>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR, this is "Breaking Analysis" with Dave Vellante. >> A decade of big data investments combined with cloud scale, the rise of much more cost effective processing power. And the introduction of advanced tooling has catapulted machine intelligence to the forefront of technology investments. No matter what job you have, your operation will be AI powered within five years and machines may actually even be doing your job. Artificial intelligence is being infused into applications, infrastructure, equipment, and virtually every aspect of our lives. AI is proving to be extremely helpful at things like controlling vehicles, speeding up medical diagnoses, processing language, advancing science, and generally raising the stakes on what it means to apply technology for business advantage. But business value realization has been a challenge for most organizations due to lack of skills, complexity of programming models, immature technology integration, sizable upfront investments, ethical concerns, and lack of business alignment. Mastering AI technology will not be a requirement for success in our view. However, figuring out how and where to apply AI to your business will be crucial. That means understanding the business case, picking the right technology partner, experimenting in bite-sized chunks, and quickly identifying winners to double down on from an investment standpoint. Hello and welcome to this week's Wiki-bond CUBE Insights powered by ETR. In this breaking analysis, we update you on the state of AI and what it means for the competition. And to do so, we invite into our studios Andy Thurai of Constellation Research. Andy covers AI deeply. He knows the players, he knows the pitfalls of AI investment, and he's a collaborator. Andy, great to have you on the program. Thanks for coming into our CUBE studios. >> Thanks for having me on. >> You're very welcome. Okay, let's set the table with a premise and a series of assertions we want to test with Andy. I'm going to lay 'em out. And then Andy, I'd love for you to comment. So, first of all, according to McKinsey, AI adoption has more than doubled since 2017, but only 10% of organizations report seeing significant ROI. That's a BCG and MIT study. And part of that challenge of AI is it requires data, is requires good data, data proficiency, which is not trivial, as you know. Firms that can master both data and AI, we believe are going to have a competitive advantage this decade. Hyperscalers, as we show you dominate AI and ML. We'll show you some data on that. And having said that, there's plenty of room for specialists. They need to partner with the cloud vendors for go to market productivity. And finally, organizations increasingly have to put data and AI at the center of their enterprises. And to do that, most are going to rely on vendor R&D to leverage AI and ML. In other words, Andy, they're going to buy it and apply it as opposed to build it. What are your thoughts on that setup and that premise? >> Yeah, I see that a lot happening in the field, right? So first of all, the only 10% of realizing a return on investment. That's so true because we talked about this earlier, the most companies are still in the innovation cycle. So they're trying to innovate and see what they can do to apply. A lot of these times when you look at the solutions, what they come up with or the models they create, the experimentation they do, most times they don't even have a good business case to solve, right? So they just experiment and then they figure it out, "Oh my God, this model is working. Can we do something to solve it?" So it's like you found a hammer and then you're trying to find the needle kind of thing, right? That never works. >> 'Cause it's cool or whatever it is. >> It is, right? So that's why, I always advise, when they come to me and ask me things like, "Hey, what's the right way to do it? What is the secret sauce?" And, we talked about this. The first thing I tell them is, "Find out what is the business case that's having the most amount of problems, that that can be solved using some of the AI use cases," right? Not all of them can be solved. Even after you experiment, do the whole nine yards, spend millions of dollars on that, right? And later on you make it efficient only by saving maybe $50,000 for the company or a $100,000 for the company, is it really even worth the experiment, right? So you got to start with the saying that, you know, where's the base for this happening? Where's the need? What's a business use case? It doesn't have to be about cost efficient and saving money in the existing processes. It could be a new thing. You want to bring in a new revenue stream, but figure out what is a business use case, how much money potentially I can make off of that. The same way that start-ups go after. Right? >> Yeah. Pretty straightforward. All right, let's take a look at where ML and AI fit relative to the other hot sectors of the ETR dataset. This XY graph shows net score spending velocity in the vertical axis and presence in the survey, they call it sector perversion for the October survey, the January survey's in the field. Then that squiggly line on ML/AI represents the progression. Since the January 21 survey, you can see the downward trajectory. And we position ML and AI relative to the other big four hot sectors or big three, including, ML/AI is four. Containers, cloud and RPA. These have consistently performed above that magic 40% red dotted line for most of the past two years. Anything above 40%, we think is highly elevated. And we've just included analytics and big data for context and relevant adjacentness, if you will. Now note that green arrow moving toward, you know, the 40% mark on ML/AI. I got a glimpse of the January survey, which is in the field. It's got more than a thousand responses already, and it's trending up for the current survey. So Andy, what do you make of this downward trajectory over the past seven quarters and the presumed uptick in the coming months? >> So one of the things you have to keep in mind is when the pandemic happened, it's about survival mode, right? So when somebody's in a survival mode, what happens, the luxury and the innovations get cut. That's what happens. And this is exactly what happened in the situation. So as you can see in the last seven quarters, which is almost dating back close to pandemic, everybody was trying to keep their operations alive, especially digital operations. How do I keep the lights on? That's the most important thing for them. So while the numbers spent on AI, ML is less overall, I still think the AI ML to spend to sort of like a employee experience or the IT ops, AI ops, ML ops, as we talked about, some of those areas actually went up. There are companies, we talked about it, Atlassian had a lot of platform issues till the amount of money people are spending on that is exorbitant and simply because they are offering the solution that was not available other way. So there are companies out there, you can take AoPS or incident management for that matter, right? A lot of companies have a digital insurance, they don't know how to properly manage it. How do you find an intern solve it immediately? That's all using AI ML and some of those areas actually growing unbelievable, the companies in that area. >> So this is a really good point. If you can you bring up that chart again, what Andy's saying is a lot of the companies in the ETR taxonomy that are doing things with AI might not necessarily show up in a granular fashion. And I think the other point I would make is, these are still highly elevated numbers. If you put on like storage and servers, they would read way, way down the list. And, look in the pandemic, we had to deal with work from home, we had to re-architect the network, we had to worry about security. So those are really good points that you made there. Let's, unpack this a little bit and look at the ML AI sector and the ETR data and specifically at the players and get Andy to comment on this. This chart here shows the same x y dimensions, and it just notes some of the players that are specifically have services and products that people spend money on, that CIOs and IT buyers can comment on. So the table insert shows how the companies are plotted, it's net score, and then the ends in the survey. And Andy, the hyperscalers are dominant, as you can see. You see Databricks there showing strong as a specialist, and then you got to pack a six or seven in there. And then Oracle and IBM, kind of the big whales of yester year are in the mix. And to your point, companies like Salesforce that you mentioned to me offline aren't in that mix, but they do a lot in AI. But what are your takeaways from that data? >> If you could put the slide back on please. I want to make quick comments on a couple of those. So the first one is, it's surprising other hyperscalers, right? As you and I talked about this earlier, AWS is more about logo blocks. We discussed that, right? >> Like what? Like a SageMaker as an example. >> We'll give you all the components what do you need. Whether it's MLOps component or whether it's, CodeWhisperer that we talked about, or a oral platform or data or data, whatever you want. They'll give you the blocks and then you'll build things on top of it, right? But Google took a different way. Matter of fact, if we did those numbers a few years ago, Google would've been number one because they did a lot of work with their acquisition of DeepMind and other things. They're way ahead of the pack when it comes to AI for longest time. Now, I think Microsoft's move of partnering and taking a huge competitor out would open the eyes is unbelievable. You saw that everybody is talking about chat GPI, right? And the open AI tool and ChatGPT rather. Remember as Warren Buffet is saying that, when my laundry lady comes and talk to me about stock market, it's heated up. So that's how it's heated up. Everybody's using ChatGPT. What that means is at the end of the day is they're creating, it's still in beta, keep in mind. It's not fully... >> Can you play with it a little bit? >> I have a little bit. >> I have, but it's good and it's not good. You know what I mean? >> Look, so at the end of the day, you take the massive text of all the available text in the world today, mass them all together. And then you ask a question, it's going to basically search through that and figure it out and answer that back. Yes, it's good. But again, as we discussed, if there's no business use case of what problem you're going to solve. This is building hype. But then eventually they'll figure out, for example, all your chats, online chats, could be aided by your AI chat bots, which is already there, which is not there at that level. This could build help that, right? Or the other thing we talked about is one of the areas where I'm more concerned about is that it is able to produce equal enough original text at the level that humans can produce, for example, ChatGPT or the equal enough, the large language transformer can help you write stories as of Shakespeare wrote it. Pretty close to it. It'll learn from that. So when it comes down to it, talk about creating messages, articles, blogs, especially during political seasons, not necessarily just in US, but anywhere for that matter. If people are able to produce at the emission speed and throw it at the consumers and confuse them, the elections can be won, the governments can be toppled. >> Because to your point about chatbots is chatbots have obviously, reduced the number of bodies that you need to support chat. But they haven't solved the problem of serving consumers. Most of the chat bots are conditioned response, which of the following best describes your problem? >> The current chatbot. >> Yeah. Hey, did we solve your problem? No. Is the answer. So that has some real potential. But if you could bring up that slide again, Ken, I mean you've got the hyperscalers that are dominant. You talked about Google and Microsoft is ubiquitous, they seem to be dominant in every ETR category. But then you have these other specialists. How do those guys compete? And maybe you could even, cite some of the guys that you know, how do they compete with the hyperscalers? What's the key there for like a C3 ai or some of the others that are on there? >> So I've spoken with at least two of the CEOs of the smaller companies that you have on the list. One of the things they're worried about is that if they continue to operate independently without being part of hyperscaler, either the hyperscalers will develop something to compete against them full scale, or they'll become irrelevant. Because at the end of the day, look, cloud is dominant. Not many companies are going to do like AI modeling and training and deployment the whole nine yards by independent by themselves. They're going to depend on one of the clouds, right? So if they're already going to be in the cloud, by taking them out to come to you, it's going to be extremely difficult issue to solve. So all these companies are going and saying, "You know what? We need to be in hyperscalers." For example, you could have looked at DataRobot recently, they made announcements, Google and AWS, and they are all over the place. So you need to go where the customers are. Right? >> All right, before we go on, I want to share some other data from ETR and why people adopt AI and get your feedback. So the data historically shows that feature breadth and technical capabilities were the main decision points for AI adoption, historically. What says to me that it's too much focus on technology. In your view, is that changing? Does it have to change? Will it change? >> Yes. Simple answer is yes. So here's the thing. The data you're speaking from is from previous years. >> Yes >> I can guarantee you, if you look at the latest data that's coming in now, those two will be a secondary and tertiary points. The number one would be about ROI. And how do I achieve? I've spent ton of money on all of my experiments. This is the same thing theme I'm seeing across when talking to everybody who's spending money on AI. I've spent so much money on it. When can I get it live in production? How much, how can I quickly get it? Because you know, the board is breathing down their neck. You already spend this much money. Show me something that's valuable. So the ROI is going to become, take it from me, I'm predicting this for 2023, that's going to become number one. >> Yeah, and if people focus on it, they'll figure it out. Okay. Let's take a look at some of the top players that won, some of the names we just looked at and double click on that and break down their spending profile. So the chart here shows the net score, how net score is calculated. So pay attention to the second set of bars that Databricks, who was pretty prominent on the previous chart. And we've annotated the colors. The lime green is, we're bringing the platform in new. The forest green is, we're going to spend 6% or more relative to last year. And the gray is flat spending. The pinkish is our spending's going to be down on AI and ML, 6% or worse. And the red is churn. So you don't want big red. You subtract the reds from the greens and you get net score, which is shown by those blue dots that you see there. So AWS has the highest net score and very little churn. I mean, single low single digit churn. But notably, you see Databricks and DataRobot are next in line within Microsoft and Google also, they've got very low churn. Andy, what are your thoughts on this data? >> So a couple of things that stands out to me. Most of them are in line with my conversation with customers. Couple of them stood out to me on how bad IBM Watson is doing. >> Yeah, bring that back up if you would. Let's take a look at that. IBM Watson is the far right and the red, that bright red is churning and again, you want low red here. Why do you think that is? >> Well, so look, IBM has been in the forefront of innovating things for many, many years now, right? And over the course of years we talked about this, they moved from a product innovation centric company into more of a services company. And over the years they were making, as at one point, you know that they were making about majority of that money from services. Now things have changed Arvind has taken over, he came from research. So he's doing a great job of trying to reinvent themselves as a company. But it's going to have a long way to catch up. IBM Watson, if you think about it, that played what, jeopardy and chess years ago, like 15 years ago? >> It was jaw dropping when you first saw it. And then they weren't able to commercialize that. >> Yeah. >> And you're making a good point. When Gerstner took over IBM at the time, John Akers wanted to split the company up. He wanted to have a database company, he wanted to have a storage company. Because that's where the industry trend was, Gerstner said no, he came from AMEX, right? He came from American Express. He said, "No, we're going to have a single throat to choke for the customer." They bought PWC for relatively short money. I think it was $15 billion, completely transformed and I would argue saved IBM. But the trade off was, it sort of took them out of product leadership. And so from Gerstner to Palmisano to Remedi, it was really a services led company. And I think Arvind is really bringing it back to a product company with strong consulting. I mean, that's one of the pillars. And so I think that's, they've got a strong story in data and AI. They just got to sort of bring it together and better. Bring that chart up one more time. I want to, the other point is Oracle, Oracle sort of has the dominant lock-in for mission critical database and they're sort of applying AI there. But to your point, they're really not an AI company in the sense that they're taking unstructured data and doing sort of new things. It's really about how to make Oracle better, right? >> Well, you got to remember, Oracle is about database for the structure data. So in yesterday's world, they were dominant database. But you know, if you are to start storing like videos and texts and audio and other things, and then start doing search of vector search and all that, Oracle is not necessarily the database company of choice. And they're strongest thing being apps and building AI into the apps? They are kind of surviving in that area. But again, I wouldn't name them as an AI company, right? But the other thing that that surprised me in that list, what you showed me is yes, AWS is number one. >> Bring that back up if you would, Ken. >> AWS is number one as you, it should be. But what what actually caught me by surprise is how DataRobot is holding, you know? I mean, look at that. The either net new addition and or expansion, DataRobot seem to be doing equally well, even better than Microsoft and Google. That surprises me. >> DataRobot's, and again, this is a function of spending momentum. So remember from the previous chart that Microsoft and Google, much, much larger than DataRobot. DataRobot more niche. But with spending velocity and has always had strong spending velocity, despite some of the recent challenges, organizational challenges. And then you see these other specialists, H2O.ai, Anaconda, dataiku, little bit of red showing there C3.ai. But these again, to stress are the sort of specialists other than obviously the hyperscalers. These are the specialists in AI. All right, so we hit the bigger names in the sector. Now let's take a look at the emerging technology companies. And one of the gems of the ETR dataset is the emerging technology survey. It's called ETS. They used to just do it like twice a year. It's now run four times a year. I just discovered it kind of mid-2022. And it's exclusively focused on private companies that are potential disruptors, they might be M&A candidates and if they've raised enough money, they could be acquirers of companies as well. So Databricks would be an example. They've made a number of investments in companies. SNEAK would be another good example. Companies that are private, but they're buyers, they hope to go IPO at some point in time. So this chart here, shows the emerging companies in the ML AI sector of the ETR dataset. So the dimensions of this are similar, they're net sentiment on the Y axis and mind share on the X axis. Basically, the ETS study measures awareness on the x axis and intent to do something with, evaluate or implement or not, on that vertical axis. So it's like net score on the vertical where negatives are subtracted from the positives. And again, mind share is vendor awareness. That's the horizontal axis. Now that inserted table shows net sentiment and the ends in the survey, which informs the position of the dots. And you'll notice we're plotting TensorFlow as well. We know that's not a company, but it's there for reference as open source tooling is an option for customers. And ETR sometimes like to show that as a reference point. Now we've also drawn a line for Databricks to show how relatively dominant they've become in the past 10 ETS surveys and sort of mind share going back to late 2018. And you can see a dozen or so other emerging tech vendors. So Andy, I want you to share your thoughts on these players, who were the ones to watch, name some names. We'll bring that data back up as you as you comment. >> So Databricks, as you said, remember we talked about how Oracle is not necessarily the database of the choice, you know? So Databricks is kind of trying to solve some of the issue for AI/ML workloads, right? And the problem is also there is no one company that could solve all of the problems. For example, if you look at the names in here, some of them are database names, some of them are platform names, some of them are like MLOps companies like, DataRobot (indistinct) and others. And some of them are like future based companies like, you know, the Techton and stuff. >> So it's a mix of those sub sectors? >> It's a mix of those companies. >> We'll talk to ETR about that. They'd be interested in your input on how to make this more granular and these sub-sectors. You got Hugging Face in here, >> Which is NLP, yeah. >> Okay. So your take, are these companies going to get acquired? Are they going to go IPO? Are they going to merge? >> Well, most of them going to get acquired. My prediction would be most of them will get acquired because look, at the end of the day, hyperscalers need these capabilities, right? So they're going to either create their own, AWS is very good at doing that. They have done a lot of those things. But the other ones, like for particularly Azure, they're going to look at it and saying that, "You know what, it's going to take time for me to build this. Why don't I just go and buy you?" Right? Or or even the smaller players like Oracle or IBM Cloud, this will exist. They might even take a look at them, right? So at the end of the day, a lot of these companies are going to get acquired or merged with others. >> Yeah. All right, let's wrap with some final thoughts. I'm going to make some comments Andy, and then ask you to dig in here. Look, despite the challenge of leveraging AI, you know, Ken, if you could bring up the next chart. We're not repeating, we're not predicting the AI winter of the 1990s. Machine intelligence. It's a superpower that's going to permeate every aspect of the technology industry. AI and data strategies have to be connected. Leveraging first party data is going to increase AI competitiveness and shorten time to value. Andy, I'd love your thoughts on that. I know you've got some thoughts on governance and AI ethics. You know, we talked about ChatGBT, Deepfakes, help us unpack all these trends. >> So there's so much information packed up there, right? The AI and data strategy, that's very, very, very important. If you don't have a proper data, people don't realize that AI is, your AI is the morals that you built on, it's predominantly based on the data what you have. It's not, AI cannot predict something that's going to happen without knowing what it is. It need to be trained, it need to understand what is it you're talking about. So 99% of the time you got to have a good data for you to train. So this where I mentioned to you, the problem is a lot of these companies can't afford to collect the real world data because it takes too long, it's too expensive. So a lot of these companies are trying to do the synthetic data way. It has its own set of issues because you can't use all... >> What's that synthetic data? Explain that. >> Synthetic data is basically not a real world data, but it's a created or simulated data equal and based on real data. It looks, feels, smells, taste like a real data, but it's not exactly real data, right? This is particularly useful in the financial and healthcare industry for world. So you don't have to, at the end of the day, if you have real data about your and my medical history data, if you redact it, you can still reverse this. It's fairly easy, right? >> Yeah, yeah. >> So by creating a synthetic data, there is no correlation between the real data and the synthetic data. >> So that's part of AI ethics and privacy and, okay. >> So the synthetic data, the issue with that is that when you're trying to commingle that with that, you can't create models based on just on synthetic data because synthetic data, as I said is artificial data. So basically you're creating artificial models, so you got to blend in properly that that blend is the problem. And you know how much of real data, how much of synthetic data you could use. You got to use judgment between efficiency cost and the time duration stuff. So that's one-- >> And risk >> And the risk involved with that. And the secondary issues which we talked about is that when you're creating, okay, you take a business use case, okay, you think about investing things, you build the whole thing out and you're trying to put it out into the market. Most companies that I talk to don't have a proper governance in place. They don't have ethics standards in place. They don't worry about the biases in data, they just go on trying to solve a business case >> It's wild west. >> 'Cause that's what they start. It's a wild west! And then at the end of the day when they are close to some legal litigation action or something or something else happens and that's when the Oh Shit! moments happens, right? And then they come in and say, "You know what, how do I fix this?" The governance, security and all of those things, ethics bias, data bias, de-biasing, none of them can be an afterthought. It got to start with the, from the get-go. So you got to start at the beginning saying that, "You know what, I'm going to do all of those AI programs, but before we get into this, we got to set some framework for doing all these things properly." Right? And then the-- >> Yeah. So let's go back to the key points. I want to bring up the cloud again. Because you got to get cloud right. Getting that right matters in AI to the points that you were making earlier. You can't just be out on an island and hyperscalers, they're going to obviously continue to do well. They get more and more data's going into the cloud and they have the native tools. To your point, in the case of AWS, Microsoft's obviously ubiquitous. Google's got great capabilities here. They've got integrated ecosystems partners that are going to continue to strengthen through the decade. What are your thoughts here? >> So a couple of things. One is the last mile ML or last mile AI that nobody's talking about. So that need to be attended to. There are lot of players in the market that coming up, when I talk about last mile, I'm talking about after you're done with the experimentation of the model, how fast and quickly and efficiently can you get it to production? So that's production being-- >> Compressing that time is going to put dollars in your pocket. >> Exactly. Right. >> So once, >> If you got it right. >> If you get it right, of course. So there are, there are a couple of issues with that. Once you figure out that model is working, that's perfect. People don't realize, the moment you decide that moment when the decision is made, it's like a new car. After you purchase the value decreases on a minute basis. Same thing with the models. Once the model is created, you need to be in production right away because it starts losing it value on a seconds minute basis. So issue number one, how fast can I get it over there? So your deployment, you are inferencing efficiently at the edge locations, your optimization, your security, all of this is at issue. But you know what is more important than that in the last mile? You keep the model up, you continue to work on, again, going back to the car analogy, at one point you got to figure out your car is costing more than to operate. So you got to get a new car, right? And that's the same thing with the models as well. If your model has reached a stage, it is actually a potential risk for your operation. To give you an idea, if Uber has a model, the first time when you get a car from going from point A to B cost you $60. If the model decayed the next time I might give you a $40 rate, I would take it definitely. But it's lost for the company. The business risk associated with operating on a bad model, you should realize it immediately, pull the model out, retrain it, redeploy it. That's is key. >> And that's got to be huge in security model recency and security to the extent that you can get real time is big. I mean you, you see Palo Alto, CrowdStrike, a lot of other security companies are injecting AI. Again, they won't show up in the ETR ML/AI taxonomy per se as a pure play. But ServiceNow is another company that you have have mentioned to me, offline. AI is just getting embedded everywhere. >> Yep. >> And then I'm glad you brought up, kind of real-time inferencing 'cause a lot of the modeling, if we can go back to the last point that we're going to make, a lot of the AI today is modeling done in the cloud. The last point we wanted to make here, I'd love to get your thoughts on this, is real-time AI inferencing for instance at the edge is going to become increasingly important for us. It's going to usher in new economics, new types of silicon, particularly arm-based. We've covered that a lot on "Breaking Analysis", new tooling, new companies and that could disrupt the sort of cloud model if new economics emerge. 'Cause cloud obviously very centralized, they're trying to decentralize it. But over the course of this decade we could see some real disruption there. Andy, give us your final thoughts on that. >> Yes and no. I mean at the end of the day, cloud is kind of centralized now, but a lot of this companies including, AWS is kind of trying to decentralize that by putting their own sub-centers and edge locations. >> Local zones, outposts. >> Yeah, exactly. Particularly the outpost concept. And if it can even become like a micro center and stuff, it won't go to the localized level of, I go to a single IOT level. But again, the cloud extends itself to that level. So if there is an opportunity need for it, the hyperscalers will figure out a way to fit that model. So I wouldn't too much worry about that, about deployment and where to have it and what to do with that. But you know, figure out the right business use case, get the right data, get the ethics and governance place and make sure they get it to production and make sure you pull the model out when it's not operating well. >> Excellent advice. Andy, I got to thank you for coming into the studio today, helping us with this "Breaking Analysis" segment. Outstanding collaboration and insights and input in today's episode. Hope we can do more. >> Thank you. Thanks for having me. I appreciate it. >> You're very welcome. All right. I want to thank Alex Marson who's on production and manages the podcast. Ken Schiffman as well. Kristen Martin and Cheryl Knight helped get the word out on social media and our newsletters. And Rob Hoof is our editor-in-chief over at Silicon Angle. He does some great editing for us. Thank you all. Remember all these episodes are available as podcast. Wherever you listen, all you got to do is search "Breaking Analysis" podcast. I publish each week on wikibon.com and silicon angle.com or you can email me at david.vellante@siliconangle.com to get in touch, or DM me at dvellante or comment on our LinkedIn posts. Please check out ETR.AI for the best survey data and the enterprise tech business, Constellation Research. Andy publishes there some awesome information on AI and data. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching everybody and we'll see you next time on "Breaking Analysis". (gentle closing tune plays)

(bright music) >> Hello everyone and welcome back to AWS re:Invent, here in wonderful Las Vegas, Nevada. We're theCUBE. I am Savannah Peterson. Joined with my co-host, Dave Vellante. Day four, you look great. Your voice has come back somehow. >> Yeah, a little bit. I don't know how. I took last night off. You guys, I know, were out partying all night, but - >> I don't know what you're talking about. (Dave laughing) >> Well, you were celebrating John's birthday. John Furrier's birthday today. >> Yes, happy birthday John! >> He's on his way to England. >> Yeah. >> To attend his nephew's wedding. Awesome family. And so good luck, John. I hope you feel better, he's got a little cold. >> I know, good luck to the newlyweds. I love this. I know we're both really excited for our next guest, so I'm going to bring out, Lena Smart from MongoDB. Thank you so much for being here. >> Thank you for having me. >> How's the show going for you? >> Good. It's been a long week. And I just, not much voice left, so. >> We'll be gentle on you. >> I'll give you what's left of it. >> All right, we'll take that. >> Okay. >> You had a fireside chat, at the show? >> Lena: I did. >> Can you tell us a little bit about that? >> So we were talking about the Rise, The developer is a platform. In this massive theater. I thought it would be like an intimate, you know, fireside chat. I keep believing them when they say to me come and do these talks, it'll be intimate. And you turn up and there's a stage and a theater and it's like, oh my god. But it was really interesting. It was well attended. Got some really good questions at the end as well. Lots of follow up, which was interesting. And it was really just about, you know, how we've brought together this developer platform that's got our integrated services. It's just what developers want, it gives them time to innovate and disrupt, rather than worry about the minutia of management. >> Savannah: Do the cool stuff. >> Exactly. >> Yeah, so you know Lena, it's funny that you're saying that oh wow, the lights came on and it was this big thing. When when we were at re:Inforced, Lena was on stage and it was so funny, Lena, you were self deprecating like making jokes about the audience. >> Savannah: (indistinct) >> It was hilarious. And so, but it was really endearing to the audience and so we were like - >> Lena: It was terrifying. >> You got huge props for that, I'll tell you. >> Absolutely terrifying. Because they told me I wouldn't see anyone. Because we did the rehearsal the day before, and they were like, it's just going to be like - >> Sometimes it just looks like blackness out there. >> Yeah, yeah. It wasn't, they lied. I could see eyeballs. It was terrifying. >> Would you rather know that going in though? Or is it better to be, is ignorance bliss in that moment? >> Ignorance is bliss. >> Yeah, yeah yeah. >> Good call Savannah, right? Yeah, just go. >> The older I get, the more I'm just, I'm on the ignorance is bliss train. I just, I don't need to know anything that's going to hurt my soul. >> Exactly. >> One of the things that you mentioned, and this has actually been a really frequent theme here on the show this week, is you said that this has been a transformative year for developers. >> Lena: Yeah. >> What did you mean by that? >> So I think developers are starting to come to the fore, if you like, the fore. And I'm not in any way being deprecating about developers 'cause I love them. >> Savannah: I think everyone here does. >> I was married to one, I live with one now. It's like, they follow me everywhere. They don't. But, I think they, this is my opinion obviously but I think that we're seeing more and more the value that developers bring to the table. They're not just code geeks anymore. They're not just code monkeys, you know, churning out lines and lines of code. Some of the most interesting discussions I've had this week have been with developers. And that's why I'm so pleased that our developer data platform is going to give these folks back time, so that they can go and innovate. And do super interesting things and do the next big thing. It was interesting, I was talking to Mary, our comms person earlier and she had said that Dave I guess, my boss, was on your show - >> Dave: Yeah, he was over here last night. >> Yeah. And he was saying that two thirds of the companies that had been mentioned so far, within the whole gamut of this conference use MongoDB. And so take that, extrapolate that, of all the developers >> Wow. >> who are there. I know, isn't that awesome? >> That's awesome. Congrats on that, that's like - >> Did I hear that right now? >> I know, I just had that moment. >> I know she just told me, I'm like, really? That's - >> That's so cool. >> 'Cause the first thing I thought of was then, oh my god, how many developers are we reaching then? 'Cause they're the ones. I mean, it's kind of interesting. So my job has kind of grown from, over the years, being the security geek in the back room that nobody talks to, to avoiding me in the lift, to I've got a seat at the table now. We meet with the board. And I think that I can see that that's where the developer mindset is moving towards. It's like, give us the right tools and we'll change your world. >> And let the human capital go back to doing the fun stuff and not just the maintenance stuff. >> And, but then you say that, you can't have everything automated. I get that automation is also the buzzword of the week. And I get that, trust me. Someone has to write the code to do the automation. >> Savannah: Right. >> So, so yeah, definitely give these people back time, so that they can work on ML, AI, choose your buzzword. You know, by giving people things like queriable encryption for example, you're going to free up a whole bunch of head space. They don't have to worry about their data being, you know harvested from memory or harvested while at rest or in motion. And it's like, okay, I don't have to worry about that now, let me go do something fun. >> How about the role of the developer as it relates to SecOps, right? They're being asked to do a lot. You and I talked about this at re:Inforce. You seem to have a pretty good handle on it. Like a lot of companies I think are struggling with it. I mean, the other thing you said said to me is you don't have a lack of talent at Mongo, right? 'Cause you're Mongo. But a lot of companies do. But a lot of the developers, you know we were just talking about this earlier with Capgemini, the developer metrics or the application development team's metrics might not be aligned with the CSO's metrics. How, what are you seeing there? What, how do you deal with it within Mongo? What do you advise your customers? >> So in terms of internal, I work very closely with our development group. So I work with Tara Hernandez, who's our new VP of developer productivity. And she and her team are very much interested in making developers more productive. That's her job. And so we get together because sometimes security can definitely be seen as a blocker. You know, funnily enough, I actually had a Slack that I had to respond to three seconds before I come on here. And it was like, help, we need some help getting this application through procurement, because blah, blah, blah. And it's weird the kind of change, the shift in mindset. Whereas before they might have gone to procurement or HR or someone to ask for this. Now they're coming to the CSO. 'Cause they know if I say yes, it'll go through. >> Talk about social engineering. >> Exactly. >> You were talking about - >> But turn it around though. If I say no, you know, I don't like to say no. I prefer to be the CSO that says yes, but. And so that's what we've done. We've definitely got that culture of ask, we'll tell you the risks, and then you can go away and be innovative and do what you need to do. And we basically do the same with our customers. Here's what you can do. Our application is secure out of the box. Here's how we can help you make it even more, you know, streamlined or bespoke to what you need. >> So mobile was a big inflection point, you know, I dunno, it seems like forever ago. >> 2007. >> 2007. Yeah, iPhone came out in 2007. >> You remember your first iPhone? >> Dave: Yeah. >> Yeah? Same. >> Yeah. It was pretty awesome, actually. >> Yeah, I do too. >> Yeah, I was on the train to Boston going up to see some friends at MIT on the consortium that I worked with. And I had, it was the wee one, 'member? But you thought it was massive. >> Oh, it felt - >> It felt big. And I remember I was sitting on the train to Boston it was like the Estella and there was these people, these two women sitting beside me. And they were all like glam, like you and unlike me. >> Dave: That's awesome. >> And they, you could see them like nudging each other. And I'm being like, I'm just sitting like this. >> You're chilling. >> Like please look at my phone, come on just look at it. Ask me about it. And eventually I'm like - >> You're baiting them. >> nonchalantly laid it on the table. And you know, I'm like, and they're like, is that an iPhone? And I'm like, yeah, you want to see it? >> I thought you'd never ask. >> I know. And I really played with it. And I showed them all the cool stuff, and they're like, oh we're going to buy iPhones. And so I should have probably worked for Apple, but I didn't. >> I was going to say, where was your referral kickback on that? Especially - >> It was a little like Tesla, right? When you first, we first saw Tesla, it was Ray Wong, you know, Ray? From Pasadena? >> It really was a moment and going from the Blackberry keyboard to that - >> He's like want to see my car? And I'm like oh yeah sure, what's the big deal? >> Yeah, then you see it and you're like, ooh. >> Yeah, that really was such a pivotal moment. >> Anyway, so we lost a track, 2007. >> Yeah, what were we talking about? 2007 mobile. >> Mobile. >> Key inflection point, is where you got us here. Thank you. >> I gotchu Dave, I gotchu. >> Bring us back here. My mind needs help right now. Day four. Okay, so - >> We're all getting here on day four, we're - >> I'm socially engineering you to end this, so I can go to bed and die quietly. That's what me and Mary are, we're counting down the minutes. >> Holy. >> That's so sick. >> You're breaking my heart right now. I love it. I'm with you, sis, I'm with you. >> So I dunno where I was, really where I was going with this, but, okay, there's - >> 2007. Three things happened. >> Another inflection point. Okay yeah, tell us what happened. But no, tell us that, but then - >> AWS, clones, 2006. >> Well 2006, 2007. Right, okay. >> 2007, the iPhone, the world blew up. So you've already got this platform ready to take all this data. >> Dave: Right. >> You've got this little slab of gorgeousness called the iPhone, ready to give you all that data. And then MongoDB pops up, it's like, woo-hoo. But what we could offer was, I mean back then was awesome, but it was, we knew that we would have to iterate and grow and grow and grow. So that was kind of the three things that came together in 2007. >> Yeah, and then Cloud came in big time, and now you've got this platform. So what's the next inflection point do you think? >> Oh... >> Good question, Dave. >> Don't even ask me that. >> I mean, is it Edge? Is it IOT? Is there another disruptor out there? >> I think it's going to be artificial intelligence. >> Dave: Is it AI? >> I mean I don't know enough about it to talk about it, to any level, so don't ask me any questions about it. >> This is like one of those ignorance is bliss moments. It feels right. >> Yeah. >> Well, does it scare you, from a security perspective? Or? >> Great question, Dave. >> Yeah, it scares me more from a humanity standpoint. Like - >> More than social scared you? 'Cause social was so benign when it started. >> Oh it was - >> You're like, oh - I remember, >> It was like a yearbook. I was on the Estella and we were - >> Shout out to Amtrak there. >> I was with, we were starting basically a wikibond, it was an open source. >> Yeah, yeah. >> Kind of, you know, technology community. And we saw these and we were like enamored of Facebook. And there were these two young kids on the train, and we were at 'em, we were picking the brain. Do you like Facebook? "I love Facebook." They're like "oh, Facebook's unbelievable." Now, kids today, "I hate Facebook," right? So, but social at the beginning it was kind of, like I say, benign and now everybody's like - >> Savannah: We didn't know what we were getting into. >> Right. >> I know. >> Exactly. >> Can you imagine if you could have seen into the future 20 years ago? Well first of all, we'd have all bought Facebook and Apple stock. >> Savannah: Right. >> And Tesla stock. But apart from, but yeah apart from that. >> Okay, so what about Quantum? Does that scare you at all? >> I think the only thing that scares me about Quantum is we have all this security in place today. And I'm not an expert in Quantum, but we have all this security in place that's securing what we have today. And my worry is, in 10 years, is it still going to be secure? 'Cause we're still going to be using that data in some way, shape, or form. And my question is to the quantum geniuses out there, what do we do in 10 years like to retrofit the stuff? >> Dave: Like a Y2K moment? >> Kind of. Although I think Y2K is coming in 2038, isn't it? When the Linux date flips. I'll be off the grid by then, I'll be living in Scotland. >> Somebody else's problem. >> Somebody else's problem. I'll be with the sheep in Glasgow, in Scotland. >> Y2K was a boondoggle for tech, right? >> What a farce. I mean, that whole - >> I worked in the power industry in Y2K. That was a nightmare. >> Dave: Oh I bet. >> Savannah: Oh my God. >> Yeah, 'cause we just assumed that the world was going to stop and there been no power, and we had nuclear power plants. And it's like holy moly. Yeah. >> More than moly. >> I was going to say, you did a good job holding that other word in. >> I think I was going to, in case my mom hears this. >> I grew up near Diablo Canyon in, in California. So you were, I mean we were legitimately worried that that exactly was going to happen. And what about the waste? And yeah it was chaos. We've covered a lot. >> Well, what does worry you? Like, it is culture? Is it - >> Why are you trying to freak her out? >> No, no, because it's a CSO, trying to get inside the CSO's head. >> You don't think I have enough to worry about? You want to keep piling on? >> Well if it's not Quantum, you know? Maybe it's spiders or like - >> Oh but I like spiders, well spiders are okay. I don't like bridges, that's my biggest fear. Bridges. >> Seriously? >> And I had to drive over the Tappan Zee bridge, which is one of the longest, for 17 years, every day, twice. The last time I drove over it, I was crying my heart out, and happy as anything. >> Stay out of Oakland. >> I've never driven over it since. Stay out of where? >> Stay out of Oakland. >> I'm staying out of anywhere that's got lots of water. 'Cause it'll have bridges. >> Savannah: Well it's good we're here in the desert. >> Exactly. So what scares me? Bridges, there you go. >> Yeah, right. What? >> Well wait a minute. So if I'm bridging technology, is that the scary stuff? >> Oh God, that was not - >> Was it really bad? >> It was really bad. >> Wow. Wow, the puns. >> There's a lot of seems in those bridges. >> It is lit on theCUBE A floor, we are all struggling. I'm curious because I've seen, your team is all over the place here on the show, of course. Your booth has been packed the whole time. >> Lena: Yes. >> The fingerprint. Talk to me about your shirt. >> So, this was designed by my team in house. It is the most wanted swag in the company, because only my security people wear it. So, we make it like, yeah, you could maybe have one, if this turns out well. >> I feel like we're on the right track. >> Dave: If it turns out well. >> Yeah, I just love it. It's so, it's just brilliant. I mean, it's the leaf, it's a fingerprint. It's just brilliant. >> That's why I wanted to call it out. You know, you see a lot of shirts, a lot of swag shirts. Some are really unfortunately sad, or not funny, >> They are. >> or they're just trying too hard. Now there's like, with this one, I thought oh I bet that's clever. >> Lena: It is very cool. Yes, I love it. >> I saw a good one yesterday. >> Yeah? >> We fix shit, 'member? >> Oh yeah, yeah. >> That was pretty good. >> I like when they're >> That's a pretty good one. >> just straightforward, like that, yeah yeah. >> But the only thing with this is when you're say in front of a green screen, you look as though you've got no tummy. >> A portal through your body. >> And so, when we did our first - >> That's a really good point, actually. >> Yeah, it's like the black hole to nothingless. And I'm like wow, that's my soul. >> I was just going to say, I don't want to see my soul like that. I don't want to know. >> But we had to do like, it was just when the pandemic first started, so we had to do our big presentation live announcement from home. And so they shipped us all this camera equipment for home and thank God my partner knows how that works, so he set it all up. And then he had me test with a green screen, and he's like, you have no tummy. I'm like, what the hell are you talking about? He's like, come and see. It's like this, I dunno what it was. So I had to actually go upstairs and felt tip with a magic marker and make it black. >> Wow. >> So that was why I did for two hours on a Friday, yeah. >> Couldn't think of another alternative, huh? >> Well no, 'cause I'm myopic when it comes to marketing and I knew I had to keep the tshirt on, and I just did that. >> Yeah. >> In hindsight, yes I could have worn an "I Fix Shit" tshirt, but I don't think my husband would've been very happy. I secure shit? >> There you go, yeah. >> There you go. >> Over to you, Savannah. >> I was going to say, I got acquainted, I don't know if I can say this, but I'm going to say it 'cause we're here right now. I got acquainted with theCUBE, wearing a shirt that said "Unfuck Kubernetes," 'cause it was a marketing campaign that I was running for one of my clients at Kim Con last year. >> That's so good. >> Yeah, so - >> Oh my God. I'll give you one of these if you get me one of those. >> I can, we can do a swapskee. We can absolutely. >> We need a few edits on this film, on the file. >> Lena: Okay, this is nothing - >> We're fallin' off the wheel. Okay, on that note, I'm going to bring us to our challenge that we discussed, before we got started on this really diverse discussion that we have had in the last 15 minutes. We've covered everything from felt tip markers to nuclear power plants. >> To the darkness of my soul. >> To the darkness of all of our souls. >> All of our souls, yes. >> Which is perhaps a little too accurate, especially at this stage in the conference. You've obviously seen a lot Lena, and you've been rockin' it, I know John was in your suite up here, at at at the Venetian. What's your 30 second hot take? Most important story, coming out of the show or for you all at Mongo this year? >> Genuinely, it was when I learned that two-thirds of the customers that had been mentioned, here, are MongoDB customers. And that just exploded in my head. 'Cause now I'm thinking of all the numbers and the metrics and how we can use that. And I just think it's amazing, so. >> Yeah, congratulations on that. That's awesome. >> Yeah, I thought it was amazing. >> And it makes sense actually, 'cause Mongo so easy to use. We were talking about Tengen. >> We knew you when, I feel that's our like, we - >> Yeah, but it's true. And so, Mongo was just really easy to use. And people are like, ah, it doesn't scale. It's like, turns out it actually does scale. >> Lena: Turns out, it scales pretty well. >> Well Lena, without question, this is my favorite conversation of the show so far. >> Thank you. >> Thank you so much for joining us. >> Thank you very much for having me. >> Dave: Great to see you. >> It's always a pleasure. >> Dave: Thanks Lena. >> Thank you. >> And thank you all, tuning in live, for tolerating wherever we take these conversations. >> Dave: Whatever that was. >> I bet you weren't ready for this one, folks. We're at AWS re:Invent in Las Vegas, Nevada. With Dave Vellante, I'm Savannah Peterson. You're washing theCUBE, the leader for high tech coverage.

