Meagen Eisenberg, Lacework | International Women's Day 2023
>> Hello and welcome to theCUBE's coverage of International Women's Day. I'm John Furrier, host of theCUBE. Got a variety of interviews across the gamut from topics, women in tech, mentoring, pipelining, developers, open source, executives. Stanford's having International Women's Day celebration with the women in data science, which we're streaming that live as well. Variety of programs. In this segment, Meagen Eisenberg, friend of theCUBE, she's the CMO of Laceworks, is an amazing executive, got a great journey story as a CMO but she's also actively advising startups, companies and really pays it forward. I want to say Meagen, thank you for coming on the program and thanks for sharing. >> Yeah, thank you for having me. I'm happy to be here. >> Well, we're going to get into some of the journey celebrations that you've gone through and best practice what you've learned is pay that forward. But I got to say, one of the things that really impresses me about you as an executive is you get stuff done. You're a great CMO but also you're advised a lot of companies, you have a lot of irons in the fires and you're advising companies and sometimes they're really small startups to bigger companies, and you're paying it forward, which I love. That's kind of the spirit of this day. >> Yeah, I mean, I agree with you. When I think about my career, a lot of it was looking to mentors women out in the field. This morning I was at a breakfast by Eileen and we had the CEO of General Motors on, and she was talking about her journey nine years as a CEO. And you know, and she's paying it forward with us. But I think about, you know, when you're advising startups, you know, I've gathered knowledge and pattern recognition and to be able to share that is, you know, I enjoy it. >> Yeah. And the startups are also fun too, but it's not always easy and it can get kind of messy as you know. Some startups don't make it some succeed and it's always like the origination story is kind of rewritten and then that's that messy middle. And then it's like that arrows that don't look like a straight line but everyone thinks it's great and you know, it's not for the faint of heart. And Teresa Carlson, who I've interviewed many times, former Amazon, now she's the president of Flexport, she always says, sometimes startups on certain industries aren't for the faint of heart so you got to have a little bit of metal, right? You got to be tough. And some cases that you don't need that, but startups, it's not always easy. What have you learned? >> Yeah, I mean, certainly in the startup world, grit, creativity. You know, when I was at TripActions travel company, pandemic hits, nobody's traveling. You cut budget, you cut heads, but you focus on the core, right? You focus on what you need to survive. And creativity, I think, wins. And, you know, as a CMO when you're marketing, how do you get through that noise? Even the security space, Lacework, it's a fragmented market. You've got to be differentiated and position yourself and you know, be talking to the right target audience and customers. >> Talk about your journey over the years. What have you learned? What's some observations? Can you share any stories and best practices that someone watching could learn from? I know there's a lot of people coming into the tech space with the generative AI things going on in Cloud computing, scaling to the edge, there's a lot more aperture for technical jobs as well as just new roles and new roles that haven't, you really don't go to college for anymore. You got cybersecurity you're in. What are some of the things that you've done over your career if you can share and some best practices? >> Yeah, I think number one, continual learning. When I look through my career, I was constantly reading, networking. Part of the journey is who you're meeting along the way. As you become more senior, your ability to hire and bring in talent matters a lot. I'm always trying to meet with new people. Yeah, if I look at my Amazon feed of books I've bought, right, it kind of chronicle of my history of things I was learning about. Right now I'm reading a lot about cybersecurity, how the, you know, how how they tell me the world ends is the one I'm reading most recently. But you've got to come up to speed and then know the product, get in there and talk to customers. Certainly on the marketing front, anytime I can talk with the customer and find out how they're using us, why they love us, that, you know, helps me better position and differentiate our company. >> By the way, that book is amazing. I saw Nicole speak on Tuesday night with John Markoff and Palo Alto here. What a great story she told there. I recommend that book to everyone. It goes in and she did eight years of research into that book around zero day marketplaces to all the actors involved in security. And it was very interesting. >> Yeah, I mean, it definitely wakes you up, makes you think about what's going on in the world. Very relevant. >> It's like, yeah, it was happening all the time, wasn't it. All the hacking. But this brings me, this brings up an interesting point though, because you're in a cybersecurity area, which by the way, it's changing very fast. It's becoming a bigger industry. It's not