in those areas and I'm sure we'll be digging in even deeper. >> That's exciting. Speaking of digging in deeper, tell us a little bit more about Capella. >> Capella. It's a cloud databases services I mentioned. We launched it last October and we are super excited by the uptake, the interest that we're seeing. We have a free 30 day trial, so, you know, people can come and try it and get their hands dirty just getting experience with the product and then, you know, become a customer after that. And we're seeing very strong interest from our existing customer base as well. So, we're really excited about how things are going. >> Talk about Capella and the latest release and how it's really enabling Couchbase to invest deeper into the developer experience. >> Yeah, so, at the end of October, we announced a revamp of our user interface, our user experience for Capella really focused on developers. And what we've done is make it so that it's familiar to developers, right? It's a GitHub-like experience. So, developer comes in, they're very familiar, of course, with GitHub, they are familiar with how the Couchbase Capella interface will work. And so that's something that, you know, we've really invested, in fact, we've invested in developers quite a bit. We announced a Couchbase community hub and a Couchbase ambassadors program, both focused on developers and getting out there and building our community. >> A community is a big topic that we've been talking about at all the conferences this year. We're all back in person, in community. How often are you communicating with your community to get feedback on what that experience should be like? >> Yeah, I mean, we actually have a Discord server, so we're in constant communication. (Savannah laughing) >> Savannah: Yes. (John laughing) 24/7. (laughing) >> Basically, you know, we have staff who's dedicated to making sure that the users on there are getting their answers and giving us feedback on the experience. The ambassadors are somebody who have a really strong relationship, who get early insight and give us feedback before we even release a product. So, it gives us a chance to really test-drive it with core developers and get the insight we need before we get it in the market. >> Yeah. It matters so much. You can build it, but they won't come if it's not fantastic. >> John: Exactly. >> Lisa: Right. >> Let's shift a little bit and talk about customers. How, and price, how do you guys compare? >> Customers and? >> And price, your price performance? >> Price, oh. So, customers, we also announced this week a joint customer Arthrex with AWS. Arthrex is a orthopedics medical devices company and they use our Edge capabilities along with running Couchbase on AWS. So, you think of the kinds of surgeries that orthopedic surgeons do, it's scopes and they are often inside. So, what it does is it collects the data, the video data and all of that on a medical devices and then brings it back to a centralized app for the doctors to use sort of in post when they're actually doing further medical recommendations. >> Savannah: It's so cool. >> So, it's cool, the thing about it is it can work whether it's online or offline, it's one of the reasons that Arthrex selected us because the fact that it can, you know, often sometimes there's not connectivity in the operating room, I'd say deep inside of a hospital. So, these devices work regardless and then when they get connectivity, it sinks back to that centralized service. So, it's one of the main reasons that they selected us. >> That's outstanding. You know, one of the things that John Furrier, you know, John, well, you guys go way back. >> John: Way back. >> He had a sit down with Adam Selensky, oh, about 10 days or so ago. He gets an exclusive with the CEO of AWS every pre re:Invent. And one of the things that Adam said is that the role or the title, data analyst, is going to go away, in that every role will have responsibilities of analyzing data. And I always think of that in terms of operations, marketing, finance, sales, but you just brought up physicians as data analysts in their jobs, right? Probably not, we're thinking about it in that way. >> Yeah. >> But it's so interesting how data is really being democratized. >> John: Yeah. >> And how Couchbase is an enabler of that in an operating room. >> John: Yeah, yeah, yeah. >> That's amazing. >> It's a great story. There's many others and I think, you know, we have embedded operational analytics in Couchbase Capella, and, you know, in our offerings in general. So, what that does is allows us to do real-time, highly personalized applications based on that analytics that are coming in real-time from the data from the applications. And so that's something that's actually driving a highly interactive user experience, one that's very personalized and customized. And that's one of the things that our customers really like about what we do. >> It's fascinating. I never thought about it from a medical device perspective. >> Lisa: No, no. >> John: No. >> My gosh is if doctors don't have enough cognitive burden load. >> John: I know. >> You know, right? Like, they don't need to be a data analyst. I would much rather they were just good at the surgery part. That's a piece of the puzzle I need them to do. Yeah, for sure. That's a fascinating customer example. Can you share any other joint AWS examples with us? >> Joint AW- I mean, there's many in the gaming area where, because Couchbase is memory-first architecture, we deliver very, very interactive user experiences and we're used a lot for session management, user ID management in the gaming space, specifically with AWS. It's an area we've done some joint work already and had a lot of success, you know, with small and large gaming companies. >> Yeah. It looks like you also, according to my notes here, we've got things in travel and hospitality as well. >> Yes. Also Carnival Cruises is a great example. We enable their on-ship, on-board experience, highly customized, everybody wears a device called a medallion, and as they move around the ship, it knows where they are and it's able to provide customized services. You walk up to a bar, you have your favorite drink, it can be hit the bar when you land there. >> I'll take that. >> How about that? (laugh) >> That's outstanding. >> Isn't that great? >> Can we carry that onto the AWS show floor? >> Exactly. >> Or Starbucks order? >> Yeah, yeah. Yes, please. Yes, please. Well, another thing that's so interesting these days, is that every company has to be a data company. Say they have to be a software company. They have to be a data company. You just gave some great examples. Hospitality, gaming, healthcare, where that data democratization has to happen. >> John: Yeah. >> Businesses has to transform. But one of the things that Adam also told John is that CIOs, CEOs are coming to him not wanting to talk about technology but about transformation. >> Yeah. >> Huge topic. >> And that's a journey where every customer is at different levels. >> Yeah. >> How is Couchbase helping businesses transform and where are your customer conversations these days? >> Yeah, yeah, yeah. So, I mean, the transformation of the business is a major topic of conversation. So, we completely agree with that. How Couchbase helps is, you know, in our database, one of the things we have is the SQL engine. And so as people are looking to move and modernize their infrastructure, if they're moving off of, or from like a technology that's principally based on SQL but doesn't give all the flexibility of a JSON database or document database like we do, we actually enable them to get more easily onto our platform so that they can start that transformation. And then it's a, you know, it's a journey of how they want to transform their business and it's really focused on how do they better serve their customers and clients, whether it's internal or external? >> It really matters. I mean, and that ease of use as well as the transformation journey. It takes a long time for people to adapt. So, every piece of that puzzle, every Lego being quicker or easier, more intuitive, like you said, with the user experience, we can tell you're very thoughtful. How does this improve the total cost of ownership for your customers? >> That's one of the things that we announced along with that developer changes, was a new storage engine underneath Couchbase Capella. And it's 10 X more dense storage. And what that means is fewer servers. So, fewer servers is a much better cost of ownership story. That plus just the performance of the platform itself, we find, you know, against competition, we can do things on say six nodes that take 18 nodes for others. >> Lisa: Oh wow. >> And we have a great consolidation story as well because we have, it's a multi-modal database, meaning that it has SQL engine, document database, full tech search, eventing and analytics, all these pieces on one common data layer. So, you can actually consolidate off of other technologies onto one, onto Couchbase, and that actually saves you money. So, that's a great story for us. >> There's got to be a sustainability element to that as well? >> Yeah, I mean it's, obviously, if you're using less, using fewer servers, there's a kind of power consumption aspect of it as well. Absolutely. >> Are you finding that a lot of customers and companies we talk to these days have in their RFPs, they must only work with vendors who have an actual ESG program? Are you finding more customers coming to you saying, how can you help us dial down our carbon emissions? >> John: Yeah. >> Savannah: Great question. >> We've got a sustainability program that we've got to meet, we've got commitments to our customers. >> John: Yeah. >> Is that something that's really now kind of a hard and fast requirement? >> We're hearing it, we're definitely hearing it. I wouldn't say it's, you know, massively pervasive but I would say it's a growing component of, as you said, RFPs. And it's something that we feel like we have a great story for. And so, you know, it's something that helps when we get into those conversations, we can clearly articulate how we can provide that value and how we meet some of those needs that they have. >> Yeah, that's awesome. So, we have a bit of a challenge, new to the show at re:Invent. >> John: Mm-hm. >> Where we are prompting you to give us your 30 second Instagram Reel sizzle highlight. Don't worry, I'm not actually timing you, but your thought leadership hot-take on the most important theme or takeaway from this year's show. >> From the conference here. I would say that, and I think this was talked about a little bit by AWS as well, but the convergence of analytics and operational data, you know, through the applications is one that we're certainly seeing as well. It's the reason we have analytics in our database. But as I walk around and look at it, I see that very much as a common theme as well, in terms of what other vendors are saying and just the conversations we're having. So for me, that's one of the things I think would be a takeaway from this show. >> Yeah. Embedded