(upbeat music) (air whooshing) >> Good afternoon, cloud nerds, and welcome back to beautiful Las Vegas, Nevada. We are at AWS re:invent day four. Afternoon of day four here on theCUBE. I'm Savannah Peterson, joined by my fabulous cohost, Paul Gillin. Paul, you look sharp today. How you doing? >> Oh, you're just as fabulous, Savannah. You always look sharp. >> I appreciate that. They pay you enough to keep me buttered up over here at- (Paul laughing) It's wonderful. >> You're holding up well. >> Yeah, thank you. I am excited about our next conversation. Two fabulous gentlemen. Please welcome Sam and Monty, welcome to the show. >> Thank you. >> And it was great. Of the PR 2%, the most interesting man alive. (Paul and Savannah laughing) >> In person. Yeah, yeah. >> In the flesh. Our favorite guests so far. So how's the show been for you guys? >> Sam: It's been phenomenal. >> Just spending a lot of time with customers and partners and AWS. It's been great. It's been great. >> It is great. It's really about the community. It feels good to be back. >> Monty: Eating good food, getting my steps in above goals. >> I feel like the balance is good. We walk enough of these convention centers that you can enjoy the libations and the delicious food that's in Las Vegas and still not go home feeling like a cow. It is awesome. It's a win-win. >> To Sam's point though, meeting with customers, meeting with other technology providers that we may be able to partner with. And most importantly, in my role especially, meeting with all of our AWS key stakeholders in the partnership. So yeah, it's been great. >> Everyone's here. It's just different having a conversation in person. Even like us right now. So just in case folks aren't familiar, tell me about Talend. >> Yeah. Well, Talend is a data integration company. We've been around for a while. We have tons of different ways to get data from point A to point B, lots of different sources, lots of different connectors, and it's all about creating accessibility to that data. And then on top of that, we also have a number of solutions around governance, data health, data quality, data observability, which I think is really taking off. And so that's kind of how we're changing the business here. >> Casual change, data and governance. I don't know if anyone's talking about that at all on the snow floor. >> Been on big topic here. We've had a lot of conversations with the customers about that. >> So governance, what new dynamics has the cloud introduced into data governance? >> Well, I think historically, customers have been able to have their data on-prem. They put it into things like data lakes. And now having the flexibility to be able to bring that data to the clouds, it opens up a lot of doors, but it also opens up a lot of risks. So if you think about the chief data officer role, where you have, okay, I want to be able to bring my data to the users. I want to be able to do that at scale, operationally. But at the same time you have a tension then between the governance and the rules that really restrict the way that you can do that. Very strong tension between those two things. >> It really is a delicate balance. And especially as people are trying to accelerate and streamline their cloud projects, a lot to consider. How do you all help them do that? Monty, let's go to you. >> Yeah, we keep saying data, data, what is it really? It's ones and zeros. In this day and age, everything we see, we touch, we do, we either use data, or we create data, and then that... >> Savannah: We are data quite literally. >> We literally are data. And so then what you end up with is all these disparate data silos and different applications with different data, and how do you bring all that together? And that's where customers really struggle. And what we do is we bring it all together, and we make it actionable for the customer. We make it very simple for them to take the data, use it for the outcomes that they're looking for in their business initiatives. >> Expand on that. What do you mean make it actionable? Do you tag it? Do you organize it in some way? What's different about your approach? >> I mean, it's a really flexible platform. And I think we're part of a broader ecosystem. Even internally, we are a data driven company. Coming into the company in April, I was able to come in and get this realtime view of like, "Hey, here's where our teams are." And it's all in front of me in a Tableau dashboard that's populated from Talend integration, bringing data out of our different systems, different systems like Workday where we're giving offers out to people. And so everything from managing headcount to where our AWS spend is, all of that stuff. >> Now, we've heard a lot of talk about data and in fact the keynote yesterday that was focused mainly on data and getting data out of silos. How do you play with AWS in that role? Because AWS has other data integration partners. >> Sam: For sure. >> What's different about your relationship? Yeah. >> Go ahead. >> Yeah, we've had a strong relationship with AWS for many years now. We've got more than 80 connectors into the different AWS services. So we're not new to the AWS game. We align with the sales teams, we align with the partner teams, and then of course, we align with all the different business units and verticals so that we can enact that co-sell motion together with AWS. >> Sam: Yeah. And I think from our product standpoint, again, just being a hyper flexible platform, being able to put, again, any different type of source of data, to any type of different destination, so things like Redshift, being able to bring data into those cloud data warehouses is really how we do that. And then I think we have between bringing data from A to B, we're also able to do that along a number of different dimensions. Whether that's just like, "Hey, we just need to do this once a day to batch, all the way down to event driven things, streaming and the like. >> That customization must be really valuable for your customers as well. So one of the big themes of the show has been cost reduction. Obviously with the economic times as we're potentially dipping our toes into as well, is just in general, always wanting to increase margins. How do you help customers cut cost? >> Well, it's cost cutting, but it's also speed to market. The faster you can get a product to market, the faster you can help your customers. Let's say healthcare life sciences, pharmaceutical companies, patient outcomes. >> Great and timely example there. >> Patient outcomes, how do they get drugs to market quicker? Well, AstraZeneca leveraged our platform along with AWS. And they even said >> Cool. >> for every dollar that they spend on data initiatives, they get $40 back. That's a billion dollars >> Wow. >> savings by getting a drug to market one month faster. >> Everybody wins. >> How do you accelerate that process? >> Well, by giving them the right data, taking all the massive data that I mentioned, siloed in everywhere, and making it so that the data scientists can take all of this data and make use of it, makes sense of it, and move their drug production along much quicker. >> Yeah. And I think there's other things too like being very flexible in the way that it's deployed. Again, I think like you have this historical story of like, it takes forever for data to get updated, to get put together. >> Savannah: I need it now. And in context. >> And I think where we're coming from is almost more of a developer focus where your jobs are able to be deployed in any way you want. If you want to containerize those, you want to scale them, you need to schedule them that way. We plug into a lot of different ecosystems. I think that's a differentiation as well. >> I want to hang out on this one just for a second 'cause it's such a great customer success story and so powerful. I mean, in VC land, if you can take a dollar and make two, they'll give you a 10x valuation, 40. That is so compelling. I mean, do you think other customers could expect that kind of savings? A billion dollars is nothing to laugh at especially when we're talking about developing a vaccine. Yeah, go for it, Sam. >> It really depends on the use case. I think what we're trying to do is being able to say, "Hey, it's not just about cost cutting, but it's about tailoring the offerings." We have other customers like major fast food vendors. They have mobile apps and when you pull up that mobile app and you're going to do a delivery, they want to be able to have a customized offering. And it's not like mass market, 20% off. It's like, they want to have a very tailored offer to that customer or to that person that's pulling open that app. And so we're able to help them architect and bring that data together so that it's immediately available and reliable to be able to give those promotions. >> We had ARP on the show yesterday. We're talking about 50 million subscribers and how they customize each one of their experiences. We all want it to be about us. We don't want that generic at... Yeah, go for it, Paul. >> Oh, okay. >> Yeah. >> Well, I don't want to break break the rhythm here, but one area where you have differentiated, about two years ago you introduced something called the trust score. >> Sam: Yeah. >> Can you explain what that is and how that has resonated with your customers? >> Yeah, let's talk about this. >> Yeah, the thing about the trust score is, how many times have you gotten a set of data? And you look at it and you say, "Where did you get this data? Something doesn't look right here." And with the trust score, what we're able to do is quantify and value the different attributes of the data. Whether it's how much this is being used. We can profile the data, and we have a trust score that runs over time where you can actually then look at each of these data sets. You can look at aggregates of data sets to then say... If you're the data engineer, you can say, "Oh my, something has gone wrong with this particular dataset." Go in, quickly pull up the data. You can see if some third party integration has polluted your data source. I mean, this happens all the time. And I think if you sort of compare this to the engineering world, you're always looking to solve those problems sooner, earlier in the chain. You don't want your consumer calling you saying, "Hey, I've got a problem with the data, or I've got a problem- >> You don't want them to know there was ever a problem in theory. >> Yeah, the trust score helps those data engineers and those people that are taking care of the data address those problems sooner. >> How much data does somebody need to be able to get to the point where they can have a trust score? If you know what I'm trying to say. How do we train that? >> I mean, it can be all the way from just like a single data source that's getting updated, all the way to very large complex ones. That's where we've introduced this hierarchy of data sets. So it's not just like, "Hey, you've got a billion data sources here and here are the trust scores." But it's like, you can actually architect this to say like, "Okay, well, I have these data sets that belong to finance." And then finance will actually get, "Here's the trust score for these data sets that they rely on." >> What causes datasets to become untrustworthy? >> Yeah. Yeah. I mean, it happens all the time. >> A of different things, right? >> In my history, in the different companies that I've been at, on the product side, we have seen different integrations that maybe somebody changes something. In upstream, some of those integrations can actually be quite brittle. And as a consumer of that data, it's not necessarily your fault, but that data ends up getting put into your production database. All of a sudden your data engineering team is spending two days unwinding those transactions, fixing the data that's in there. And all the while, that bad data that's in your production system, is causing a problem for somebody that is ultimately relying on that. >> Is that usually a governance problem? >> I think governance is probably a separate set of constraints. This is sort of the tension between wanting to get all of the data available to your consumers versus wanting to have the quality around it as well. >> It's tough balance. And I think that it's really interesting. Everybody wants great data, and you could be making decisions that affect people's wellness, quite frankly. >> For sure. >> Very dramatically if you're ill-informed. So that's very exciting. >> To your point, we are all data. So if the data is bad, we're not going to get the outcomes that we want ultimately, >> I know. We certainly want the best outcomes for ourselves. >> We track that data health for its entire life cycle throughout the process. >> That's cool. And that probably increases your confidence in the trust score as well 'cause you're looking at so much data all the time. You got a smart thing going on over here. I like it. I like it a lot. >> We believe in it and so does AWS because they are a strong partner of ours, and so do customers. I think we mentioned we've had some phenomenal customer conversations along with- >> What a success story and case study. I want to dust your shoulders off right now if I wasn't tethered in. That's super impressive. So what's next for you all? >> Yeah, so I think we're going to continue down this path of data health and data governance. Again, I kind of talked about the... you're talking about data health being this differentiator on top of just moving the data around and being really good at that. I think you're also going to have different things around country level or state level governance, literal laws that you need to comply with. And so like- >> Savannah: CCPA- >> I mean, a long list- >> Oodles. Yeah. Yeah, yeah, yeah. >> I think we're going to be doing some interesting things there. We are continuing to proliferate the sources of data that we connect to. We're always looking for the latest and greatest things to put the data into. I think you're going to see some interesting things come out of that too. >> And we continue to grow our relationship with AWS, our already strong relationship. So you can procure Talend products to the AWS marketplace. We just announced Redshift serverless support for Talend. >> All their age. >> Which sounds amazing, but because we've been doing this for so long with AWS, dirty little secret, that was easy for us to do because we're already doing all this stuff. So we made the announcement and everyone was like, "Congratulations." Like, "Thanks." >> Look at you all. Full of the humble brags. I love it. >> Talend has gone through some twists and turns over the last couple of years. Company went private, was purchased by Thoma Bravo about a year and a half ago. At that time, your CEO said that it was a chance to really refocus the company on some core strategic initiatives and move forward. Both of you joined obviously after that happened. But what did you see about sort of the new Talend that attracted you, made you want to come over here? >> For sure. Yeah. I think, when I got a chance to talk to the board and talk to Chris, our chair, we talked about there being the growth thesis behind it. So I think Thoma been a great partner to Talend. I think we're able to do some things internally that would be I think, fairly challenging for companies that are in the public markets right now. I think especially, just a lot of pressure on different prices and the cost capital and all of that. >> Right now. >> That was a really casual way of stating that. But yeah, just a little pressure. >> Little bit of pressure. And who knows? Who knows how long that's going to last, right? But I think we've got a great board in place. They've been very strong strategic partner for us talking about all the different ways that we can grow. I think it's been a good partner for us- >> One of the strengths of Thoma's strategy is synergy between the companies they've acquired. >> Oh, for sure. >> They've acquired about 40 software companies. Are you seeing synergy? You talk to those other companies a lot? >> Yeah, so I have an operating partner. I talk with him on a weekly, sometimes daily basis. If we have questions or like, "Hey, what are you seeing in this space?" We can get plugged in to advisors very quickly. I think it's been a very helpful thing where... otherwise, you're relying on your personal network or things like that. >> This is why Monty was saying it was easy for you guys to go serverless. >> And we keep talking about trust, but in this case, Thoma Bravo really trusts our senior leadership team to make the right decisions that Sam and I are here making as we move forward. It's a great relationship. >> Sam: A good team. >> It sounds like it. All the love. I can feel the love even from you guys talking about it, it's genuine. You're not just getting paid to show this. That's fantastic. >> Are we getting paid for this or... >> Yeah. (Savannah giggling) (Paul laughing) I mean, some folks in the audience are probably going to want your autograph after this, although you get that a lot- >> Pictures are available after- >> Yeah, selfies are 10 bucks. That's how I get my boos budget. So last question for you. We have a challenge here on the theCUBE re:invent. We're looking for your 32nd hot take. Think of it as your thought leadership sizzle reel. Biggest takeaway, key themes from the show or looking forward into 2023? Sam, you're ready to rock, go. >> Yeah, totally. >> I think you're going to continue to hear the tension between being able to bring the data to the masses versus the simplicity and being able to do that in a way that is compliant with all the different laws, and then clean data. It's like a lot of different challenges that arise when you do this at scale. And so I think if you look at the things that AWS is announcing, I think you look at any sort of vendor in the data space are announcing, you see them sort of coming around to that set of ideas. Gives me a lot of confidence in the direction that we're going that we're doing the right stuff and we're meeting customers and prospects and partners, and everybody is like... We kind of get into this conversation and I'll say, "Yeah, that's it. We want to get involved in that." >> You can really feel the momentum. Yeah, it's true. It's great. What about you, Monty? >> I mean, I don't need 30 seconds. I mentioned it. >> Great. >> Between Talend and AWS, we're aligned from the sales teams to the product teams, the partner teams and the alliances. We're just moving forward and growing this relationship. >> I love it. That was perfect. And on that note, Sam, Monty, thank you so much for joining us. >> Yeah, thanks for having us. >> I'm sure your careers are going to continue to be rad at Talend and I can't wait to continue the conversation. >> Sam: Yeah, it's a great team. >> Yeah, clearly. I mean, look at you two. If you're any representation of the culture over there, they're doing something great. (Monty laughing) I thank all of you for tuning in to our nearly... Well, shoot. I think now over 100 interviews at AWS Reinvent in Sin City. We are hanging out here. Paul and I've got a couple more for you. So we hope to see you tuning in with Paul Gillin. I'm Savannah Peterson. You're watching theCUBE, the leader in high tech coverage. (upbeat music)

(lively music) >> Good afternoon cloud community and welcome back to beautiful Las Vegas, Nevada. We are here at AWS re:Invent, day four of our wall to wall coverage. It is day four in the afternoon and we are holding strong. I'm Savannah Peterson, joined by my fabulous co-host Paul Gillen. Paul, how you doing? >> I'm doing well, fine Savannah. You? >> You look great. >> We're in the home stretch here. >> Yeah, (laughs) we are. >> You still look fresh as a daisy. I don't know how you do it. >> (laughs) You're too kind. You're too kind, but I'm vain enough to take that compliment. I'm very excited about the conversation that we're going to have up next. We get to get a little DevRel and we got a little swagger on the stage. Welcome, Austin. How you doing? >> Hey, great to be here. Thanks for having me. >> Savannah: Yeah, it's our pleasure. How's the show been for you so far? >> Busy, exciting. Feels a lot like, you know it used to be right? >> Yeah, I know. A little reminiscent of the before times. >> Well, before times. >> Before we dig into the technical stuff, you're the most intriguingly dressed person we've had on the show this week. >> Austin: I feel extremely underdressed. >> Well, and we were talking about developer fancy. Talk to me a little bit about your approach to fashion. Wasn't expecting to lead with this, but I like this but I like this actually. >> No, it's actually good with my PR. You're going to love it. My approach, here's the thing, I give free advice all the time about developer relations, about things that work, have worked, and don't work in community and all that stuff. I love talking about that. Someone came up to me and said, "Where do you get your fashion tips from? What's the secret Discord server that I need to go on?" I'm like, "I will never tell." >> Oh, okay. >> This is an actual trait secret. >> Top secret. Wow! Talk about. >> If someone else starts wearing the hat, then everyone's going to be like, "There's so many white guys." Look, I'm a white guy with a beard that works in technology. >> Savannah: I've never met one of those. >> Exactly, there's none of them at all. So, you have to do something to kind stand out from the crowd a little bit. >> I love it, and it's a talk trigger. We're talking about it now. Production team loved it. It's fantastic. >> It's great. >> So your DevRel for Lightstep, in case the audience isn't familiar tell us about Lightstep. >> So Lightstep is a cloud native observability platform built at planet scale, and it powers observability at some places you've heard of like Spotify, GitHub, right? We're designed to really help developers that are working in the cloud with Kubernetes, with these huge distributed systems, understand application performance and being able to find problems, fix problems. We're also part of the ServiceNow family and as we all know ServiceNow is on a mission to help the world of work work better by powering digital transformation around IT and customer experiences for their many, many, many global 2000 customers. We love them very much. >> You know, it's a big love fest here. A lot of people have talked about the collaboration, so many companies working together. You mentioned unified observability. What is unified observability? >> So if you think about a tradition, or if you've heard about this traditional idea of observability where you have three pillars, right? You have metrics, and you have logs, and you have traces. All those three things are different data sources. They're picked up by different tools. They're analyzed by different people for different purposes. What we believe and what we're working to accomplish right now is to take all that and if you think those pillars, flip 'em on their side and think of them as streams of data. If we can take those streams and integrate them together and let you treat traces and metrics and logs not as these kind of inviolate experiences where you're kind of paging between things and going between tab A to tab B to tab C, and give you a standard way to query this, a standard way to display this, and letting you kind of find the most relevant data, then it really unlocks a lot of power for like developers and SREs to spend less time like managing tools. You know, figuring out where to build their query or what dashboard to check, more just being able to like kind of ask a question, get an answer. When you have an incident or an outage that's the most important thing, right? How quickly can you get those answers that you need so that you can restore system health? >> You don't want to be looking in multiple spots to figure out what's going on. >> Absolutely. I mean, some people hear unified observability and they go to like tool consolidation, right? That's something I hear from a lot of our users and a lot of people in re:Invent. I'll talk to SREs, they're like, "Yeah, we've got like six or seven different metrics products alone, just on services that they cover." It is important to kind of consolidate that but we're really taking it a step lower. We're looking at the data layer and trying to say, "Okay, if the data is all consistent and vendor neutral then that gives you flexibility not only from a tool consolidation perspective but also you know, a consistency, reliability. You could have a single way to deploy your observability out regardless of what cloud you're on, regardless if you're using Kubernetes or Fargate or whatever else. or even just Bare Metal or EC2 Bare Metal, right? There's been so much historically in this space. There's been a lot of silos and we think that unify diversability means that we kind of break down those silos, right? The way that we're doing it primarily is through a project called OpenTelemetry which you might have heard of. You want to talk about that in a minute? . >> Savannah: Yeah, let's talk about it right now. Why don't you tell us about it? Keep going, you're great. You're on a roll. >> I am. >> Savannah: We'll just hang out over here. >> It's day four. I'm going to ask the questions and answer the questions. (Savannah laughs) >> Yes, you're right. >> I do yeah. >> Open Tele- >> OpenTelemetry . >> Explain what OpenTelemetry is first. >> OpenTelemetry is a CNCF project, Cloud Native Computing Foundation. The goal is to make telemetry data, high quality telemetry data, a builtin feature of cloud native software right? So right now if you wanted to get logging data out, depending on your application stack, depending on your application run time, depending on language, depending on your deployment environment. You might have a lot... You have to make a lot of choices, right? About like, what am I going to use? >> Savannah: So many different choices, and the players are changing all the time. >> Exactly, and a lot of times what people will do is they'll go and they'll say like, "We have to use this commercial solution because they have a proprietary agent that can do a lot of this for us." You know? And if you look at all those proprietary agents, what you find very quickly is it's very commodified right? There's no real difference in what they're doing at a code level and what's stopped the industry from really adopting a standard way to create this logs and metrics and traces, is simply just the fact that there was no standard. And so, OpenTelemetry is that standard, right? We've got dozens of companies many of them like very, many of them here right? Competitors all the same, working together to build this open standard and implementation of telemetry data for cloud native software and really any software right? Like we support over 12 languages. We support Kubernetes, Amazon. AWS is a huge contributor actually and we're doing some really exciting stuff with them on their Amazon distribution of OpenTelemetry. So it's been extremely interesting to see it over the past like couple years go from like, "Hey, here's this like new thing that we're doing over here," to really it's a generalized acceptance that this is the way of the future. This is what we should have been doing all along. >> Yeah. >> My opinion is there is a perception out there that observability is kind of a commodity now that all the players have the same set of tools, same set of 15 or 17 or whatever tools, and that there's very little distinction in functionality. Would you agree with that? >> I don't know if I would characterize it that way entirely. I do think that there's a lot of duplicated effort that happens and part of the reason is because of this telemetry data problem, right? Because you have to wind up... You know, there's this idea of table stakes monitoring that we talk about right? Table stakes monitoring is the stuff that you're having to do every single day to kind of make sure your system is healthy to be able to... When there's an alert, gets triggered, to see why it got triggered and to go fix it, right? Because everyone has the kind of work on that table stake stuff and then build all these integrations, there's very little time for innovation on top of that right? Because you're spending all your time just like working on keeping up with technology. >> Savannah: Doing the boring stuff to make sure the wheels don't fall off, basically. >> Austin: Right? What I think the real advantage of OpenTelemetry is that it really, from like a vendor perspective, like it unblocks us from having to kind of do all this repetitive commodified work. It lets us help move that out to the community level so that... Instead of having to kind of build, your Kubernetes integration for example, you can just have like, "Hey, OpenTelemetry is integrated into Kubernetes and you just have this data now." If you are a commercial product, or if you're even someone that's interested in fixing a, scratching a particular itch about observability. It's like, "I have this specific way that I'm doing Kubernetes and I need something to help me really analyze that data. Well, I've got the data now I can just go create a project. I can create an analysis tool." I think that's what you'll see over time as OpenTelemetry promulgates out into the ecosystem is more people building interesting analysis features, people using things like machine learning to analyze this large amount, large and consistent amount of OpenTelemetry data. It's going to be a big shakeup I think, but it has the potential to really unlock a lot of value for our customers. >> Well, so you're, you're a developer relations guy. What are developers asking for right now out of their observability platforms? >> Austin: That's a great question. I think there's two things. The first is that they want it to just work. It's actually the biggest thing, right? There's so many kind of... This goes back to the tool proliferation, right? People have too much data in too many different places, and getting that data out can still be really challenging. And so, the biggest thing they want is just like, "I want something that I can... I want a lot of these questions I have to ask, answered already and OpenTelemetry is going towards it." Keep in mind it's the project's only three years old, so we obviously have room to grow but there are people running it in production and it works really well for them but there's more that we can do. The second thing is, and this isn't what really is interesting to me, is it's less what they're asking for and more what they're not asking for. Because a lot of the stuff that you see people, saying around, "Oh, we need this like very specific sort of lower level telemetry data, or we need this kind of universal thing." People really just want to be able to get questions or get questions answered, right? They want tools that kind of have these workflows where you don't have to be an expert because a lot of times this tooling gets locked behind sort of is gate kept almost in a organization where there are teams that's like, "We're responsible for this and we're going to set it up and manage it for you, and we won't let you do things outside of it because that would mess up- >> Savannah: Here's your sandbox and- >> Right, this is your sandbox you can play in and a lot of times that's really useful and very tuned for the problems that you saw yesterday, but people are looking at like what are the problems I'm going to get tomorrow? We're deploying more rapidly. We have more and more intentional change happening in the system. Like it's not enough to have this reactive sort of approach where our SRE teams are kind of like or this observability team is building a platform for us. Developers want to be able to get in and have these kind of guided workflows really that say like, "Hey, here's where you're starting at. Let's get you to an answer. Let's help you find the needle in the haystack as it were, without you having to become a master of six different or seven different tools." >> Savannah: Right, and it shouldn't be that complicated. >> It shouldn't be. I mean we've certainly... We've been working on this problem for many years now, starting with a lot of our team that started at Google and helped build Google's planet scale monitoring systems. So we have a lot of experience in the field. It's actually one... An interesting story that our founder or now general manager tells BHS, Ben Sigelman, and he told me this story once and it's like... He had built this really cool thing called Dapper that was a tracing system at Google, and people weren't using it. Because they were like, "This is really cool, but I don't know how to... but it's not relevant to me." And he's like, the one thing that we did to get to increase usage 20 times over was we just put a link. So we went to the place that people were already looking for that data and we added a link that says, "Hey, go over here and look at this." It's those simple connections being able to kind of draw people from like point A to point B, take them from familiar workflows into unfamiliar ones. You know, that's how we think about these problems right? How is this becoming a daily part of someone's usage? How is this helping them solve problems faster and really improve their their life? >> Savannah: Yeah, exactly. It comes down to quality of life. >> Warner made the case this morning that computer architecture should be inherently event-driven and that we are moving toward a world where the person matters less than what the software does, right? The software is triggering events. Does this complicate observability or simplify it? >> Austin: I think that at the end of the day, it's about getting the... Observability to me in a lot of ways is about modeling your system, right? It's about you as a developer being able to say this is what I expect the system to do and I don't think the actual application architecture really matters that much, right? Because it's about you. You are building a system, right? It can be event driven, can be support request response, can be whatever it is. You have to be able to say, "This is what I expect to... For these given inputs, this is the expected output." Now maybe there's a lot of stuff that happens in the middle that you don't really care about. And then, I talk to people here and everyone's talking about serverless right? Everyone... You can see there's obviously some amazing statistics about how many people are using Lambda, and it's very exciting. There's a lot of stuff that you shouldn't have to care about as a developer, but you should care about those inputs and outputs. You will need to have that kind of intermediate information and understand like, what was the exact path that I took through this invented system? What was the actual resources that were being used? Because even if you trust that all this magic behind the scenes is just going to work forever, sometimes it's still really useful to have that sort of lower level abstraction, to say like, "Well, this is what actually happened so that I can figure out when I deployed a new change, did I make performance better or worse?" Or being able to kind of segregate your data out and say like... Doing AB testing, right? Doing canary releases, doing all of these things that you hear about as best practices or well architected applications. Observability is at the core of all that. You need observability to kind of do any of, ask any of those higher level interesting questions. >> Savannah: We are here at ReInvent. Tell us a little bit more about the partnership with AWS. >> So I would have to actually probably refer you to someone at Service Now on that. I know that we are a partner. We collaborate with them on various things. But really at Lightstep, we're very focused on kind of the open source part of this. So we work with AWS through the OpenTelemetry project, on things like the AWS distribution for OpenTelemetry which is really... It's OpenTelemetry, again is really designed to be like a neutral standard but we know that there are going to be integrators and implementers that need to package up and bundle it in a certain way to make it easy for their end users to consume it. So that's what Amazon has done with ADOT which is the shortening for it. So it's available in several different ways. You can use it as like an SDK and drop it into your application. There's Lambda layers. If you want to get Lambda observability, you just add this extension in and then suddenly you're getting OpenTelemetry data on the other side. So it's really cool. It's been a really exciting to kind of work with people on the AWS side over the past several years. >> Savannah: It's exciting, >> I've personally seen just a lot of change. I was talking to a PM earlier this week... It's like, "Hey, two years ago I came and talked to you about OpenTelemetry and here we are today. You're still talking about OpenTelemetry." And they're like, "What changes?" Our customers have started coming to us asking for OpenTelemetry and we see the same thing now. >> Savannah: Timing is right. >> Timing is right, but we see the same thing... Even talking to ServiceNow customers who are... These very big enterprises, banks, finance, healthcare, whatever, telcos, it used to be... You'd have to go to them and say like, "Let me tell you about distributed tracing. Let me tell you about OpenTelemetry. Let me tell you about observability." Now they're coming in and saying, "Yeah, so we're standard." If you think about Kubernetes and how Kubernetes, a lot of enterprises have spent the past five-six years standardizing, and Kubernetes is a way to deploy applications or manage containerized applications. They're doing the same journey now with OpenTelemetry where they're saying, "This is what we're betting on and we want partners we want people to help us go along that way." >> I love it, and they work hand in hand in all CNCF projects as well that you're talking about. >> Austin: Right, so we're integrated into Kubernetes. You can find OpenTelemetry and things like kept in which is application standards. And over time, it'll just like promulgate out from there. So it's really exciting times. >> A bunch of CNCF projects in this area right? Prometheus. >> Prometheus, yeah. Yeah, so we inter-operate with Prometheus as well. So if you have Prometheus metrics, then OpenTelemetry can read those. It's a... OpenTelemetry metrics are like a super set of Prometheus. We've been working with the Prometheus community for quite a while to make sure that there's really good compatibility because so many people use Prometheus you know? >> Yeah. All right, so last question. New tradition for us here on theCUBE. We're looking for your 32nd hot take, Instagram reel, biggest theme, biggest buzz for those not here on the show floor. >> Oh gosh. >> Savannah: It could be for you too. It could be whatever for... >> I think the two things that are really striking to me is one serverless. Like I see... I thought people were talking about servers a lot and they were talking about it more than ever. Two, I really think it is observability right? Like we've gone from observability being kind of a niche. >> Savannah: Not that you're biased. >> Huh? >> Savannah: Not that you're biased. >> Not that I'm biased. It used to be a niche. I'd have to go niche thing where I would go and explain what this is to people and nowpeople are coming up. It's like, "Yeah, yeah, we're using OpenTelemetry." It's very cool. I've been involved with OpenTelemetry since the jump, since it was started really. It's been very exciting to see and gratifying to see like how much adoption we've gotten even in a short amount of time. >> Yeah, absolutely. It's a pretty... Yeah, it's been a lot. That was great. Perfect soundbite for us. >> Austin: Thanks, I love soundbites. >> Savannah: Yeah. Awesome. We love your hat and your soundbites equally. Thank you so much for being on the show with us today. >> Thank you for having me. >> Savannah: Hey, anytime, anytime. Will we see you in Amsterdam, speaking of KubeCon? Awesome, we'll be there. >> There's some real exciting OpenTelemetry stuff coming up for KubeCon. >> Well, we'll have to get you back on theCUBE. (talking simultaneously) Love that for us. Thank you all for tuning in two hour wall to wall coverage here, day four at AWS re:Invent in fabulous Las Vegas, Nevada, with Paul Gillin. I'm Savannah Peterson and you're watching theCUBE, the leader in high tech coverage. (lively music)