just male dominated, although it is now, it's still male dominated, but it's becoming much more and then just tech. >> Yeah, I mean it's a constantly evolving threat landscape and we're learning, and I think more than ever you need to be able to use the data that companies have and, you know, learn from it. That's one of the ways we position ourselves. We're not just about writing rules that won't help you with those zero day attacks. You've got to be able to understand your particular environment and at any moment if it changes. And that's how we help you detect a threat. >> How is, how are things going with you? Is there any new things you guys got going on? Initiatives or programs for women in tech and increasing the range of diversity inclusion in the industry? Because again, this industry's getting much wider too. It's not just specialized, it's also growing. >> Yes, actually I'm excited. We're launching secured by women, securedbywomen.com and it's very much focused on women in the industry, which some studies are showing it's about 25% of security professionals are women. And we're going to be taking nominations and sponsoring women to go to upcoming security events. And so excited to launch that this month and really celebrate women in security and help them, you know, part of that continual learning that I talked about, making sure they're there learning, having the conversations at the conferences, being able to network. >> I have to ask you, what inspired you to pursue the career in tech? What was the motivation? >> You know, if I think way back, originally I wanted to be on the art side and my dad said, "You can do anything as long as it's in the sciences." And so in undergrad I did computer science and MIS. Graduated with MIS and computer science minor. And when I came out I was a IT engineer at Cisco and you know, that kind of started my journey and decided to go back and get my MBA. And during that process I fell in love with marketing and I thought, okay, I understand the buyer, I can come out and market technology to the IT world and developers. And then from there went to several tech companies. >> I mean my father was an engineer. He had the same kind of thing. You got to be an engineer, it's a steady, stable job. But that time, computer science, I mean we've seen the evolution of computer science now it's the most popular degree at Berkeley we've heard and around the world and the education formats are changing. You're seeing a lot of people's self-training on YouTube. The field has really changed. What are some of the challenges you see for folks trying to get into the industry and how would you advise today if you were talking to your young self, what would you, what would be the narrative? >> Yeah, I mean my drawback then was HTML pages were coming out and I thought it would be fun to design, you know, webpages. So you find something you're passionate about in the space today, whether it's gaming or it's cybersecurity. Go and be excited about it and apply and don't give up, right? Do whatever you can to read and learn. And you're right, there are a ton of online self-help. I always try to hire women and people who are continual learners and are teaching themselves something. And I try to find that in an interview to know that they, because when you come to a business, you're there to solve problems and challenges. And the folks that can do that and be innovative and learn, those are the ones I want on my team. >> It's interesting, you know, technology is now impacting society and we need everyone involved to participate and give requirements. And that kind of leads my next question for you is, like, in your opinion, or let me just step back, let me rephrase. What are some of the things that you see technology being used for, for society right now that will impact people's lives? Because this is not a gender thing. We need everybody involved 'cause society is now digital. Technology's pervasive. The AI trends now we're seeing is clearly unmasking to the mainstream that there's some cool stuff happening. >> Yeah, I mean, I think ChatGPT, think about that. All the different ways we're using it we're writing content and marketing with it. We're, you know, I just read an article yesterday, folks are using it to write children's stories and then selling those stories on Amazon, right? And the amount that they can produce with it. But if you think about it, there's unlimited uses with that technology and you've got all the major players getting involved on it. That one major launch and piece of technology is going to transform us in the next six months to a year. And it's the ability to process so much data and then turn that into just assets that we use and the creativity that's building on top of it. Even TripActions has incorporated ChatGPT into your ability to figure out where you want when you're traveling, what's happening in that city. So it's just, you're going to see that incorporated everywhere. >> I mean we've done an interview before TripAction, your other company you were at. Interesting point you don't have to type in a box to say, I'm traveling, I want a hotel. You can just say, I'm going to Barcelona for Mobile World Congress, I want to have a good time. I want some tapas and a nice dinner out. >> Yes. Yeah. That