analytics, real-time, everybody wants to know what's going on, in context. >> Yeah. That's right. >> Right now, not last week, not what we're processing from last month. >> Exactly. >> I mean, right? (cross-talking) >> So, I can react and take advantage or take an action if I have to. >> Exactly. And then deliver that personalized experience that we all expect these days. >> Oh, yes. >> I'll take that medallion- >> It's about the medallion. I was like, okay. >> You up with that, John? >> We'll get right on it. >> Lisa: All right. (laughs) >> About this. So, what's next for Couchbase? >> John: Well- >> I know you got the partnership, you've got all this exciting momentum. >> So, we're excited heading into next year. We're going to continue to innovate on Capella, right? Continue to deliver more value, lean into our developer community that we have. We're investing heavily, not just from a product standpoint but from a company standpoint in terms of, you know, our community meetups and some of those things. We have a big community-focused event coming up in March called Connect, Couchbase Connect. So, that's something that we'll, you know, continue to drive. That'll be a major theme for us next year. Cloud and developers and, you know, continuing to enable that ecosystem. >> Lisa: Excellent. >> I just had a Microsoft moment where I saw you saying, "Cloud developers," on stage. (Lisa and Savannah laughing) >> I'm not going Steve Ballmer on you. (all laughing) >> Pardon. I was trying to get someone to sing yesterday. I was hoping you were my Ballmer dance. Oh, man. Well, this has been a really great way to start the day. John, thank you so much for being on the show with us, seriously. And it's great that you keep coming back. I'm glad we haven't scared you off. (John laughing) >> Never. >> Savannah: We will have you anytime. >> Thank you. >> And thank you all for tuning in for yet another fantastic day of all day live coverage here from AWS re:Invent. We are in Sin City, having a fabulous time with Lisa Martin. I'm Savannah Peterson. This is theCUBE and we are the leader in high-tech technology coverage. (upbeat music) (upbeat music fades)

>> Well, thanks for joining us here on theCUBE. I'm John Walls. We're at Reinvent AWS's big show going on here in Las Vegas at the Venetian. Going to be here all week, so be sure to tune in here to theCUBE as we continue our executive summit sponsored by Accenture today. Joined now by Steve Steuart, who's the worldwide principal on mainframe migration at Go to Market at AWS. Steve, good to see you, sir. >> Nice to meet you. >> Just found out we're neighbors, as a matter of fact, down in northeastern Florida. >> That's right. >> So we'll exchange addresses later, I'm sure. And Joel Rosenberger, who is a global mainframe monetization lead for the Accenture AWS business group. Joel, good to see you. >> Nice to meet you. >> Thanks for joining us here on theCUBE. >> Absolutely. >> All right, so what's up with the mainframe? We're kind of kidding about 64 Corvette's versus 22 Teslas and making that old Corvette. Dress it up, take it out for the street ride. Make it nice and fun. But let's just set the stage here first off for our viewers about mainframe and kind of the status in terms of modernization and getting it up to 22 standards. >> Right, I mean, I think the big thing is that, you know modernization for mainframes is different for every customer based on their drivers and where they want to go. You know, at AWS we like to say transform with AWS, augmentation pattern, hybrid pattern, working coexisting or transform too. So move some of those workloads into the cloud. And it's not that, you know mainframes are fantastic machines, but they are in dire need of modernization with their applications. And that's really the driving force and the business needs to make a decision based on their drivers, what's best fit for them. And we're here to help. >> So how, Joel, go ahead. >> Oh, I was going to say, and we're saying that too is basically the mainframe is a great technology platform but it's the processes around that that not kept up. So making changes to the mainframe applications can take a couple years, for the simplest changes. And so when Steve talks about modernizing with or on the mainframe it's really how do we improve those processes? And from our perspective and companies are really struggling with that right now. >> Yeah, and how do you go about this, because the mainframe is so center, right? It is so integral, right? >> Oh it's center. >> Oh yeah, absolutely. >> Absolutely essential. And yet you're talking about changes being made over a period of time of years. A lot of sensitivity there, right? >> Oh absolutely. >> Lot of complexity there. So how do you start factoring all that in and selling that to somebody that this journey might take you till 2025 to get it done? >> Well it could be a multi-year process. The selling is really the business drivers. You have to, businesses today need to leverage the cloud to be competitive. >> Absolutely. >> Right, that's just a fact. Right? So, how do you transform with modernize in place, or transform over. But it is a transformational change. If you look at the number one drivers is agility. The CEO say, I want this green next week and well we can't get it to you next week. We can get it to you Q2 of next year. Born in the cop companies... >> That's probably not the answer they want to hear. >> No, they don't want hear that. >> That is not the answer they want to hear. >> Our number one issue is that there are CEOs saying that we can't be agile, but mainframes can't be agile, if you develop, adopt DevOps for your mainframe. >> Yep. >> IBM has an offering, we have an offering as well. And so they need to start looking at that. So what are your drivers? Go to market responsiveness, competitive, what are the drivers? And then you make a decision as to where you want to move the workload. >> Joel: Yep. >> Is it hard though, Joel, just because as you know this environment is so dynamic now, right? >> Yep. >> And change is rapid, and I mean like capital R. >> Yep, absolutely. Yep. >> So all of a sudden you set this two/three year trajectory and yet opportunities, solutions, options can vary in year one or year two and all of a sudden this path you had set is going to have to take a left turn instead of a right turn because of a new development. Right? So it's... >> Absolutely, I mean, and that's one of the biggest struggles that people have is with business agility. Exactly what you're saying is the market is changing faster, like Steve said, it might be a year or so before I can deliver that but the market has already changed from that perspective. >> Right. >> And so I think a lot of people are trying to modernize with that. So they're connecting a lot of web properties to mainframes but that causes additional problems. >> Right. >> And those problems are the mainframe now scales unpredictably, because I don't know, how do I predict web traffic and from that perspective, so a lot of people are struggling do I have enough capacity on the mainframe to do that? Cause it's not elastic like the cloud from that perspective. So there's a lot of patterns that have to be reinvented, or already been invented with the cloud and how do we do that with the mainframe now? >> So you could get benefits not waiting three to four years. >> Absolutely. >> You get benefit pretty much immediately by doing augmentation patterns consuming processing on the mainframe, consuming it maybe certain movements, certain workloads, bringing on down quicker. You know, if you're a large estate it'll take you time but you are able to drive that. Part of our assessments is bottom up what you currently have, and what are your business drivers. >> Yep, absolutely. >> What are the big boulder items you need to do and tackle those. And so it's a process that we work together with our customers to start transforming their mainframe. >> Right. >> Yeah I hear about, I'm sorry, go on Joel. >> Yeah, and a key thing on that is a lot of people look at the mainframe is this big monolith. >> John: Right. >> It's basically the this big thing, I don't know what to do with, I don't want to touch because if I touch it I might break it. I don't have people to fix it. And so there's a lot of concern around that, but one of the things like Steve said is how Accenture and AWS work together is figuring out how do I take that monolith, divide it into smaller pieces either through data augmentation, through an analysis, and figure out a roadmap through that application or that monolithic applications and figure out how to move. >> Well that's, how you get an elephant, right? Leverage is one part at a time. >> Exactly, one part at a time. >> It's just one. >> Right, it's just leverage AI, leverage or AI and our platforms and machine learning. All these things are available and you can coexist with that. >> All right, so tell me about technical debt. I read about technical debt and you know, it kind of comes with the territory, >> Right. >> in terms of mainframe. So how do you, first off, you know, how do you define that and then how do you deal with that? How do you make that go away as far as concerns go? >> Well, you know, you have to look at your, for my definition for technical debts is the same thing when my wife says I have to do something in the backyard and I push it, I'll do it next time. Right? So it starts piling up, right? There's a lot of to-dos at the house. >> Absolutely. >> Right, it's the same thing, it's the IT to-dos that you just put off. >> I'll catch up to that some other time. >> Yep. >> And there you are, they keep on... And so next thing you know, you have this, oh my gosh I got all this work I got to do. >> Right. And that's part of the technical debt. And then so you got to look at how does that resolving that meet my needs for the cloud. So leveraging the cloud, if you're under mainframe you have limited solutions for addressing your technical debt. Leveraging the cloud with the mainframe, now you have multiple options for you. to tackle and eliminate your technical debt. So that's one of the benefits of leveraging the cloud for that. >> And I would add on to what Steve said about technical debt. It's exactly that, it's I haven't done that yet, but one of the things that I've seen is there's multiple ways to solve any problem, any programming problem technical problem from that, there's a shortcut way to get it done quickly, >> John: Right. >> that may not be clean and scalable and that. And what happens is, especially on the mainframe over 40 or 50 years, a lot of those shortcuts have been taken. And so it's not even as easy as, it's basically, you think about it, I didn't do it but now my grass is this high, >> John: Right. >> And now I got to do it, type of thing. So it's really about... >> And you can't use a lawnmower >> You can't use a lawnmower so you have to figure out different ways. >> You can't bag it, >> No, no. >> No, no, a whole nother >> Absolutely. >> Right. >> So understanding technical debt and overcoming it is realizing that those shortcuts