>>Hello, brilliant humans and welcome back to Las Vegas, Nevada, where we are live from the AWS Reinvent Show floor here with the cube. My name is Savannah Peterson, joined with Dave Valante, and we have a very exciting conversation with you. Two, two companies you may have heard of. We've got AWS and Red Hat in the house. Manu and Joel, thank you so much for being here. Love this little fist bump. Started off, that's right. Before we even got rolling, Manu, you said that you wanted this to be the best segment of, of the cubes airing. We we're doing over a hundred segments, so you're gonna have to bring the heat. >>We're ready. We're did go. Are we ready? Yeah, go. We're ready. Let's bring it on. >>We're ready. All right. I'm, I'm ready. Dave's ready. Let's do it. How's the show going for you guys real quick before we dig in? >>Yeah, I think after Covid, it's really nice to see that we're back into the 2019 level and, you know, people just want to get out, meet people, have that human touch with each other, and I think a lot of trust gets built as a functional that, so it's super amazing to see our partners and customers here at Reedman. Yeah, >>And you've got a few in the house. That's true. Just a few maybe, maybe a couple >>Very few shows can say that, by the way. Yeah, it's maybe a handful. >>I think one of the things we were saying, it's almost like the entire Silicon Valley descended in the expo hall area, so >>Yeah, it's >>For a few different reasons. There's a few different silicon defined. Yeah, yeah, yeah. Don't have strong on for you. So far >>It's, it's, it is amazing. It's the 10th year, right? It's decade, I think I've been to five and it's, it grows every single year. It's the, you have to be here. It's as simple as that. And customers from every single industry are here too. You don't get, a lot of shows have every single industry and almost every single location around the globe. So it's, it's a must, must be >>Here. Well, and the personas evolved, right? I was at reinvent number two. That was my first, and it was all developers, not all, but a lot of developers. And today it's a business mix, really is >>Totally, is a business mix. And I just, I've talked about it a little bit down the show, but the diversity on the show floor, it's the first time I've had to wait in line for the ladies' room at a tech conference. Almost a two decade career. It is, yeah. And it was really refreshing. I'm so impressed. So clearly there's a commitment to community, but also a commitment to diversity. Yeah. And, and it's brilliant to see on the show floor. This is a partnership that is robust and has been around for a little while. Money. Why don't you tell us a little bit about the partnership here? >>Yes. So Red Hand and AWS are best friends, you know, forever together. >>Aw, no wonder we got the fist bumps and all the good vibes coming out. I know, it's great. I love that >>We have a decade of working together. I think the relationship in the first phase was around running rail bundled with E two. Sure. We have about 70,000 customers that are running rail, which are running mission critical workloads such as sap, Oracle databases, bespoke applications across the state of verticals. Now, as more and more enterprise customers are finally, you know, endorsing and adopting public cloud, I think that business is just gonna continue to grow. So a, a lot of progress there. The second titration has been around, you know, developers tearing Red Hat and aws, Hey, listen, we wanna, it's getting competitive. We wanna deliver new features faster, quicker, we want scale and we want resilience. So just entire push towards devs containers. So that's the second chapter with, you know, red Hat OpenShift on aws, which launched as a, a joint manage service in 2021 last year. And I think the third phase, which you're super excited about, is just bringing the ease of consumption, one click deployment, and then having our customers, you know, benefit from the joint committed spend programs together. So, you know, making sure that re and Ansible and JBoss, the entire portfolio of Red Hat products are available on AWS marketplace. So that's the 1, 2, 3, it of our relationship. It's a decade of working together and, you know, best friends are super committed to making sure our customers and partners continue successful. >>Yeah, that he said it, he said it perfectly. 2008, I know you don't like that, but we started with Rel on demand just in 2008 before E two even had a console. So the partnership has been there, like Manu says, for a long time, we got the partnership, we got the products up there now, and we just gotta finalize that, go to market and get that gas on the fire. >>Yeah. So Graviton Outpost, local zones, you lead it into all the new stuff. So that portends, I mean, 2008, we're talking two years after the launch of s3. >>That's right. >>Right. So, and now look, so is this a harbinger of things to come with these new innovations? >>Yeah, I, I would say, you know, the innovation is a key tenant of our partnership, our relationship. So if you look at from a product standpoint, red Hat or Rel was one of the first platforms that made a support for graviton, which is basically 40% better price performance than any other distribution. Then that translated into making sure that Rel is available on all of our regions globally. So this year we launched Switzerland, Spain, India, and Red Hat was available on launch there, support for Nitro support for Outpost Rosa support on Outpost as well. So I think that relationship, that innovation on the product side, that's pretty visible. I think that innovation again then translates into what we are doing on marketplace with one click deployments we spoke about. I think the third aspect of the know innovation is around making sure that we are making our partners and our customers successful. So one of the things that we've done so far is Joe leads a, you know, a black belt team that really goes into each customer opportunity, making sure how can we help you be successful. We launched and you know, we should be able to share that on a link. After this, we launched like a big playlist, which talks about every single use case on how do you get successful and running OpenShift on aws. So that innovation on behalf of our customers partners to make them successful, that's been a key tenant for us together as >>Well. That's right. And that team that Manu is talking about, we're gonna, gonna 10 x that team this year going into January. Our fiscal yield starts in January. Love that. So yeah, we're gonna have a lot of no hiring freeze over here. Nope. No ma'am. No. Yeah, that's right. Yeah. And you know what I love about working with aws and, and, and Manu just said it very, all of that's customer driven. Every single event that we, that he just talked about in that timeline, it's customer driven, right? Customers wanted rail on demand, customers want JBoss up in the cloud, Ansible this week, you know, everything's up there now. So it's just getting that go to market tight and we're gonna, we're gonna get that done. >>So what's the algorithm for customer driven in terms of taking the input? Because if every customers saying, Hey, I this a >>Really similar >>Question right up, right? I, that's what I want. And if you know, 95% of the customers say it, Jay, maybe that's a good idea. >>Yeah, that's right. Trends. But >>Yeah. You know, 30% you might be like, mm, you know, 20%, you know, how do you guys decide when to put gas on the fire? >>No, that, I think, as I mentioned, there are about 70,000 large customers that are running rail on Easy Two, many of these customers are informing our product strategy. So we have, you know, close to about couple of thousand power users. We have customer advisory booths, and these are the, you know, customers are informing us, Hey, let's get all of the Red Hat portfolio and marketplace support for graviton, support for Outpost. Why don't we, why are we not able to dip into the consumption committed spend programs for both Red Hat and aws? That's right. So it's these power users both at the developer level as well as the guys who are actually doing large commercial consumption. They are the ones who are informing the roadmap for both Red Hat and aws. >>But do, do you codify the the feedback? >>Yeah, I'm like, I wanna see the database, >>The, I think it was, I don't know, it was maybe Chasy, maybe it was Besos, that that data beats intuition. So do you take that information and somehow, I mean, it's global, 70,000 customers, right? And they have different weights, different spending patterns, different levels of maturity. Yeah. Do you, how do you codify that and then ultimately make the decision? Yeah, I >>If, I mean, well you, you've got the strategic advisory boards, which are made up of customers and partners and you know, you get, you get a good, you gotta get a good slice of your customer base to get, and you gotta take their feedback and you gotta do something with it, right? That's the, that's the way we do it and codify it at the product level, I'm sure open source. That's, that's basically how we work at the product level, right? The most elegant solution in open source wins. And that's, that's pretty much how we do that at the, >>I would just add, I think it's also just the implicit trust that the two companies had built with each other, working in the trenches, making our customers and partners successful over the last decade. And Alex, give an example. So that manifests itself in context of like, you know, Amazon and Red Hat just published the entire roadmap for OpenShift. What are the new features that are becoming over the next six to nine to 12 months? It's open source available on GitHub. Customers can see, and then they can basically come back and give feedback like, Hey, you know, we want hip compliance. We just launched. That was a big request that was coming from our >>Customers. That is not any process >>Also for Graviton or Nvidia instances. So I I I think it's a, >>Here's the thing, the reason I'm pounding on this is because you guys have a pretty high hit rate, and I think as a >>Customer, mildly successful company >>As, as a customer advocate, the better, you know, if, if you guys make bets that pay off, it's gonna pay off for customers. Right. And because there's a lot of failures in it. Yeah. I mean, let's face it. That's >>Right. And I think, I think you said the key word bets. You place a lot of small bets. Do you have the, the innovation engine to do that? AWS is the perfect place to place those small bets. And then you, you know, pour gas on the fire when, when they take off. >>Yeah, it's a good point. I mean, it's not expensive to experiment. Yeah. >>Especially in the managed service world. Right? >>And I know you love taking things to market and you're a go to market guy. Let's talk gtm, what's got your snow pumped about GTM for 2023? >>We, we are gonna, you know, 10 x the teams that's gonna be focused on these products, right? So we're gonna also come out with a hybrid committed spend program for our customers that meet them where they want to go. So they're coming outta the data center going into a cloud. We're gonna have a nice financial model for them to do that. And that's gonna take a lot of the friction out. >>Yeah. I mean, you've nailed it. I, I think the, the fact that now entire Red Hat portfolio is available on marketplace, you can do it on one click deployment. It's deeply integrated with Amazon services and the most important part that Joel was making now customers can double dip. They can drive benefit from the consumption committed spend programs, both from Red Hat and from aws, which is amazing. Which is a game changer That's right. For many of our large >>Customers. That's right. And that, so we're gonna, we're gonna really go to town on that next year. That's, and all the, all the resources that I have, which are the technology sellers and the sas, you know, the engineers we're growing this team the most out that team. So it's, >>When you say 10 x, how many are you at now? I'm >>Curious to see where you're headed. Tell you, okay. There's not right? Oh no, there's not one. It's triple digit. Yeah, yeah. >>Today. Oh, sweet. Awesome. >>So, and it's a very sizable team. They're actually making sure that each of our customers are successful and then really making sure that, you know, no customer left behind policy. >>And it's a great point that customers love when Amazonians and Red Hats show up, they love it and it's, they want to get more of it, and we're gonna, we're gonna give it to 'em. >>Must feel great to be loved like that. >>Yeah, that's right. Yeah. Yeah. I would say yes. >>Seems like it's safe to say that there's another decade of partnership between your two companies. >>Hope so. That's right. That's the plan. >>Yeah. And I would say also, you know, just the IBM coming into the mix here. Yeah. I, you know, red Hat has informed the way we have turned around our partnership with ibm, essentially we, we signed the strategic collaboration agreement with the company. All of IBM software now runs on Rosa. So that is now also providing a lot of tailwinds both to our rail customers and as well as Rosa customers. And I think it's a very net creative, very positive for our partnership. >>That's right. It's been very positive. Yep. Yeah. >>You see the >>Billboards positive. Yeah, right. Also that, that's great. Great point, Dave. Yep. We have a, we have a new challenge, a new tradition on the cube here at Reinvent where we're, well, it's actually kind of a glamor moment for you, depending on how you leverage it. We're looking for your 32nd hot take your Instagram reel, your sizzle thought leadership, biggest takeaway, most important theme from this year's show. I know you want, right, Joel? I mean, you TM boy, I feel like you can spit the time. >>Yeah. It is all about Rosa for us. It is all in on that, that's the native OpenShift offering on aws and that's, that's the soundbite we're going go to town with. Now, I don't wanna forget all the other products that are in there, but Rosa is a, is a very key push for us this year. >>Fantastic. All right. Manu. >>I think our customers, it's getting super competitive. Our customers want to innovate just a >>Little bit. >>The enterprise customers see the cloud native companies. I wanna do what these guys are doing. I wanna develop features at a fast clip. I wanna scale, I wanna be resilient. And I think that's really the spirit that's coming out. So to Joel's point, you know, move to worlds containers, serverless, DevOps, which was like, you know, aha, something that's happening on the side of an enterprise is not becoming mainstream. The business is demanding it. The, it is becoming the centerpiece in the business strategy. So that's been really like the aha. Big thing that's happening here. >>Yeah. And those architectures are coming together, aren't they? That's correct. Right. You know, VMs and containers, it used to be one architecture and then at the other end of the spectrum is serverless. People thought of those as different things and now it's a single architecture and, and it's kind of right approach for the right job. >>And, and a compliments say to Red Hat, they do an incredible job of hiding that complexity. Yeah. Yes. And making sure that, you know, for example, just like, make it easier for the developers to create value and then, and you know, >>Yeah, that's right. Those, they were previously siloed architectures and >>That's right. OpenShift wanna be place where you wanna run containers or virtual machines. We want that to be this Yeah. Single place. Not, not go bolt on another piece of architecture to just do one or the other. Yeah. >>And hey, the hybrid cloud vision is working for ibm. No question. You know, and it's achievable. Yeah. I mean, I just, I've said unlike, you know, some of the previous, you know, visions on fixing the world with ai, hybrid cloud is actually a real problem that you're attacking and it's showing the results. Agreed. Oh yeah. >>Great. Alright. Last question for you guys. Cause it might be kind of fun, 10 years from now, oh, we're at another, we're sitting here, we all look the same. Time has passed, but we are not aging, which is a part of the new technology that's come out in skincare. That's my, I'm just throwing that out there. Why not? What do you guys hope that you can say about the partnership and, and your continued commitment to community? >>Oh, that's a good question. You go first this time. Yeah. >>I think, you know, the, you know, for looking into the future, you need to look into the past. And Amazon has always been driven by working back from our customers. That's like our key tenant, principle number 1 0 1. >>Couple people have said that on this stage this week. Yeah. >>Yeah. And I think our partnership, I hope over the next decade continues to keep that tenant as a centerpiece. And then whatever comes out of that, I think we, we are gonna be, you know, working through that. >>Yeah. I, I would say this, I think you said that, well, the customer innovation is gonna lead us to wherever that is. And it's, it's, it's gonna be in the cloud for sure. I think we can say that in 10 years. But yeah, anything from, from AI to the quant quantum computing that IBM's really pushing behind that, you know, those are, those are gonna be things that hopefully we show up on a, on a partnership with Manu in 10 years, maybe sooner. >>Well, whatever happens next, we'll certainly be covering it here on the cube. That's right. Thank you both for being here. Joel Manu, fantastic interview. Thanks to see you guys. Yeah, good to see you brought the energy. I think you're definitely ranking high on the top interviews. We >>Love that for >>The day. >>Thank >>My pleasure >>Job, guys. Now that you're competitive at all, and thank you all for tuning in to our live coverage here from AWS Reinvent in Las Vegas, Nevada, with Dave Valante. I'm Savannah Peterson. You're watching The Cube, the leading source for high tech coverage.

(upbeat music playing) >> Hey, all you cool cats and kittens, and welcome back to AWS re:Invent. We are live from the show floor, here in fabulous Las Vegas, Nevada. My name is Savannah Peterson, joined by my co-host Paul Gillian. Paul, how you doing? We're now full blown into your first day of AWS re:Invent ever. >> Overwhelmed. >> Overwhelmed! >> Drinking from the fire hose. There's so much going on here. >> Yeah. There really is, isn't there? Anything stood out to you in that fire hose? >> I think the importance of data, hearing about a lot of tools here, a lot of talk about how organizations need to take advantage of the cloud to leverage their data more effectively, that's clearly a theme in the show. Hearing a lot about vertical industries and the move of the cloud into more verticalization which we're going to be talking about here with our next guest, among other things. Monty Bhatia, who's the Vice President of Global Systems Integrators at VMware, a company that really pioneered partnerships with AWS, as well as other cloud providers. And also Ranjit Bawa, the principal, US cloud leader for Deloitte, a company that has been a leader in vertical clouds as well as in cloudefying its customers, if you will. Welcome, thank you both for joining us. >> Thank you very much. >> Thank you for having us. >> We're happy to be here. >> Monty, I just have to say, I know I said it before, I think you might be the best dressed. >> You know, you may have to say it again. I've got to record this and show it to my wife, because she always says that I should wear age appropriate colors, and she thinks yellow and hot pinks are not age appropriate. So I've made a deal with her that when I'm traveling, and everybody else has heard the story, when I'm traveling and she's not around I can wear any colors I want. It is an attention grabber, it is a conversation starter, and I love it. >> I'm all for the talk trigger and you told me you have 32 different sets. >> That's right. >> And you're branded, right? Give us a little lapel peak. >> I am branded. (Monty and Ranjit chuckling) >> Brilliant. We don't always do a fashion segment to open each clip but I just, I couldn't let this pass, Monty- >> Thank you, I appreciate that. >> You're just absolutely, absolutely smashing it. Deloitte and VMware, you've got a unique strategic partnership. Ranjit can you tell me a little bit about that? >> Yeah, absolutely. We've been working together for close to a decade now with VMware. >> Nice. In Techland that might as well be a century. >> That's right. >> It is. (Savannah chuckling) >> And we've had a number of very successful large scale transformations across industries together, particularly as our clients are moving to cloud, which really in our world is a metaphor for modern engineering, modern technology, how tech shows up differently to support the business. So we're really excited about what we've done and where we are going together. >> I want to ask you about the transition that we see going on at AWS really going from being an infrastructure to provider to more of a platform provider for vertical applications for HPC, for AI, for specific uses. Is this a transition that you see your customers- are they applauding this transition? >> Yeah, most certainly, and we saw this coming a while ago, and as does AWS and VMware and others, that for more horizontal clouds we're going to start to move into vertical clouds that support industries and sectors and sub-sectors. So increasingly as we move from IIS to more PaaS and even into SaaS land, that is going to continue. The good news is that AWS has formed a really good foundation and a set of common frameworks that people can use to build upon. And then with VMware as well, we've started to build these vertical clouds and insurance and life sciences and healthcare and all kinds of other sectors, including manufacturing and you know, in our booth here, we have a demo of our manufacturing vertical clouds as well. So we certainly see that the direction of travel and our clients are really egging us on as well. >> So what is VMware's role in building these vertical clouds? Because you're not a vertical, I don't think of you as being a vertical services provider. >> Yeah, so from a VMware standpoint, we're going through a transition ourselves, right? It's a transformation happening at VMware. And while we are traditionally an infrastructure we're a plumbing company, right? We are, we provide all the horizontal space, that's where we need the partnership. So we do have some capability built around industries but that's where our partnership with Deloitte is very important to us because they have all these industry clouds. We have the tech platform that provides that. And then when partnering three way partnerships with you know, hyperscalers like AWS you know we can bring the scale and everything together to serve our customers. So it's very important for us to make use of our technology stack. We have customers in all industries, right? We have huge customer base, and we have customers in all industries, right? And so we want to really create that industry angle, working with our partners like Deloitte to serve those customers and working with, you know, our ecosystem partners ISV partners, hyperscaler partners. Obviously AWS is a big partner of ours and want to bring it all together to serve our customers you know, their journeys, basically. >> Let's hang out there for a second because you you see, you both see extraordinarily large customers across different verticals and industries. Talk about some of the trends that you might be seeing that transcend across all of them. Ranjit, we'll start with you. >> Yeah, it's a great question. You know, certainly more, you know, sort of fundamentally, we see this as a huge opportunity this decade. Many folks that I work with call this the roaring twenties all over again. You know, hopefully it won't end the same way as the last one. But in many ways, every client of ours, across every industry, is going through a huge disruption as they're thinking about the businesses they're in, the products they serve, the segments they support, the client demographics that are changing. So that's one big mega sort of trend. The other one is the rate of change. I think most everybody's dealing with the rate of change of technology, right? You come here last year and this year there are a thousand new services. Every day they release five or seven more and every other, you know, technology provider out there as well. So our clients in general are struggling with how do they embrace and adopt this change quickly. >> Right. >> And today they're not set up for that, right? >> Decision overload too, so much. >> Absolutely. >> That one, and then their ability to be able to absorb this change, right? A typical client of ours, enterprise client, has a three to four year journey to embrace new technology. That's the refresh cycle. But now we see that half life going down to three months and six months. So large part of this transformation is how do you build that muscle to be able to deal with this change that's only going to continue to accelerate. So not only are we helping them think about new products and new businesses, but also how to build this muscle and fundamentally change the way they deliver technology. And that's, I think also a place where our partnership is really valuable. >> It's like your sprint muscles versus your marathon muscles, you know? >> Right. >> You're totally fast, which is an entirely different set. >> Exactly right. >> What about you Monty? >> Yeah, and so from a technology standpoint, also one of the biggest trends that we are seeing, you know, two years ago when you looked at it, you know it was all about hyperscaler, public cloud, cloud first. Now we're seeing more of a multicloud approach, right? We're seeing that pull back in towards hybrid cloud. I know John talks about the- >> The Super cloud. >> The Super cloud, right? >> Yes, one of our favorite- >> I know Deloitte talks about Meta cloud, we talk about cross cloud services. So that's a trend that's coming up. And, and you know, we're, from a VM VMware standpoint we're very well positioned in the multicloud space, you know, our partnership with other hyperscalers, actually all cloud providers and then our partnerships with, you know, system integrators like Deloitte, it is really helping us propel, you know that solution to our customers. And so that's a big trend we're seeing around the multicloud and the modern application space. >> How, I mean the multicloud issue seem to be very hot a couple of years ago to die down, at least with, you know, the amount of coverage that's afforded to it. Is that because customers are less interested in multiple clouds or is it because that's become simply part of the landscape? >> Yeah, well, you know, I think it's there was a recent study done that over 70% of the enterprise customers are inherently multicloud, right? And multicloud just doesn't meet the hyperscalers, right? We take multicloud as the hyperscalers the private cloud, the edge cloud, the industry cloud. They've got data all over the place, right? So inherently, most enterprises are multicloud. They're realizing it now that the, when they're lock-in is an issue with them. And so, you know, over 70% of the hundred customers are actually looking at building that orchestration layer on top of the clouds which can provide them a, you know, a more meaningful and simplified decision making for their cloud workloads. >> And maybe to add to that, John, I think your point about the fascination with multicloud four or five years ago and how that tapered off I think the use case people were solving for back then was to have three different cloud options for the same workload. That they could swap between those three, maybe they could arbitrage on cost, et cetera. That in our view is a fool's errand because it's just the you know, the juice isn't worth the squeeze. But what we are seeing now is for different workloads you want to give people optionality. So you an edge computing workload you're serving a restaurant, you need that to run on a different cloud provider because they have better analytics the better geospatial data, that's fine. But your main core application, we run on a different cloud. So you're still supporting multicloud but you're not confusing the same workload to be trying to run them on multiple clouds at the same time or things of that nature. So I think that's where it's kind of moving towards. >> So I, we've talked a lot about big partnerships. One of the exciting trends at the show is all the new collaboration that's happening. I love that you've been partners for a decade. It shows a long term commitment to the community. If I'm an AWS customer who has not yet taken advantage of your fabulous partnership, what is it about it that makes it so magic? Give me a little bit of the pitch. >> So.. >> Go for it, Monty. You're rolling, I like it. (Monty chuckling) Let's go with it. >> Right. So I think for an AWS customer, so we have, VMware has an offering that we built with AWS VMC on AWS right? I think there is a real value in it. There are specific use cases that create a financial benefit an operational benefit for the customers, right? We've traditionally not done a great job of elevating that message. And that's our goal, right? That's our goal is to make sure that the VMC on AWS offering, it's not a competitive offering to AWS, it's actually a complimentary offering. It helps everybody, it helps the customer, it helps VMware it helps AWS in bringing all these pieces together to solve the customer problems. There are certain use cases that are really good for moving to a native cloud like AWS. There are definitely use cases, there are financial advantages, operational advantages that the customers will get out of doing the VMC on AWS offering. And again, our partnerships with our, you know, most strategic partners, who are bringing the industry expertise on top of it will even accelerate that even faster. >> I know you're not at liberty to talking at length about the Broadcom acquisition but can you offer our listeners any insight into what will be continued, what Broadcom's approach or attitude toward the partnerships that you've already built and how strong those are, how committed they are to continuing them. >> You know, there's things we can share, there's things we cannot share and I'll let Ranjit talk about it, but from our standpoint, I think, you know, know what Broadcom has openly stated, we'll say that again, right? They are looking at this as a very strategic acquisition. From their standpoint, they've made it clear that multicloud and modern applications are two of the big strategic initiatives they want to continue. They've also stated openly that, you know, in order for us to scale, we still need these partnerships. And so the partnerships and the ecosystem that VMware has built, you know, it's going to be looked upon as, you know, something they'll continue to do for at least for the near future. You know, what's going to happen in future, we don't know. But in the near future, they don't want to disrupt the partnership, the channel programs that we've already built, you know? And that's very important to us because that's one of our biggest go-to market routes through the partners. >> And most importantly, that logo isn't changing. So you get to wear all of your- >> Well, yes, I was worried if they change the logo then I have to reorder my T-shirts again. But now, you know, we're good for now. (Monty chuckling) >> We're good for now. You both are such wonderfully seasoned veterans so you don't look it like we talked about earlier, but both of you with 20 plus years of experience in the industry. We're doing a new thing on theCUBE this show, where we're looking for your 30 second hot take. Think of it as your thought leadership sizzle reel. What is the most important story or theme coming out of this year's show? I'll see who looks most ready. Monty looks ready. All right, let's go. >> Well, you know, I, you know, one of the things that I've seen, and I've been coming to re:Invents for quite some time you know, this is my sixth re:Ivent, but I really like the ecosystem story that is now building, right? It used to be from an Amazon standpoint, it used to be always customer obsession, which is still there, but they've added partner obsession now, right? And that's a new thing. That means now they are focusing on the ecosystem, just like we are focusing, just like Deloitte is focusing on ecosystem and that to me is a trend worth talking about. >> I love that. And very holistic and very astute. All right, Ranjit, what about you? >> Well, first I love the energy. It almost feels like there was no pandemic, right? So that's a good reminder- >> We're all ready for that feeling- >> and hopefully we're world beyond what we've been through. I also think, you know to that point, there's a lot more focus on ecosystem plays that move beyond just the less lift and shift with the cloud. But let's be thoughtful about changing the way you serve your clients, the capabilities you want to deliver. And a lot of that is through the ecosystem around client problems and working backwards from clients I think is also amazing. >> Yeah. >> And finally, I'm also always energized by the the team that's here or the folks that are here. I think it's become more pervasive, you know, earlier on it was more CIOs and, you know, senior execs. I think we're seeing a lot more across the organization, which is a great way to drive adoption and things. >> Really beautiful point. I love that. The diversity here is definitely noticeable. This is a cheeky thing to say live, but I noticed this is probably the first tech conference I've ever been to as a woman where I, there was actually a line for the restroom. Normally we're straight in at these and it's a silly thing. Yeah, now at breaks I have to allow a little extra time, but it was one of those moments where I very much noticed it earlier today and had to text to know I was going to be a little later back to the set, but I think it- I'm glad you brought that up cuz this community is special, it's inclusive, it's collaborative, it's massive companies as well as tiny startups from all over the world. It's very exciting. I really enjoyed talking with both of you. I hope we get to have you back on the show. It was fun. It was fashionable. Ranjit, Monty, thank you both so much for bringing your energy and your thoughts >> We'd love to come back. Yes, we'd love to come back in hot pink next time and talk about. >> I mean, the Deloitte consultants usually know how to thread up but (Savannah chuckling) >> I know. I'm seriously overshadowed >> And I'm wearing my neons next time. I wear a very brave pink. So generally speaking, although the sequence were- We'll definitely do it. Thank you so much for being here, and thank all of you for tuning in for our continuous live coverage here from AWS re:Invent in Las Vegas in Nevada. My name is Savannah Peterson with Paul Gillian. We are theCUBE and we are the source for leading and spicy, zesty, fashionable tech coverage. (upbeat music playing)