easy. We're making it easy. >> It's efficiency. >> And actually I was going to say for women specifically, I think the reason why we can do so much today is all the technology and apps that we have. I think about DoorDash, I think about Waze you know, when I was younger you had to print out instructions. Now I get in the car real quick, I need to go to soccer practice, I enter it, I need to pick them up at someone's house. I enter it. It's everything's real time. And so it takes away all the things that I don't add value to and allows me to focus on what I want in business. And so there's a bunch of, you know, apps out there that have allowed me to be so much more efficient and productive that my mother didn't have for sure when I was growing up. >> That is an amazing, I think that actually illustrates, in my opinion, the best example of ChatGPT because the maps and GPS integration were two techs, technologies merged together that replace driving and looking at the map. You know, like how do you do that? Like now it's automatically. This is what's going to happen to creative, to writing, to ideation. I even heard Nicole from her book read said that they're using ChatGPT to write zero day exploits. So you seeing it... >> That's scary stuff. You're right. >> You're seeing it everywhere. Super exciting. Well, I got to ask you before you get into some of the Lacework things that you're involved with, cause I think you're doing great work over there is, what was the most exciting projects you've worked on in your career? You came in Cisco, very technical company, so got the technical chops, CSMIS which stands for Management of Information Science for all the young people out there, that was the state of the art back then. What are some of the exciting things you've done? >> Yeah, I mean, I think about, I think about MongoDB and learning to market to developers. Taking the company public in 2017. Launching Atlas database as a service. Now there's so much more of that, you know, the PLG motion, going to TripActions, you know, surviving a pandemic, still being able to come out of that and all the learnings that went with it. You know, they recently, I guess rebranded, so they're Navan now. And then now back in the security space, you know, 14 years ago I was at ArcSite and we were bought by HP. And so getting back into the security world is exciting and it's transformed a ton as you know, it's way more complicated than it was. And so just understanding the pain of our customers and how we protect them as is fun. And I like, you know, being there from a marketing standpoint. >> Well we really appreciate you coming on and sharing that. I got to ask you, for folks watching they might be interested in some advice that you might have for them and their career in tech. I know a lot of young people love the tech. It's becoming pervasive in our lives, as we mentioned. What advice would you give for folks watching that want to start a career in tech? >> Yeah, so work hard, right? Study, network, your first job, be the best at it because every job after that you get pulled into a network. And every time I move, I'm hiring people from the last job, two jobs before, three jobs before. And I'm looking for people that are working hard, care, you know, are continual learners and you know, add value. What can you do to solve problems at your work and add value? >> What's your secret networking hack or growth hack or tip that you can share? Because you're a great networker by the way. You're amazing and you do add a lot of value. I've seen you in action. >> Well, I try never to eat alone. I've got breakfast, I've got lunch, I've got coffee breaks and dinner. And so when I'm at work, I try and always sit and eat with a team member, new group. If I'm out on the road, I'm, you know, meeting people for lunch, going for dinner, just, you know, don't sit at your desk by yourself and don't sit in the hotel room. Get out and meet with people. >> What do you think about now that we're out of the pandemic or somewhat out of the pandemic so to speak, events are back. >> Yes. >> RSA is coming up. It's a big event. The bigger events are getting bigger and then the other events are kind of smaller being distributed. What's your vision of how events are evolving? >> Yeah, I mean, you've got to be in person. Those are the relationships. Right now more than ever people care about renewals and you are building that rapport. And if you're not meeting with your customers, your competitors are. So what I would say is get out there Lacework, we're going to be at RSA, we're going to be at re:Inforce, we're going to be at all of these events, building relationships, you know, coffee, lunch, and yeah, I think the future of events are here to stay and those that don't embrace in person are going to give up business. They're going to lose market share to us. >> And networking is obviously very key on events as well. >> Yes. >> A good opportunity as always get out to the events. What's the event networking trick or advice do you give folks that are going to get out to the networking world? >> Yeah, schedule ahead of time. Don't go to an event and expect people just to come by for great swag. You should be partnering with your sales team and scheduling ahead of time, getting on people's