need to be re-architected, redesigned, modernized, >> All right. >> from that perspective. And you need to take that perspective on. >> So you guys have to be kind of sometimes the bearer of bad news in a way, right? Because they have these, you said monolithic of systems in place that need revised they got to be modernized. >> Yep. >> And they've been kicking that can down the road. We've talked about some big companies for a long time. So they got a lot of baggage on that side and they have to get up to speed. So if, if you were talking to a prospective client, about understanding why it's time to start doing that necessary housekeeping, how do you convince people that this is the time? >> What are your top three absolutely mission critical applications that you have today, right? What is the staff that maintains it? What is the average age of those resources? And what is your succession strategy? >> Joel: Yep. >> It's as simple as that. >> Oh. >> I would add on to that. A lot of times we don't have to convince the customer right now. >> John: Right. >> The customers are coming to us, because what's happened is this whole digital transformation that's happening in the web and all that kind of stuff. Their competitors are already moving off of that. Or have come up with something else. So the business is coming and saying, why can't I move that fast? >> Right. >> And then, like Steve said is those are the reasons why you can't move that fast. So let's address those reasons. >> All right, the born of the cloud company is coming in, but also another driving force that's happening, If you look at a lot of our new customers. Are the digital natives arriving in the C-suites. So the folks that have always known the internet understand the benefits of the cloud, or where there's a new CIO, new CEO. >> Yep. >> And so we're seeing that changing of the guard type scenario. >> Because a lot of those people grew up with a mainframe. >> Right. Right. >> And of the old guard. >> Sure. >> And they're like, well it's worked for the last 30 years, why don't I just keep it working the same way it is. >> And don't we need it to work? >> Yeah >> Right? The way it has been? >> Yeah, exactly. >> Yeah. >> Well, and that's the other key thing, is the core applications. So what has happened with the cloud is over the last you know, 10, 15 years is a lot of the applications that could move moved. Now we're left with the core applications on the mainframe and those are the ones that a multi-billion dollar company, if they get that wrong, they're out business. So there's a lot of scrutiny and a lot of other things. So a lot of the stuff that we're doing now is to help understand that risk and get over that risk. >> And do companies have the expertise in house, to do this? And where do you find it outside? Because it, you know, might not be the sexiest thing to do. >> That's a great question because, you know Steve and I talk about this all the time which is running the mainframe is different than modernizing the mainframe. >> Steve: Right. And so I might have a lot of skills in house to run the mainframe, but how do I figure out to get, to break up that monolith into pieces. >> Steve: Right. How do I figure out, you know, how the best way to put that on AWS? How do I figure that out? You need to leverage people like AWS and Accenture and others to be able to do that. >> This is, there's a psychology to this and more technical, there's more psychological than technical. So you got to find your unicorns. People should have gas in the tank that want to adopt. >> Joel: Yep, absolutely. >> And the ones that don't, then, you know, they're out. You know, nothing like passive aggressive people showing up to help, to really cause havoc. (all laugh) And that's really what you got to kind of focus on. >> Yes. We see that a lot. >> Right. Right. But that's where the managing service comes in too right? >> Absolutely. >> You can get people there. You can, this is a worry they can check the box and move on and get help in that. >> Yeah. AWS, this is an industry first, where you have a managed service within your console to provision tooling to analyze, develop for the mainframe or deploy onto AWS. But the running of it, specific servers that have been you know, optimized for mainframe workloads with your monitoring and security and all those things it's an industry first. I've been in this business 30 years it's fantastic with what I'm seeing over here. >> And do you have any kind of a guess about what share is still out there to be had, in terms of modernizing mainframes, in terms of businesses? I mean, are there still, well, you know it might be hard to put a, to quantify it with a number, but there's still a lot of folks... >> Oh yeah. >> who haven't made that commitment yet. >> Well, they're beginning to, so if you look at, I think, I'm going to throw a number out, I think it's like 80% of the Fortune 100 companies have mainframes. >> Absolutely. >> Is that right? >> So yeah, if you paid your mortgage today, if you used your cell phone today, if you've done any of those things, core stuff is run on mainframe. >> Financial transactions are huge. >> Oh huge, huge, you've got airlines, manufacturing, >> Insurance. >> healthcare. >> John: Right. >> Pretty much everything runs on a mainframe, if you go deep enough in the organization. >> And so that's all, you know people are making those decisions. And what we've done is what I call an earn trust moment. You know, AWS standing up and saying, 'hey we're here to help our customers to move' we're a large organization, we're doing heavy investments in this. We have R&Dand staff, to help our customers transform with or to AWS. >> And we're seeing that resonated in the marketplace. So last year AWS announced the mainframe modernization service Over the last year, we've seen clients, like I said is they're coming to us now. >> Right. >> Saying we want to go mainframe zero, for lack of a better expression. And so we're just seeing a lot of activity. So what AWS did last year has really resonated within the marketplace and changed that dynamic. >> Well, the mainframe ain't dead yet. >> No. >> It isn't. >> It's not going to die. I think there's going to be a different >> Too big, two powerful and too necessary. >> Absolutely. >> Yeah I think we're going to coexist with it and some will leave, so. >> But you still need that same functionality, just somewhere else. >> All right. >> That's right. Well, appreciate the conversation, neighbor. >> Thank you. (all laugh) >> And have a great show. Look forward to seeing you down the road here. >> Thank you very much. >> Thanks John, appreciate it. >> Thanks for joining us here. You are watching theCUBE here at Reinvent 22. And theCUBE, as I remind you is the leader in high tech coverage. (soothing music)

(upbeat music) >> You got it, it's theCUBE. We are in Vegas. This is the Cube's live coverage day one of the full event coverage of AWS reInvent '22 from the Venetian Expo Center. Lisa Martin here with Dave Vellante. We love being in Vegas, Dave. >> Well, you know, this is where Super Cloud sort of was born. >> It is. >> Last year, just about a year ago. Steve Mullaney, CEO of of Aviatrix, you know, kind of helped us think it through. And we got some fun stories around. It's happening, but... >> It is happening. We're going to be talking about Super Cloud guys. >> I guess I just did the intro, Steve Mullaney >> You did my intro, don't do it again. >> Sorry I stole that from you, yeah. >> Steve Mullaney, joined just once again, one of our alumni. Steve, great to have you back on the program. >> Thanks for having me back. >> Dave: It's happening. >> It is happening. >> Dave: We talked about a year ago. Net Studio was right there. >> That was two years. Was that year ago, that was a year ago. >> Dave: It was last year. >> Yeah, I leaned over >> What's happening? >> so it's happening. It's happening. You know what, the thing I noticed what's happening now is the maturity of the cloud, right? So, if you think about this whole journey to cloud that has been, what, AWS 12 years. But really over the last few years is when enterprises have really kind of joined that journey. And three or four years ago, and this is why I came out of retirement and went to Aviatrix, was they all said, okay, now we're going to do cloud. You fast forward now three, four years from now, all of a sudden those five-year plans of evacuating the data center, they got one year left, two year left, and they're going, oh crap, we don't have five years anymore. We're, now the maturity's starting to say, we're starting to put more apps into the cloud. We're starting to put business critical apps like SAP into the cloud. This is not just like the low-hanging fruit anymore. So what's happening now is the business criticality, the scale, the maturity. And they're all now starting to hit a lot of limits that have been put into the CSPs that you never used to hit when you didn't have business critical and you didn't have that scale. They were always there. The rocks were always there. Just it was, you never hit 'em. People are starting to hit 'em now. So what's happening now is people are realizing, and I'm going to jump the gun, you asked me for my bumper sticker. The bumper sticker for Aviatrix is, "Good enough is no longer good enough." Now it's funny, it came in a keynote today, but what we see from our customers is it's time to upgrade the native constructs of networking and network security to be enterprise-grade now. It's no longer good enough to just use the native constructs because of a lack of visibility, the lack of controls, the lack of troubleshooting capabilities, all these things. "I now need enterprise grade networking." >> Let me ask you a question 'cause you got a good historical perspective on the industry. When you think about when Maritz was running VMWare. He was like any app, he said basically we're building a software mainframe. And they kind of did that, right? But then they, you know, hit the issue with scale, right? And they can't replicate the cloud. Are there things that we can draw from that experience and apply that to the cloud? What's the same, what's different? >> Oh yeah. So, 1992, do you remember what happened in 1992? I do this, weird German software company called SAP >> Yeah, R3. announced a release as R/3. Which was their first three-tier client-server application of SAP. Before that it ran on mainframes, TCP/IP. Remember that Protocol War? Guess what happened post-1992, everybody goes up like this. Infrastructure completely changes. Cisco, EMC, you name it, builds out these PCE client-server architectures. The WAN changes, MPLS, the campus, everything's home running back to that data center running SAP. That was the last 30 years ago. Great transformation of SAP. They've did it again. It's called S/4Hana. And now it's running and people are switching to S/4Hana and they're moving to the cloud. It's just starting. And that is going to alter how you build infrastructure. And so when you have that, being able to troubleshoot in hours versus minutes is