(bright upbeat music) >> Good morning fellow cloud community nerds and welcome back to theCube's live coverage of AWS re:Invent, we're here in fabulous Las Vegas, Nevada. You can tell by my sequence. My name's Savannah Peterson and I'm delighted to be here with theCUBE. Joining me this morning is a packed house. We have three fabulous guests from AWS's global startup program. Immediately to my right is Eric. Eric, welcome to the show. >> Thank you. >> We've also got Jimmy and Jeff. Before we get into the questions, how does it feel? This is kind of a show off moment for you all. Is it exciting to be back on the show floor? >> Always, I mean, you live for this event, right? I mean, we've got 50,000. >> You live for this? >> Yeah, I mean, 50,000 customers. Like we really appreciate the fact that time, money and resources they spend to be here. So, yeah, I love it. >> Savanna: Yeah, fantastic. >> Yeah, everyone in the same place at the same time, energy is just pretty special, so, it's fun. >> It is special. And Jimmy, I know you joined the program during the pandemic. This is probably the largest scale event you've been at with AWS. >> First time at re:Invent. >> Welcome >> (mumbles) Customers, massive. And I love seeing some of the startups that I partner with directly behind me here from theCUBE set as well. >> Yeah, it's fantastic. First time on theCUBE, welcome. >> Jimmy: Thank you. >> We hope to have you back. >> Jimmy: Proud to be here. >> Jimmy, I'm going to keep it on you to get us started. So, just in case someone hasn't heard of the global startup program with AWS. Give us the lay of the land. >> Sure, so flagship program at AWS. We partner with venture backed, product market fit B2B startups that are building on AWS. So, we have three core pillars. We help them co-built, co-market, and co-sell. Really trying to help them accelerate their cloud journey and get new customers build with best practices while helping them grow. >> Savanna: Yeah, Jeff, anything to add there? >> Yeah, I would say we try our best to find the best technology out there that our customers are demanding today. And basically, give them a fast track to the top resources we have to offer to help them grow their business. >> Yeah, and not a casual offering there at AWS. I just want to call out some stats so everyone knows just how many amazing startups and businesses that you touch. We've talked a lot about unicorns here on the show, and one of Adam's quotes from the keynote was, "Of the 1200 global unicorns, 83% run on AWS." So, at what stage are most companies trying to come and partner with you? And Eric we'll go to you for that. >> Yeah, so I run the North American startup team and our mission is to get and support startups as early as inception as possible, right? And so we've got kind of three, think about three legs of stool. We've got our business development team who works really closely with everything from seed, angel investors, incubators, accelerators, top tier VCs. And then we've got a sales team, we've got a BD team. And so really, like we're even looking before customers start even building or billing, we want to find those stealth startups, help them understand kind of product, where they fit within AWS, help them understand kind of how we can support them. And then as they start to build, then we've got a commercial team of solution architects and sales professionals that work with them. So, we actually match that life cycle all the way through. >> That's awesome. So, you are looking at seed, stealth. So, if I'm a founder listening right now, it doesn't matter what stage I'm at. >> No, I mean, really we want to get, and so we have credit programs, we have enablement programs, focus everything from very beginning to hyper scale. And that's kind of how we think about it. >> That's pretty awesome. So Jeff, what are the keys to success for a startup in working with you all? >> Yeah, good question. Highly differentiated technology is absolutely critical, right? There's a lot of startups out there but finding those that have differentiated technology that meets the demands of AWS customers, by far the biggest piece right there. And then it's all about figuring out how to lean into the partnership and really embrace what Jimmy said. How do you do the co build, the co-marketing, co-sell to put the full package together to make sure that your software's going to have the greatest visibility with our customers out there. >> Yeah, I love that. Jimmy, how do you charm them? What do the startups see in working with AWS? (indistinct) >> But that aside, Jeff just alluded to it. It's that better together story and it takes a lot of buy-in from the partner to get started. It is what we say, a partner driven flywheel. And the successful partners that I work with understand that and they're committing the resources to the relationship because we manage thousands and thousands of startups and there's thousands listed on Marketplace. And then within our co-sell ISV Accelerate program, there's hundreds of startups. So startups have to, one, differentiate themselves with their technology, but then two, be able to lean in to do the tactical engagement that myself and my PDM peers help them manage. >> Awesome, yeah. So Eric. >> Yes. >> Let's say I talk to a lot of founders because I do, and how would I pitch an AWS partnership through the global startup program to them? >> Yeah, well, so this... >> Give me my sound back. >> Yeah, yeah, look for us, like it's all about scaling your business, right? And so my team, and we have a partnership. I run the North American startup team, they run the global startup program, okay? So what my job is initially is to help them build up their services and their programs and products. And then as they get to product market fit, and we see synergy with selling with Amazon, the whole idea is to lead them into the go-to market programs, right? And so really for us, that pitch is this, simply put, we're going to help you extend your reach, right? We're going to take what you know about your service and having product market fit understanding your sales cycle, understanding your customer and your value, and then we're going to amplify that voice. >> Sounds good to me, I'm sold. I like that, I mean, I doubt there's too many companies with as much reach as you have. Let's dig in there a little bit. So, how much is the concentration of the portfolio in North America versus globally? I know you've got your fingers all over the place. >> Jimmy: Yeah. >> Go for it, Jeff. >> Jimmy: Well, yeah, you start and I'll... >> On the partnership side, it's pretty balanced between North America and AMEA and APJ, et cetera, but the type of partners is very different, right? So North America, we have a high focus on infrastructure led partners, right? Where that might be a little different in other regions internationally. >> Yeah, so I have North America, I have a peer that has AMEA, a peer that has Latin America and a peer that has APJ. And so, we have the startup team which is global, and we break it up regionally, and then the global startup program, which is partnership around APN, Amazon Partner Network, is also global. So like, we work in concert, they have folks married up to our team in each region. >> Savannah, what I'm hearing is you want do a global startup showcase? >> Yeah. (indistinct) >> We're happy to sponsor. >> Are you reading my mind? We are very aligned, Jimmy. >> I love it, awesome. >> I'm going to ask you a question, since you obviously are in sync with me all ready. You guys see what you mentioned, 50,000 startups in the program? 100, 000, how many? >> Well you're talking about for the global startup program, the ISV side? >> Sure, yeah, let's do both the stats actually. >> So, the global startup program's a lot smaller than that, right? So globally, there might be around 1,000 startups that are in the program. >> Savanna: Very elite little spot. >> Now, a lot bigger world on Eric's side. >> Eric: Yeah, globally over 200,000. >> Savanna: Whoa. >> Yeah, I mean, you think about, so just think about the... >> To keep track, those all in your head? >> Yeah, I can't keep track. North America's quite large. Yeah, no, because look, startups are getting created every day, right? And then there's positive exits and negative exits, right? And so, yeah, I mean, it's impressive. And particularly over the last two years, over the last two years are a little bit crazy, bonkers with the money coming. (mumbles) And yet the creation that's going to happen right now in the market disruption is going to mirror what happened in 2008, 2009. And so, the creation is not going to slow down. >> Savanna: No, hopefully not. >> No. >> No, and our momentum, I mean everyone's doing things faster, more data, it's all that we're talking about, do more and make it easier for everybody in the same central location. Jimmy, of those thousand global startups that you're working with, can you tell us some of the trends? >> Yeah, so I think one of the big things, especially, I cover data analytics startups specifically. So, one moving from batch to real time analytics. So, whether that's IOT, gaming, leader boards, querying data where it sits in an AWS data, like companies need to make operational decisions now and not based off of historic data from a week ago or last night or a month ago. So, that's one. And then I'm going to steal one of John's lines, is data is code. That is becoming that base layer that a lot of startups are building off of and operationalizing. So, I think those are the two big things I'm seeing, but would love... >> Curious to both, Jeff, let's go to you next, I'm curious, yeah. >> Yeah, totally. I think from a broader perspective, the days of completely free money and infinite resources are coming to a close, if not already closed. >> We all work with startups, we can go ahead and just talk about all the well is just a little (indistinct)... >> So, I think it's closed, and so because of that, it's how do you deal with a lot? How do you produce the results on the go to market side with fewer resources, right? And so it's incumbent on our team to figure out how to make it an easier, simpler process to partner with AWS, knowing those constraints are very real now. >> Savanna: Yeah. >> Yeah. >> Yeah, and to build on that. I think mid stage, it's all about cash preservation, right? And it's in that runway... >> Especially right now. >> Yeah, and so part of that is getting into the right infrastructure, when you had a lot of people, suddenly you don't have as many people moving into managed services, making sure that you can scale at a cost efficient way versus at any cost. That's kind of the latter stage. Now what's really been fascinating more at the at the early stages, I call it the rise of the AIML native. And so, where you say three years ago, you saw customers bolting on AI, now they're building AI from the start, right? And that's pervasive across every industry, whether it's in FinTech, life sciences, healthcare, climate tech, you're starting to see it all the way across the board. And then of course the other thing is, yeah, the other one is just the rise of just large language models, right? And just, I think there's the hype and there's the promise, but you know, over time, like the amount of customers big and small, whom are used in large language models is pretty fascinating. >> Yeah, you must have fascinating jobs. I mean, genuinely, it's so cool to get to not only see and have your finger on the pulse of what's coming next, essentially that's what startups are, but also be able to support them and to collaborate with them. And it's clear, the commitment to community and to the customers that you're serving. Last question for each of you, and then we're talking about your DJing. >> Oh yeah, I definitely, I want to see that. >> No, we're going to close with that as a little pitch for everyone watching this show. So, we make sure the crowd's just packed for that. This is your show, as you said, you live for this show, love that. >> Yeah. >> Give us your 30 second hot take, most important soundbites, think of this as your thought leadership shining moment. What's the biggest takeaway from the show? Biggest trend, thing that has you most excited? >> Oh, that's a difficult one. There's a lot going on. >> There is a lot going on. I mean, you can say a couple things. I'll allow you more than 30 seconds if you want. >> No, I mean, look, I just think the, well, what's fascinating to me in having this is my third or fourth re:Invent is just the volume of new announcements that come out. It's impressive, right? I mean it's impressive in terms of number of services, but then the depth of those services and the building on, I think it's just really amazing. I think that the trend you're going to continue to see and there's going to be more keynotes tomorrow, so, I can't let anything out. But just the AI, ML, real excited about that, analytic space, serverless, just continue to see the maturation of that space, particularly for startups. I think that to me is what's really exciting. And just seeing folks come together, start exchanging ideas, and I think the last piece I'll do is a pitch for my own team, like we have like 18 different sessions from the North American startup team. And so, I mean, shout out to our solution architects putting those sessions together, geared towards startups for startups, and so, that's probably what I'm most excited about. >> Casual, that was good, and you pitched it in time. I think that was great. >> There you go. >> All right, Jeff, you just had a little practice time while he was going. Let's (indistinct). >> No, so it's just exciting to see all the partners that we support here, so many of them have booths here and are showcasing their technology. And being able to connect them with customers to show how advanced their capabilities are that they're bringing to the table to supplement and compliment all the new capabilities that AWS is launching. So, to be able to see all of that in the same place at the same time and really hear what they need from a partnership perspective, that's what's special for us. >> Savanna: This is special. All right, Jimmy. >> My thoughts on re:Invent or? >> Not DJ yet. >> Not DJ. Not DJ, but I mean, your first re:Invent. Probably your first time getting to interact with a lot of the people that you chat with face to face. How does it feel? What's your hot take? Your look through the crystal ball, if you want to take it farther out in front. >> I think it's finally getting FaceTime with some of the relationships that I've built purely over Chime and virtual calls over the past two years has been incredible. And then secondly, to the technical enablement piece, I can announce this 'cause it was already announced earlier, is AWS Security Lake, one of my partners, Cribl, was actually a launch partner for that service. So, a little too to the Horn for Global Startup program, one of the coolest things at the tactical level as a PDM is working with them throughout the year and my partner solution architect finding these unique alignment opportunities with native AWS services and then seeing it build all the way through fruition at the finish line, announced at re:Invent, their logo up on screen, like that's, I can sleep well tonight. >> Job well done. >> Yeah. >> Yeah. >> That's pretty cool. >> That is cool. >> So, I've already told you before you even got here that you're a DJ and you happen to be DJing at re:Invent. Where can we all go dance and see you? >> So, shout out to Mission Cloud, who has sponsored Tao, Day Beach Club on Wednesday evening. So yes, I do DJ, I appreciate AWS's flexibility work life balance. So, I'll give that plug right here as well. But no, it's something I picked up during COVID, it's a creative outlet for me. And then again, to be able to do it here is just an incredible opportunity. So, Wednesday night I hope to see all theCUBE and everyone that... >> We will definitely be there, be careful what you wish for. >> What's your stage name? >> Oh, stage name, DJ Hot Hands, so, find me on SoundCloud. >> DJ Hot Hands. >> All right, so check out DJ Hot Hands on SoundCloud. And if folks want to learn more about the Global Startup program, where do they go? >> AWS Global Startup Program. We have a website you can easily connect with. All our startups are listed on AWS Marketplace. >> Most of them are Marketplace, you can go to our website, (mumbles) global startup program and yeah, find us there. >> Fantastic. Well, Jeff, Jimmy, Eric, it was an absolute pleasure starting the day. We got startups for breakfast. I love that. And I can't wait to go dance to you tomorrow night or tonight actually. I'm here for the fist bumps. This is awesome. And you all are great. Hope to have you back on theCUBE again very soon and we'll have to coordinate on that global Startup Showcase. >> Jimmy: All right. >> I think it's happening, 2023, get ready folks. >> Jimmy: Here we go. >> Get ready. All right, well, this was our first session here at AWS re:Invent. We are live from Las Vegas, Nevada. My name is Savannah Peterson, we're theCUBE, the leader in high tech reporting. (bright upbeat music)

>>Hello, wonderful humans and welcome back to The Cube's Thrilling live coverage of AWS Reinvent here in Las Vegas, Nevada. I'm joined by my fantastic co-host, John Farer. John, things are really ramping up in here. Day one. >>Yep, it's packed already. I heard 70,000 maybe attendees really this year. I just saw that on Twitter. Again, it continues to show that over the past 10 years we've been here, you're seeing some of the players that were here from the beginning growing up and getting bigger and stronger, becoming more platforms, not just point solutions. You're seeing new entrants coming in, new startups, and the innovation you start to see happening, it's really compelling to fun to watch. And our next segment, we have multi 10 time Cube alumni coming on and a first timer, so it should be great. We'll get into some of the innovation, >>Not only as this guest went on the cube 10 times, he also spoke at the first AWS reinvent, just like you were covering it here with Cube. But without further ado, please welcome Ronan and Kevin from NetApp. Thank you gentlemen, both for being here and for matching in your dark blue. How's the show going for you? Ronan, I'm gonna ask you first, you've been here since the beginning. How does it feel in 2022? >>First, it's amazing to see so many people, right? So many humans in one place, flesh and blood. And it's also amazing to see, it's such a celebration for people in the cloud, right? Like this is our, this is our event, the people in the cloud. I'm really, really happy to be here and be in the cube as well. >>Fantastic. It, it is a party, it's a cloud party. Yes. How are you feeling being here, Kevin? I'm >>Feeling great. I mean, going all the way back to the early days of Spot T, which was the start that eventually got acquired as Spot by NetApp. I mean this was, this was our big event. This is what we lived for. We've gone, I've gone from everything, one of the smaller booths out here on the floor all the way up to the, the huge booth that we have today. So we've kind of grown along with the AWS ecosystem and it's just a lot of fun to get here, see all the customers and talk to everybody. >>That's a lot of fun. Fun. That's the theme that we've been talking about. And we wrote a story about on, on Silicon Angle, more that growth from that getting in and getting bigger, not just an ISV or part of the startup showcase or ecosystem. The progression of the investment on how cloud has changed deliverables. You've been part of that wave. What's the biggest walk away, what's, and what's the most important thing going on now cuz it's not stopping. You got new interests coming in and the folks are rising with the tide and getting platforms built around their products. >>Yeah, I would say, you know, years ago is, is cloud in my decision path and now it's cloud is in my decision path. How much is it and how am I going to use it? And I think especially coming up over the next year, macroeconomic events and everything going on is how do I make my next dollar in the cloud go further than my last dollar? Because I know I'm gonna be there, I know I'm gonna be growing in the cloud, so how do I effectively use it to run my business going forward? >>All right, take a minute to explain Spot now part of NetApp. What's the story? What take us through for the folks that aren't familiar with the journey, where it's come from, where it's today? >>Sure. So SPOT is all about cloud optimization. We help all of our customers deploy scale and optimize their applications in the cloud. And what we do is everything from VMs to containers to any type of custom application you want to deploy, we analyze those applications, we find the best price point to run them, we right size them, we do the automation so your DevOps team doesn't have to do it. And we basically make the whole cloud serverless for you at the end of the day. So whatever you're doing in the cloud, we'll manage that for you from the lowest level of the stack all the way up to the highest level financials. >>Is this what you call the evolved cloud state? >>It is in the evolve clouds a little bit more, and Ronan can touch on that a little bit too. The Evolve clouds not only the public cloud but also the cloud that you're building OnPrem, right? A lot of big companies, it's not necessarily a hundred percent one way or the other. The Evolve cloud is which cloud am I on? Am I on an OnPrem cloud and a public cloud or am I on multiple public clouds in an OnPrem cloud? And I think Ronan, you probably have an opinion on that too. >>Yeah, and and I think what we are hearing from our customers is that many of them are in a situation where a lot of their data has been built for years on premises. They're accelerating their move to the cloud, some of them are accelerating, they're moving into multiple cloud and that situation of an on-prem that is becoming cloudy and cloudy all the time. And then accelerated cloud adoption. This is what the customers are calling the Evolve cloud and that's what we're trying to support them in that journey. >>How many customers are you supporting in this Evolve cloud? You made it seem like you can just turnkey this for everyone, which I am here >>For it. Yeah, just to be clear, I mean we have thousands of customers, right? Everything from your small startups, people just getting going with a few VMs all the way to people scaling to tens and thousands of VMs in the cloud or even beyond VM services and you know, tens of millions of spend a month. You know, people are putting a lot of investment into the cloud and we have all walks of life under our, you know, customer portfolio. >>You know, multi-cloud has been a big topic in the industry. We call it super cloud. Cause we think super cloud kind of more represents the destination to multi-cloud. I mean everyone has multiple clouds, but they're best of breed defaults. They're not by design in most cases, but we're starting to see traction towards that potential common level services fix to late. See, I still think we're on the performance game now, so I have to ask, ask you guys. Performance has becoming back in VO speeds and feeds back during the data center days. Well, I wouldn't wanna talk speeds and feeds of solutions and then cloud comes in. Now we're at the era of cloud where people are moving their workloads there. There's a lot more automation going on, A lot more, as you said, part of the decision. It is the path. Yeah. So they say, now I wanna run my workloads on the better, faster infrastructure. No developer wants to run their apps on the slower hardware. >>I think that's a tall up for you. Ronan go. >>I mean, I put out my story, no developer ever said, give me the slower software performance and and pay more fast, >>Fastest find too fastest. >>Speed feeds your back, >>Right? And and performance comes in different, in different parameters, right? They think it is come throughput, it comes through latency. And I think even a stronger word today is price performance, right? How much am I paying for the performance that that I need? NetApp is actually offering a very, very big advantage for customers on both the high end performance as well as in the dollar per performance. That is, that is needed. This is actually one of the key differentiator that Fsx for NetApp on top is an AWS storage based on the NetApp on top storage operating system. This is one of the biggest advantages it is offering. It is SAP certified, for example, where latency is the key, is the key item. It is offering new and fastest throughput available, but also leveraging some advanced features like tiering and so on, is offering unique competitive advantage in the dollar for performance specifically. >>And why, why is performance important now, in your opinion? Obviously besides the obvious of no one wants to run their stuff on the slower infrastructure, but why are some people so into it now? >>I think performance as a single parameter is, is definitely a key influencer of the user experience. None, none of us will, will compromise our our experience. The second part is performance is critical when scale is happening, right? And especially with the scale of data performance to handle massive amounts of data is is becoming more and more critical. The last thing that I'll emphasize is again is the dollar for performance. The more data you have, the more you need to handle, the more critical for you is to handle it in a cost effective way. This is kind of, that's kind of in the, in the, in the secret sauce of the success of every workload. >>There isn't a company or person here who's not thinking about doing more faster for cheaper. So you're certainly got your finger on the pulse With that, I wanna talk about a, a customer case study. A little birdie told me that a major US airline recently just had a mass of when we're where according to my notes response time and customer experience was improved by 17 x. Now that's the type of thing that cuts cost big time. Can one of you tell me a little bit more about that? >>Yeah, so I think we all flew here somehow, right? >>Exactly. It's airlines matter. Probably most folks listening, they're >>Doing very well right now. Yes, the >>Airlines and I think we all also needed to deal with changes in the flights with, with really enormous amount of complexity in managing a business like that. We actually rank and choose what, what airline to use among other things based on the level of service that they give us. And especially at the time of crunch, a lot of users are looking through a lot of data to try to optimize, >>Plus all of them who just work this holiday weekend sidebar >>E Exactly right. Can't even, and Thanksgiving is one of these crunch times that are in the middle of this. So 70 x improvement in performance means a loss seven >>Zero or >>17 1 7 1 7 x Right? >>Well, and especially when we're talking about it looks like 50,000, 50,000 messages per minute that this customer was processing. Yes. That that's a lot. That's almost a thousand messages a second. Wow. I think my math tees up there. Yeah. >>It does allow them to operate in the next level of scale and really increase their support for the customer. It also allows them to be more efficient when it comes to cost. Now they need less infrastructure to give better service across the board. The nice thing is that it didn't require them for a lot of work. Sometimes when the customers are doing their journey to the cloud, one of the things that kind of hold them back is like, is either the fear or, or maybe is the, the concern of how much effort will it take me to achieve the same performance or even a better performance in the cloud? They are a live example that not only can you achieve, you can actually exceed the performance that I have on premises and really give customer a better service >>Customer a better service. And reliability is extremely important there. 99.9%. 99% >>99. Yes. >>Yes. That second nine obviously being very important, especially when we're talking about the order of magnitude of, of data and, and actions being taken place. How much of a priority is, is reliability and security for y'all as a team? >>So reliability is a key item for, for everybody, especially in crunch times. But reliability goes beyond the nines. Specifically reliability goes into how simple it is for you to enable backup n dr, how protected are you against ransomware? This is where netup and, and including the fsx for NETUP on top richness of data management makes a huge difference. If you are able to make your copy undeletable, that is actually a game changer when it comes to, to data protection. And this is, this is something that in the past requires a lot of work, opening vaults and other things. Yeah. Now it becomes a very simple configuration that is attached to every net up on top storage, no matter where it is. >>We heard some news at VMware explorer this past fall. Early fall. You guys were there. We saw the Broadcom acquisition. Looks like it's gonna get finalized maybe sooner than later. Lot of, so a lot of speculation around VMware. Someone called the VMware like where is VMware as in where they now, nice pun it was, it was actually Nutanix people, they go at each other all the time. But Broadcom's gonna keep vse and that's where the bread and butter, that's the, that's the goose that lays the Golden eggs. Customers are there. How do you guys see your piece there with VMware cloud on AWS that integrates solution? You guys have a big part of that ecosystem. We've covered it for years. I mean we've been to every VM world now called explorer. You guys have a huge customer base with VMware customers. What's the, what's the outlook? >>Yeah, and, and I think the important part is that a big part of the enterprise workloads are running on VMware and they will continue to run on VMware in, in, in the future. And most of them will try to run in a hybrid mode if not moving completely to the cloud. The cloud give them unparallel scale, it give them DR and backup opportunities. It does a lot of goodness to that. The partnership that NetApp brings with both VMware as well ass as well as other cloud vendors is actually a game changer. Because the minute that you go to the cloud, things like DR and backup have a different economics connected to them. Suddenly you can do compute less dr definitely on backup you can actually achieve massive savings. NetApp is the only data store that is certified to run with VMware cloud. And that actually opens to the customer's huge opportunity for unparalleled data protection as well as real, real savings, hard savings. And customers that look today and they say, I'm gonna shrink my data center, I'm gonna focus on, on moving certain things to the cloud, DR and backup and especially DR and backup VMware might be one of the easiest, fastest things to take into the cloud. And the partnership betweens VMware and NetApp might actually give you >>And the ONAP is great solution. Fsx there? Yes. I think you guys got a real advantage here and I want to get into something that's kind of a gloom and doom. I don't have to go negative on this one, Savannah, but they me nervous John. But you know, if you look at the economic realities you got a lot of companies like that are in the back of a Druva, Netta, Druva, cohesive rub. Others, you know, they, you know, there's a, their generational cloud who breaks through. What's the unique thing? Because you know there's gonna be challenges in the economy and customers are gonna vote with their wallets and they start to see as they make these architectural decisions, you guys are in the middle of it. There's not, there may not be enough to go around and the musical chairs might stop or, or not, I'm not sure. But I feel like if there's gonna be a consolidation, what does that look like? What are customers thinking? Backup recovery, cloud. That's a unique thing. You mentioned economics, it's not, you can't take the old strategy and put it there from five, 10 years ago. What's different now? >>Yeah, I think when it comes to data protection, there is a real change in, in the technology landscape that opened the door for a lot of new vendors to come and offer. Should we expect consolidation? I think microeconomic outside and other things will probably drive some of that to happen. I think there is one more parameter, John, that I wanna mention in this context, which is simplicity. Many of the storage vendors, including us, including aws, you wanna make as much of the backup NDR at basically a simple checkbox that you choose together with your main workload. This is another key capabilities that is, that is being, bringing and changing the market, >>But it also needs to move up. So it's not only simplicity, it's also about moving to the applications that you use, use, and just having it baked in. It's not about you going out and finding a replication. It's like what Ronan said, we gotta make it simple and then we gotta bake it into what they use. So one of our most recent acquisitions of Insta Cluster allows us to provide our customers with open source databases and data streaming services. When those sit on top of on tap and they sit on top of spots, infrastructure optimization, you get all that for free through the database that you use. So you don't worry about it. Your database is replicated, it's highly available, and it's running at the best cost. That's where it's going. >>Awesome. >>You also recently purchased Cloud Checker as well. Yes. Do you just purchase wonderful things all the time? We >>Do. We do. We, >>I'm not >>The, if he walk and act around and then we find the best thing and then we, we break out the checkbook, no, but more seriously, it, it rounds out what customers need for the cloud. So a lot of our customers come from storage, but they need to operate the entire cloud around the storage that they have. Cloud Checker gives us that financial visibility across every single dollar that you spend in the cloud and also gives us a better go to market motion with our MSPs and our distributors than we had in the past. So we're really excited about what cloud checker can unlock for us in >>The future. Makes a lot of sense and congratulations on all the extremely exciting things going on. Our final and closing question for our guests on this year's show is we would love your, your Instagram hot take your 32nd hot take on the most important stories, messages, themes of AWS reinvent 2022. Ronan, I'm gonna start with you cause you have a smirk >>And you do it one day ahead of the keynotes, one day ahead with you. >>You can give us a little tease a little from you. >>I think that pandemic or no pandemic face to face or no face to face, the innovation in the cloud is, is actually breaking all records. And I think this year specifically, you will see a lot of focus on data and scale. I think that's, these are two amazing things that you'll see, I think doubling down. But I'm also anxious to see tomorrow, so I'll learn more about it. >>All right. We might have to chat with you a little bit after tomorrow. Is keynotes and whatnot coming up? What >>About you? I think you're gonna hear a lot about cost. How much are you spending? How far are your dollars going? How are you using the cloud to the best of your abilities? How, how efficient are you being with your dollars in the cloud? I think that's gonna be a huge topic. It's on everybody's mind. It's the macro economics situation right now. I think it's gonna be in every session of the keynote tomorrow. All >>Right, so every >>Session. Every session, >>A bulk thing. John, we're gonna have >>That. >>I'm with him. You know, all S in general, you >>Guys have, and go look up what I said. >>Yeah, >>We'll go back and look at, >>I'm gonna check on you >>On that. The record now states. There you go, Kevin. Thank both. Put it down so much. We hope that it's a stellar show for Spotify, my NetApp. Thank you. And that we have you 10 more times and more than just this once and yeah, I, I can't wait to see, well, I can't wait to hear when your predictions are accurate tomorrow and we get to learn a lot more. >>No, you gotta go to all the sessions down just to check his >>Math on that. Yeah, no, exactly. Now we have to do our homework just to call him out. Not that we're competitive or those types of people at all. John. No. On that note, thank you both for being here with us. John, thank you so much. Thank you all for tuning in from home. We are live from Las Vegas, Nevada here at AWS Reinvent with John Furrier. My name is Savannah Peterson. You're watching the Cube, the leader in high tech coverage.