calendars. Don't go there without having 100 or 200 meetings already booked. >> Got it. All right. Let's talk about you, your career. You're currently at Lacework. It's a very hot company in a hot field, security, very male dominated, you're a leader there. What's it like? What's the strategies? How does a woman get in there and be successful? What are some tricks, observations, any data you can share? What's the best practice? What's the secret sauce from Meagen Eisenberg? >> Yes. Yeah, for Meagen Eisenberg. For Lacework, you know, we're focused on our customers. There's nothing better than getting, being close to them, solving their pain, showcasing them. So if you want to go into security, focus on their, the issues and their problems and make sure they're aware of what you're delivering. I mean, we're focused on cloud security and we go from build time to run time. And that's the draw for me here is we had a lot of, you know, happy, excited customers by what we were doing. And what we're doing is very different from legacy security providers. And it is tapping into the trend of really understanding how much data you have and what's happening in the data to detect the anomalies and the threats that are there. >> You know, one of the conversations that I was just having with a senior leader, she was amazing and I asked her what she thought of the current landscape, the job market, the how to get promoted through the careers, all those things. And the response was interesting. I want to get your reaction. She said interdisciplinary skills are critical. And now more than ever, the having that, having a set of skills, technical and social and emotional are super valuable. Do you agree? What's your reaction to that and what would, how would you reframe that? >> Yeah, I mean, I completely agree. You can't be a leader without balance. You've got to know your craft because you're developing and training your team, but you also need to know the, you know, how to build relationships. You're not going to be successful as a C-level exec if you're not partnering across the functions. As a CMO I need to partner with product, I need to partner with the head of sales, I need to partner with finance. So those relationships matter a ton. I also need to attract the right talent. I want to have solid people on the team. And what I will say in the security, cybersecurity space, there's a talent shortage and you cannot hire enough people to protect your company in that space. And that's kind of our part of it is we reduce the number of alerts that you're getting. So you don't need hundreds of people to detect an issue. You're using technology to show, you know, to highlight the issue and then your team can focus on those alerts that matter. >> Yeah, there's a lot of emerging markets where leveling up and you don't need pedigree. You can just level up skill-wise pretty quickly. Which brings me to the next question for you is how do you keep up with all the tech day-to-day and how should someone watching stay on top of it? Because I mean, you got to be on top of this stuff and you got to ride the wave. It's pretty turbulent, but it's still growing and changing. >> Yeah, it's true. I mean, there's a lot of reading. I'm watching the news. Anytime something comes out, you know, ChatGPT I'm playing with it. I've got a great network and sharing. I'm on, you know, LinkedIn reading articles all the time. I have a team, right? Every time I hire someone, they bring new information and knowledge in and I'm you know, Cal Poly had this learn by doing that was the philosophy at San Luis Obispo. So do it. Try it, don't be afraid of it. I think that's the advice. >> Well, I love some of the points you mentioned community and network. You mentioned networking. That brings up the community question, how could people get involved? What communities are out there? How should they approach communities? 'Cause communities are also networks, but also they're welcoming people in that form networks. So it's a network of networks. So what's your take on how to engage and work with communities? How do you find your tribe? If someone's getting into the business, they want support, they might want technology learnings, what's your approach? >> Yeah, so a few, a few different places. One, I'm part of the operator collective, which is a strong female investment group that's open and works a lot with operators and they're in on the newest technologies 'cause they're investing in it. Chief I think is a great organization as well. You've got a lot of, if you're in marketing, there's a ton of CMO networking events that you can go to. I would say any field, even for us at Lacework, we've got some strong CISO networks and we do dinners around you know, we have one coming up in the Bay area, in Boston, New York, and you can come and meet other CISOs and security leaders. So when I get an invite and you know we all do, I will go to it. I'll carve out the time and meet with others. So I think, you know, part of the community is get out there and, you know, join some of these different groups. >> Meagen, thank you so much for spending the time. Final question for you. How do you see the future of tech evolving and how do you see your role in it? >> Yeah, I mean, marketing's changing wildly. There's so many