a big deal. This is business critical, millions of dollars. This is not fun and games. So again, back to my, what was good enough for the last three or four years for enterprises no longer good enough, now I'm running business critical apps like SAP, and it's going to completely change infrastructure. That's happening in the cloud right now. And that's obviously a significant seismic shift, but what are some of the barriers that customers have been able to eliminate in order to get there? Or is it just good enough isn't good enough anymore? >> Barriers in terms of, well, I mean >> Lisa: The adoption. Yeah well, I mean, I think it's all the things that they go to cloud is, you know, the complexity, really, it's the agility, right? So the barrier that they have to get over is how do I keep the developer happy because the developer went to the cloud in the first place, why? Swipe the credit card because IT wasn't doing their job, 'cause every time I asked them for something, they said no. So I went around 'em. We need that. That's what they have to overcome in the move to the cloud. That is the obstacle is how do I deliver that visibility, that control, the enterprise, great functionality, but yet give the developer what they want. Because the minute I stop giving them that swipe the card operational model, what do you think they're going to do? They're going to go around me again and I can't, and the enterprise can't have that. >> That's a cultural shift. >> That's the main barrier they've got to overcome. >> Let me ask you another question. Is what we think of as mission critical, the definition changing? I mean, you mentioned SAP, obviously that's mission critical for operations, but you're also seeing new applications being developed in the cloud. >> I would say anything that's, I call business critical, same thing, but it's, business critical is internal to me, like SAP, but also anything customer-facing. That's business critical to me. If that app goes down or it has a problem, I'm not collecting revenue. So, you know, back 30 years ago, we didn't have a lot of customer-facing apps, right? It really was just SAP. I mean there wasn't a heck of a lot of cust- There were customer-facing things. But you didn't have all the digitalization that we have now, like the digital economy, where that's where the real explosion has come, is you think about all the customer-facing applications. And now every enterprise is what? A technology, digital company with a customer-facing and you're trying to get closer and closer to who? The consumer. >> Yeah, self-service. >> Self-service, B2C, everybody wants to do that. Get out of the middle man. And those are business critical applications for people. >> So what's needed under the covers to make all this happen? Give us a little double click on where you guys fit. >> You need consistent architecture. Obviously not just for one cloud, but for any cloud. But even within one cloud, forget multicloud, it gets worst with multicloud. You need a consistent architecture, right? That is automated, that is as code. I can't have the human involved. These are all, this is the API generation, you've got to be able to use automation, Terraform. And all the way from the application development platform you know, through Jenkins and all other software, through CICD pipeline and Terraform, when you, when that developer says, I want infrastructure, it has to go build that infrastructure in real time. And then when it says, I don't need it anymore it's got to take it away. And you cannot have a human involved in that process. That's what's completely changed. And that's what's giving the agility. And that's kind of a cloud model, right? Use software. >> Well, okay, so isn't that what serverless does, right? >> That's part of it. Absolutely. >> But I might still want control sometimes over the runtime if I'm running those mission critical applications. Everything in enterprise is a heterogeneous thing. It's like people, people say, well there's going to, the people going to repatriate back to on-prem, they are not repatriating back to on-prem. >> We were just talking about that, I'm like- >> Steve: It's not going to happen, right? >> It's a myth, it's a myth. >> And there's things that maybe shouldn't have ever gone into the cloud, I get that. Look, do people still have mainframes? Of course. There's certain things that you just, doesn't make sense to move to the new generation. There were things, certain applications that are very static, they weren't dynamic. You know what, keeping it on-prem it's, probably makes sense. So some of those things maybe will go back, but they never should have gone. But we are not repatriating ever, you know, that's not going to happen. >> No I agree. I mean, you know, there was an interesting paper by Andreessen, >> Yeah. >> But, I mean- >> Steve: Yeah it was a little self-serving for some company that need more funding, yeah. You look at the numbers. >> Steve: Yeah. >> It tells the story. It's just not happening. >> No. And the reason is, it's that agility, right? And so that's what people, I would say that what you need to do is, and in order to get that agility, you have to have that consistency. You have to have automation, you have to get these people out of the way. You have to use software, right? So it's that you have that swipe the card operational model for the developers. They don't want to hear the word no. >> Lisa: Right. >> What do you think is going to happen with AWS? Because we heard, I don't know if you heard Selipsky's keynote this morning, but you've probably heard the hallway talk. >> Steve: I did, yeah. >> Okay. You did. So, you know, connecting the dots, you know doubling down on all the primitives, that we expected. We kind of expected more of the higher level stuff, which really didn't see much of that, a little bit. >> Steve: Yeah. So, you know, there's a whole thing about, okay, does the cloud get commoditized? Does it not? I think the secret weapon's the ecosystem, right? Because they're able to sell through with guys like you. Make great margins on that. >> Steve: Yeah, well, yeah. >> What are your thoughts though on the future of AWS? >> IAS is going to get commoditized. So this is the fallacy that a lot of the CSPs have, is they thought that they were going to commoditize enterprise. It never happens that way. What's going to happen is infrastructure as a service, the lower level, which is why you see all the CSPs talking about what? Oracle Cloud, industry cloud. >> Well, sure, absolutely, yeah. >> We got to get to the apps, we got to get to SAP, we got to get to all that, because that's not going to get commoditized, right. But all the infrastructural service where AWS is king that is going to get commoditized, absolutely. >> Okay, so, but historically, you know Cisco's still got 60% plus gross margins. EMC always had good margin. How pure is the lone survivor in Flash? They got 70% gross margins. So infrastructure actually has always been a pretty good business. >> Yeah that's true. But it's a hell of a lot easier, particularly with people like Aviatrix and others that are building these common architectural things that create simplicity and abstract the way the complexities of underneath such that we allow your network to run an AWS, Azure, Google, Oracle, whatever, exactly the same. So it makes it a hell of a lot easier >> Dave: Super cloud. >> to go move. >> But I want to tap your brain because you have a good perspective of this because servers used to be a great margin business too on-prem and now it's not. It's a low margin business 'cause all the margin went to Intel. >> Yeah. But the cloud guys, you know, AWS in particular, makes a ton of dough on servers, so, or compute. So it's going to be interesting to see over time if that gets com- that's why they're going so hard after silicon. >> I think if they can, I think if you can capture the workload. So AWS and everyone else, as another example, this SAP, they call that a gravity workload. You know what gravity workload is? It's a black hole. It drags everything else with it. If you get SAP or Oracle or a mainframe app, it ain't going anywhere. And then what's going to happen is all your other apps are going to follow it. So that's what they're all going to fight for, is type of app. >> You said something earlier about, forget multicloud, for a moment, but, that idea of the super cloud, this abstraction layer, I mean, is that a real business value for customers other than, oh I got all these clouds, I need 'em to work together. You know, from your perspective from Aviatrix perspective, is it an opportunity for you to build on top of that? Or are you just looking at, look, I'm going to do really good work in AWS, in Azure? Now we're making the same experience. >> I hear this every single day from our customers is they look and they say, good enough isn't good enough. I've now hit the point, I'm hitting route limitations. I'm hitting, I'm doing things manually, and that's fine when I don't have that many applications or I don't have mission critical. The dogs are eating the dog food, we're going into the cloud and they're looking and then saying this is not an operational model for me. I've hit the point where I can't keep doing this, I can't throw bodies at this, I need software. And that's the opportunity for us, is they look and they say, I'm doing it in one cloud, but, and there's zero chance I'm going to be able to figure that out in the two or three other clouds. Every enterprise I talk to says multicloud is inevitable. Whether they're in it now, they all know they're going to go, because it's the business units that demand it. It's not the IT teams that demand it, it's the line of business that says, I like GCP for this reason. >> The driver's functionality that they're getting. >> It's the app teams that say, I have this service and GCP's better at it than AWS. >> Yeah, so it's not so much a cost game or the end all coffee mug, right? >> No, no. >> Google does this better than Microsoft, or better than- >> If you asked an IT person, they would rather not have multicloud. They actually tried to fight it. No, why would you want to support four clouds when you could support one right? That's insane. >> Dave and Lisa: Right. If they didn't have a choice and, and so it, the decision was made without them, and actually they weren't even notified until day before. They said, oh, good news, we're going to GCP tomorrow. Well, why wasn't I notified? Well, we're notifying you now. >> Yeah, you would've said, no. >> Steve: This is cloud bottle, let's go. >> Super cloud again. Did you see the Berkeley paper, sky computing I think they call it? Down at Berkeley, yep Dave Linthicum from Deloitte. He's talking about, I think he calls it meta cloud. It's happening. >> Yeah, yeah, yeah. >> It's happening. >> No, and because customers, customers want that. They... >> And talk about some customer example or two that you think really articulates the value of why it's happening and the outcomes that it's generating. >> I mean, I was just talking to Lamb Weston last night. So