(soft music) >> Hello, fellow hardware nerds and welcome back to Dallas Texas where we're reporting live from Supercomputing 2022. My name is Savannah Peterson, joined with the John Furrier on my left. >> Looking good today. >> Thank you, John, so are you. It's been a great show so far. >> We've had more hosts, more guests coming than ever before. >> I know. >> Amazing, super- >> We've got a whole thing going on. >> It's been a super computing performance. >> It, wow. And, we'll see how many times we can say super on this segment. Speaking of super things, I am in a very unique position right now. I am a flanked on both sides by people who have been doing content on theCUBE for 12 years. Yes, you heard me right, our next guest was on theCUBE 12 years ago, the third event, was that right, John? >> Man: First ever VM World. >> Yeah, the first ever VM World, third event theCUBE ever did. We are about to have a lot of fun. Please join me in welcoming Justin Emerson of Pure Storage. Justin, welcome back. >> It's a pleasure to be here. It's been too long, you never call, you don't write. (Savannah laughs) >> Great to see you. >> Yeah, likewise. >> How fun is this? Has the set evolved? Is everything looking good? >> I mean, I can barely remember what happened last week, so. (everyone laughs) >> Well, I remember lot's changed that VM world. You know, Paul Moritz was the CEO if you remember at that time. His actual vision actually happened but not the way, for VMware, but the industry, the cloud, he called the software mainframe. We were kind of riffing- >> It was quite the decade. >> Unbelievable where we are now, how we got here, but not where we're going to be. And you're with Pure Storage now which we've been, as you know, covering as well. Where's the connection into the supercomputing? Obviously storage performance, big part of this show. >> Right, right. >> What's the take? >> Well, I think, first of all it's great to be back at events in person. We were talking before we went on, and it's been so great to be back at live events now. It's been such a drought over the last several years, but yeah, yeah. So I'm very glad that we're doing in person events again. For Pure, this is an incredibly important show. You know, the product that I work with, with FlashBlade is you know, one of our key areas is specifically in this high performance computing, AI machine learning kind of space. And so we're really glad to be here. We've met a lot of customers, met a lot of other folks, had a lot of really great conversations. So it's been a really great show for me. And also just seeing all the really amazing stuff that's around here, I mean, if you want to find, you know, see what all the most cutting edge data center stuff that's going to be coming down the pipe, this is the place to do it. >> So one of the big themes of the show for us and probably, well, big theme of your life, is balancing power efficiency. You have a product in this category, Direct Flash. Can you tell us a little bit more about that? >> Yeah, so Pure as a storage company, right, what do we do differently from everybody else? And if I had to pick one thing, right, I would talk about, it's, you know, as the name implies, we're an all, we're purely flash, we're an all flash company. We've always been, don't plan to be anything else. And part of that innovation with Direct Flash is the idea of rather than treating a solid state disc as like a hard drive, right? Treat it as it actually is, treat it like who it really is and that's a very different kind of thing. And so Direct Flash is all about bringing native Flash interfaces to our product portfolio. And what's really exciting for me as a FlashBlade person, is now that's also part of our FlashBlade S portfolio, which just launched in June. And so the benefits of that are our myriad. But, you know, talking about efficiency, the biggest difference is that, you know, we can use like 90% less DRAM in our drives, which you know, everything uses, everything that you put in a drive uses power, it adds cost and all those things and so that really gives us an efficiency edge over everybody else and at a show like this, where, I mean, you walk the aisles and there's there's people doing liquid cooling and so much immersion stuff, and the reason they're doing that is because power is just increasing everywhere, right? So if you can figure out how do we use less power in some areas means you can shift that budget to other places. So if you can talk to a customer and say, well, if I could shrink your power budget for storage by two thirds or even, save you two-thirds of power, how many more accelerators, how many more CPUs, how much more work could you actually get done? So really exciting. >> I mean, less power consumption, more power and compute. >> Right. >> Kind of power center. So talk about the AI implications, where the use cases are. What are you seeing here? A lot of simulations, a lot of students, again, dorm room to the boardroom we've been saying here on theCUBE this is a great broad area, where's the action in the ML and the AI for you guys? >> So I think, not necessarily storage related but I think that right now there's this enormous explosion of custom silicon around AI machine learning which I as a, you said welcome hardware nerds at the beginning and I was like, ah, my people. >> We're all here, we're all here in Dallas. >> So wonderful. You know, as a hardware nerd we're talking about conferences, right? Who has ever attended hot chips and there's so much really amazing engineering work going on in the silicon space. It's probably the most exciting time for, CPU and accelerator, just innovation in, since the days before X 86 was the defacto standard, right? And you could go out and buy a different workstation with 16 different ISAs. That's really the most exciting thing, I walked past so many different places where you know, our booth is right next to Havana Labs with their gout accelerator, and they're doing this cute thing with one of the AI image generators in their booth, which is really cute. >> Woman: We're going to have to go check that out. >> Yeah, but that to me is like one of the more exciting things around like innovation at a, especially at a show like this where it's all about how do we move forward, the state of the art. >> What's different now than just a few years ago in terms of what's opening up the creativity for people to look at things that they could do with some of the scale that's different now. >> Yeah well, I mean, every time the state of the art moves forward what it means is, is that the entry level gets better, right? So if the high end is going faster, that means that the mid-range is going faster, and that means the entry level is going faster. So every time it pushes the boundary forward, it's a rising tide that floats all boats. And so now, the kind of stuff that's possible to do, if you're a student in a dorm room or if you're an enterprise, the world, the possible just keeps expanding dramatically and expanding almost, you know, geometrically like the amount of data that we are, that we have, as a storage guy, I was coming back to data but the amount of data that we have and the amount of of compute that we have, and it's not just about the raw compute, but also the advances in all sorts of other things in terms of algorithms and transfer learning and all these other things. There's so much amazing work going on in this area and it's just kind of this Kay Green explosion of innovation in the area. >> I love that you touched on the user experience for the community, no matter the level that you're at. >> Yeah. >> And I, it's been something that's come up a lot here. Everyone wants to do more faster, always, but it's not just that, it's about making the experience and the point of entry into this industry more approachable and digestible for folks who may not be familiar, I mean we have every end of the ecosystem here, on the show floor, where does Pure Storage sit in the whole game? >> Right, so as a storage company, right? What AI is all about deriving insights from data, right? And so everyone remembers that magazine cover data's the new oil, right? And it's kind of like, okay, so what do you do with it? Well, how do you derive value from all of that data? And AI machine learning and all of this supercomputing stuff is about how do we take all this data? How do we innovate with it? And so if you want data to innovate with, you need storage. And so, you know, our philosophy is that how do we make the best storage platforms that we can using the best technology for our customers that enable them to do really amazing things with AI machine learning and we've got different products, but, you know at the show here, what we're specifically showing off is our new flashlight S product, which, you know, I know we've had Pure folks on theCUBE before talking about FlashBlade, but for viewers out there, FlashBlade is our our scale out unstructured data platform and AI and machine learning and supercomputing is all about unstructured data. It's about sensor data, it's about imaging, it's about, you know, photogrammetry, all this other kinds of amazing stuff. But, you got to land all that somewhere. You got to process that all somewhere. And so really high performance, high throughput, highly scalable storage solutions are really essential. It's an enabler for all of the amazing other kinds of engineering work that goes on at a place like Supercomputing. >> It's interesting you mentioned data's oil. Remember in 2010, that year, our first year of theCUBE, Hadoop World, Hadoop just started to come on the scene, which became, you know kind of went away and, but now you got, Spark and Databricks and Snowflake- >> Justin: And it didn't go away, it just changed, right? >> It just got refactored and right size, I think for what the people wanted it to be easy to use but there's more data coming. How is data driving innovation as you bring, as people see clearly the more data's coming? How is data driving innovation as you guys look at your products, your roadmap and your customer base? How is data driving innovation for your customers? >> Well, I think every customer who has been, you know collecting all of this data, right? Is trying to figure out, now what do I do with it? And a lot of times people collect data and then it will end up on, you know, lower slower tiers and then suddenly they want to do something with it. And it's like, well now what do I do, right? And so there's all these people that are reevaluating you know, we, when we developed FlashBlade we sort of made this bet that unstructured data was going to become the new tier one data. It used to be that we thought unstructured data, it was emails and home directories and all that stuff the kind of stuff that you didn't really need a really good DR plan on. It's like, ah, we could, now of course, as soon as email goes down, you realize how important email is. But, the perspectives that people had on- >> Yeah, exactly. (all laughing) >> The perspectives that people had on unstructured data and it's value to the business was very different and so now- >> Good bet, by the way. >> Yeah, thank you. So now unstructured data is considered, you know, where companies are going to derive their value from. So it's whether they use the data that they have to build better products whether it's they use the data they have to develop you know, improvements in processes. All those kinds of things are data driven. And so all of the new big advancements in industry and in business are all about how do I derive insights from data? And so machine learning and AI has something to do with that, but also, you know, it all comes back to having data that's available. And so, we're working very hard on building platforms that customers can use to enable all of this really- >> Yeah, it's interesting, Savannah, you know, the top three areas we're covering for reinventing all the hyperscale events is data. How does it drive innovation and then specialized solutions to make customers lives easier? >> Yeah. >> It's become a big category. How do you compose stuff and then obviously compute, more and more compute and services to make the performance goes. So those seem to be the three hot areas. So, okay, data's the new oil refineries. You've got good solutions. What specialized solutions do you see coming out because once people have all this data, they might have either large scale, maybe some edge use cases. Do you see specialized solutions emerging? I mean, obviously it's got DPU emerging which is great, but like, do you see anything else coming out at that people are- >> Like from a hardware standpoint. >> Or from a customer standpoint, making the customer's lives easier? So, I got a lot of data flowing in. >> Yeah. >> It's never stopping, it keeps powering in. >> Yeah. >> Are there things coming out that makes their life easier? Have you seen anything coming out? >> Yeah, I think where we are as an industry right now with all of this new technology is, we're really in this phase of the standards aren't quite there yet. Everybody is sort of like figuring out what works and what doesn't. You know, there was this big revolution in sort of software development, right? Where moving towards agile development and all that kind of stuff, right? The way people build software change fundamentally this is kind of like another wave like that. I like to tell people that AI and machine learning is just a different way of writing software. What is the output of a training scenario, right? It's a model and a model is just code. And so I think that as all of these different, parts of the business figure out how do we leverage these technologies, what it is, is it's a different way of writing software and it's not necessarily going to replace traditional software development, but it's going to augment it, it's going to let you do other interesting things and so, where are things going? I think we're going to continue to start coalescing around what are the right ways to do things. Right now we talk about, you know, ML Ops and how development and the frameworks and all of this innovation. There's so much innovation, which means that the industry is moving so quickly that it's hard to settle on things like standards and, or at least best practices you know, at the very least. And that the best practices are changing every three months. Are they really best practices right? So I think, right, I think that as we progress and coalesce around kind of what are the right ways to do things that's really going to make customers' lives easier. Because, you know, today, if you're a software developer you know, we build a lot of software at Pure Storage right? And if you have people and developers who are familiar with how the process, how the factory functions, then their skills become portable and it becomes easier to onboard people and AI is still nothing like that right now. It's just so, so fast moving and it's so- >> Wild West kind of. >> It's not standardized. It's not industrialized, right? And so the next big frontier in all of this amazing stuff is how do we industrialize this and really make it easy to implement for organizations? >> Oil refineries, industrial Revolution. I mean, it's on that same trajectory. >> Yeah. >> Yeah, absolutely. >> Or industrial revolution. (John laughs) >> Well, we've talked a lot about the chaos and sort of we are very much at this early stage stepping way back and this can be your personal not Pure Storage opinion if you want. >> Okay. >> What in HPC or AIML I guess it all falls under the same umbrella, has you most excited? >> Ooh. >> So I feel like you're someone who sees a lot of different things. You've got a lot of customers, you're out talking to people. >> I think that there is a lot of advancement in the area of natural language processing and I think that, you know, we're starting to take things just like natural language processing and then turning them into vision processing and all these other, you know, I think the, the most exciting thing for me about AI is that there are a lot of people who are, you are looking to use these kinds of technologies to make technology more inclusive. And so- >> I love it. >> You know the ability for us to do things like automate captioning or the ability to automate descriptive, audio descriptions of video streams or things like that. I think that those are really,, I think they're really great in terms of bringing the benefits of technology to more people in an automated way because the challenge has always been bandwidth of how much a human can do. And because they were so difficult to automate and what AI's really allowing us to do is build systems whether that's text to speech or whether that's translation, or whether that's captioning or all these other things. I think the way that AI interfaces with humans is really the most interesting part. And I think the benefits that it can bring there because there's a lot of talk about all of the things that it does that people don't like or that they, that people are concerned about. But I think it's important to think about all the really great things that maybe don't necessarily personally impact you, but to the person who's not cited or to the person who you know is hearing impaired. You know, that's an enormously valuable thing. And the fact that those are becoming easier to do they're becoming better, the quality is getting better. I think those are really important for everybody. >> I love that you brought that up. I think it's a really important note to close on and you know, there's always the kind of terminator, dark side that we obsess over but that's actually not the truth. I mean, when we think about even just captioning it's a tool we use on theCUBE. It's, you know, we see it on our Instagram stories and everything else that opens the door for so many more people to be able to learn. >> Right? >> And the more we all learn, like you said the water level rises together and everything is magical. Justin, it has been a pleasure to have you on board. Last question, any more bourbon tasting today? >> Not that I'm aware of, but if you want to come by I'm sure we can find something somewhere. (all laughing) >> That's the spirit, that is the spirit of an innovator right there. Justin, thank you so much for joining us from Pure Storage. John Furrier, always a pleasure to interview with you. >> I'm glad I can contribute. >> Hey, hey, that's the understatement of the century. >> It's good to be back. >> Yeah. >> Hopefully I'll see you guys in, I'll see you guys in 2034. >> No. (all laughing) No, you've got the Pure Accelerate conference. We'll be there. >> That's right. >> We'll be there. >> Yeah, we have our Pure Accelerate conference next year and- >> Great. >> Yeah. >> I love that, I mean, feel free to, you know, hype that. That's awesome. >> Great company, great runs, stayed true to the mission from day one, all Flash, continue to innovate congratulations. >> Yep, thank you so much, it's pleasure being here. >> It's a fun ride, you are a joy to talk to and it's clear you're just as excited as we are about hardware, so thanks a lot Justin. >> My pleasure. >> And thank all of you for tuning in to this wonderfully nerdy hardware edition of theCUBE live from Dallas, Texas, where we're at, Supercomputing, my name's Savannah Peterson and I hope you have a wonderful night. (soft music)

(upbeat music) >> Hello everyone, welcome to this special Cube conversation here in Palo Alto, California. I'm John Furrier, host of theCUBE in theCUBE Studios. We've got a special video here. We love when we have startups that are launching. It's an exclusive video of a hot startup that's launching. Got great reviews so far. You know, word on the street is, they got something different and unique. We're going to' dig into it. Amit Govrin who's the CEO and co-founder of Kubiya, which stands for Cube in Hebrew, and they're headquartered in Bay Area and in Tel Aviv. Amit, congratulations on the startup launch and thanks for coming in and talk to us in theCUBE >> Thank you, John, very nice to be here. >> So, first of all, a little, 'cause we love the Cube, 'cause theCUBE's kind of an open brand. We've never seen the Cube in Hebrew, so is that true? Kubiya is? >> Kubiya literally means cube. You know, clearly there's some additional meanings that we can discuss. Obviously we're also launching a KubCon, so there's a dual meaning to this event. >> KubCon, not to be confused with CubeCon. Which is an event we might have someday and compete. No, I'm only kidding, good stuff. I want to get into the startup because I'm intrigued by your story. One, you know, conversational AI's been around, been a category. We've seen chat bots be all the rage and you know, I kind of don't mind chat bots on some sites. I can interact with some, you know, form based knowledge graph, whatever, knowledge database and get basic stuff self served. So I can see that, but it never really scaled or took off. And now with Cloud Native kind of going to the next level, we're starting to see a lot more open source and a lot more automation, in what I call AI as code or you know, AI as a service, machine learning, developer focused action. I think you guys might have an answer there. So if you don't mind, could you take a minute to explain what you guys are doing, what's different about Kubiya, what's happening? >> Certainly. So thank you for that. Kubiya is what we would consider the first, or one of the first, advanced virtual assitants with a domain specific expertise in DevOps. So, we respect all of the DevOps concepts, GitOps, workflow automation, of those categories you've mentioned, but also the added value of the conversational AI. That's really one of the few elements that we can really bring to the table to extract what we call intent based operations. And we can get into what that means in a little bit. I'll save that maybe for the next question. >> So the market you're going after is kind of, it's, I love to hear starters when they, they don't have a Gartner Magic quadrant, they can fit nicely, it means they're onto something. What is the market you're going after? Because you're seeing a lot of developers driving a lot of the key successes in DevOps. DevOps has evolved to the point where, and DevSecOps, where developers are driving the change. And so having something that's developer focused is key. Are you guys targeting the developers, IT buyers, cloud architects? Who are you looking to serve with this new opportunity? >> So essentially self-service in the world of DevOps, the end user typically would be a developer, but not only, and obviously the operators, those are the folks that we're actually looking to help augment a lot of their efforts, a lot of the toil that they're experiencing in a day to day. So there's subcategories within that. We can talk about the different internal developer tools, or platforms, shared services platforms, service catalogs are tangential categories that this kind of comes on. But on top of that, we're adding the element of conversational AI. Which, as I mentioned, that's really the "got you". >> I think you're starting to see a lot of autonomous stuff going on, autonomous pen testing. There's a company out there doing I've seen autonomous AI. Automation is a big theme of it. And I got to ask, are you guys on the business side purely in the cloud? Are you born in the cloud, is it a cloud service? What's the product choice there? It's a service, right? >> Software is a service. We have the classic, Multi-Tenancy SAAS, but we also have a hybrid SAAS solution, which allows our customers to run workflows using remote runners, essentially hosted at their own location. >> So primary cloud, but you're agnostic on where they could consume, how they want to' consume the product. >> Technology agnostic. >> Okay, so that's cool. So let's get into the problem you're solving. So take me through, this will drive a lot of value here, when you guys did the company, what problems did you hone in on and what are you guys seeing as the core problem that you solve? >> So we, this is a unique, I don't know how unique, but this is a interesting proposition because I come from the business side, so call it the top down. I've been in enterprise sales, I've been in a CRO, VP sales hat. My co-founder comes from the bottom up, right? He ran DevOps teams and SRE teams in his previous company. That's actually what he did. So, we met each other halfway, essentially with me seeing a lot of these problems of self-service not being so self-service after all, platforms hitting walls with adoption. And he actually created his own self-service platform, within his last company, to address his own personal pains. So we essentially kind of met with both perspectives. >> So you're absolutely hardcore on self-service. >> We're enabling self-service. >> And that basically is what everybody wants. I mean, the developers want self-service. I mean, that's kind of like, you know, that's the nirvana. So take us through what you guys are offering, give us an example of use cases and who's buying your product, why, and take us through that whole piece. >> Do you mind if I take a step back and say why we believe self-service has somewhat failed or not gotten off. >> Yeah, absolutely. >> So look, this is essentially how we're looking at it. All the analysts and the industry insiders are talking about self-service platforms as being what's going to' remove the dependency of the operator in the loop the entire time, right? Because the operator, that scarce resource, it's hard to hire, hard to train, hard to retain those folks, Developers are obviously dependent on them for productivity. So the operators in this case could be a DevOps, could be a SecOps, it could be a platform engineer. It comes in different flavors. But the common denominator, somebody needs an access request, provisioning a new environment, you name it, right? They go to somebody, that person is operator. The operator typically has a few things on their plate. It's not just attending and babysitting platforms, but it's also innovating, spinning up, and scaling services. So they see this typically as kind of, we don't really want to be here, we're going to' go and do this because we're on call. We have to take it on a chin, if you may, for this. >> It's their child, they got to' do it. >> Right, but it's KTLOs, right, keep the lights on, this is maintenance of a platform. It's not what they're born and bred to do, which is innovate. That's essentially what we're seeing, we're seeing that a lot of these platforms, once they finally hit the point of maturity, they're rolled out to the team. People come to serve themselves in platform, and low and behold, it's not as self-service as it may seem. >> We've seen that certainly with Kubernetes adoption being, I won't say slow, it's been fast, but it's been good. But I think this is kind of the promise of what SRE was supposed to be. You know, do it once and then babysit in the sense of it's working and automated. Nothing's broken yet. Don't call me unless you need something, I see that. So the question, you're trying to make it easier then, you're trying to free up the talent. >> Talent to operate and have essentially a human, like in the loop, essentially augment that person and give the end users all of the answers they require, as if they're talking to a person. >> I mean it's basically, you're taking the virtual assistant concept, or chat bot, to a level of expertise where there's intelligence, jargon, experience into the workflows that's known. Not just talking to chat bot, get a support number to rebook a hotel room. >> We're converting operational workflows into conversations. >> Give me an example, take me through an example. >> Sure, let's take a simple example. I mean, not everyone provisions EC2's with two days (indistinct). But let's say you want to go and provision new EC2 instances, okay? If you wanted to do it, you could go and talk to the assistant and say, "I want to spin up a new server". If it was a human in the loop, they would ask you the following questions: what type of environment? what are we attributing this to? what type of instance? security groups, machine images, you name it. So, these are the questions that typically somebody needs to be armed with before they can go and provision themselves, serve themselves. Now the problem is users don't always have these questions. So imagine the following scenario. Somebody comes in, they're in Jira ticket queue, they finally, their turn is up and the next question they don't have the answer to. So now they have to go and tap on a friend, or they have to go essentially and get that answer. By the time they get back, they lost their turn in queue. And then that happens again. So, they lose a context, they lose essentially the momentum. And a simple access request, or a simple provision request, can easily become a couple days of ping pong back and forth. This won't happen with the virtual assistant. >> You know, I think, you know, and you mentioned chat bots, but also RPA is out there, you've seen a lot of that growth. One of the hard things, and you brought this up, I want to get your reaction to, is contextualizing the workflow. It might not be apparent, but the answer might be there, it disrupts the entire experience at that point. RPA and chat bots don't have that contextualization. Is that what you guys do differently? Is that the unique flavor here? Is that difference between current chat bots and RPA? >> The way we see it, I alluded to the intent based operations. Let me give a tangible experience. Even not from our own world, this will be easy. It's a bidirectional feedback loop 'cause that's actually what feeds the context and the intent. We all know Waze, right, in the world of navigation. They didn't bring navigation systems to the world. What they did is they took the concept of navigation systems that are typically satellite guided and said it's not just enough to drive down the 280, which typically have no traffic, right, and to come across traffic and say, oh, why didn't my satellite pick that up? So they said, have the end users, the end nodes, feed that direction back, that feedback, right. There has to be a bidirectional feedback loop that the end nodes help educate the system, make the system be better, more customized. And that's essentially what we're allowing the end users. So the maintenance of the system isn't entirely in the hands of the operators, right? 'Cause that's the part that they dread. And the maintenance of the system is democratized across all the users that they can teach the system, give input to the system, hone in the system in order to make it more of the DNA of the organization. >> You and I were talking before you came on this camera interview, you said playfully that the Siri for DevOps, which kind of implies, hey infrastructure, do something for me. You know, we all know Siri, so we get that. So that kind of illustrates kind of where the direction is. Explain why you say that, what does that mean? Is that like a NorthStar vision that you guys are approaching? You want to' have a state where everything's automated in it's conversational deployments, that kind of thing. And take us through why that Siri for DevOps is. >> I think it helps anchor people to what a virtual assistant is. Because when you hear virtual assistant, that can mean any one of various connotations. So the Siri is actually a conversational assistant, but it's not necessarily a virtual assistant. So what we're saying is we're anchoring people to that thought and saying, we're actually allowing it to be operational, turning complex operations into simple conversations. >> I mean basically they take the automate with voice Google search or a query, what's the score of the game? And, it also, and talking to the guy who invented Siri, I actually interviewed on theCUBE, it's a learning system. It actually learns as it gets more usage, it learns. How do you guys see that evolving in DevOps? There's a lot of jargon in DevOps, a lot of configurations, a lot of different use cases, a lot of new technologies. What's the secret sauce behind what you guys do? Is it the conversational AI, is it the machine learning, is it the data, is it the model? Take us through the secret sauce. >> In fact, it's all the above. And I don't think we're bringing any one element to the table that hasn't been explored before, hasn't been done. It's a recipe, right? You give two people the same ingredients, they can have complete different results in terms of what they come out with. We, because of our domain expertise in DevOps, because of our familiarity with developer workflows with operators, we know how to give a very well suited recipe. Five course meal, hopefully with Michelin stars as part of that. So a few things, maybe a few of the secret sauce element, conversational AI, the ability to essentially go and extract the intent of the user, so that if we're missing context, the system is smart enough to go and to get that feedback and to essentially feed itself into that model. >> Someone might say, hey, you know, conversational AI, that was yesterday's trend, it never happened. It was kind of weak, chat bots were lame. What's different now and with you guys, and the market, that makes a redo or a second shot at this, a second bite at the apple, as they say. What do you guys see? 'Cause you know, I would argue that it's, you know, it's still early, real early. >> Certainly. >> How do you guys view that? How would you handle that objection? >> It's a fair question. I wasn't around the first time around to tell you what didn't work. I'm not afraid to share that the feedback that we're getting is phenomenal. People understand that we're actually customizing the workflows, the intent based operations to really help hone in on the dark spots. We call it last mile, you know, bottlenecks. And that's really where we're helping. We're helping in a way tribalize internal knowledge that typically hasn't been documented because it's painful enough to where people care about it but not painful enough to where you're going to' go and sit down an entire day and document it. And that's essentially what the virtual assistant can do. It can go and get into those crevices and help document, and operationalize all of those toils. And into workflows. >> Yeah, I mean some will call it grunt work, or low level work. And I think the automation is interesting. I think we're seeing this in a lot of these high scale situations where the talented hard to hire person is hired to do, say, things that were hard to do, but now harder things are coming around the corner. So, you know, serverless is great and all this is good, but it doesn't make the complexity go away. As these inflection points continue to drive more scale, the complexity kind of grows, but at the same time so is the ability to abstract away the complexity. So you're starting to see the smart, hired guns move to higher, bigger problems. And the automation seems to take the low level kind of like capabilities or the toil, or the grunt work, or the low level tasks that, you know, you don't want a high salaried person doing. Or I mean it's not so much that they don't want to' do it, they'll take one for the team, as you said, or take it on the chin, but there's other things to work on. >> I want to add one more thing, 'cause this goes into essentially what you just said. Think about it's not the virtual system, what it gives you is not just the intent and that's one element of it, is the ability to carry your operations with you to the place where you're not breaking your workflows, you're actually comfortable operating. So the virtual assistant lives inside of a command line interface, it lives inside of chat like Slack, and Teams, and Mattermost, and so forth. It also lives within a low-code editor. So we're not forcing anyone to use uncomfortable language or operations if they're not comfortable with. It's almost like Siri, it travels in your mobile phone, it's on your laptop, it's with you everywhere. >> It makes total sense. And the reason why I like this, and I want to' get your reaction on this because we've done a lot of interviews with DevOps, we've met at every CubeCon since it started, and Kubernetes kind of highlights the value of the containers at the orchestration level. But what's really going on is the DevOps developers, and the CICD pipeline, with infrastructure's code, they're basically have a infrastructure configuration at their disposal all the time. And all the ops challenges have been around that, the repetitive mundane tasks that most people do. There's like six or seven main use cases in DevOps. So the guardrails just need to be set. So it sounds like you guys are going down the road of saying, hey here's the use cases you can bounce around these use cases all day long. And just keep doing your jobs cause they're bolting on infrastructure to every application. >> There's one more element to this that we haven't really touched on. It's not just workflows and use cases, but it's also knowledge, right? Tribal knowledge, like you asked me for an example. You can type or talk to the assistant and ask, "How much am I spending on AWS, on US East 1, on so and so customer environment last week?", and it will know how to give you that information. >> Can I ask, should I buy a reserve instances or not? Can I ask that question? 'Cause there's always good trade offs between buying the reserve instances. I mean that's kind of the thing that. >> This is where our ecosystem actually comes in handy because we're not necessarily going to' go down every single domain and try to be the experts in here. We can tap into the partnerships, API, we have full extensibility in API and the software development kit that goes into. >> It's interesting, opinionated and declarative are buzzwords in developer language. So you started to get into this editorial thing. So I can bring up an example. Hey cube, implement the best service mesh. What answer does it give you? 'Cause there's different choices. >> Well this is actually where the operator, there's clearly guard rails. Like you can go and say, I want to' spin up a machine, and it will give you all of the machines on AWS. Doesn't mean you have to get the X one, that's good for a SAP environment. You could go and have guardrails in place where only the ones that are relevant to your team, ones that have resources and budgetary, you know, guidelines can be. So, the operator still has all the control. >> It was kind of tongue in cheek around the editorialized, but actually the answer seems to be as you're saying, whatever the customer decided their service mesh is. So I think this is where it gets into as an assistant to architecting and operating, that seems to be the real value. >> Now code snippets is a different story because that goes on to the web, that goes onto stock overflow, and that's actually one of the things. So inside the CLI, you could actually go and ask for code snippets and we could actually go and populate that, it's a smart CLI. So that's actually one of the things that are an added value of that. >> I was saying to a friend and we were talking about open source and how when I grew up, there was no open source. If you're a developer now, I mean there's so much code, it's not so much coding anymore as it is connecting and integrating. >> Certainly. >> And writing glue layers, if you will. I mean there's still code, but it's not, you don't have to build it from scratch. There's so much code out there. This low-code notion of a smart system is interesting 'cause it's very matrix like. It can build its own code. >> Yes, but I'm also a little wary with low-code and no code. I think part of the problem is we're so constantly focused on categories and categorizing ourselves, and different categories take on a life of their own. So low-code no code is not necessarily, even though we have the low-code editor, we're not necessarily considering ourselves low-code. >> Serverless, no code, low-code. I was so thrown on a term the other day, architecture-less. As a joke, no we don't need architecture. >> There's a use case around that by the way, yeah, we do. Show me my AWS architecture and it will build the architect diagram for you. >> Again, serverless architect, this is all part of infrastructure's code. At the end of the day, the developer has infrastructure with code. Again, how they deploy it is the neuron. That's what we've been striving for. >> But infrastructure is code. You can destroy, you know, terraform, you can go and create one. It's not necessarily going to' operate it for you. That's kind of where this comes in on top of that. So it's really complimentary to infrastructure. >> So final question, before we get into the origination story, data and security are two hot areas we're seeing fill the IT gap, that has moved into the developer role. IT is essentially provisioned by developers now, but the OP side shifted to large scale SRE like environments, security and data are critical. What's your opinion on those two things? >> I agree. Do you want me to give you the normal data as gravity? >> So you agree that IT is now, is kind of moved into the developer realm, but the new IT is data ops and security ops basically. >> A hundred percent, and the lines are so blurred. Like who's what in today's world. I mean, I can tell you, I have customers who call themselves five different roles in the same day. So it's, you know, at the end of the day I call 'em operators 'cause I don't want to offend anybody because that's just the way it is. >> Architectural-less, we're going to' come back to that. Well, I know we're going to' see you at CubeCon. >> Yes. >> We should catch up there and talk more. I'm looking forward to seeing how you guys get the feedback from the marketplace. It should be interesting to hear, the curious question I have for you is, what was the origination story? Why did you guys come together, was it a shared problem? Was it a big market opportunity? Was it an itch you guys were scratching? Did you feel like you needed to come together and start this company? What was the real vision behind the origination? Take a take a minute to explain the story. >> No, absolutely. So I've been living in Palo Alto for the last couple years. Previous, also a founder. So, you know, from my perspective, I always saw myself getting back in the game. Spent a few years in AWS essentially managing partnerships for tier one DevOps partners, you know, all of the known players. Some in public, some of them not. And really the itch was there, right. I saw what everyone's doing. I started seeing consistency in the pains that I was hearing back, in terms of what hasn't been solved. So I already had an opinion where I wanted to go. And when I was visiting actually Israel with the family, I was introduced by a mutual friend to Shaked, Shaked Askayo, my co-founder and CTO. Amazing guy, unbelievable technologists, probably one the most, you know, impressive folks I've had a chance to work with. And he actually solved a very similar problem, you know, in his own way in a previous company, BlueVine, a FinTech company where he was head of SRE, having to, essentially, oversee 200 developers in a very small team. The ratio was incongruent to what the SRE guideline would tell. >> That's more than 10 x rate developer. >> Oh, absolutely. Sure enough. And just imagine it's four different time zones. He finishes day shift and you already had the US team coming, asking for a question. He said, this is kind of a, >> Got to' clone himself, basically. >> Well, yes. He essentially said to me, I had no day, I had no life, but I had Corona, I had COVID, which meant I could work from home. And I essentially programed myself in the form of a bot. Essentially, when people came to him, he said, "Don't talk to me, talk to the bot". Now that was a different generation. >> Just a trivial example, but the idea was to automate the same queries all the time. There's an answer for that, go here. And that's the benefit of it. >> Yes, so he was able to see how easy it was to solve, I mean, how effective it was solving 70% of the toil in his organization. Scaling his team, froze the headcount and the developer team kept on going. So that meant that he was doing some right. >> When you have a problem, and you need to solve it, the creativity comes out of the woodwork, you know, invention is the mother of necessity. So final question for you, what's next? Got the launch, what are you guys hope to do over the next six months to a year, hiring? Put a plug in for the company. What are you guys looking to do? Take a minute to share the future vision and get a plug in. >> A hundred percent. So, Kubiya, as you can imagine, announcing ourselves at CubeCon, so in a couple weeks. Opening the gates towards the public beta and NGA in the next couple months. Essentially working with dozens of customers, Aston Martin, and business earn in. We have quite a few, our website's full of quotes. You can go ahead. But effectively we're looking to go and to bring the next operator, generation of operators, who value their time, who value the, essentially, the value of tribal knowledge that travels between organizations that could be essentially shared. >> How many customers do you guys have in your pre-launch? >> It's above a dozen. Without saying, because we're actually looking to onboard 10 more next week. So that's just an understatement. It changes from day to day. >> What's the number one thing people are saying about you? >> You got that right. I know it's, I'm trying to be a little bit more, you know. >> It's okay, you can be cocky, startups are good. But I mean they're obviously, they're using the product and you're getting good feedback. Saving time, are they saying this is a dream product? Got it right, what are some of the things? >> I think anybody who doesn't feel the pain won't know, but the folks who are in the trenches, or feeling the pain, or experiencing this toil, who know what this means, they said, "You're doing this different, you're doing this right. You architected it right. You know exactly what the developer workflows," you know, where all the areas, you know, where all the skeletons are hidden within that. And you're attending to that. So we're happy about that. >> Everybody wants to clone themselves, again, the tribal knowledge. I think this is a great example of where we see the world going. Make things autonomous, operationally automated for the use cases you know are lock solid. Why wouldn't you just deploy? >> Exactly, and we have a very generous free tier. People can, you know, there's a plugin, you can sign up for free until the end of the year. We have a generous free tier. Yeah, free forever tier, as well. So we're looking for people to try us out and to give us feedback. >> I think the self-service, I think the point is, we've talked about it on the Cube at our events, everyone says the same thing. Every developer wants self-service, period. Full stop, done. >> What they don't say is they need somebody to help them babysit to make sure they're doing it right. >> The old dashboard, green, yellow, red. >> I know it's an analogy that's not related, but have you been to Whole Foods? Have you gone through their self-service line? That's the beauty of it, right? Having someone in a loop helping you out throughout the time. You don't get confused, if something's not working, someone's helping you out, that's what people want. They want a human in the loop, or a human like in the loop. We're giving that next best thing. >> It's really the ratio, it's scale. It's a scaling. It's force multiplier, for sure. Amit, thanks for coming on, congratulations. >> Thank you so much. >> See you at KubeCon. Thanks for coming in, sharing the story. >> KubiyaCon. >> CubeCon. Cube in Hebrew, Kubiya. Founder, co-founder and CEO here, sharing the story in the launch. Conversational AI for DevOps, the theory of DevOps, really kind of changing the game, bringing efficiency, solving a lot of the pain points of large scale infrastructure. This is theCUBE, CUBE conversation, I'm John Furrier, thanks for watching. (upbeat electronic music)

(dramatic wooshing) >> Hello, and I'm John Furrier, host of theCUBE. Check out the upcoming Season 2, Episode 4 AWS Startup Showcase featuring Cybersecurity. We got 10 hot growing startups. We got keynote from Jon Ramsey, Vice President of AWS Security, as well as amazing Heroes, AWS Cloud Heroes in security, Liz Rice, and we've got some amazing, talented people sharing their insights. Here on theCUBE, every episode is a new topic. This topic is cybersecurity. Check it out. It's an ongoing series. It's the hottest startups in the ecosystem of AWS, Amazon Web Services. It's theCUBE.