different channels. You think about all the social media channels that have changed over the last five years. So when I think about the future of tech, I'm looking at apps on my phone. I have three daughters, 13, 11, and 8. I'm telling you, they come to me with new apps and new technology all the time, and I'm paying attention what they're, you know, what they're participating in and what they want to be a part of. And certainly it's going to be a lot more around the data and AI. I think we're only at the beginning of that. So we will continue to, you know, learn from it and wield it and deal with the mass amount of data that's out there. >> Well, you saw TikTok just got banned by the European Commission today around their staff. Interesting times. >> It is. >> Meagen, thank you so much as always. You're a great tech athlete. Been following your career for a while, a long time. You're an amazing leader. Thank you for sharing your story here on theCUBE, celebration of International Women's Day. Every day is IWD and thanks for coming on. >> Thank you for having me. >> Okay. I'm John Furrier here in theCUBE Studios in Palo Alto. Thank you for watching, more to come stay with us. (bright music)
SUMMARY :
you for coming on the program Yeah, thank you for having me. That's kind of the spirit of this day. But I think about, you know, and it can get kind of messy as you know. and you know, be talking to the right What are some of the how the, you know, I recommend that book to everyone. makes you think about what's happening all the time, wasn't it. rules that won't help you you guys got going on? and help them, you know, and you know, that kind and around the world and the to design, you know, webpages. It's interesting, you know, to figure out where you Interesting point you That easy. I think about Waze you know, and looking at the map. You're right. Well, I got to ask you before you get into And I like, you know, some advice that you might have and you know, add value. You're amazing and you If I'm out on the road, I'm, you know, What do you think about now and then the other events and you are building that rapport. And networking is obviously do you give folks that just to come by for great swag. any data you can share? and the threats that are there. the how to get promoted You're using technology to show, you know, and you got to ride the wave. and I'm you know, the points you mentioned and you can come and meet other and how do you see your role in it? and new technology all the time, Well, you saw TikTok just got banned Thank you for sharing your Thank you for watching,
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theCUBE's New Analyst Talks Cloud & DevOps
(light music) >> Hi everybody. Welcome to this Cube Conversation. I'm really pleased to announce a collaboration with Rob Strechay. He's a guest cube analyst, and we'll be working together to extract the signal from the noise. Rob is a long-time product pro, working at a number of firms including AWS, HP, HPE, NetApp, Snowplow. I did a stint as an analyst at Enterprise Strategy Group. Rob, good to see you. Thanks for coming into our Marlboro Studios. >> Well, thank you for having me. It's always great to be here. >> I'm really excited about working with you. We've known each other for a long time. You've been in the Cube a bunch. You know, you're in between gigs, and I think we can have a lot of fun together. Covering events, covering trends. So. let's get into it. What's happening out there? We're sort of exited the isolation economy. Things were booming. Now, everybody's tapping the brakes. From your standpoint, what are you seeing out there? >> Yeah. I'm seeing that people are really looking how to get more out of their data. How they're bringing things together, how they're looking at the costs of Cloud, and understanding how are they building out their SaaS applications. And understanding that when they go in and actually start to use Cloud, it's not only just using the base services anymore. They're looking at, how do I use these platforms as a service? Some are easier than others, and they're trying to understand, how do I get more value out of that relationship with the Cloud? They're also consolidating the number of Clouds that they have, I would say to try to better optimize their spend, and getting better pricing for that matter. >> Are you seeing people unhook Clouds, or just reduce maybe certain Cloud activities and going maybe instead of 60/40 going 90/10? >> Correct. It's more like the 90/10 type of rule where they're starting to say, Hey I'm not going to get rid of Azure or AWS or Google. I'm going to move a portion of this over that I was using on this one service. Maybe I got a great two-year contract to start with on this platform as a service or a database as a service. I'm going to unhook from that and maybe go with an independent. Maybe with something like a Snowflake or a Databricks on top of another Cloud, so that I can consolidate down. But it also gives them more flexibility as well. >> In our last breaking analysis, Rob, we identified six factors that were reducing Cloud consumption. There were factors and customer tactics. And I want to get your take on this. So, some of the factors really, you got fewer mortgage originations. FinTech, obviously big