we had a reception, Lamb Weston, huge, frozen potatoes. They serve like, I dunno, some ungodly percentage of all the french fries to all the fast food. It's unbelievable what they do. Do you know, they have special chemicals they put on the french fries. So when you get your DoorDash, they stay crispy longer. They've invented that patented it. But anyway, it's all these businesses you've never heard of and they do all the, and again, they're moving to SAP or they're actually SAP in the cloud, they're one of the first ones. They did it through Accenture. They're pulling it back off from Accenture. They're not happy with the service they're getting. They're going to use us for their networking and network security because they're going to get that visibility and control back. And they're going to repatriate it back from a managed service and bring it back and run it in-house. And the SAP basis engineers want it to happen because they see the visibility and control that the infrastructure guy's going to get because of us, which leads to, all they care about is uptime and performance. That's it. And they're going to say the infrastructure team's going to lead to better uptime and better performance if it's running on Aviatrix. >> And business performance and uptime, business critical >> That is the business. That is the business. >> It is. So what are some of the things next coming down the pike from Aviatrix? Any secret sauce you can share? >> Lot of secrets. So, two secrets. One, the next thing people really want to do, embedded network security into the network. We've kind of talked about this. You're going to be seeing some things from us. Where does network security belong? In the network. Embedded in the fabric of the network, not as this dumb device called the next-gen firewall that you steer traffic to. It has to be into the fabric of what we do, what we call airspace. You're going to see us talk about that. And then the next thing, back to the maturity of the cloud, as they build out the core, guess what they're doing? It's this thing called edge, Dave, right? And guess what they're going to do? It's not about connecting the cloud to the edge to the cloud with dumb things like SD-WAN, right? Or SaaS. It's actually the other way around. Go into the cloud, turn around, look out at the edge and say, how do I extend the cloud out to the edge, and make it look like a VPC. That's what people are doing. Why, 'cause I want the operational model. I want all the things that I can do in the cloud out at the edge. And everyone knows it's been in networking. I've been in networking for 37 years. He who wins the core does what? Wins the edge, 'cause that's what happens. You do it first in the core and then you want one architecture, one common architecture, one consistent way of doing everything. And that's going to go out to the edge and it's going to look like a VPC from an operational model. >> And Amazon's going to support that, no doubt. >> Yeah, I mean every, you know, every, and then it's just how do you want to go do that? And us as the networking and network security provider, we're getting dragged to the edge by our customer. Because you're my networking provider. And that means, end to end. And they're trying to drag us into on-prem too, yeah. >> Lot's going on, you're going to have to come back- >> Because they want one networking vendor. >> But wait, and you say what? >> We will never do like switches and any of the keep Arista, the Cisco, and all that kind of stuff. But we will start sucking in net flow. We will start doing, from an operational perspective, we will integrate a lot of the things that are happening in on-prem into our- >> No halfway house. >> Copilot. >> No halfway house, no two architectures. But you'll take the data in. >> You want one architecture. >> Yeah. >> Yeah, totally. >> Right play. >> Amazing stuff. >> And he who wins the core, guess what's more strategic to them? What's more strategic on-prem or cloud? Cloud. >> It flipped three years ago. >> Dave: Yeah. >> So he who wins in the clouds going to win everywhere. >> Got it, We'll keep our eyes on that. >> Steve: Cause and effect. >> Thank you so much for joining us. We've got your bumper sticker already. It's been a great pleasure having you on the program. You got to come back, there's so, we've- >> You posting the bumper sticker somewhere? >> Lisa: It's going to be our Instagram. >> Oh really, okay. >> And an Instagram sto- This is new for you guys. Always coming up with new ideas. >> Raising the bar. >> It is, it is. >> Me advance, I mean, come on. >> I love it. >> All right, for our guest Steve Mullaney and Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live enterprise and emerging tech coverage.

>>Hello everyone. Welcome to the Cubes Live here in Dallas, Texas. I'm John Ferer, host of the Cube, Three days of wall to wall coverage. Of course, we've got the three fabulous guests here, myself, Savannah, Peterson. S look wonderful. >>Thank you. Jong on. I, I feel lucky to play the part here with my 10 gallon hat. >>Dave Nicholson, who's the analyst uncovering all the Dell Supercomputing, hpe all the technology is changing the game. Dave, you look great. Thanks for coming on. >>Thanks, John. I appreciate >>It. All right, so, so, so you look good. So we're in Dallas, Texas is a trade show conference. I don't know what you'd call this these days, but thousands of booths are here. What's the take here? Why supercomputing 22? What's the big deal? >>Well, the big deal is dramatic incremental progress in terms of supercomputing capability. So what this conference represents is the leading edge in what it can deliver to the world. We're talking about scale that is impossible to comprehend with the human brain, but you can toss out facts and figures like performance measured in ex flops, millions of CPU cores working together, thousands of kilowatts of power required to power these systems. And I think what makes this, what makes this show unique is that it's not just a bunch of vendors, but it's academia. It's PhD candidates coming and looking for companies that they might work with. So it's a very, very different vibe here. >>Savannah, we were talking last night before we were setting up our agenda for it to drill down on this week. And you know, you were, by the way, that looks great. I mean, I wish I had one. >>We'll get you one by the end of the show, >>John. Don't worry. You know, Texas is always big in Texas and that's the, the thing here, but Supercomputing seems like that had a lull for a while. Yeah, it seems like it's gonna explode and you get a chance to review the papers, take a look at it. You, you're a, I won't say closet hardware nerd, but that's your roots. >>Yeah, yeah. Very openly hardware nerd. And, and I'm excited because I, we saw a lot of hype around quantum and around AI five, 10 years ago, but we weren't seeing the application at scale and we also weren't seeing, quite frankly, the hardware wasn't ready to power these types of endeavors at scale. Whereas now, you know, we've got, we've got air cooling, we've got liquid cooling, we've got multiple GPU's. Dell was just showing me all eight of theirs that they put in their beautiful million dollar piece of equipment, which is extremely impressive for folks to run complex calculations. And, but what I'm excited about with all the, I love when we fuse business and academia together, I think that that doesn't happen very often. I've been impressed. I mean, when I walked in today, right away, I'm sure y'all can't see this at home just yet, but we'll try and give you a feel over the course of the next few days. This conference is huge. This >>Is, yeah, it is >>Way bigger than I was expecting, You know, a lot larger than where we just were in Detroit. And, and I love it because we've got the people that are literally inventing the calculations that will determine a lot of our future from sequencing our genome to powering our weather forecasting, as well as all of the companies that create the hardware and the software that's gonna actually support that. Those algorithms and >>Those, and, and the science and the engineering involved has just been going on since 1988. This conference, this trade show going on since 1988, which is, it, it passes the test of time and now the future with all the new use cases emerging from the compute and supercomputing architectures out there, it's from cradle to grave. If you're, if you're in this business, you, you're in school all the way through the industry, it doesn't seem to stop that, that university student side of it. I mean that whole student section here. So you don't see that very often in some of these tech shows, like from students to boardroom. >>Yeah. I actually brought the super computer from 1988 with me in my pocket. And I'm not sure that I'm even joking. I this may have as much processing power, certainly as much storage with one terabyte on board. I sprung for the one terabyte folks. But it is mind boggling the amount of compute power we're, we're talking about. When you dig below the surface, which we'll be doing in the coming days, you see things like leaping from P C I E, you know, gen four to gen five, and the increase that that gives us in, in terms of capabilities for plugging into the motherboard and accessing the CPU complex and on and on and on. But, but you know, something Savannah alluded to, we're talking about the leading edge of what is possible from a humanity perspective. 