>>And welcome back to the cubes coverage of a, of us. Reinforc here in Boston, Massachusetts. I'm John furrier. We're here for a great interview on the next generation topic of state of industrial security. We have two great guests, Tim Jefferson, senior vice president data network and application security at Barracuda. And Cenon Aron vice president of zero trust engineering at Barracuda. Gentlemen. Thanks for coming on the queue. Talk about industrial security. >>Yeah, thanks for having us. >>So one of the, one of the big things that's going on, obviously you got zero trust. You've got trusted, trusted software supply chain challenges. You've got hardware mattering more than ever. You've got software driving everything, and all this is talking about industrial, you know, critical infrastructure. We saw the oil pipeline had a hack and ransomware attack, and that's just constant barrage of threats in the industrial area. And all the data is pointing to that. This area is gonna be fast growth machine learning's kicking in automation is coming in. You see a huge topic, huge growth trend. What is the big story going on here? >>Yeah, I think at a high level, you know, we did a survey and saw that, you know, over 95% of the organizations are experiencing, you know, security challenges in this space. So, you know, the blast radius in the, of the, the interface that this creates so many different devices and things and objects that are getting network connected now create a huge challenge for security teams to kind of get their arms around that. >>Yeah. And I can add that, you know, majority of these incidents that, that these organizations suffer lead to significant downtime, right? And we're talking about operational technology here, you know, lives depend on, on these technologies, right? Our, our wellbeing everyday wellbeing depend on those. So, so that is a key driver of initiatives and projects to secure industrial IOT and operational technologies in, in these businesses. >>Well, it's great to have both of you guys on, you know, Tim, you know, you had a background at AWS and sit on your startup, founder, soldier, coming to Barracuda, both very experienced, seeing the ways before in this industry. And I'd like to, if you don't mind talk about three areas, remote access, which we've seen in huge demand with, with the pandemic and the out, coming out with the hybrid and certainly industrial, that's a big part of it. And then secondly, that the trend of clear commitment from enterprises to have in a public cloud component, and then finally the secure access edge, you know, with SAS business models, securing these things, these are the three hot areas let's go into the first one, remote access. Why is this important? It seems that this is the top priority for having immediate attention on what's the big challenge here? Is it the most unsecure? Is it the most important? What, why is this relevant? >>So now I'll let you jump in there. >>Yeah, sure. Happy to. I mean, if you think about it, especially now, we've been through a, a pandemic shelter in place cycle for almost two years. It, it becomes essentially a business continuity matter, right? You do need remote access. We also seen a tremendous shift in hiring the best talent, wherever they are, right. Onboarding them and bringing the talent into, into, into, into businesses that have maybe a lot more distributed environments than traditionally. So you have to account for remote access in every part of everyday life, including industrial technologies, you need remote support, right? You need vendors that might be overseas providing you, you know, guidance and support for these technologies. So remote support is every part of life. Whether you work from home, you work on your, on the go, or you are getting support from a vendor that happens to be in Germany, you know, teleporting into your environment in Hawaii. You know, all these things are essentially critical parts of everyday life. Now >>Talk about ZT and a zero trust network access is a, this is a major component for companies. Obviously, you know, it's a position taking trust and verifies. One other approach, zero trust is saying, Hey, I don't trust you. Take us through why that's important. Why is zero trust network access important in this area? >>Yeah. I mean, I could say that traditionally remote access, if you think about infancy of the internet in the nineties, right? It was all about encryption in, in transit, right? You were all about internet was vastly clear text, right? We didn't have even SSL TLS, widely distributed and, and available. So when VPNs first came out, it was more about preventing sniffing, clear tech clear text information from, from, from the network, right? It was more about securing the, the transport, but now that kind of created a, a big security control gap, which implicitly trusted user users, once they are teleported into a remote network, right? That's the essence of having a remote access session you're brought from wherever you are into an internal network. They implicitly trust you that simply breakdown over time because you are able to compromise end points relatively easily using browser exploits. >>You know, so, so for supply chain issues, water hole attacks, and leverage the existing VPN tunnels to laterally move into the organization from within the network, you literally move in further and further and further down, you know, down the network, right? So the VPN needed a, a significant innovation. It was meant to be securing packets and transit. It was all about an encryption layer, but it had an implicit trust problem with zero trust. We turn it into an explicit trust problem, right? Explicit trust concept, ideally. Right? So you are, who do you say you are? And you are authorized to access only to things that you need to access to get the work done. >>So you're talking about granular levels versus the one time database look up you're in >>That's right. >>Tim, talk about the OT it side of this equation of industrial, because it, you know, is IP based, networking, OT have been purpose built, you know, maybe some proprietary technology yeah. That connects to the internet internet, but it's mainly been secure. Those have come together over the years and now with no perimeter security, how is this world evolving? Because there's gonna be more cloud there, be more machine learning, more hybrid on premise, that's going on almost a reset if you will. I mean, is it a reset? What's the, what's the situation. >>Yeah. I think, you know, in typical human behavior, you know, there's a lot of over rotation going on. You know, historically a lot of security controls are all concentrated in a data center. You know, a lot of enterprises had very large sophisticated well-established security stacks in a data center. And as those applications kind of broke down and, and got rearchitected for the cloud, they got more modular, they got more distributed that centralized security stack became an anti pattern. So now this kind of over rotation, Hey, let's take this stack and, and put it up in the cloud. You know, so there's lots of names for this secure access, service edge, you know, secure service edge. But in the end, you know, you're taking your controls and, and migrating them into the cloud. And, you know, I think ultimately this creates a great opportunity to embrace some of security, best practices that were difficult to do in some of the legacy architectures, which is being able to push your controls as far out to the edge as possible. >>And the interesting thing about OT and OT now is just how far out the edge is, right? So instead of being, you know, historically it was the branch or user edge, remote access edge, you know, Syon mentioned that you, you have technologies that can VPN or bring those identities into those networks, but now you have all these things, you know, partners, devices. So it's the thing, edge device edge, the user edge. So a lot more fidelity and awareness around who users are. Cause in parallel, a lot of the IDP and I IBM's platforms have really matured. So marrying those concepts of this, this lot of maturity around identity management yeah. With device in and behavior management into a common security framework is really exciting. But of course it's very nascent. So people are, it's a difficult time getting your arms around >>That. It's funny. We were joking about the edge. We just watching the web telescope photos come in the deep space, the deep edge. So the edge is continuing to be pushed out. Totally see that. And in fact, you know, one of the things we're gonna, we're gonna talk about this survey that you guys had done by an independent firm has a lot of great data. I want to unpack that, but one of the things that was mentioned in there, and I'll get, I wanna get your both reaction to this is that virtually all organizations are committing to the public cloud. Okay. I think it was like 96% or so was the stat. And if you combine in that, the fact that the edge is expanding, the cloud model is evolving at the edge. So for instance, a building, there's a lot behind it. You know, how far does it go? So we don't and, and what is the topology because the topology seem to change too. So there's this growth and change where we need cloud operations, DevOps at, at the edge and the security, but it's changing. It's not pure cloud, but it's cloud. It has to be compatible. What's your reaction to that, Tim? I mean, this is, this is a big part of the growth of industrial. >>Yeah. I think, you know, if you think about, there's kind of two exciting developments that I would think of, you know, obviously there's this increase to the surface area, the tax surface areas, people realize, you know, it's not just laptops and devices and, and people that you're trying to secure, but now they're, you know, refrigerators and, you know, robots and manufacturing floors that, you know, could be compromised, have their firmware updated or, you know, be ransomware. So this a huge kind of increase in surface area. But a lot of those, you know, industrial devices, weren't built around the concept with network security. So kind of bolting on, on thinking through how can you secure who and what ultimately has access to those, to those devices and things. And where is the control framework? So to your point, the control framework now is typically migrated now into public cloud. >>These are custom applications, highly distributed, highly available, very modular. And then, you know, so how do you, you know, collect the telemetry or control information from these things. And then, you know, it creates secure connections back into these, these control applications, which again, are now migrated to public cloud. So you have this challenge, you know, how do you secure? We were talking about this last time we discussed, right. So how do you secure the infrastructure that I've, I've built in deploying now, this control application and in public cloud, and then connect in with this, this physical presence that I have with these, you know, industrial devices and taking telemetry and control information from those devices and bringing it back into the management. And this kind marries again, back into the remote axis that Sunan was mentioning now with this increase awareness around the efficacy of ransomware, we are, you know, we're definitely seeing attackers going after the management frameworks, which become very vulnerable, you know, and they're, they're typically just unprotected web applications. So once you get control of the management framework, regardless of where it's hosted, you can start moving laterally and, and causing some damage. >>Yeah. That seems to be the common thread. So no talk about, what's your reaction to that because, you know, zero trust, if it's evolving and changing, you, you gotta have zero trust you. I didn't even know it's out there and then it gets connected. How do you solve that problem? Cuz you know, there's a lot of surface area that's evolving all the OT stuff and the new, it, what's the, what's the perspective and posture that the clients your clients are having and customers. Well, >>I, I think they're having this conversation about further mobilizing identity, right? We did start with, you know, user identity that become kind of the first foundational building block for any kind of zero trust implementation. You work with, you know, some sort of SSO identity provider, you get your, you sync with your user directories, you have a single social truth for all your users. >>You authenticate them through an identity provider. However that didn't quite cut it for industrial OT and OT environments. So you see like we have the concept of hardware machines, machine identities now become an important construct, right? The, the legacy notion of being able to put controls and, and, and, and rules based on network constructs doesn't really scale anymore. Right? So you need to have this concept of another abstraction layer of identity that belongs to a service that belongs to an application that belongs to a user that belongs to a piece of hardware. Right. And then you can, yeah. And then you can build a lot more, of course, scalable controls that basically understand the, the trust relation between these identities and enforce that rather than trying to say this internal network can talk to this other internal network through a, through a network circuit. No, those things are really, are not scalable in this new distributed landscape that we live in today. So identity is basically going to operationalize zero trust and a lot more secure access going forward. >>And that's why we're seeing the sassy growth. Right. That's a main piece of it. Is that what you, what you're seeing too? I mean, that seems to be the, the approach >>I think like >>Go >>Ahead to, yeah. I think like, you know, sassy to me is really about, you know, migrating and moving your security infrastructure to the cloud edge, you know, as we talked to the cloud, you know, and then, you know, do you funnel all ingress and egress traffic through this, you know, which is potentially an anti pattern, right? You don't wanna create, you know, some brittle constraint around who and what has access. So again, a security best practices, instead of doing all your enforcement in one place, you can distribute and push your controls out as far to the edge. So a lot of SASI now is really around centralizing policy management, which is the big be one of the big benefits is instead of having all these separate management plans, which always difficult to be very federated policy, right? You can consolidate your policy and then decide mechanism wise how you're gonna instrument those controls at the edge. >>So I think that's the, the real promise of, of the, the sassy movement and the, I think the other big piece, which you kind of touched on earlier is around analytics, right? So it creates an opportunity to collect a whole bunch of telemetry from devices and things, behavior consumption, which is, which is a big, common, best practice around once you have SA based tools that you can instrument in a lot of visibility and how users and devices are behaving in being operated. And to Syon point, you can marry that in with their identity. Yeah. Right. And then you can start building models around what normal behavior is and, you know, with very fine grain control, you can, you know, these types of analytics can discover things that humans just can't discover, you know, anomalous behavior, any kind of indicators are compromised. And those can be, you know, dynamic policy blockers. >>And I think sun's point about what he was talking about, talks about the, the perimeters no longer secure. So you gotta go to the new way to do that. Totally, totally relevant. I love that point. Let me ask you guys a question on the, on the macro, if you don't mind, how concerned are you guys on the current threat landscape in the geopolitical situation in terms of the impact on industrial IOT in this area? >>So I'll let you go first. Yeah. >>I mean, it's, it's definitely significantly concerning, especially if now with the new sanctions, there's at least two more countries being, you know, let's say restricted to participate in the global economic, you know, Mar marketplace, right? So if you look at North Korea as a pattern, since they've been isolated, they've been sanctioned for a long time. They actually double down on rents somewhere to even fund state operations. Right? So now that you have, you know, BES be San Russia being heavily sanctioned due to due to their due, due to their activities, we can envision more increase in ransomware and, you know, sponsoring state activities through illegal gains, through compromising, you know, pipelines and, you know, industrial, you know, op operations and, and seeking large payouts. So, so I think the more they will, they're ized they're pushed out from the, from the global marketplace. There will be a lot more aggression towards critical infrastructure. >>Oh yeah. I think it's gonna ignite more action off the books, so to speak as we've seen. Yeah. We've >>Seen, you know, another point there is, you know, Barracuda also runs a, a backup, you know, product. We do a, a purpose built backup appliance and a cloud to cloud backup. And, you know, we've been running this service for over a decade. And historically the, the amount of ransomware escalations that we got were very slow, you know, is whenever we had a significant one, helping our customers recover from them, you know, you know, once a month, but over the last 18 months, this is routine now for us, this is something we deal with on a daily basis. And it's becoming very common. You know, it's, it's been a well established, you know, easily monetized route to market for the bad guys. And, and it's being very common now for people to compromise management planes, you know, they use account takeover. And the first thing they're doing is, is breaking into management planes, looking at control frameworks. And then first thing they'll do is delete, you know, of course the backups, which this sort of highlights the vulnerability that we try to talk to our customers about, you know, and this affects industrial too, is the first thing you have to do is among other things, is, is protect your management planes. Yeah. And putting really fine grain mechanisms like zero trust is, is a great, >>Yeah. How, how good is backup, Tim, if you gets deleted first is like no backup. There it is. So, yeah. Yeah. Air gaping. >>I mean, obviously that's kinda a best practice when you're bad guys, like go in and delete all the backups. So, >>And all the air gaps get in control of everything. Let me ask you about the, the survey pointed out that there's a lot of security incidents happening. You guys pointed that out and discussed a little bit of it. We also talked about in the survey, you know, the threat vectors and the threat landscape, the common ones, ransomware was one of them. The area that I liked, what that was interesting was the, the area that talked about how organizations are investing in security and particularly around this, can you guys share your thoughts on how you see the, the market, your customers and, and the industry investing? What are they investing in? What stage are they in when it comes to IOT and OT, industrial IOT and OT security, do they do audits? Are they too busy? I mean, what's the state of their investment thesis progress of, of, of how they're investing in industrial IOT? >>Yeah. Our, our view is, you know, we have a next generation product line. We call, you know, our next, our cloud chain firewalls. And we have a form factor that sports industrial use cases we call secure connectors. So it's interesting that if you, what we learned from that business is a tremendous amount of bespoke efforts at this point, which is sort of indicative of a, of a nascent market still, which is related to another piece of information I thought was really interested in the survey that I think it was 93% of the, the participants, the enterprises had a failed OT initiative, you know, that, you know, people tried to do these things and didn't get off the ground. And then once we see build, you know, strong momentum, you know, like we have a, a large luxury car manufacturer that uses our secure connectors on the, on the robots, on the floor. >>So well established manufacturing environments, you know, building very sophisticated control frameworks and, and security controls. And, but again, a very bespoke effort, you know, they have very specific set of controls and specific set of use cases around it. So it kind of reminds me of the late nineties, early two thousands of people trying to figure out, you know, networking and the blast radi and networking and, and customers, and now, and a lot of SI are, are invested in this building, you know, fast growing practices around helping their customers build more robust controls in, in helping them manage those environments. So, yeah, I, I think that the market is still fairly nascent >>From what we seeing, right. But there are some encouraging, you know, data that shows that at least helpful of the organizations are actively pursuing. There's an initiative in place for OT and a, you know, industrial IOT security projects in place, right. They're dedicating time and resources and budget for this. And, and in, in regards to industries, verticals and, and geographies oil and gas, you know, is, is ahead of the curve more than 50% responded to have the project completed, which I guess colonial pipeline was the, you know, the call to arms that, that, that was the big, big, you know, industrial, I guess, incident that triggered a lot of these projects to be accelerating and, and, you know, coming to the finish line as far as geographies go DACA, which is Germany, Austria, Switzerland, and of course, north America, which happens to be the industrial powerhouses of, of the world. Well, APAC, you know, also included, but they're a bit behind the curve, which is, you know, that part is a bit concerning, but encouragingly, you know, Western Europe and north America is ahead of these, you know, projects. A lot of them are near completion or, or they're in the middle of some sort of an, you know, industrial IOT security project right >>Now. I'm glad you brought the colonial pipeline one and, and oil and gas was the catalyst. Again, a lot of, Hey, scared that better than, than me kinda attitude, better invest. So I gotta ask you that, that supports Tim's point about the management plane. And I believe on that hack or ransomware, it wasn't actually control of the pipeline. It was control over the management billing, and then they shut down the pipeline cuz they were afraid it was gonna move over. So it wasn't actually the critical infrastructure itself to your point, Tim. >>Yeah. It's hardly over the critical infrastructure, by the way, you always go through the management plane, right. It's such an easier lying effort to compromise because it runs on an endpoint it's standard endpoint. Right? All this control software will, will be easier to get to rather than the industrial hardware itself. >>Yeah. It's it's, it's interesting. Just don't make a control software at the endpoint, put it zero trust. So down that was a great point. Oh guys. So really appreciate the time and the insight and, and the white paper's called NETEC it's on the Barracuda. Netex industrial security in 2022. It's on the barracuda.com website Barracuda network guys. So let's talk about the read force event hasn't been around for a while cuz of the pandemic we're back in person what's changed in 2019 a ton it's like security years is not dog years anymore. It's probably dog times too. Right. So, so a lot's gone on where are we right now as an industry relative to the security cybersecurity. Could you guys summarize kind of the, the high order bit on where we are today in 2022 versus 2019? >>Yeah, I think, you know, if you look at the awareness around how to secure infrastructure in applications that are built in public cloud in AWS, it's, you know, exponentially better than it was. I think I remember when you and I met in 2018 at one of these conferences, you know, there were still a lot of concerns, whether, you know, IAS was safe, you know, and I think the amount of innovation that's gone on and then the amount of education and awareness around how to consume, you know, public cloud resources is amazing. And you know, I think that's facilitated a lot of the fast growth we've seen, you know, the consistent, fast growth that we've seen across all these platforms >>Say that what's your reaction to the, >>I think the shared responsibility model is well understood, you know, and, and, and, and we can see a lot more implementation around, you know, CSBM, you know, continuously auditing the configurations in these cloud environments become a, a standard table stake, you know, investment from every stage of any business, right? Whether from early state startups, all the way to, you know, public companies. So I think it's very well understood and, and the, and the investment has been steady and robust when it comes to cloud security. We've been busy, you know, you know, helping our customers and AWS Azure environments and, and others. So I, I think it's well understood. And, and, and we are on a very optimistic note actually in a good place when it comes to public cloud. >>Yeah. A lot of great momentum, a lot of scale and data act out there. People sharing data, shared responsibility. Tim is in, thank you for sharing your insights here in this cube segment coverage of reinforce here in Boston. Appreciate it. >>All right. Thanks for having >>Us. Thank you. >>Okay, everyone. Thanks for watching the we're here at the reinforced conference. AWS, Amazon web services reinforced. It's a security focused conference. I'm John furier host of the cube. We'd right back with more coverage after the short break.

>> The rapid rise of ransomware attacks has added yet another challenge that business technology executives have to worry about these days, cloud storage, immutability, and air gaps have become a must have arrows in the quiver of organization's data protection strategies. But the important reality that practitioners have embraced is data protection, it can't be an afterthought or a bolt on it, has to be designed into the operational workflow of technology systems. The problem is, oftentimes, data protection is complicated with a variety of different products, services, software components, and storage formats, this is why object storage is moving to the forefront of data protection use cases because it's simpler and less expensive. The put data get data syntax has always been alluring, but object storage, historically, was seen as this low-cost niche solution that couldn't offer the performance required for demanding workloads, forcing customers to make hard tradeoffs between cost and performance. That has changed, the ascendancy of cloud storage generally in the S3 format specifically has catapulted object storage to become a first class citizen in a mainstream technology. Moreover, innovative companies have invested to bring object storage performance to parity with other storage formats, but cloud costs are often a barrier for many companies as the monthly cloud bill and egress fees in particular steadily climb. Welcome to Secure Storage Hot Takes, my name is Dave Vellante, and I'll be your host of the program today, where we introduce our community to Wasabi, a company that is purpose-built to solve this specific problem with what it claims to be the most cost effective and secure solution on the market. We have three segments today to dig into these issues, first up is David Friend, the well known entrepreneur who co-founded Carbonite and now Wasabi will then dig into the product with Drew Schlussel of Wasabi, and then we'll bring in the customer perspective with Kevin Warenda of the Hotchkiss School, let's get right into it. We're here with David Friend, the President and CEO and Co-founder of Wasabi, the hot storage company, David, welcome to theCUBE. >> Thanks Dave, nice to be here. >> Great to have you, so look, you hit a home run with Carbonite back when building a unicorn was a lot more rare than it has been in the last few years, why did you start Wasabi? >> Well, when I was still CEO of Wasabi, my genius co-founder Jeff Flowers and our chief architect came to me and said, you know, when we started this company, a state of the art disk drive was probably 500 gigabytes and now we're looking at eight terabyte, 16 terabyte, 20 terabyte, even 100 terabyte drives coming down the road and, you know, sooner or later the old architectures that were designed around these much smaller disk drives is going to run out of steam because, even though the capacities are getting bigger and bigger, the speed with which you can get data on and off of a hard drive isn't really changing all that much. And Jeff foresaw a day when the architectures sort of legacy storage like Amazon S3 and so forth was going to become very inefficient and slow. And so he came up with a new, highly parallelized architecture, and he said, I want to go off and see if I can make this work. So I said, you know, good luck go to it and they went off and spent about a year and a half in the lab, designing and testing this new storage architecture and when they got it working, I looked at the economics of this and I said, holy cow, we can sell cloud storage for a fraction of the price of Amazon, still make very good gross margins and it will be faster. So this is a whole new generation of object storage that you guys have invented. So I recruited a new CEO for Carbonite and left to found Wasabi because the market for cloud storage is almost infinite. You know, when you look at all the world's data, you know, IDC has these crazy numbers, 120 zetabytes or something like that and if you look at that as you know, the potential market size during that data, we're talking trillions of dollars, not billions and so I said, look, this is a great opportunity, if you look back 10 years, all the world's data was on-prem, if you look forward 10 years, most people agree that most of the world's data is going to live in the cloud, we're at the beginning of this migration, we've got an opportunity here to build an enormous company. >> That's very exciting. I mean, you've always been a trend spotter, and I want to get your perspectives on data protection and how it's changed. It's obviously on people's minds with all the ransomware attacks and security breaches, but thinking about your experiences and past observations, what's changed in data protection and what's driving the current very high interest in the topic? >> Well, I think, you know, from a data protection standpoint, immutability, the equivalent of the old worm tapes, but applied to cloud storage is, you know, become core to the backup strategies and disaster recovery strategies for most companies. And if you look at our partners who make backup software like Veeam, Convo, Veritas, Arcserve, and so forth, most of them are really taking advantage of mutable cloud storage as a way to protect customer data, customers backups from ransomware. So the ransomware guys are pretty clever and they, you know, they discovered early on that if someone could do a full restore from their backups, they're never going to pay a ransom. So, once they penetrate your system, they get pretty good at sort of watching how you do your backups and before they encrypt your primary data, they figure out some way to destroy or encrypt your backups as well, so that you can't do a full restore from your backups. And that's where immutability comes in. You know, in the old days you, you wrote what was called a worm tape, you know, write once read many, and those could not be overwritten or modified once they were written. And so we said, let's come up with an equivalent of that for the cloud, and it's very tricky software, you know, it involves all kinds of encryption algorithms and blockchain and this kind of stuff but, you know, the net result is if you store your backups in immutable buckets, in a product like Wasabi, you can't alter it or delete it for some period of time, so you could put a timer on it, say a year or six months or something like that, once that data is written, you know, there's no way you can go in and change it, modify it, or anything like that, including even Wasabi's engineers. >> So, David, I want to ask you about data sovereignty. It's obviously a big deal, I mean, especially for companies with the presence overseas, but what's really is any digital business these days, how should companies think about approaching data sovereignty? Is it just large firms that should be worried about this? Or should everybody be concerned? What's your point of view? >> Well, all around the world countries are imposing data sovereignty laws and if you're in the storage business, like we are, if you don't have physical data storage in-country, you're probably not going to get most of the business. You know, since Christmas we've built data centers in Toronto, London, Frankfurt, Paris, Sydney, Singapore, and I've probably forgotten one or two, but the reason we do that is twofold; one is, you know, if you're closer to the customer, you're going to get better response time, lower latency, and that's just a speed of light issue. But the bigger issue is, if you've got financial data, if you have healthcare data, if you have data relating to security, like surveillance videos, and things of that sort, most countries are saying that data has to be stored in-country, so, you can't send it across borders to some other place. And if your business operates in multiple countries, you know, dealing with data sovereignty is going to become an increasingly important problem. >> So in May of 2018, that's when the fines associated with violating GDPR went into effect and GDPR was like this main spring of privacy and data protection laws and we've seen it spawn other public policy things like the CCPA and think it continues to evolve, we see judgments in Europe against big tech and this tech lash that's in the news in the U.S. and the elimination of third party cookies, what does this all mean for data protection in the 2020s? >> Well, you know, every region and every country, you know, has their own idea about privacy, about security, about the use of even the use of metadata surrounding, you know, customer data and things of this sort. So, you know, it's getting to be increasingly complicated because GDPR, for example, imposes different standards from the kind of privacy standards that we have here in the U.S., Canada has a somewhat different set of data sovereignty issues and privacy issues so it's getting to be an increasingly complex, you know, mosaic of rules and regulations around the world and this makes it even more difficult for enterprises to run their own, you know, infrastructure because companies like Wasabi, where we have physical data centers in all kinds of different markets around the world and we've already dealt with the business of how to meet the requirements of GDPR and how to meet the requirements of some of the countries in Asia and so forth, you know, rather than an enterprise doing that just for themselves, if you running your applications or keeping your data in the cloud, you know, now a company like Wasabi with, you know, 34,000 customers, we can go to all the trouble of meeting these local requirements on behalf of our entire customer base and that's a lot more efficient and a lot more cost effective than if each individual country has to go deal with the local regulatory authorities. >> Yeah, it's compliance by design, not by chance. Okay, let's zoom out for the final question, David, thinking about the discussion that we've had around ransomware and data protection and regulations, what does it mean for a business's operational strategy and how do you think organizations will need to adapt in the coming years? >> Well, you know, I think there are a lot of forces driving companies to the cloud and, you know, and I do believe that if you come back five or 10 years from now, you're going to see majority of the world's data is going to be living in the cloud and I think storage, data storage is going to be a commodity much like electricity or bandwidth, and it's going to be done right, it will comply with the local regulations, it'll be fast, it'll be local, and there will be no strategic advantage that I can think of for somebody to stand up and run their own storage, especially considering the cost differential, you know, the most analysts think that the full, all in costs of running your own storage is in the 20 to 40 terabytes per month range, whereas, you know, if you migrate your data to the cloud, like Wasabi, you're talking probably $6 a month and so I think people are learning how to deal with the idea of an architecture that involves storing your data in the cloud, as opposed to, you know, storing your data locally. >> Wow, that's like a six X more expensive in the clouds, more than six X, all right, thank you, David,-- >> In addition to which, you know, just finding the people to babysit this kind of equipment has become nearly impossible today. >> Well, and with a focus on digital business, you don't want to be wasting your time with that kind of heavy lifting. David, thanks so much for coming in theCUBE, a great Boston entrepreneur, we've followed your career for a long time and looking forward to the future. >> Thank you. >> Okay, in a moment, Drew Schlussel will join me and we're going to dig more into product, you're watching theCUBE, the leader in enterprise and emerging tech coverage, keep it right there. ♪ Whoa ♪ ♪ Brenda in sales got an email ♪ ♪ Click here for a trip to Bombay ♪ ♪ It's not even called Bombay anymore ♪ ♪ But you clicked it anyway ♪ ♪ And now our data's been held hostage ♪ ♪ And now we're on sinking ship ♪ ♪ And a hacker's in our system ♪ ♪ Just 'cause Brenda wanted a trip ♪ ♪ She clicked on something stupid ♪ ♪ And our data's out of our control ♪ ♪ Into the hands of a hacker's ♪ ♪ And he's a giant asshole. ♪ ♪ He encrypted it in his basement ♪ ♪ He wants a million bucks for the key ♪ ♪ And I'm pretty sure he's 15 ♪ ♪ And still going through puberty ♪ ♪ I know you didn't mean to do us wrong ♪ ♪ But now I'm dealing with this all week long ♪ ♪ To make you all aware ♪ ♪ Of all this ransomware ♪ ♪ That is why I'm singing you this song ♪ ♪ C'mon ♪ ♪ Take it from me ♪ ♪ The director of IT ♪ ♪ Don't click on that email from a prince Nairobi ♪ ♪ 'Cuz he's not really a prince ♪ ♪ Now our data's locked up on our screen ♪ ♪ Controlled by a kid who's just fifteen ♪ ♪ And he's using our money to buy a Ferrari ♪ (gentle music) >> Joining me now is Drew Schlussel, who is the Senior Director of Product Marketing at Wasabi, hey Drew, good to see you again, thanks for coming back in theCUBE. >> Dave, great to be here, great to see you. >> All right, let's get into it. You know, Drew, prior to the pandemic, Zero Trust, just like kind of like digital transformation was sort of a buzzword and now it's become a real thing, almost a mandate, what's Wasabi's take on Zero Trust. >> So, absolutely right, it's been around a while and now people are paying attention, Wasabi's take is Zero Trust is a good thing. You know, there are too many places, right, where the bad guys are getting in. And, you know, I think of Zero Trust as kind of smashing laziness, right? It takes a little work, it takes some planning, but you know, done properly and using the right technologies, using the right vendors, the rewards are, of course tremendous, right? You can put to rest the fears of ransomware and having your systems compromised. >> Well, and we're going to talk about this, but there's a lot of process and thinking involved and, you know, design and your Zero Trust and you don't want to be wasting time messing with infrastructure, so we're going to talk about that, there's a lot of discussion in the industry, Drew, about immutability and air gaps, I'd like you to share Wasabi's point of view on these topics, how do you approach it and what makes Wasabi different? >> So, in terms of air gap and immutability, right, the beautiful thing about object storage, which is what we do all the time is that it makes it that much easier, right, to have a secure immutable copy of your data someplace that's easy to access and doesn't cost you an arm and a leg to get your data back. You know, we're working with some of the best, you know, partners in the industry, you know, we're working with folks like, you know, Veeam, Commvault, Arc, Marquee, MSP360, all folks who understand that you need to have multiple copies of your data, you need to have a copy stored offsite, and that copy needs to be immutable and we can talk a little bit about what immutability is and what it really means. >> You know, I wonder if you could talk a little bit more about Wasabi's solution because, sometimes people don't understand, you actually are a cloud, you're not building on other people's public clouds and this storage is the one use case where it actually makes sense to do that, tell us a little bit more about Wasabi's approach and your solution. >> Yeah, I appreciate that, so there's definitely some misconception, we are our own cloud storage service, we don't run on top of anybody else, right, it's our systems, it's our software deployed globally and we interoperate because we adhere to the S3 standard, we interoperate with practically hundreds of applications, primarily in this case, right, we're talking about backup and recovery applications and it's such a simple process, right? I mean, just about everybody who's anybody in this business protecting data has the ability now to access cloud storage and so we've made it really simple, in many cases, you'll see Wasabi as you know, listed in the primary set of available vendors and, you know, put in your private keys, make sure that your account is locked down properly using, let's say multifactor authentication, and you've got a great place to store copies of your data securely. >> I mean, we just heard from David Friend, if I did my math right, he was talking about, you know, 1/6 the cost per terabyte per month, maybe even a little better than that, how are you able to achieve such attractive economics? >> Yeah, so, you know, I can't remember how to translate my fractions into percentages, but I think we talk a lot about being 80%, right, less expensive than the hyperscalers. And you know, we talked about this at Vermont, right? There's some secret sauce there and you know, we take a different approach to how we utilize the raw capacity to the effective capacity and the fact is we're also not having to run, you know, a few hundred other services, right? We do storage, plain and simple, all day, all the time, so we don't have to worry about overhead to support, you know, up and coming other services that are perhaps, you know, going to be a loss leader, right? Customers love it, right, they see the fact that their data is growing 40, 80% year over year, they know they need to have some place to keep it secure, and, you know, folks are flocking to us in droves, in fact, we're seeing a tremendous amount of migration actually right now, multiple petabytes being brought to Wasabi because folks have figured out that they can't afford to keep going with their current hyperscaler vendor. >> And immutability is a feature of your product, right? What the feature called? Can you double-click on that a little bit? >> Yeah, absolutely. So, the term in S3 is Object Lock and what that means is your application will write an object to cloud storage, and it will define a retention period, let's say a week. And for that period, that object is immutable, untouchable, cannot be altered in any way, shape, or form, the application can't change it, the system administration can't change it, Wasabi can't change it, okay, it is truly carved in stone. And this is something that it's been around for a while, but you're seeing a huge uptick, right, in adoption and support for that feature by all the major vendors and I named off a few earlier and the best part is that with immutability comes some sense of, well, it comes with not just a sense of security, it is security. Right, when you have data that cannot be altered by anybody, even if the bad guys compromise your account, they steal your credentials, right, they can't take away the data and that's a beautiful thing, a beautiful, beautiful thing. >> And you look like an S3 bucket, is that right? >> Yeah, I mean, we're fully compatible with the S3 API, so if you're using S3 API based applications today, it's a very simple matter of just kind of redirecting where you want to store your data, beautiful thing about backup and recovery, right, that's probably the simplest application, simple being a relative term, as far as lift and shift, right? Because that just means for your next full, right, point that at Wasabi, retain your other fulls, you know, for whatever 30, 60, 90 days, and then once you've kind of made that transition from vine to vine, you know, you're often running with Wasabi. >> I talked to my open about the allure of object storage historically, you know, the simplicity of the get put syntax, but what about performance? Are you able to deliver performance that's comparable to other storage formats? >> Oh yeah, absolutely, and we've got the performance numbers on the site to back that up, but I forgot to answer something earlier, right, you said that immutability is a feature and I want to make it very clear that it is a feature but it's an API request. Okay, so when you're talking about gets and puts and so forth, you know, the comment you made earlier about being 80% more cost effective or 80% less expensive, you know, that API call, right, is typically something that the other folks charge for, right, and I think we used the metaphor earlier about the refrigerator, but I'll use a different metaphor today, right? You can think of cloud storage as a magical coffee cup, right? It gets as big as you want to store as much coffee as you want and the coffee's always warm, right? And when you want to take a sip, there's no charge, you want to, you know, pop the lid and see how much coffee is in there, no charge, and that's an important thing, because when you're talking about millions or billions of objects, and you want to get a list of those objects, or you want to get the status of the immutable settings for those objects, anywhere else it's going to cost you money to look at your data, with Wasabi, no additional charge and that's part of the thing that sets us apart. >> Excellent, so thank you for that. So, you mentioned some partners before, how do partners fit into the Wasabi story? Where do you stop? Where do they pick up? You know, what do they bring? Can you give us maybe, a paint a picture for us example, or two? >> Sure, so, again, we just do storage, right, that is our sole purpose in life is to, you know, to safely and securely store our customer's data. And so they're working with their application vendors, whether it's, you know, active archive, backup and recovery, IOT, surveillance, media and entertainment workflows, right, those systems already know how to manage the data, manage the metadata, they just need some place to keep the data that is being worked on, being stored and so forth. Right, so just like, you know, plugging in a flash drive on your laptop, right, you literally can plug in Wasabi as long as your applications support the API, getting started is incredibly easy, right, we offer a 30-day trial, one terabyte, and most folks find that within, you know, probably a few hours of their POC, right, it's giving them everything they need in terms of performance, in terms of accessibility, in terms of sovereignty, I'm guessing you talked to, you know, Dave Friend earlier about data sovereignty, right? We're global company, right, so there's got to be probably, you know, wherever you are in the world some place that will satisfy your sovereignty requirements, as well as your compliance requirements. >> Yeah, we did talk about sovereignty, Drew, this is really, what's interesting to me, I'm a bit of a industry historian, when I look back to the early days of cloud, I remember the large storage companies, you know, their CEOs would say, we're going to have an answer for the cloud and they would go out, and for instance, I know one bought competitor of Carbonite, and then couldn't figure out what to do with it, they couldn't figure out how to compete with the cloud in part, because they were afraid it was going to cannibalize their existing business, I think another part is because they just didn't have that imagination to develop an architecture that in a business model that could scale to see that you guys have done that is I love it because it brings competition, it brings innovation and it helps lower clients cost and solve really nagging problems. Like, you know, ransomware, of mutability and recovery, I'll give you the last word, Drew. >> Yeah, you're absolutely right. You know, the on-prem vendors, they're not going to go away anytime soon, right, there's always going to be a need for, you know, incredibly low latency, high bandwidth, you know, but, you know, not all data's hot all the time and by hot, I mean, you know, extremely hot, you know, let's take, you know, real time analytics for, maybe facial recognition, right, that requires sub-millisecond type of processing. But once you've done that work, right, you want to store that data for a long, long time, and you're going to want to also tap back into it later, so, you know, other folks are telling you that, you know, you can go to these like, you know, cold glacial type of tiered storage, yeah, don't believe the hype, you're still going to pay way more for that than you would with just a Wasabi-like hot cloud storage system. And, you know, we don't compete with our partners, right? We compliment, you know, what they're bringing to market in terms of the software vendors, in terms of the hardware vendors, right, we're a beautiful component for that hybrid cloud architecture. And I think folks are gravitating towards that, I think the cloud is kind of hitting a new gear if you will, in terms of adoption and recognition for the security that they can achieve with it. >> All right, Drew, thank you for that, definitely we see the momentum, in a moment, Drew and I will be back to get the customer perspective with Kevin Warenda, who's the Director of Information technology services at The Hotchkiss School, keep it right there. >> Hey, I'm Nate, and we wrote this song about ransomware to educate people, people like Brenda. >> Oh, God, I'm so sorry. We know you are, but Brenda, you're not alone, this hasn't just happened to you. >> No! ♪ Colonial Oil Pipeline had a guy ♪ ♪ who didn't change his password ♪ ♪ That sucks ♪ ♪ His password leaked, the data was breached ♪ ♪ And it cost his company 4 million bucks ♪ ♪ A fake update was sent to people ♪ ♪ Working for the meat company JBS ♪ ♪ That's pretty clever ♪ ♪ Instead of getting new features, they got hacked ♪ ♪ And had to pay the largest crypto ransom ever ♪ ♪ And 20 billion dollars, billion with a b ♪ ♪ Have been paid by companies in healthcare ♪ ♪ If you wonder buy your premium keeps going ♪ ♪ Up, up, up, up, up ♪ ♪ Now you're aware ♪ ♪ And now the hackers they are gettin' cocky ♪ ♪ When they lock your data ♪ ♪ You know, it has gotten so bad ♪ ♪ That they demand all of your money and it gets worse ♪ ♪ They go and the trouble with the Facebook ad ♪ ♪ Next time, something seems too good to be true ♪ ♪ Like a free trip to Asia! ♪ ♪ Just check first and I'll help before you ♪ ♪ Think before you click ♪ ♪ Don't get fooled by this ♪ ♪ Who isn't old enough to drive to school ♪ ♪ Take it from me, the director of IT ♪ ♪ Don't click on that email from a prince in Nairobi ♪ ♪ Because he's not really a prince ♪ ♪ Now our data's locked up on our screen ♪ ♪ Controlled by a kid who's just fifteen ♪ ♪ And he's using our money to buy a Ferrari ♪ >> It's a pretty sweet car. ♪ A kid without facial hair, who lives with his mom ♪ ♪ To learn more about this go to wasabi.com ♪ >> Hey, don't do that. ♪ Cause if we had Wasabi's immutability ♪ >> You going to ruin this for me! ♪ This fifteen-year-old wouldn't have on me ♪ (gentle music) >> Drew and I are pleased to welcome Kevin Warenda, who's the Director of Information Technology Services at The Hotchkiss School, a very prestigious and well respected boarding school in the beautiful Northwest corner of Connecticut, hello, Kevin. >> Hello, it's nice to be here, thanks for having me. >> Yeah, you bet. Hey, tell us a little bit more about The Hotchkiss School and your role. >> Sure, The Hotchkiss School is an independent boarding school, grades nine through 12, as you said, very prestigious and in an absolutely beautiful location on the deepest freshwater lake in Connecticut, we have 500 acre main campus and a 200 acre farm down the street. My role as the Director of Information Technology Services, essentially to oversee all of the technology that supports the school operations, academics, sports, everything we do on campus. >> Yeah, and you've had a very strong history in the educational field, you know, from that lens, what's the unique, you know, or if not unique, but the pressing security challenge that's top of mind for you? >> I think that it's clear that educational institutions are a target these days, especially for ransomware. We have a lot of data that can be used by threat actors and schools are often underfunded in the area of IT security, IT in general sometimes, so, I think threat actors often see us as easy targets or at least worthwhile to try to get into. >> Because specifically you are potentially spread thin, underfunded, you got students, you got teachers, so there really are some, are there any specific data privacy concerns as well around student privacy or regulations that you can speak to? >> Certainly, because of the fact that we're an independent boarding school, we operate things like even a health center, so, data privacy regulations across the board in terms of just student data rights and FERPA, some of our students are under 18, so, data privacy laws such as COPPA apply, HIPAA can apply, we have PCI regulations with many of our financial transactions, whether it be fundraising through alumni development, or even just accepting the revenue for tuition so, it's a unique place to be, again, we operate very much like a college would, right, we have all the trappings of a private college in terms of all the operations we do and that's what I love most about working in education is that it's all the industries combined in many ways. >> Very cool. So let's talk about some of the defense strategies from a practitioner point of view, then I want to bring in Drew to the conversation so what are the best practice and the right strategies from your standpoint of defending your data? >> Well, we take a defense in-depth approach, so we layer multiple technologies on top of each other to make sure that no single failure is a key to getting beyond those defenses, we also keep it simple, you know, I think there's some core things that all organizations need to do these days in including, you know, vulnerability scanning, patching , using multifactor authentication, and having really excellent backups in case something does happen. >> Drew, are you seeing any similar patterns across other industries or customers? I mean, I know we're talking about some uniqueness in the education market, but what can we learn from other adjacent industries? >> Yeah, you know, Kevin is spot on and I love hearing what he's doing, going back to our prior conversation about Zero Trust, right, that defense in-depth approach is beautifully aligned, right, with the Zero Trust approach, especially things like multifactor authentication, always shocked at how few folks are applying that very, very simple technology and across the board, right? I mean, Kevin is referring to, you know, financial industry, healthcare industry, even, you know, the security and police, right, they need to make sure that the data that they're keeping, evidence, right, is secure and immutable, right, because that's evidence. >> Well, Kevin, paint a picture for us, if you would. So, you were primarily on-prem looking at potentially, you know, using more cloud, you were a VMware shop, but tell us, paint a picture of your environment, kind of the applications that you support and the kind of, I want to get to the before and the after Wasabi, but start with kind of where you came from. >> Sure, well, I came to The Hotchkiss School about seven years ago and I had come most recently from public K12 and municipal, so again, not a lot of funding for IT in general, security, or infrastructure in general, so Nutanix was actually a hyperconverged solution that I implemented at my previous position. So when I came to Hotchkiss and found mostly on-prem workloads, everything from the student information system to the card access system that students would use, financial systems, they were almost all on premise, but there were some new SaaS solutions coming in play, we had also taken some time to do some business continuity, planning, you know, in the event of some kind of issue, I don't think we were thinking about the pandemic at the time, but certainly it helped prepare us for that, so, as different workloads were moved off to hosted or cloud-based, we didn't really need as much of the on-premise compute and storage as we had, and it was time to retire that cluster. And so I brought the experience I had with Nutanix with me, and we consolidated all that into a hyper-converged platform, running Nutanix AHV, which allowed us to get rid of all the cost of the VMware licensing as well and it is an easier platform to manage, especially for small IT shops like ours. >> Yeah, AHV is the Acropolis hypervisor and so you migrated off of VMware avoiding the VTax avoidance, that's a common theme among Nutanix customers and now, did you consider moving into AWS? You know, what was the catalyst to consider Wasabi as part of your defense strategy? >> We were looking at cloud storage options and they were just all so expensive, especially in egress fees to get data back out, Wasabi became across our desks and it was such a low barrier to entry to sign up for a trial and get, you know, terabyte for a month and then it was, you know, $6 a month for terabyte. After that, I said, we can try this out in a very low stakes way to see how this works for us. And there was a couple things we were trying to solve at the time, it wasn't just a place to put backup, but we also needed a place to have some files that might serve to some degree as a content delivery network, you know, some of our software applications that are deployed through our mobile device management needed a place that was accessible on the internet that they could be stored as well. So we were testing it for a couple different scenarios and it worked great, you know, performance wise, fast, security wise, it has all the features of S3 compliance that works with Nutanix and anyone who's familiar with S3 permissions can apply them very easily and then there was no egress fees, we can pull data down, put data up at will, and it's not costing as any extra, which is excellent because especially in education, we need fixed costs, we need to know what we're going to spend over a year before we spend it and not be hit with, you know, bills for egress or because our workload or our data storage footprint grew tremendously, we need that, we can't have the variability that the cloud providers would give us. >> So Kevin, you explained you're hypersensitive about security and privacy for obvious reasons that we discussed, were you concerned about doing business with a company with a funny name? Was it the trial that got you through that knothole? How did you address those concerns as an IT practitioner? >> Yeah, anytime we adopt anything, we go through a risk review. So we did our homework and we checked the funny name really means nothing, there's lots of companies with funny names, I think we don't go based on the name necessarily, but we did go based on the history, understanding, you know, who started the company, where it came from, and really looking into the technology and understanding that the value proposition, the ability to provide that lower cost is based specifically on the technology in which it lays down data. So, having a legitimate, reasonable, you know, excuse as to why it's cheap, we weren't thinking, well, you know, you get what you pay for, it may be less expensive than alternatives, but it's not cheap, you know, it's reliable, and that was really our concern. So we did our homework for sure before even starting the trial, but then the trial certainly confirmed everything that we had learned. >> Yeah, thank you for that. Drew, explain the whole egress charge, we hear a lot about that, what do people need to know? >> First of all, it's not a funny name, it's a memorable name, Dave, just like theCUBE, let's be very clear about that, second of all, egress charges, so, you know, other storage providers charge you for every API call, right? Every get, every put, every list, everything, okay, it's part of their process, it's part of how they make money, it's part of how they cover the cost of all their other services, we don't do that. And I think, you know, as Kevin has pointed out, right, that's a huge differentiator because you're talking about a significant amount of money above and beyond what is the list price. In fact, I would tell you that most of the other storage providers, hyperscalers, you know, their list price, first of all, is, you know, far exceeding anything else in the industry, especially what we offer and then, right, their additional cost, the egress costs, the API requests can be two, three, 400% more on top of what you're paying per terabyte. >> So, you used a little coffee analogy earlier in our conversation, so here's what I'm imagining, like I have a lot of stuff, right? And I had to clear up my bar and I put some stuff in storage, you know, right down the street and I pay them monthly, I can't imagine having to pay them to go get my stuff, that's kind of the same thing here. >> Oh, that's a great metaphor, right? That storage locker, right? You know, can you imagine every time you want to open the door to that storage locker and look inside having to pay a fee? >> No, that would be annoying. >> Or, every time you pull into the yard and you want to put something in that storage locker, you have to pay an access fee to get to the yard, you have to pay a door opening fee, right, and then if you want to look and get an inventory of everything in there, you have to pay, and it's ridiculous, it's your data, it's your storage, it's your locker, you've already paid the annual fee, probably, 'cause they gave you a discount on that, so why shouldn't you have unfettered access to your data? That's what Wasabi does and I think as Kevin pointed out, right, that's what sets us completely apart from everybody else. >> Okay, good, that's helpful, it helps us understand how Wasabi's different. Kevin, I'm always interested when I talk to practitioners like yourself in learning what you do, you know, outside of the technology, what are you doing in terms of educating your community and making them more cyber aware? Do you have training for students and faculty to learn about security and ransomware protection, for example? >> Yes, cyber security awareness training is definitely one of the required things everyone should be doing in their organizations. And we do have a program that we use and we try to make it fun and engaging too, right, this is often the checking the box kind of activity, insurance companies require it, but we want to make it something that people want to do and want to engage with so, even last year, I think we did one around the holidays and kind of pointed out the kinds of scams they may expect in their personal life about, you know, shipping of orders and time for the holidays and things like that, so it wasn't just about protecting our school data, it's about the fact that, you know, protecting their information is something do in all aspects of your life, especially now that the folks are working hybrid often working from home with equipment from the school, the stakes are much higher and people have a lot of our data at home and so knowing how to protect that is important, so we definitely run those programs in a way that we want to be engaging and fun and memorable so that when they do encounter those things, especially email threats, they know how to handle them. >> So when you say fun, it's like you come up with an example that we can laugh at until, of course, we click on that bad link, but I'm sure you can come up with a lot of interesting and engaging examples, is that what you're talking about, about having fun? >> Yeah, I mean, sometimes they are kind of choose your own adventure type stories, you know, they stop as they run, so they're telling a story and they stop and you have to answer questions along the way to keep going, so, you're not just watching a video, you're engaged with the story of the topic, yeah, and that's what I think is memorable about it, but it's also, that's what makes it fun, you're not just watching some talking head saying, you know, to avoid shortened URLs or to check, to make sure you know the sender of the email, no, you're engaged in a real life scenario story that you're kind of following and making choices along the way and finding out was that the right choice to make or maybe not? So, that's where I think the learning comes in. >> Excellent. Okay, gentlemen, thanks so much, appreciate your time, Kevin, Drew, awesome having you in theCUBE. >> My pleasure, thank you. >> Yeah, great to be here, thanks. >> Okay, in a moment, I'll give you some closing thoughts on the changing world of data protection and the evolution of cloud object storage, you're watching theCUBE, the leader in high tech enterprise coverage. >> Announcer: Some things just don't make sense, like showing up a little too early for the big game. >> How early are we? >> Couple months. Popcorn? >> Announcer: On and off season, the Red Sox cover their bases with affordable, best in class cloud storage. >> These are pretty good seats. >> Hey, have you guys seen the line from the bathroom? >> Announcer: Wasabi Hot Cloud Storage, it just makes sense. >> You don't think they make these in left hand, do you? >> We learned today how a serial entrepreneur, along with his co-founder saw the opportunity to tap into the virtually limitless scale of the cloud and dramatically reduce the cost of storing data while at the same time, protecting against ransomware attacks and other data exposures with simple, fast storage, immutability, air gaps, and solid operational processes, let's not forget about that, okay? People and processes are critical and if you can point your people at more strategic initiatives and tasks rather than wrestling with infrastructure, you can accelerate your process redesign and support of digital transformations. Now, if you want to learn more about immutability and Object Block, click on the Wasabi resource button on this page, or go to wasabi.com/objectblock. Thanks for watching Secure Storage Hot Takes made possible by Wasabi. This is Dave Vellante for theCUBE, the leader in enterprise and emerging tech coverage, well, see you next time. (gentle upbeat music)