Cloud user. Crypto, not as much activity there. Lower ad spending means less Cloud. And then one of 'em, which you kind of disagreed with was less, less analytics, you know, fewer... Less frequency of calculations. I'll come back to that. But then optimizing compute using Graviton or AMD instances moving to cheaper storage tiers. That of course makes sense. And then optimize pricing plans. Maybe going from On Demand, you know, to, you know, instead of pay by the drink, buy in volume. Okay. So, first of all, do those make sense to you with the exception? We'll come back and talk about the analytics piece. Is that what you're seeing from customers? >> Yeah, I think so. I think that was pretty much dead on with what I'm seeing from customers and the ones that I go out and talk to. A lot of times they're trying to really monetize their, you know, understand how their business utilizes these Clouds. And, where their spend is going in those Clouds. Can they use, you know, lower tiers of storage? Do they really need the best processors? Do they need to be using Intel or can they get away with AMD or Graviton 2 or 3? Or do they need to move in? And, I think when you look at all of these Clouds, they always have pricing curves that are arcs from the newest to the oldest stuff. And you can play games with that. And understanding how you can actually lower your costs by looking at maybe some of the older generation. Maybe your application was written 10 years ago. You don't necessarily have to be on the best, newest processor for that application per se. >> So last, I want to come back to this whole analytics piece. Last June, I think it was June, Dev Ittycheria, who's the-- I call him Dev. Spelled Dev, pronounced Dave. (chuckles softly) Same pronunciation, different spelling. Dev Ittycheria, CEO of Mongo, on the earnings call. He was getting, you know, hit. Things were starting to get a little less visible in terms of, you know, the outlook. And people were pushing him like... Because you're in the Cloud, is it easier to dial down? And he said, because we're the document database, we support transaction applications. We're less discretionary than say, analytics. Well on the Snowflake earnings call, that same month or the month after, they were all over Slootman and Scarpelli. Oh, the Mongo CEO said that they're less discretionary than analytics. And Snowflake was an interesting comment. They basically said, look, we're the Cloud. You can dial it up, you can dial it down, but the area under the curve over a period of time is going to be the same, because they get their customers to commit. What do you say? You disagreed with the notion that people are running their calculations less frequently. Is that because they're trying to do a better job of targeting customers in near real time? What are you seeing out there? >> Yeah, I think they're moving away from using people and more expensive marketing. Or, they're trying to figure out what's my Google ad spend, what's my Meta ad spend? And what they're trying to do is optimize that spend. So, what is the return on advertising, or the ROAS as they would say. And what they're looking to do is understand, okay, I have to collect these analytics that better understand where are these people coming from? How do they get to my site, to my store, to my whatever? And when they're using it, how do they they better move through that? What you're also seeing is that analytics is not only just for kind of the retail or financial services or things like that, but then they're also, you know, using that to make offers in those categories. When you move back to more, you know, take other companies that are building products and SaaS delivered products. They may actually go and use this analytics for making the product better. And one of the big reasons for that is maybe they're dialing back how many product managers they have. And they're looking to be more data driven about how they actually go and build the product out or enhance the product. So maybe they're, you know, an online video service and they want to understand why people are either using or not using the whiteboard inside the product. And they're collecting a lot of that product analytics in a big way so that they can go through that. And they're doing it in a constant manner. This first party type tracking within applications is growing rapidly by customers. >> So, let's talk about who wins in that. So, obviously the Cloud guys, AWS, Google and Azure. I want to come back and unpack that a little bit. Databricks and Snowflake, we reported on our last breaking analysis, it kind of on a collision course. You know, a couple years ago we were thinking, okay, AWS, Snowflake and Databricks, like perfect sandwich. And then of course they started to become more competitive. My sense is they still, you know, compliment each other in the field, right? But, you know, publicly, they've got bigger aspirations, they get big TAMs that they're going after. But it's interesting, the data shows that-- So, Snowflake was off the charts in terms of spending momentum and our EPR surveys. Our partner down in New York, they kind of came into line. They're both growing in terms of market presence. Databricks couldn't get to IPO. So, we don't have as much, you know, visibility on their