1%. And, and so I'd like to get into, you know, as we're we're talking to some of the experts that we'll get a chance to talk to, I'd like to get their view on what the future holds and whether we can simply grow through quantitative increases in compute power, or if the real promise is out there in the land of quantum computing, are we all sort of hanging our hats, our large 10 gallon hats? >>If that's yes. Our hats, if we're hanging our hats on that, that that's when truly we'll be able to tease insight out of chaos. I'd like to hear from some of the real experts on that subject. >>I'm glad you brought that up, cuz I'm personally pretty pumped about quantum computing, but I've seen it sit in this hype stage for quite a while and I'm ready for the application. So I'm curious to hear >>What our experts, That's an awesome, that would be, I think that would be an awesome bumper sticker. Frankly. Savannah, I'm pumped, I'm pumped about quantum computing. Who is this person? Who is this person? >>I wanna see it first. Did someone show me it? >>Yeah, yeah. 400 qubits I think was the latest IBM announcement, which, which means something. I'll pretend like I completely understand what it means. >>Tell us what that means, David. >>Well, well, so, so Savannah, let me man explain it to you. Yeah, >>Let's >>Hear it. So, so it's basically, it's, you know, in conventional computing you can either, you can either be on or off zero or one in quantum computing, you can be both, neither or all of the above. That's, that's, that's, that's the depth to which I can go. I >>Like that. That was actually a succinct, as humanly possible >>Really sounds like a Ponzi scheme to me. I, I'm not sure if I, >>Well, let's get into some of the thoughts that you guys have on some of the papers. We saw Savannah and Dave, your perspective on this whole next level kind of expansion with supercomputing and super cloud and super apps will do for this next gen. What use cases are kind of shining out of this, because, you know, it used to be you were limited by how much gear you had stacked up, how big the server could be, the supercomputer. Now you've got large scale cloud computing, you got the ability to have different subsystems like advances in networking. So you're seeing a new architectural, almost bigger. Super computing isn't just a machine, it's a collection of machines, It's a collection of Yeah. Of other stuff. What's your thoughts on these, this architecture and then the use cases that are gonna emerge that were not getable before? >>So in the past, you, you talk about, you know, 1988 and, and you know, let's say a decade ago, the race was to assemble enough compute power to be able to do things quickly enough to be practical. So we knew that if we applied software to hardware, we could get an answer to a problem because we were asking very, very specific questions. And how quickly we got the answer would determine whether it was practical to pursue it or not. So if something took a day instead of a month, okay, fantastic. But now we've reached this critical mass. You could argue when that happened, but definitely I think we're there where things like artificial intelligence and machine learning are the core of what we're doing. We're not just simply asking systems to deliver defined answers. We're asking them to learn from their experiences, starts getting a little spooky, and we're asking them to tease insights out in a way that we haven't figured out. >>So we're saying give us the insight. We're not telling the system specifically how to give us that insight. So I think that's, that's the fundamental difference that's the frontier, is, you know, you're gonna hear a lot about AI and ml and then if you retreat back a bit from Supercomputing, you're in the realm of high performance computing, which is sort of junior version of supercomputing. It's instead of the billion dollar system, it's the system that, you know, schlubs like, like, like, like Facebook or AWS might be able to afford, you know, maybe a hundred million dollars for a system casual, just, just sort of casual kind of thing next to the coffee table in the living room. But I think that's really gonna be the talk. So that's a huge tent when you talk about AI and ml. Yeah, >>I I, I totally agree. We're having some of the conversations that we've had for a long time about AI and bias. I saw a lot of the papers were looking at that. I think that's what's gonna be really interesting to me, what's most exciting about this is how are we pulling together all of this on a global scale. So I'm excited to see how supercomputing impacts climate change, our ability to monitor environmental conditions around the globe and different governments and bodies can all combine. And all of this information can be going into a central brain and learning from it and figuring out how we can make the world a better place. We're learning about the body. There's a lot of people doing molecular biology and sequencing of the genome here. We've got, there's, there's, It's just, it's very, I I don't think a lot of people realize that supercomputing pretty much touches every aspect of our >>Lives. I mean, we've had it, we've had it for a while. I think cloud computing took a lot of the attention, given that that brought in massive capabilities, a lot of agility. And I think what's interesting here at this show, if you look at, you know, what's going on from the guess, like I said, from the dorm room to the boardroom, everyone's here, but you look at what's actually going on above the hardware, CNCF is here. They have a booth, the whole cloud native software business. It's gonna be interesting to see how the software business takes advantage of totally. How these architectures, because let's face it, I've never heard a developer pointer say, I wanna run on slower hardware. So no one wants that. So now if you abstract away the hardware, as we know with, with cloud computing and DevOps cloud on premises and Edge, David, this is like, this is again, nirvana for the industry because you want, it's an exciting thing, the fastest possible compute system for the software. >>Yeah, yeah. >>I I, at the end of the day, that's what we're talking >>About. So I asked, I asked the, the gift question to my Wharton students this morning on a call, and I, you know, I asked specifically if, if I could give you something that was the result of super computing's amazing nature, what would it be? Would it be personalized therapeutics in healthcare? Would it be something related to climate? Being able to figure out exactly what we can do. There's a whole range of possibilities. And what's interesting is >>What were some of the answers? >>So, so, so a lot of the answers, a lot of the answers came down to, to two categories and it was really, it was healthcare and climate. Yeah. A lot of, a lot of understanding and of course, and of course a lot of jokes about how eventually supercomputers will determine that. The problem is people, >>It's people. Yeah, no. So I knew you were headed there, >>But >>Don't people just want custom jeans? Yeah. >>Or, well, so one of the, one of the good ones though was, >>Was also that >>While we're >>Here, a person from a company who shall not be named said, oh, advertising, it was the, it was the what if you could predict with a high degree of certainty that when you sent someone an email saying, Hey, do you wanna buy this? They would say, Well, yeah, I do. Dramatically lowering the cost of acquisition for an individual customer as an example. Those are the kinds of breakthroughs that will transform how we live. Because all of a sudden, industries are completely disrupted, disrupted, not necessarily directly related to supercomputing, but you think about automating the entire fleet of, of, of trucks in, in North America. What does that do to people who currently drive those trucks? Yeah, so there are, there are societal questions at hand that I don't necessarily know the academics are, are, are considering when they're thinking what's possible. >>Well, I think, I think the point about the ad thing brings up the whole cultural shift that's going on from the old generation of, Hey, let's use our best minds in the industry to figure out how to place an ad at the right place in the right pixel, at the right time. Versus solving real problems like climate change our, you know, culture and society and get us getting along as a country and world water sustainability fires in California. Yeah, I mean, come on. >>There's a lot. So I, I gotta say, I was curious when you were playing with your pocket computer there and talking about the terabyte that you have inside. So back in 1988 when Supercomputing started, the first show was in Orlando. It was actually the same four days that we're here right now. I was born in 1988 if we're just talking about how great 1988 is. And so I guess I, >>I was born, So were we Savannah? So were we >>The era of, I think I was in third grade at that time. >>We won't tell, we won't say what you told me earlier about 1988 for you. But that said, so 1988 was when Steve Jobs released the next computer. He was out of Apple at that time. Yeah, that's right. >>Eight >>Megabytes of Ram. >>It's called the Cube. I think >>It's respectable. That's all it was called. It was, it was, it was, it was the cube, which is pretty, pretty exciting. But when we were looking at, yeah, on the supercomputing side, your phone would've been about, is a capable, >>So where will we be in 20 years? It's amazing >>What we gonna, >>Will our holograms be here instead of us physically sitting, sitting at the table? I don't know. >>Well, it's gonna be very interesting to see how the global ecosystem evolves. It used to be very nationalistic culture with computing. I think, I think we're gonna see global, you know, flattening of culture relative to computing. I think space will be a, a massive hopeful, massive discussion. I think software and automation will be at levels we don't even see. So I think software, to me, I'm looking at, that's the enablement of this supercomputing show. In terms of the next five years, what are they gonna do to enable more faster intelligent horsepower? And, and what does that look like? Is it, it used to be simple processor, more processors, more threads, multicores, and then stuff around it. I think this is where I think it's gonna shift to more network computing, network processing, edge latency, physics is involved. I mean, every, everything you can squeeze out of the physics will be Yeah. Interesting to watch. Well, when >>We, when we, when we peel back the cover on the actual pieces of hardware that are driving this revolution, parallelizing, you know, of workloads is critical to this. It's what super computing consists of. There's no such thing as a supercomputer sitting by itself on a table. Even the million dollar system from Dell, which is crazy when you hear Dell and million dollar system. >>And it's still there too, >>Right? Just, just hanging out. Yeah. But, but it's all about the interconnect. When you want to take advantage of parallel processing, you have to have software that can leverage all of the resources and connectivity becomes increasingly important. I think that's gonna be a thread that we're gonna see throughout the next few days with the, with the, you know, the motherboards, for lack of a lack of a better term, allowing faster access to memory, faster access to cpu, gpu, dpu, networking, storage devices, plugging in those all work together. But increasingly it's that connectivity layer that's critically important. Questions of InfiniBand versus ethernet. Our DMA over converged ethernet as an example, a lot of these architectural decisions are gonna be based on power cooling, dead city. So lot of details behind the scenes to make the magic happen. I >>Think the power is gonna be, you know, thinking 20 years out, hopefully everything here is powered sustainably 20 years from now because power pull, I mean these, the more exciting things going on in your supercomputer. The power suck is massive. That when we were talking to Dell, they were saying that's one of the biggest problems, >>Concerns, that's gonna their customers and that's gonna play into sustainability. So a lot of great guests, we got folks from Dell and the industry, a lot of the manufacturers, a lot of the hardware software experts gonna come on and share what's going on. You know, we did a, we did a post why hardware matters a few months ago, Dave. Everyone's like, well it does now more than ever. So we're gonna get into it here at Supercomputing 22, where the hardware matters. Faster power, as we say for the applications. Mr. Cube, moving back with more live coverage. Stay with us back.