>>Okay, welcome back. Everyone. Live cube coverage here in Las Vegas for Amazon re Mars hot event, machine learning, automation, robotics, and space. Two days of live coverage. We're talking to all the hot technologists. We got all the action startups and segment on sustainability and F pan hero for vet global lead, Amazon sustainability data initiative. Thanks for coming on the cube. Can I get that right? Can >>You, you, you did. >>Absolutely. Okay, great. <laugh> thank >>You. >>Great to see you. We met at the analyst, um, mixer and, um, blown away by the story going on at Amazon around sustainability data initiative, because we were joking. Everything's a data problem now, cuz that's cliche. But in this case you're using data in your program and it's really kind of got a bigger picture. Take a minute to explain what your project is, scope of it on the sustainability. >>Yeah, absolutely. And thank you for the opportunity to be here. Yeah. Um, okay. So, um, I, I lead this program that we launched several years back in 2018 more specifically, and it's a tech for good program. And when I say the tech for good, what that means is that we're trying to bring our technology and our infrastructure and lend that to the world specifically to solve the problems related to sustainability. And as you said, sustainability, uh, inherently needs data. You need, we need data to understand the baseline of where we are and also to understand the progress that we are making towards our goals. Right? But one of the big challenges that the data that we need is spread everywhere. Some of it is too large for most people to be able to, um, access and analyze. And so, uh, what we're trying to tackle is really the data problem in the sustainability space. >>Um, what we do more specifically is focus on Democrat democratizing access to data. So we work with a broader community and we try to understand what are those foundational data sets that most people need to use in the space to solve problems like climate change or food security or think about sustainable development goals, right? Yeah. Yeah. Like all the broad space. Um, and, and we basically then work with the data providers, bring the data to the cloud, make it free and open to everybody in the world. Um, I don't know how deep you want me to go into it. There's many other layers into that. So >>The perspective is zooming out. You're, you're, you're looking at creating a system where the democratizing data means making it freely available so that practitioners or citizens, data, Wrangler, people interested in helping the world could get access to it and then maybe collaborate with people around the world. Is that right? >>Absolutely. So one of the advantages of using the cloud for this kind of, uh, effort is that, you know, cloud is virtually accessible from anywhere where you have, you know, internet or bandwidth, right? So, uh, when, when you put data in the cloud in a centralized place next to compute, it really, uh, removes the, the need for everybody to have their own copy. Right. And to bring it into that, the traditional way is that you bring the data next to your compute. And so we have this multiple copies of data. Some of them are on the petabyte scale. There's obviously the, the carbon footprint associated with the storage, but there's also the complexity that not everybody's able to actually analyze and have that kind of storage. So by putting it in the cloud, now anyone in the world independent of where of their computer capabilities can have access to the same type of data to solve >>The problems. You don't remember doing a report on this in 2018 or 2017. I forget what year it was, but it was around public sector where it was a movement with universities and academia, where they were doing some really deep compute where Amazon had big customers. And there was a movement towards a open commons of data, almost like a national data set like a national park kind of vibe that seems to be getting momentum. In fact, this kind of sounds like what you're doing some similar where it's open to everybody. It's kinda like open source meets data. >>Uh, exactly. And, and the truth is that these data, the majority of it's and we primarily work with what we call authoritative data providers. So think of like NASA Noah, you came me office organizations whose mission is to create the data. So they, their mandate is actually to make the data public. Right. But in practice, that's not really the case. Right. A lot of the data is stored like in servers or tapes or not accessible. Um, so yes, you bring the data to the cloud. And in this model that we use, Amazon never actually touches the data and that's very intentional so that we preserve the integrity of the data. The data provider owns the data in the cloud. We cover all the costs, but they commit to making it public in free to anybody. Um, and obviously the computer is next to it. So that's, uh, evaluated. >>Okay. Anna. So give me some examples of, um, some successes. You've had some of the challenges and opportunities you've overcome, take me through some of the activities because, um, this is really needed, right? And we gotta, sustainability is top line conversation, even here at the conference, re Mars, they're talking about saving climate change with space mm-hmm <affirmative>, which is legitimate. And they're talking about all these new things. So it's only gonna get bigger. Yeah. This data, what are some of the things you're working on right now that you can share? >>Yeah. So what, for me, honestly, the most exciting part of all of this is, is when I see the impact that's creating on customers and the community in general, uh, and those are the stories that really bring it home, the value of opening access to data. And, and I would just say, um, the program actually offers in addition to the data, um, access to free compute, which is very important as well. Right? You put the data in the cloud. It's great. But then if you wanna analyze that, there's the cost and we want to offset that. So we have a, basically an open call for proposals. Anybody can apply and we subsidize that. But so what we see by putting the data in the cloud, making it free and putting the compute accessible is that like we see a lot, for instance, startups, startups jump on it very easily because they're very nimble. They, we basically remove all the cost of investing in the acquisition and storage of the data. The data is connected directly to the source and they don't have to do anything. So they easily build their applications on top of it and workloads and turn it on and off if you know, >>So they don't have to pay for it. >>They have to pay, they basically just pay for the computes whenever they need it. Right. So all the data is covered. So that makes it very visible for, for a lot of startups. And then we see anything like from academia and nonprofits and governments working extensively on the data, what >>Are some of the coolest things you've seen come out of the woodwork in terms of, you know, things that built on top of the, the data, the builders out there are creative, all that heavy, lifting's gone, they're being creative. I'm sure there's been some surprises, um, or obvious verticals that jump healthcare jumps out at me. I'm not sure if FinTech has a lot of data in there, but it's healthcare. I can see, uh, a big air vertical, obviously, you know, um, oil and gas, probably concern. Um, >>So we see it all over the space, honestly. But for instance, one of the things that is very, uh, common for people to use this, uh, Noah data like weather data, because no, basically weather impacts almost anything we do, right? So you have this forecast of data coming into the cloud directly streamed from Noah. And, um, a lot of applications are built on top of that. Like, um, forecasting radiation, for instance, for the solar industry or helping with navigation. But I would say some of the stories I love to mention because are very impactful are when we take data to remote places that traditionally did not have access to any data. Yeah. And for instance, we collaborate with a, with a program, a nonprofit called digital earth Africa where they, this is a basically philanthropically supported program to bring earth observations to the African continents in making it available to communities and governments and things like illegal mining fighting, illegal mining are the forestation, you know, for mangroves to deep forest. Um, it's really amazing what they are doing. And, uh, they are managing >>The low cost nature of it makes it a great use case there >>Yes. Cloud. So it makes it feasible for them to actually do this work. >>Yeah. You mentioned the Noah data making me think of the sale drone. Mm-hmm <affirmative> my favorite, um, use case. Yes. Those sales drones go around many them twice on the queue at reinvent over the years. Yeah. Um, really good innovation. That vibe is here too at the show at Remar this week at the robotics showcases you have startups and growing companies in the ML AI areas. And you have that convergence of not obvious to many, but here, this culture is like, Hey, we have, it's all coming together. Mm-hmm <affirmative>, you know, physical, industrial space is a function of the new O T landscape. Mm-hmm <affirmative>. I mean, there's no edge in space as they say, right. So the it's unlimited edge. So this kind of points to the major trend. It's not stopping this innovation, but sustainability has limits on earth. We have issues. >>We do have issues. And, uh, and I, I think that's one of my hopes is that when we come to the table with the resources and the skills we have and others do as well, we try to remove some of these big barriers, um, that make it things harder for us to move forward as fast as we need to. Right. We don't have time to spend that. Uh, you know, I've been accounted that 80% of the effort to generate new knowledge is spent on finding the data you need and cleaning it. Uh, we, we don't have time for that. Right. So can we remove that UN differentiated, heavy lifting and allow people to start at a different place and generate knowledge and insights faster. >>So that's key, that's the key point having them innovate on top of it, right. What are some things that you wanna see happen over the next year or two, as you look out, um, hopes, dreams, KPIs, performance metrics, what are you, what are you driving to? What's your north star? What are some of those milestones? >>Yeah, so some, we are investing heavily in some areas. Uh, we support, um, you know, we support broadly sustainability, which as, you know, it's like, it's all over, <laugh> the space, but, uh, there's an area that is, uh, becoming more and more critical, which is climate risk. Um, climate risk, you know, for obvious reasons we are experienced, but also there's more regulatory pressures on, uh, business and companies in general to disclose their risks, not only the physical, but also to transition risks. And that's a very, uh, data heavy and compute heavy space. Right. And so we are very focusing in trying to bring the right data and the right services to support that kind of, of activity. >>What kind of break was you looking for? >>Um, so I think, again, it goes back to this concept that there's all that effort that needs to be done equally by so many people that we are all repeating the effort. So I'll put a plug here actually for a project we are supporting, which is called OS climates. Um, I don't know if you're familiar with it, but it's the Linux foundation effort to create an open source platform for climate risk. And so they, they bought the SMP global Airbus, you know, Alliance all these big companies together. And we are one of the funding partners to basically do that basic line work. What are the data that is needed? What are the basic tools let's put it there and do the pre-competitive work. So then you can do the build the, the, the competitive part on top of it. So >>It's kinda like a data clean room. >>It kind of is right. But we need to do those things, right. So >>Are they worried about comp competitive data or is it more anonymized out? How do you, >>It has both actually. So we are primarily contributing, contributing with the open data part, but there's a lot of proprietary data that needs to be behind the whole, the walls. So, yeah, >>You're on the cutting edge of data engineering because, you know, web and ad tech technologies used to be where all that data sharing was done. Mm-hmm <affirmative> for the commercial reasons, you know, the best minds in our industry quoted by a cube alumni are working on how to place ads better. Yeah. Jeff Acker, founder of Cloudera said that on the cube. Okay. And he was like embarrassed, but the best minds are working on how to make ads get more efficient. Right. But that tech is coming to problem solving and you're dealing with data exchange data analysis from different sources, third parties. This is a hard problem. >>Well, it is a hard problem. And I'll, I'll my perspective is that the hardest problem with sustainability is that it goes across all kinds of domains. Right. We traditionally been very comfortable working in our little, you know, swimming lanes yeah. Where we don't need to deal with interoperability and, uh, extracting knowledge. But sustainability, you, you know, you touch the economic side, it touches this social or the environmental, it's all connected. Right. And you cannot just work in the little space and then go sets the impact in the other one. So it's going to force us to work in a different way. Right. It's, uh, big data complex data yeah. From different domains. And we need to somehow make sense of all of it. And there's the potential of AI and ML and things like that that can really help us right. To go beyond the, the modeling approaches we've been done so >>Far. And trust is a huge factor in all this trust. >>Absolutely. And, and just going back to what I said before, that's one of the main reasons why, when we bring data to the cloud, we don't touch it. We wanna make sure that anybody can trust that the data is nowhere data or NASA data, but not Amazon data. >>Yes. Like we always say in the cube, you should own your data plane. Don't give it up. <laugh> well, that's cool. Great. Great. To hear the update. Is there any other projects that you're working on you think might be cool for people that are watching that you wanna plug or point out because this is an area people are, are leaning into yeah. And learning more young, younger talents coming in. Um, I, whether it's university students to people on side hustles want to play with data, >>So we have plenty of data. So we have, uh, we have over a hundred data sets, uh, petabytes and petabytes of data all free. You don't even need an AWS account to access the data and take it out if you want to. Uh, but I, I would say a few things that are exciting that are happening at Mars. One is that we are actually got integrated into ADX. So the AWS that exchange and what that means is that now you can find the open data, free data from a STI in the same searching capability and service as the paid data, right. License data. So hopefully we'll make it easier if I, if you wanna play with data, we have actually something great. We just announced a hackathon this week, uh, in partnership with UNESCO, uh, focus on sustainable development goals, uh, a hundred K in prices and, uh, so much data <laugh> you >>Too years, they get the world is your oyster to go check that out at URL at website, I'll see it's on Amazon. It use our website or a project that can join, or how do people get in touch with you? >>Yeah. So, uh, Amazon SDI, like for Amazon sustainability, that initiative, so Amazon sdi.com and you'll find, um, all the data, a lot of examples of customer stories that are using the data for impactful solutions, um, and much more >>So, and these are, there's a, there's a, a new kind of hustle going out there, seeing entrepreneurs do this. And very successfully, they pick a narrow domain and they, they own it. Something really obscure that could be off the big player's reservation. Mm-hmm <affirmative> and they just become fluent in the data. And it's a big white space for them, right. This market opportunities. And at the minimum you're playing with data. So this is becoming kind of like a long tail domain expertise, data opportunity. Yeah, absolutely. This really hot. So yes. Yeah. Go play around with the data, check it outs for good cause too. And it's free. >>It's all free. >>Almost free. It's not always free. Is it >>Always free? Well, if you, a friend of mine said is only free if your time is worth nothing. <laugh>. Yeah, >>Exactly. Well, Anna, great to have you on the cube. Thanks for sharing the stories. Sustainability is super important. Thanks for coming on. Thank you for the opportunity. Okay. Cube coverage here in Las Vegas. I'm Sean. Furier, we've be back with more day one. After this short break.