>>Hey guys. Welcome back to Detroit, Michigan. Lisa Martin and John Furrier here live with the cube at Coan Cloud Native Con North America. John, it's been a great day. This is day one of our coverage of three days of coverage. Kubernetes is growing up. Yeah, it's maturing. >>Yeah. We got three days of wall to wall coverage, all about Kubernetes. We about security, large scale, cloud native at scale. That's the big focus. This next segment's gonna be really awesome. You have a fast growing private company and a practitioner, big name, blue chip practitioner, building out next NextGen Cloud first, transforming, then building out the next level. This is classic of what we call super cloud-like, like interview. It's gonna be great. I'm looking forward >>To this anytime we can talk about Super Cloud. All right, please welcome back. One of our alumni, Bani is here, the CEO of Rafe. Great to see you Santos. Ula also joins us, the global head of Cloud SRE at Mass Mutual. Ge. Great to have you on the program. Thanks >>For having us. Thank you for having me. >>So Steve, you've been on the queue many times. You were on just recently with the momentum that that's around us today with the maturation of Kubernetes, the collaboration of the community, the recognition of the community. What are some of the things that you're excited about with on, on day one of the show? >>Wow, so many new companies. I mean, there are companies that I don't know who are here. And I, I, I live in this industry and I'm seeing companies that I don't know, which is a good thing. I mean, it means that the, the community's growing. But at the same time, I'm also seeing another thing, which is I have met more enterprise representatives at this show than other coupons. Like when we hung out at, you know, in Valencia for example, or even, you know, other places. It hasn't been this many people, which means, and this is, this is a good thing that enterprises are now taking Kubernetes seriously. It's not a toy. It's not just for developers. It's enterprises who are now investing in Kubernetes as a foundational component, right. For their applications going forward. And that to me is very, very good. >>Definitely becoming foundational. >>Yep. Well, you guys got a great traction. We had many interviews at the Cube and you got a practitioner here with you. You guys are both pioneering kind of what I call the next gen cloud. First you gotta get through gen one, which you guys done at Mass Mutual, extremely well, take us through the story of your transformation. Cause you're on the, at the front end now of that next inflection point. But take us through how you got here. You had a lot of transformation success at Mass Mutual. >>So I was actually talking about this topic few, few minutes back, right? And, and the whole cloud journey in big companies, large financial institutions, healthcare industry or, or our insurance sector. It takes generations of leadership to get, to get to that perfection level. And, and ideally the, the, the cloud for strategy starts in, and then, and then how do you, how do you standardize and optimize cloud, right? You know, that that's, that's the second gen altogether. And then operationalization of the cloud. And especially if, you know, if you're talking about Kubernetes, you know, in the traditional world, you know, almost every company is running middleware and their applications in middleware. And then containerization is a topic that come, that came in. And docker is, is you know, basically the runtime containerization. So that came in first and from Docker, you know, eventually when companies started adopting Docker, Docker Swarm is one of the technologies that they adopted. And eventually when, when, when we were taking it to a more complicated application implementations or modernization efforts, that's when Kubernetes played a key role. And, and Hasi was pointing out, you know, like you never saw so many companies working on Kubernetes. So that should tell you one story, right? How fast Kubernetes is growing and how important it is for your cloud strategy. So, >>And your success now, and what are you thinking about now? What's on your agenda now as you look forward? What's on your plate? What are you guys doing right now? >>So we are, we are past the stage of, you know, proof of concepts, proof of technologies, pilot implementations. We are actually playing it, you know, the real game now. So in the past I used the quote, you know, like, hello world to real world. So we are actually playing in the real world, not, not in the hello world anymore. Now, now this is where the real time challenges will, will pop up, right? So if you're talking about standardizing it and then optimizing the cloud and how do you put your governance structure in place? How do you make sure your regulations are met? You know, the, the, the demands that come out of regulations are met and, and how, how are you going to scale it and, and, and while scaling, however you wanna to keep up with all the governance and regulations that come with it. So we are in that stage today. >>Has Steve talked about, you talked about the great evolution of what's going on at Mass Mutual has talked a little bit about who, you mentioned one of the things that's surprising you about this Coan and Detroit is that you're seeing a lot more enterprise folks here who, who's deciding in the organization and your customer conversations, Who are the deci decision makers in terms of adoption of Kubernetes these days? Is that elevating? >>Hmm. Well this guy, >>It's usually, you know, one of the things I'm seeing here, and John and I have talked about this in the past, this idea of a platform organization and enterprises. So consistently what I'm seeing is, you know, somebody, a cto, CIO level, you know, individual is making a determin decision. I have multiple internal buss who are now modernizing applications. They're individually investing in DevOps. And this is not a good investment for my business. I'm going to centralize some of this capability so that we can all benefit together. And that team is essentially a platform organization and they're making Kubernetes a shared services platform so that everybody else can come and, and, and sort of, you know, consume it. So what that means to us is our customer is a platform organization and their customer is a developer. So we have to make two constituencies successful. Our customer who's providing a multi-tenant platform, and then their customer who's a developer, both have to be happy. If you don't solve for both, you know, constituencies, you're not gonna be >>Successful. You're targeting the builder of the infrastructure and the consumer of that infrastructure. >>Yes sir. It has to be both. Exactly. Right. Right. So, so that look, honestly, that it, it, you know, it takes iterations to figure these things out, right? But this is a consistent theme that I am seeing. In fact, what I would argue now is that every enterprise should be really stepping back and thinking about what is my platform strategy. Cuz if you don't have a platform strategy, you're gonna have a bunch of different teams who are doing different things and some will be successful and look, some will not be. And that is not good for business. >>Yeah. And, and stage, I wanna get to you, you mentioned that your transformation was what you look forward and your title, global head of cloud sre. Okay, so sre, we all know came from Google, right? Everyone wants to be like Google, but no one wants to be like Google, right? And no one is Google, Google's a unique thing. It's only one Google. But they had the dynamic and the power dynamic of one person to large scale set of servers or infrastructure. But concept is, is, is can be portable, but, but the situation isn't. So board became Kubernetes, that's inside baseball. So you're doing essentially what Google did at their scale you're doing for Mass Mutual. That's kind of what's happening. Is that kind of how I see it? And you guys are playing in there partnering. >>So I I totally agree. Google introduce, sorry, Ty engineering. And, and if you take, you know, the traditional transformation of the roles, right? In the past it was called operations and then DevOps ops came in and then SRE is is the new buzzword. And the future could be something like product engineering, right? And, and, and in this journey, you know, here is what I tell, you know, folks on my side like what worked for Google might not work for a financial company, might not work for an insurance company. So, so, so it's, it's okay to use the word sre, but but the end of the day that SRE has to be tailored down to, to your requirements and and, and the customers that you serve and the technology that you serve. Yep. >>And this is, this is why I'm coming back, this platform engineering. At the end of the day, I think SRE just translates to, you're gonna have a platform engineering team cuz you gotta enable developers to be producing more code faster, better, cheaper guardrails policy. So this, it's kind of becoming the, you serve the business, which is now the developers it used to serve the business Yep. Back in the old days. Hey, the, it serves the business. Yep. Which is a terminal, >>Which is actually true >>Now it the new, it serves the developers, which is the business. Which is the business. Because if digital transformation goes to completion, the company is the app. Yep. >>And the, you know, the, the hard line between development and operations, right? So, so that's thining down over the time, you know, like that that line might disappear. And, and, and that's where asari is fitting in. >>Yeah. And they're building platforms to scale the enablement up that what is, so what is the key challenges you guys are, are both building out together this new transformational direction? What's new and what's the same, The same is probably the business results, but what's the new dynamic involved in rolling it out and making people successful? You got the two constituents, the builders of the infrastructures and the consumers of the services on the other side. What's the new thing? >>So the new thing if, if I may go fast these, so the faster market to, you know, value, right? That we are bringing to the table. That's, that's very important. You know, business has an idea. How do you get that idea implemented in terms of technology and, and take it into real time. So that journey we have cut down, right? Technology is like Kubernetes. It makes, it makes, you know, an IT person's life so easy that, that they can, they can speed up the process in, in, in a traditional way. What used to take like an year or six months can be done in a month today or or less than that, right? So, so there's definitely the losses, speed, velocity, agility in general, and then flexibility. And then the automation that we put in, especially if you have to maintain like thousands of clusters, you know, these, these are today like, you know, it is possible to, to make that happen with a click off a button. In the past it used to take like, you know, probably, you know, a hundred, a hundred percent team and operational team to do it. And a lot of time. But, but, but that automation is happening. You know, and we can get into the technology as much as possible. But, but, you know, blueprinting and all that stuff made >>It possible. Well say that for another interview, we'll do it take time. >>But the, the end user on the other end, the consumer doesn't have the patience that they once had. Right? Right. It's, I want this in my lab now. Now, how does the culture of Mass Mutual, how is it evolv to be able to deliver the velocity that your customers are demanding? >>So if once in a while, you know, it's important to step yourself into the customer's shoes and think it from their, from their, from their perspective, business does not care how you're running your IT shop. What they care about is your stability of the product and the efficiencies of the product and, and, and how, how, how easy it is to reach out to the customers and how well we are serving the customers, right? So whether I'm implementing Docker in the background, Dr. Swam or es you know, business doesn't even care about it. What they really care about it is if your environment goes down, it's a problem. And, and, and if you, if your environment or if your solution is not as efficient as the business needs, that's the problem, right? So, so at that point, the business will step in. So our job is to make sure, you know, from an, from a technology perspective, how fast you can make implement it and how efficiently you can implement it. And at the same time, how do you play within the guardrails of security and compliance. >>So I was gonna ask you if you have VMware in your environment, cause a lot of clients compare what vCenter does for Kubernetes is really needed. And I think that's what you guys got going on. I I can say that you're the v center of Kubernetes. I mean, as a, as an as an metaphor, a place to manage it all is all 1, 1 1 paint of glass, so to speak. Is that how you see success in your environment? >>So virtualization has gone a long way, you know where we started, what we call bare metal servers, and then we virtualized operating systems. Now we are virtualizing applications and, and we are virtualizing platforms as well, right? So that's where Kubernetes basically got. >>So you see the need for a vCenter like thing for Uber, >>Definitely a need in the market in the way you need to think is like, you know, let's say there is, there is an insurance company who actually mented it and, and they gain the market advantage. Right? Now the, the the competition wants to do it as well, right? So, so, so there's definitely a virtualization of application layer that, that, that's very critical and it's, it's a critical component of cloud strategy as >>A whole. See, you're too humble to say it. I'll say you like the V center of Kubernetes, Explain what that means and your turn. If I said that to you, what would you react? How would you react to that? Would say bs or would you say on point, >>Maybe we should think about what does vCenter do today? Right? It's, it's so in my opinion, by the way, well vCenter in my opinion is one of the best platforms ever built. Like ha it's the best platform in my opinion ever built. It's, VMware did an amazing job because they took an IT engineer and they made him now be able to do storage management, networking management, VMs, multitenancy, access management audit, everything that you need to run a data center, you can do from a single, essentially single >>Platform, from a utility standpoint home >>Run. It's amazing, right? Yeah, it is because you are now able to empower people to do way more. Well why are we not doing that for Kubernetes? So the, the premise man Rafa was, well, oh, bless, I should have IT engineers, same engineers now they should be able to run fleets of clusters. That's what people that mass major are able to do now, right? So to that end, now you need cluster management, you need access management, you need blueprinting, you need policy management, you need ac, you know, all of these things that have happened before chargebacks, they used to have it in, in V center. Now they need to happen in other platforms. But for es so should do we do many of the things that vCenter does? Yes. >>Kind >>Of. Yeah. Are we a vCenter for es? Yeah, that is a John Forer question. >>All right, well, I, I'll, the speculation really goes back down to the earlier speed question. If you can take away the, the complexity and not make it more steps or change a tool chain or do something, then the devs move faster and the service layer that serves the business, the new organization has to enable speed. So this, this is becoming a, a real discussion point in the industry is that, oh yeah, we've got new tool, look at the shiny new toy. But if it doesn't move the needle, does it help productivity for developers? And does it actually scale up the enablement? That's the question. So I'm sure you guys are thinking about this a lot, what's your reaction? >>Yeah, absolutely. And one thing that just, you know, hit my mind is think about, you know, the hoteling industry before Airbnb and after Airbnb, right? Or, or, or the taxi industry, you know, before Uber and after Uber, right? So if I'm providing a platform, a Kubernetes platform for my application folks or for my application partners, they have everything ready. All they need to do is like, you know, build their application and deployed and running, right? They, they, they don't have to worry about provisioning of the servers and then building the middleware on top of it and then, you know, do a bunch of testing to make sure, you know, they, they, they iron out all the, all the compatible issues and whatnot. Yeah. Now, now, today, all I, all I say is like, hey, you have, we have a platform built for you. You just build your application and then deploy it in a development environment. That's where you put all the pieces of puzzle together, make sure you see your application working, and then the next thing that, that you do is like, you know, you know, build >>Production, chip, build production, go and chip release it. Yeah, that's the nirvana. But then we're there. I mean, we're there now we're there. So we see the future. Because if you, if that's the case, then the developers are the business. They have to be coding more features, they have to react to customers. They might see new business opportunities from a revenue standpoint that could be creatively built, got low code, no code, headless systems. These things are happening where this I call the architectural list environment where it's like, you don't need architecture, it's already happening. >>Yeah. And, and on top of it, you know, if, if someone has an idea, they want to implement an idea real quick, right? So how do you do it? Right? And, and, and you don't have to struggle building an environment to implement your idea and testers in real time, right? So, so from an innovation perspective, you know, agility plays a key role. And, and that, that's where the Kubernetes platforms or platforms like Kubernetes >>Plays. You know, Lisa, when we talked to Andy Chasy, when he was the CEO of aws, either one on one or on the cube, he always said, and this is kind of happening, companies are gonna be builders where it's not just utility. You need that table stakes to enable that new business idea. And so he, this last keynote, he did this big thing like, you know, think like your developers are the next entrepreneurial revenue generators. And I think that, I think starting to see that, what do you think about that? You see that coming sooner than later? Or is that in, in sight or is that still ways away? >>I, I think it's already happening at a level, at a certain level now. Now the question comes back to, you know, taking it to the reality, right? Yeah. I mean, you can, you can do your proof of concept, proof of technologies, and then, and then prove it out. Like, Hey, I got a new idea. This idea is great. Yeah. And, and it's to the business advantage, right? But we really want to see it in production live where your customers are actually >>Using it and the board meetings, Hey, we got a new idea that came in, generating more revenue, where'd that come from? Agile developer. Again, this is real. Yeah, >>Yeah. >>Absolutely agree. Yeah. I think, think both of you gentlemen said a word in, in your, as you were talking, you used the word guardrails, right? I think, you know, we're talking about rigidity, but you know, the really important thing is, look, these are enterprises, right? They have certain expectations. Guardrails is key, right? So it's automation with the guardrails. Yeah. Guardrails are like children, you know, you know, shouldn't be hurt. You know, they're seen but not hurt. Developers don't care about guard rails. They just wanna go fast. They also bounce >>Around a little bit. Yeah. Off the guardrails. >>One thing we know that's not gonna slow down is, is the expectations, right? Of all the consumers of this, the Ds the business, the, the business top line, and of course the customers. So the ability to, to really, as your website says, let's see, make life easy for platform teams is not trivial. And clearly what you guys are talking about here is you're, you're really an enabler of those platform teams, it sounds like to me. Yep. So, great work, guys. Thank you so much for both coming on the program, talking about what you're doing together, how you're seeing the, the evolution of Kubernetes, why, and really what the focus should be on those platform games. We appreciate all your time and your insights. >>Thank you so much for having us. Thanks >>For our pleasure. For our guests and for John Furrier, I'm Lisa Martin. You're watching The Cube Live, Cobe Con, Cloud Native con from Detroit. We've out with our next guest in just a minute, so stick around.