>>mhm >>Hello and welcome to this cube conversation here in Palo alto California, I'm john for a year host of the cube, we're here with a great guest Jt gear, Ceo and founder and ops Hot Startup. Jt Welcome to the cube conversation. >>Hey, that sound, thanks for having me. It sounds like we know each other, we used to run into each other at meat out. So yeah, >>it's fun to talk to you because I know you're, you know, scratching the devops it from the beginning before devops was devops before infrastructure of code was infrastructure as code. All that's played out. So it's really a great ride. I know you had a good time doing it a lot of action though. If you look at devops it's kind of like this new, I won't say devops two point because it kind of cliche but you're starting to see the mature ization of companies besides the early adopters and the people who are hardcore adopting and they realize this is amazing and then they? Re platform in the cloud and they go great, let's do more and next thing, you know, they have an operations issue and they got a really kind of stabilize and then also not break anything. So this is kind of the wheelhouse of what you guys are doing in ops reminds me of no ops, no operations, you know, we don't want to have a lot of extra stuff. This is a big thing. Take a but take them in to explain the company, you're what you guys stand for and what you're all about. >>Yeah, so you know, our main focus is more on the operation side, so, you know the reason why you move to cloud or the reason why you have devops practices, you want to go fast. Um but you know when you're building cloud infrastructure, you have to make trade offs right? You have to maybe some environment, maybe you have to optimize for S L A. And maybe another workload, you have to optimize for um you know, maybe costs, right? So what we're on a mission to do is to make sure that companies are able to make the right trade offs, right? We help companies to make sure all their workload, every single resource in the cloud is aligned with the business needs, you know, so we do a lot of cool things by like, you know, bringing accountability mapping and we're close to different genes. But yeah, the end goal is, can we make sure that every single resource on data Bs is aligned with the business needs >>and they're also adding stuff. Every reinvent zillion more services get announced. So a lot, a lot of stuff going on, I gotta ask you while I got you here, what is the definition of cloud apps these days, from your standpoint and why is it important? A lot of folks are looking at this and they want to have stable operations. They love the cloud really can't deny the cloud value at all. But cloud ops has become a big topic. What is cloud apps and why is it important. >>Right? I mean, first of all, Like you just mentioned, right? Like Amazon keeps on launching more services. It's over 200. So the environment is very complex, Right? And then mm complexity within the services is uh pretty uh you really need to be the main expert for example, know everything about do So, you know, our question to us is, let's say if you find a critical issue, uh let's say you want to uh you know, enable multi AZ on your RDS for example. Uh and it's critical because you know, you're running a uh high availability workloads on AWS. How do you follow up on that right to us. Operation is how do you build a cloud backlog? How do you prioritize, how do you come together as a team to actually remediate those issues? No one is tackling that job, everyone's surfaces like, hey, here's 1000 things that are wrong with your environment. No one is focused on like how do you go from these issues to prioritization to backlog to actually coming together as a team. You know, I've been fixing some of those issues. That's that's what operation means is >>I know it's totally hard because sometimes I don't even know what's going on. I gotta ask you why, why is it harder now? Why are people, I mean I get the impression that people like looking the other way? I hope it goes the problem kind of goes away. What are the challenges? What's the big blocker from getting at the root cause or trying to solve these problems? What's the big thing that's holding people back? >>Yeah, I mean, when I first got into, you know, I t you know, I was working in data center and every time we needed a server, you know, we have to ask for approvals, right? And you finally got a server, but nowadays anyone could provision resources. And normally you have different people within the team's provisioning resources and you can have hundreds of different teams who are provisioning resources. So the complexity uh and the speed that we are, you know, provisioning resources across multiple people, it just continues to go higher and higher. So that's why uh you know, on the surface it might look that hey, this, you know, maybe the biggest instance uh is, you know, aligned with the business needs, you know, looking at the changes, it's hard to know, are those aligned with the business? They're not? So that's that's that's where the complexity and player. >>So the question I get a lot from people we talk about devops and cloud, cloud apps or cloud management or whatever kind of buzz words out there, it kind of comes down to cloud apps and cloud management seems to be the category, people focus on. How is cloud ops different then? Say the traditional cloud management and what impact does it have for customers and why should they care and what do they need an option. >>Right. So one of the things we do uh and and we do think that cloud operation is sort of an evolution from cloud management. We make sure that Every single resource 1st, first of all blondes and workload. So and you know, workload could be a group of microservices uh and then uh you know every single workload has owners like define owners who are responsible for making sure they managed budget that they're responsible for security that normally doesn't exist. Right? Cloud is this black box, you know where multiple people are provisioning resources, you know, everyone tries to sort of build sort of a structure to kind of see like what are these resources for? What are these resources for as part of onboarding to end up? So what we do, we actually, you know, analyze all your metadata. We create like 56 workloads and then we say here is a bucket where there's there, this is totally unassigned, right? And then we actually walked them through assigning different roles and also we walk them through to kinda looking under this unallocated resources and assign resources for those as well. So once you're done, every single resource has clear definition, right? Is this a compliant? Uh you know hip hop workload, what are the run books, what is this for? John I don't know if he heard that before. Sometimes there are workloads running and how people don't know, I don't even know who is the owner, right? So after you're done with an office and after you're managing and uh, you know, uh, managing your workload on and off, you have full visibility and clear understanding of what are the. It's funny, it's >>funny you mentioned the workloads being kind of either not knowing the owners, but also we see people um, with the workloads sometimes it's like throwing a switch and leaving the hose on the water on. And next thing you know, they get the bill. They're like, oh my God, what happened? Why did I leave? What, what is this? So there's a lot of things that you could miss. This brings up the point you just said and what you said earlier aligning resources across the cloud uh and and having accountability. And then you, you mentioned at the top of this interview that aligning with the business needs. I find that fastest. I would like to take him in to explain because it sounds really hard. I get how you can align the resources and do some things, identify what's going on, accountability kind of map that that's, that's good tech. How does that, how do you get that to the alignment on the business side. >>Yeah. I mean we start by, first of all, like I said, you know, we use machine learning to play these workloads? And then we asked basic questions about the workload. You know, what is this workload for? Uh Do you need to meet with any kind of compliance is for this workload? Uh What is your S. O. A. For this workload? You know, depending on that. We we make recommendations. Uh So we kind of ask those questions and we also walk them through where they create roles. Like we asked who was responsible for creating budgets or managing security for this workload and guess what also the you know the bucket where resources are allocated for. We ask for you know, owners for that as well like in this bucket who's the owner for who's going to monitor the budget and things like that. So you know we asked, you know, we start by just asking the question, having teams complete that sort of information and also you know, why do you a little bit more information on how this aligns with the business needs? You know, >>talk about the complexity side of it. I love that conversation around the number of services. You said 200 services depending how you count what you call services in the thousands of so many different things uh knobs to turn on amazon uh web services. So why are people um focused on the complexity and the partnering side? Because you know, it's the clouds at E. P. I. Based system. So you're dealing with a lot of different diverse resources. So you have complexity and diversity. Can you talk me through how that works? Because that's that seems to be a tough beast to tame the difference between the complexity of services and also working with other people. >>Yeah for sure like this this normal to have um you know maybe thousands of lambda functions in their application. We're working with a customer where within last month there were nine million containers that launched and got terminated right there, pretty much leveraging, auto scaling and things like that. So these environments are like very complex. You know, there's a lot of moving pieces even, you know, depending on the type of services they're using. So again what we do, you know we when we look at tags and we look at other variables like environments and we look at who's provisioning resources, those resources and we try to group them together and that way there's accountability uh you know if the cost goes up for one workload were able to show that team like your cost is going up uh And also we can show uh unallocated bucket that hey within last week Your cost is you know, $4,000 higher in the unallocated bucket. Where would you like to move this these resources to just like an ongoing game. You >>know, you know jt I was talking with my friend jerry Chen is that Greylock partners is a V. C. Has been on the cube many times a couple of years ago. We're talking about how you can build a business within the cloud, in the shadows of the clouds, what he called it, but I called it more the enabling side and and that's happened now, you're seeing the massive growth. I'm also talking to some C X O C IOS or CSOs and they're like trying to figure out which companies that are evolving and growing to be to buy from, get to get the technology. Uh and they always say to me john I'm looking for game changing kind of impact. I'm looking for the efficiency and you know, enablement, the classic kind of criteria. So how would you guys position yourself to those buyers out there that might want to look at you guys as a solution and ups what game changing aspect of what you do is out there, how would you talk to that that C I O or C. So or buyer um out in the end the enterprise and the thieves ran his piece. What would you say to them? >>Yeah, I think the biggest uh advantage and I think right now it's a necessity, you hear these stories where, you know, people provision resources, they don't even know which project is it for. It's just very hard to govern the cloud environment, but I believe we're the only tool. Mhm where you want to compromise on the speed, right? The whole reason um cloud but they want to innovate faster. No one wants to follow that. Right? But I think what's important. We need to make sure everything is aligned with the business value. Uh, we allow people to do that. You know, we, we, we can both fast at the same time. You can have some sort of guard rails. So there are proper ownership. There's accountability. People are collaborating and people are also rightsizing terminating resources, they're not using. It's like, you know, I think if companies are looking for a tool that's gonna drive better accountability on how people build and collaborate on cloud, I think reply the best solution. >>So people are evolving with the cloud and you mentioned terminating services. That's a huge deal in cloud. Native things are being spun up and turned off all the time. So you need to have good law, You have a good visibility, observe ability is one of the hottest buzzwords out there. We see a zillion companies saying, hey, we're observe ability, which is to me is just monitoring stuff. They can sure you're tracking everything. So when you have all this and you start to operationalize this next gen, next level cloud scale, cost optimization and visibility is huge. Um, what is the, what is the secret sauce uh, for that you guys offer? Because the change management is a big 12 teams are changing too cost team accountability. All this is kind of, it's not just speeds and feeds, there's, it's kind of intersection of both. What's your take on that reaction to that? >>Yeah, I think it's the Delta. Right? So change management, What you're really looking for is not a, like a fire hose, you're looking for. What changed what the root cause who did it, what happened? Right. Because it's totally normal for someone to provision maybe thousands or even millions containers. But how many of those got shut down? What is the delta and uh, you know, if there is a, there is an anomaly, what is the root cause? Right? Uh, how we fix it. So you know the way we've changed managers, change management is a lot different. We really get to the root cause analysis and we really help companies to make, really show what changed and how they can take action to a media. But if there were issues, >>I want to put a little plug in for you guys. I noticed you guys have a really strong net promoter score. You have happy customers also get partners. A lot of enablement there. You kind of got a lot of things going on. Um, explain what you guys are all about. How did you get here? What's the day in the life of a customer that you're serving? Why then why are the scores so high? Um, take us through a use case of someone getting that value. >>Yeah. So I, I come from like a consulting background, john so you know, I was migrating companies to read the Bs when the institute was in beta and then I, you know, founded a consulting company over 100 employees. Really successful interview. S premier partner called in clouds. And so Enos was born there because because you know it was, it was born out a consulting company, there are a lot of other partners who are leveraging the tools to help their customers and it goes back to our point earlier, john like amazon has to wonder services, right? We are noticing customers are open to work with partners and uh you know with different partners that really helped them to make sure they're making the right decisions when they are building on cloud. So a lot of the partners, a lot of the consulting companies are leveraging uh and hopes to deliver value to their customers as far as uh you know how we actually operate. You know, we pay attention to uh you know what, what customers are looking for, what, where are the next sort of challenges uh you know, customers are facing in a cloud environment world like super obsessed, you know, like we're trying to figure out how do we make sure every single resource is aligned with the business value without slowing companies down so that really drives us, we're constantly welcome customers to stay true to the admission >>and that's the ethos of devops moving fast. The old quote Mark Zuckerberg used to have move fast, break stuff and then he revised it to move move fast and make it stable, which is essentially operational thing. Right, so you're starting to see that maturity, I noticed that you guys also have a really cool pricing model, very easy to get in and you have a high end too. So talk us through about how to engage with you guys, how do people get involved? Just click and just jump in there, buying software buying services, take a minute to explain how people can, can work with you. >>Yeah, it's just, it's just signing up on our site, you know, our pricing is tier model, uh you know, once you sign up, if you do need help with, you know, remediating high risk issues we can bring in partners, we have a strong partner ecosystem. Uh we could definitely help you do interviews to the right partners but it's as simple as just signing up and just taking me out. First thing I guess. >>Jt great chatting with you have been there from early days of devops, born in the field, getting, getting close to the customers and you mentioned ec two and beta, they just celebrate their 15th birthday and I remember one of my starts that didn't actually get off the off the blocks, they didn't even have custom domains at that time was still the long remember the long you are else >>everything was ephemeral like when you restart server, everything will go away a cool >>time. And I just remember saying to myself man, every entrepreneur is going to use this service who would ever go out and buy and host the server. So you were there from the beginning and it's been great to see the success. Thanks for coming on the cube >>all That's >>okay. Jt thanks so much as a cube conversation here in Palo alto. I'm john for your host. Thanks for watching. Mhm.

>>from around the globe, it's >>the cube >>With digital coverage of IBM think 2021 brought to you by IBM Hello welcome back to the cubes coverage of IBM Think 2021. I'm john for your host of the cube had a great conversation here about cloud data, AI and all things. C X O from KPMG is Vinod Swaminathan who's the strategy head of strategy of Ai data and cloud as well as the C. I. O advisory at KPMG you know thanks for coming on the cube. >>My pleasure jOHn thanks for having me. >>So you guys have an interesting perspective, you sit between the business value being created from technology and the clients trying to put it to work um and KPMG impeccable reputation over the years obviously bringing great business value to clients. You guys do that. Um you're in the middle of the hot stuff cloud data and Ai um Ai is great if you have the data and the architecture do that in cloud scale brings so many new good things to the table. Um how is this playing out right now in your mind because we're here at IBM think where the story is transformed, transformation is the innovation. Innovation does set the table for net new capabilities at scale. This seems to be a common thread here. What's your take on the current situation? >>Well, let me start with the fundamental premise that we're seeing playing out with many of our clients and that is, clients are beginning to connect the different silos within their business to better respond to what their customers are asking for. Um you know, we we tend to work with large enterprises, very well established businesses and we're also fortunate to serve the needs of high growth companies as well. So we're in a very unique position as a trusted advisor to both legacy companies transforming and high growth companies looking to drive the transformation in the industry as well. So there are a few things that we're seeing right the first and foremost is responding quickly and effectively to very rapidly changing customer needs. And I think the pandemic really you know put a spotlight on how fast organizations had to pivot and I have to commend a lot of these organizations and doing a phenomenal job, I would argue, spit band aiding and gluing together a response to what their customers expected. Right? So as I look at post pandemic, we're seeing a lot of clients now looking to take stock of things that they did during the pandemic, how they address customer demand to really smooth them out and streamline as a strategy, how they're going to become more customer driven at KPMG. We call this the connected enterprise where you really work effectively across the front, middle and back office in an enterprise to seamlessly address the client. Right? Anything you do in finance really is driven by what your customers want. It's no longer, hey finance sit in the back office, right. Anything you do in marketing is no longer hey I'm doing it just to address the demand side of the equation, right? It's very integral to connect marketing with fulfillment. Right? So we call this the connected enterprise. So that transformation is only possible if customers and our clients are able to effectively leverage cloud from an architectural perspective. And when I say cloud, what we're seeing, smarter clients of ours start to think about is cloud in its entirety. So it's not just the public cloud, it's the cloud architecture, right? The ability to scale up scale out right scale down, right, irrespective of where all of this sits from an infrastructure perspective. So cloud is very critical for becoming that connected enterprise. Uh The data pieces integral, I think the data business today represents trillions of dollars. I think everybody has bought into the fact that data is the new oil and all of that good stuff that we've heard. Uh but it really is a trillion dollar business and it has some unique challenges. So being connected requires, right? That are that an enterprise become very data driven? I think it's hard to escape ai it's everywhere. To the point where we don't even uh we're not even conscious of ai at work, Right? So I think uh five years ago a I was a novel concept today. It's the expectation of customers who interact with big brands that ai is an integral part of how they are being served. Right, So cloud data ai architecture sort of the ingredients if you will. And then cool technology really starts to bring this connected concept together and post pandemic. We're going to start to see a lot of rationalization uh and big investments and moving forward in this trajectory. >>It's interesting cloud data now you, the way you talk about it makes me think about like just the constant of the old Os I stack right? You have infrastructure and cloud, you have data in the middle layer and then A. I. Is that that wonder area where the upside takes advantage of that data? Um Very cool insight. You know. Thanks for sharing that. The question I have for you put the pandemic I want to get your reaction to some conversations I've had in the industry and they tend to go like this. Um When we come out of the pandemic this is like a C X. O. Talking to Ceo. Or C. I. O. Or C. So when we come out of the pandemic we need a growth strategy, we need to be hidden, we need to be on the upswing, okay, not on the downswing or still trying to figure it out. Um And and that's a cool conversation because there's been to use cases that we've identified companies that had no has had a headwind because of the pandemic, either because of business disruption or the second categories, they've had a tail when they had a business opportunity. So the ones that had a headwind, they would retool, they used the pandemic to retool and the ones that had the tailwind would use the pandemic to either bring net new capabilities or or transform and innovate. So either way that's a successful use case. The ones who didn't do anything aren't going to survive much. We know that, but in those two cases they're not mutually exclusive. That's what the smart money's been doing. The smart teams. What's your advice now that we're in that mode where we're coming around the corner? How do companies get on that uptick? What have you guys advise into clients? What are you hearing and what, what's your reaction to that concept? >>Well, I think every company that is going to be on the survivors list post pandemic actually has digitally transformed, um, you know, even if they don't want to acknowledge it right in a lot of different ways. Um, so I think that's here to stay. Um, what I, and I'll give you a simple example, um, you know, I, I belong to a local club, you know, kitchen shut down, you know, no activities. I was amazed that it took them only four days John four days to actually bring a digital reservation system online through their mobile app. So in the past, the mobile app was simply for me to go look at the directory. But now I can do so many more things. Right? And I was talking to my club CI. All right. I mean, really not a C I. O. But you know, it was uh, it was, it was a staff member who was charged with driving the digital transformation. So there you go >>right to consult you, you know. >>Um, but what he talked to me about was fascinating. And this is what we're going to see, right? So first he said, another was so easy to bring some of those, you know, interactive experience type capabilities online to serve our customer base. It made us think, why the hell didn't we do it before? Alright, so, back to your question, I think post pandemic, we're going to see a lot of companies recognizing that low code, no code, right? Cloud AI capabilities are very much within the reach of the average business user, right? In companies like IBM have done a phenomenal job of demystifying the technology and trying to make it much more accessible for the business user. We're going to see continued momentum, right? And adopting these kinds of simple technologies to transform right business processes, customer interaction, so on and so forth. Right? So we we see that coming out of the pandemic, there's no stopping that. I think the second thing we see is a very firm commitment at the leadership level um that you know, stopping or slowing down these kinds of activities is a non starter at the board level. That's a nonstarter at the management committee level, right? Don't come to me saying we need to slow down things. Come to me saying we need to speed up things, right? But that said, we're seeing rationalization, conversations begin to happen and that starts with the strategy, right, tailwind or headwind, irrespective of which side of the equation you fell right in that, in that dynamic, what we're seeing is clients coming back and saying, all right, we know our strategy needs to be different. Let's make sure that we have a strategy that aligns better with um where our customers want to go, where the industry is headed. And let's acknowledge that there are technological capabilities now, but actually turbocharge the execution of the strategy. Technology is not the strategy, it's still connected enterprise thought, How do I serve my customers whose expectations have dramatically changed coming out of the pandemic? And that's why I gave you the club example. I never want to call anybody to make a reservation anymore. I mean even the local hair salon has a queuing system and a reservation system because you know, that's just the way it is. Right? So there are some simple things that have happened on the customer side of uh, you know, the equation, which is forcing a lot of our clients to start, you know, accelerating their digital investments. Um, you know, rather than decelerating, >>it's interesting. That's great insight. I think just to summarize that, I think you're pointing out is the obvious, hey, it works the indifference of the digital to go the next level and see X. O. S and C I. O. S have had, you know, either politics or blockers or just will it work? And I think with the pandemic necessity is the mother of all inventions. You say, hey, we got to get back on business that the economics and the user experience is more than acceptable. It's actually preferred. I think that club example really highlights that expectation change and I >>think that's an interesting architecture discussion right? And I don't mean that technically I think businesses are starting to think about how are they architected, right. And this is where the connected enterprise concept from KPMG is resonating because now you know, we see our clients no longer thinking about finance, sales, marketing, right? And fulfillment right? That's how the architect of their business. Before now they're realizing that they need to sort of put it on its side. Right, I love the cube analogy, I'm going to borrow it, they're flipping the cube on the side and pulling out a whole new business architecture which by the way is enabled and supported by an underlying technology architecture that's very different. Right? So I think businesses are going to get re architected in technology companies like IBM and Red Hot are going to be right there helping clients go through that re architected along with partners like us, >>the script has been flipped, the cube has been turned and I think this was the revelation. The economics are clear. So I gotta ask you, I mean I've always been I've been joking with IBM the president like it, but I've been saying that, you know, business now is software enabled and the operating systems, distributed computing. As you mentioned, these subsystems are part of this fabric and red hat there and operating systems company. Um, so kind of in a good position with what Marvin's doing. If you think about if you look at squint through and connect the dots, I mean you're looking at an underlying operating system that's open and connected to business, it's not just software apps that run something like an ear piece system, it's an business software model for the entire company completely instrumented. This is what hybrid cloud is. Could you, could you take a few minutes to talk about the relationship that you guys have with IBM on how you guys are working together to bring this hybrid cloud vision to their customers into the market. >>So KPMG and IBM go back about 20 plus years long standing relationship. Um in fact, I kid around with many of my fellow partners here at KPMG that IBM is the only relationship that we did not divest off when we went through our let's flip management consulting off from our accounting business, so on and so forth that everybody went through. Right? So very long standing relationship, you know, we're a trusted partner of IBM but we're very different from a lot of the partners that IBM has were business consultants, right? We don't have, you know, we help clients think through their business first before we get into the technology implementation. So I don't have armies of IBM certified engineers sitting on the bench looking for work to do. It's actually the other way around. Right? So it's been a great marriage when IBM has phenomenal technology in this case, you know, they have been leaders in AI, we've got an AI based relationship now going back five years, um you know, where we consumed Watson proved to ourselves and the world that it can be done very innovatively supporting business transformation. And now we're able to together with IBM effectively have that conversation with clients, right? Because we're client number zero, uh we're big into a hybrid, multi cloud, um you know, we're big red hat customers. Uh you know, we use red hat in our own modernization of several different workloads. So our relationship with IBM is very strong, were a good supplier to them as well, so we help them with their strategy and go to market as well. So an interesting sort of relationship. Um look when we work with clients, we typically tend to, you know, take a trusted advisor role with clients. Our brand speaks to the trust that we're able to bring when we talk to clients. Uh I kid around um you know, when you're going through a transformation, you probably want the town skeptic holding your hand. That's us, right? We're very risk averse. We like working with clients who you know, kind of want that, you know, critical look when they're investing in technology driven transformation. Um you know, some of the things that IBM has done is pretty phenomenal. Right? So for example, I don't see um you know, I don't see a lot of providers out there who give clients the kind of options that IBM gives with their multi cloud capabilities. Right? So show me conversational ai capability that can run on private cloud, that can run on google amazon IBM and a whole bunch of other cloud providers. Right, So I think as IBM invests in that open right philosophy and obviously the Red hat acquisition only further enhances that. Right, um it's a great opportunity for us to be able to take very powerful KPMG value propositions um you know, enabled by this kind of IBM technology. Right, so that's how we tend to go to market. Um one of the solutions were offering with IBM is called the KPMG data mesh. It's built on IBM cloud pack for data, which is enabled by red hats open shift and it's a very innovative solution in the marketplace that fundamentally asked the question to clients, why are you spending inordinate amount of time and resources moving data around in order to become data driven? Uh it just amazes me john how much money is being thrown at, you know, moving data around, particularly as you get into this complex hybrid, multi cloud world. Right. How many times am I going to move data from, you know, a mainframe database into my, you know, cloud repository before I can start doing uh, you know, real higher value work. Right, So KPMG data mesh enabled by the IBM cloud back, the data says, hey, legal data, wherever it is. You know, we can take up to 30 of costs out and really get you on this journey to become data driven without spending the first nine months of every project building a data warehouse or building an expensive data where data lake. Right? Because all of those, frankly our 20th century mindset, right? So if I can leave the data where it is your favorite terminology virtually is the data and really focus on what do I do with the data as opposed to you know, how do I move the data? Right. It really starts to change the mindset around becoming data driven. Right, so that's a great example of a solution where we've married our value proposition to clients around connected and trusted and leveraged IBM technology right? In a hybrid multi cloud >>but no great insight. Love the focus. Hybrid cloud, congratulations on your KPMG mesh solution. Their cloud mesh awesome. Taking advantage of the IBM work and love your perspective on the industry. I think you you called it right. I think that's a great perspective. That's the way we're on big transformation innovation wave. Thanks for coming on the key. Appreciate it. >>Absolutely my pleasure. Thanks for having me have a good day. >>Okay, Cube coverage of IBM think 2021. I'm John for your host of the Cube. Thanks for watching.

>>mhm Yes. >>Welcome back to the cubes coverage of red hat summit 2021 virtual. I'm john for a host of the cube we're here in Palo alto. Were remote with our great guest here cube alumni. I've been on many times chris wright, Senior vice president and CTO of red hat chris great to see you. Always a pleasure to have you on the screen here too. But we're not in person but thanks for coming in remote. >>Yeah, you bet. Glad to be here. >>Not only were talking about speeds and feeds, digital transformation going under the hood here we're gonna talk about red hats, expanded collaboration with boston University to help fund education and research for open source projects. So you guys have a huge relationship with boston University. Talk about this continued commitment. What's the news, what's the, what's the story? >>Well, we have a couple different things going on uh and and the relationship we have with the EU is many years in. So this itself isn't brand new. Um one of the things that's important to highlight here is we are giving something north of $550 million dollars worth of software to be you really in pursuit of running uh powering and running scaled infrastructure. That's part of the open hybrid class. Um and that's that's an important piece which we can touch on a little bit as we talk to this conversation. The other one is like I said, this isn't a new relationship with the U. And what we're doing now is really expanding the relationship. So we've we've built a great connection directly with the You were substantially expanding that. Um The original relationship we had was a $5 million relationship spread over five years now. We're talking about a $20 million Relationship spread over five years. So really a significant expansion. And of course that expansion is connected to some of the work that we plan to do together in this open hybrid cloud infrastructure and research space. So a lot of things coming together at once to really really advance the red hat ca laboratory at the U. That combined effort in bringing you know, cloud research and open source and all these things together >>and a lot of actually going on. So basically the boston area lot of universities, but I love the shirt you're wearing with his red hat innovation in the open. This is kind of one of those things you also mentioned out of this huge subscription of software grant that's going to be you just a huge number give value for for the boston University. But you also have another project that's been going on the collaborative research and education agreement called red hat collaborative orI Okay, this was in place. You mentioned that. How's that tying in because that was pre existing. Now. You've got the grant, you got your funding more and more research. Talk about how this connects into the open cloud initiative because this is kind of interesting. You're not bringing hybrid cloud kind of research and practical value in A i ops is hot. You can't you can't go anywhere these days without having great observe ability. Cloud native more and more is more complex and you've got these young students and researchers dying and get their hands on it. Take us through the connection between the CA laboratory and open open cloud. >>So the CA laboratory is a clever name that just talks about collaboration and research laboratory type research. And initially the CA laboratory focus was on the infrastructure running the cloud and some of the application workloads that can run on top of an open cloud infrastructure uh that are that's very data centric. And so this is uh an opportunity for multidisciplinary work looking at modeling for um for health care, for example for how you can improve imaging and we've had a great results in this collaboration. Um We've talked at times about the relationship with the boston Children's Hospital and the chris project not related to me, but just similar acronym that spells chris. Um and these things come together in part through connecting relationships to academia, where academia as research is increasingly built in on and around open source software. So if you think of two parallel worlds, open source software development, just the activity of building open source software, it brings so many people together and it moves so quickly that if you're not directly connected to that as an academic researcher, you risk producing academic research results that aren't relevant because it's hard for them to connect back to these large, fast moving projects, which may have invented a solution to the problem you've been focused on as an academic if you're not directly connected. So we see academia and open source coming together to build really a next generation of understanding of the scientific in depth and he's joining the >>train operations you're talking about here though, this is significant because there's dollars behind it, right? There's real money, it's not >>just the right software, >>it's it's a center, it's a joint operation. >>That's right. And so when you think about just the academic research of producing um ideas that manifest themselves as code and software projects, we want to make sure we're first connecting the software projects to open source communities in with our own engineering experience, bringing code into these open, open source projects to just advance the the feeds and speeds and speeds, the kind of functionality the state of the art of the actual project. We're also taking this to a new level with this expanded relationship and that is software today. When you, when you operate software as a cloud, a critical part of the software is the operationalization of that software. So software just sitting there on the shelf doesn't do anybody any good. Even if the shelf is an open source project, it's a tar ball waiting for you to download. If you don't ever grab it and run it, it's not doing anybody any good. And if the challenge of running it is substantial enough that it stops you from using that software, you've created a barrier to the value that's locked inside that project. The focus here is how can we take that the operations experience of running a cloud, which itself is a big complex distributed system, tie some of those experiences back into the projects that are used to build that infrastructure. So you're taking not just the output of the project, but also the understanding of what it takes to run a project and bringing that understanding and even the automation and code associated with that back into the project. So, your operational izing this open source software and you're building deeper understanding of what it means to operate things that scale, including data and data sets that you can use to build models that show how you can create the remediation and closed loop systems with AI and machine learning, you know, sort of synthesizing all the data that you generate out of a big distributed infrastructure and feed that back into the operations of that same infrastructure. So a lot going on there at the same time operationalization as as an open source initiative but also um really the understanding advancement of A I and data centric operations, so ai ops and closed the remediation. >>Yeah, I mean, devops developer and operations to operationalize it and certainly cloud Native put an emphasis on Day two operations, which leads a lot more research, a lot more uh student work on understanding the coding environment. Um so with that I got to ask um I asked you about this uh massachusetts focused or this open cloud initiative because you guys are talking about this open cloud initiative including this massachusetts. Open Cloud, what is that? What is the massachusetts? Open Cloud sounds like you're offering a kind of open person, not just bu but other um Yeah, institutions. >>That's right. So the the M o C massachusetts open cloud is itself a cross um organizational collaboration bringing together five different academic institutions in New England In massachusetts. It's bu it's Harvard mit, its Northeastern and its U. Mass. Coming together to support a common set of infrastructure which is cloud. It's a cloud that runs in a data center and then um it serves a couple of different purposes. One is research on clouds directly. So what does it mean to run a cloud? What does it look like from a research point of view to understand large scale distributed systems? And then the other is more on top. When you have a cloud you can run workloads and those workloads scaled out to do say data processing, looking at the implications of across different fields which could be natural sciences, could be medicine, could be, even political science or social science is really a multidisciplinary view of what it means to leverage a cloud and run data centric workloads on top. So two different areas that are of a focus for the M. O. C. And this becomes this sort of vehicle for collaboration between Red Hat View and the Red Hot Laboratory. >>So I have to ask only because I'm a big fan of the area and I went to one of those schools, is there like a bean pot for technical hackathons where you get all the schools matched up against each other on the mass open cloud and compete for who gets bragging rights and the text city there. >>It's a great question. Not yet. But I'll jot that down here in hell. Up on that. >>Happy to sponsor. We'll we'll do the play by play coverage, you know. Great. >>I love that. Yeah, kind of twitch tv style. The one thing that there is which is very practical is academic research grants themselves are competitive, right? People are vying for research dollars to put together proposals, Bring those proposals to um the agency that's that's that's giving out grants and winning those grants is certainly prestigious. It's important as part of her research institutes continue to fund the work that they're doing. Uh Now we've been associated uh through the work we've done to date with the U. With Yeah almost $15 million 20 papers. So there's there's a lot of work you can't quite call the play by play. It's a >>scoreboard. I mean their numbers you can put numbers on the board. I mean that's what's one of the things you can measure. But let me ask you on those grants. So you're saying this is just the bu you guys actually have data on um the impact of the relationship in terms of grants and papers and stuff like that academic work. >>That's right. That's right. And so those numbers that I'm giving you are examples of how we've worked together with the u to help their faculty generate grant dollars that then fund some of the research that's happening there together with redhead engineers and on and on the infrastructure like the massachusetts Open cloud. >>That's a good way to look at the scoreboard. It's a good point. We have to research that if you don't mind me asking on this data that you have um are all those projects contributing to open source or do they have to be? That's just generic. Is that all of you all papers around bu is part of the research. In other words, I'm trying to think if I'm in open source, has this contributed to me as an >>open source? Yeah, it's a big and complex question because there's so much research that can happen through a research institution. And those research grants tend to be governed with agreements and some of those agreements have intellectual property rights um front and center and might require things like open source software as a result, the stuff that we're working on clearly isn't that focus area of open source software and and research activities that help kind of propel our understanding forward of what does it mean to do large scale distributed systems creation and then operation. So how do you develop software that does it? How do you how do you run the software that builds these big large distributed systems? So we're focused in that area. Um some of the work that we facilitated through that focus includes integrating non open source software that might be part of um same medical imaging. So for example work we've done with the boston Children's Hospital That isn't 100 doesn't require us to be involved 100 of the open source pieces. All the infrastructure there to support it is. And so we're learning how we can build integrated pipelines for data analysis and image analysis and data sharing across different institutions uh at the open source project level. Well maybe we have a specific imaging program that is not generated from this project. And of course that's okay with >>us. You know chris you bring up a good point with all those conversations. I could see this really connecting the dots. Most computer science programs. Most engineering programs haven't really traditionally focused on it at the scale we're talking about because we look at cloud scale but now scaling with hybrid it's real engineering going on to think about the large scale. We know all the big hyper scale ear's right so it's not just I. T. Provisioning you know network connection and doing some I. T. Work. We're talking about large scale. So I have to ask you as you guys look at these relationships with academics uh academia like like bu and others um how are the students responding to this? Are you guys seeing any specific graduate level advancements? Because you're talking about operational roles that are becoming so important whether it's cyber security and as cloud needed because once more data driven you need to have all this new scale engineered up. That's >>what how >>do you look at that? >>There's two different pieces that I would highlight. One is just the data science itself. So schools still need to produce data scientists. And having data is a big part of being a data scientist and knowing what your what your goals are with that data and then experimenting with different techniques, whether it's algorithms or tools. It's a big part of being a data scientist sort of spelunking through the data. So we're helping produce data. We're looking at data science efforts around data that's used to operationalize infrastructure, which is an interesting data science endeavor by itself. The other piece is really what you highlighted, which is there's an emergence of a skill set in the industry, often referred to as SRE site reliability engineering. Um it is a engineering discipline. And if you back up a little bit and you start thinking about what are the underlying principles behind large scale distributed systems, you get to some information theory and computer science. So this isn't just something that you might think of as um some simple training of a few key tools and knowing how to interpret a dashboard. And you're good to go, this is a much more sophisticated view of what does it mean to really operate large scale infrastructure, which to date, there aren't a lot of these large scale infrastructures available to academics to research because their commercial endeavors >>and their new to me. I was talking to some young folks my son's age and daughters age and I was saying, you know, architect in a building, a skyscraper isn't trivial. You can't just do that overnight. There's a lot of engineering that goes on in that science, but you're bringing kind of operating systems theory, systems thinking to distributed computing. I mean that's combination of a interdisciplinary shift and you got, I won't say civil engineering, but like concept is there, you've got structure, you've got networks, they're changing and then you've got software so again completely new area. >>That's right and there's not a lot of even curriculum that explores this space. So one of the opportunity, there's a great program that really focuses on um that that space of site reliability engineering or operational izing software. Um And then the other piece that I'm I'm really excited about is connecting to open source communities so that as we build software, we have a way to run and operationalize that software that doesn't have to be directly tied to a commercial outlet. So products running in the cloud will have a commercial S. L. A. And commercial agreements between the user and the producer of that service. How do you do that in open source context? How do you leverage a community, bring that community software to a community run service, learn through the running of that service. How to best build architect the service itself and then operationalized with the tooling and automation that service? How do you, how do you bring that into the open source community? And that's something that we've been referring to as the operate first initiative. How do you get the operationalization of software? Really thought of as a primary focal point in the software project where you normally think about the internals of software, the features, the capabilities of functionality, less about the operationalization. So important shift at the open source project level, which is something that I think will really be interesting and we'll see a lot of reaping a lot of rewards. Just an open source communities directly. >>Yeah, speed and durability. Certainly having that reliability is great. You know, I love talking with you guys at red hat because, you know, software, you know, open source and you know, operating systems because as it comes together in this modern era, what a great, great fit, great work you're doing with Boston University's and the mass open cloud initiative. Congratulations on that. I got I got to ask you about this Red Hat Graduate Fellows program you have because this kind of speaks to what you guys are doing, you have this kind of this redhead graduate fellows network and the work that's being done. Does that translate into red hat at all? From an engineering standpoint? How does that, how does that work together? >>Basically, what we do is we support um PhD students, we support post docs. So there's a real direct support to the, you know, that is the Red Jack Graduate Fellow program on our focus there is connecting those um uh academics, the faculty members and the students to our engineers to work together on key research initiatives that we think will help drive open source software agendas forward really broad can be in all different areas from security to virtualization too, the operating systems to cloud distributed systems, uh and one of the things that we've discovered is it creates a great relationship with the university and we find students that will be excited to leave university and come into the the industry workforce and work at Red hat. So there is a direct talent relationship between the work that we do at bu and the talent that we can bring into red hat, which is awesome. Uh We know these people we've worked with well with them, but also we're kind of expanding understanding of open source across, you know, more and more of academia, which I think is really valuable and important for red hat. We just go out to the the industry at large, um, and helping bring a set of skills to the industry that whether they're coming, whether these are students that come into red hat or go elsewhere into the industry, these are important skills to have in the industry. So we look at the, how do you work in open source communities? How to operationalize software at scale? These are important things. They didn't >>expand, expand the territory if you will in terms of systems thinking. We just talked about great collaboration. You guys do a great job chris great to have you on a quick final word from you on this year at red hat summer. I know it's virtual again, which we could be in person, but we're starting to come out of the covid kind of post covid right around the corner. Um, what's the update? How would you describe the current state of red hat? Obviously you guys still got that, that vibe. You still pumping strong a lot going on. What's the current? What's the current, uh, bumper sticker? What's the vibe? >>Well, in many ways, because we're so large and distributed. Um, the last year has been, uh, can't say business as usual because it's been an impact on everybody, but it hasn't required us to fundamentally change. And as we work across open source communities, there's been a lot of continuity that's come through a workforce that's gone completely distributed. People are anxious to get to the next phase, whatever back to normal means. Uh, and people at Red Hat are no different. So we're looking forward to what it can mean to spend time with colleagues in offices, were looking forward to what it means to spend time together with our friends and families and travel and all those things. But from a, from a business point of view, Red Hat's focus on the open hybrid cloud and that distributed view of how we work with open source communities. That's something that's, it's only continued to grow and pick up over the course of the last year. So it's clearly an important area for the industry and we've been busier than ever the last year. So, uh, interesting, interesting times for everybody. >>Well, it's great to see and I love how the culture maintains its its relevance, its coolness intersection between software, Open Source and systems. Great, Great working congratulations chris. Thanks for coming on. >>Thank you. >>All right. I'm John for here with the Cube for Red Hat Summit 2021. Thanks for watching. Mhm.