financials. You know, Snowflake obviously highly transparent cause they're a public company. And then you got AWS, Google and Azure. And it seems like AWS appears to be more partner friendly. Microsoft, you know, depends on what market you're in. And Google wants to sell BigQuery. >> Yeah. >> So, what are you seeing in the public Cloud from a data platform perspective? >> Yeah. I think that was pretty astute in what you were talking about there, because I think of the three, Google is definitely I think a little bit behind in how they go to market with their partners. Azure's done a fantastic job of partnering with these companies to understand and even though they may have Synapse as their go-to and where they want people to go to do AI and ML. What they're looking at is, Hey, we're going to also be friendly with Snowflake. We're also going to be friendly with a Databricks. And I think that, Amazon has always been there because that's where the market has been for these developers. So, many, like Databricks' and the Snowflake's have gone there first because, you know, Databricks' case, they built out on top of S3 first. And going and using somebody's object layer other than AWS, was not as simple as you would think it would be. Moving between those. >> So, one of the financial meetups I said meetup, but the... It was either the CEO or the CFO. It was either Slootman or Scarpelli talking at, I don't know, Merrill Lynch or one of the other financial conferences said, I think it was probably their Q3 call. Snowflake said 80% of our business goes through Amazon. And he said to this audience, the next day we got a call from Microsoft. Hey, we got to do more. And, we know just from reading the financial statements that Snowflake is getting concessions from Amazon, they're buying in volume, they're renegotiating their contracts. Amazon gets it. You know, lower the price, people buy more. Long term, we're all going to make more money. Microsoft obviously wants to get into that game with Snowflake. They understand the momentum. They said Google, not so much. And I've had customers tell me that they wanted to use Google's AI with Snowflake, but they can't, they got to go to to BigQuery. So, honestly, I haven't like vetted that so. But, I think it's true. But nonetheless, it seems like Google's a little less friendly with the data platform providers. What do you think? >> Yeah, I would say so. I think this is a place that Google looks and wants to own. Is that now, are they doing the right things long term? I mean again, you know, you look at Google Analytics being you know, basically outlawed in five countries in the EU because of GDPR concerns, and compliance and governance of data. And I think people are looking at Google and BigQuery in general and saying, is it the best place for me to go? Is it going to be in the right places where I need it? Still, it's still one of the largest used databases out there just because it underpins a number of the Google services. So you almost get, like you were saying, forced into BigQuery sometimes, if you want to use the tech on top. >> You do strategy. >> Yeah. >> Right? You do strategy, you do messaging. Is it the right call by Google? I mean, it's not a-- I criticize Google sometimes. But, I'm not sure it's the wrong call to say, Hey, this is our ace in the hole. >> Yeah. >> We got to get people into BigQuery. Cause, first of all, BigQuery is a solid product. I mean it's Cloud native and it's, you know, by all, it gets high marks. So, why give the competition an advantage? Let's try to force people essentially into what is we think a great product and it is a great product. The flip side of that is, they're giving up some potential partner TAM and not treating the ecosystem as well as one of their major competitors. What do you do if you're in that position? >> Yeah, I think that that's a fantastic question. And the question I pose back to the companies I've worked with and worked for is, are you really looking to have vendor lock-in as your key differentiator to your service? And I think when you start to look at these companies that are moving away from BigQuery, moving to even, Databricks on top of GCS in Google, they're looking to say, okay, I can go there if I have to evacuate from GCP and go to another Cloud, I can stay on Databricks as a platform, for instance. So I think it's, people are looking at what platform as a service, database as a service they go and use. Because from a strategic perspective, they don't want that vendor locking. >> That's where Supercloud becomes interesting, right? Because, if I can run on Snowflake or Databricks, you know, across Clouds. Even Oracle, you know, they're getting into business with Microsoft. Let's talk about some of the Cloud players. So, the big three have reported. >> Right. >> We saw AWSs Cloud growth decelerated down to 20%, which is I think the lowest growth rate since they started to disclose public numbers. And they said they exited, sorry, they said January they grew at 15%. >> Yeah. >> Year on year. Now, they had some pretty tough compares. But nonetheless, 15%, wow. Azure, kind of mid thirties, and then Google, we had kind of low thirties. But, well behind in terms of size. And Google's losing probably almost $3 billion annually. But, that's not necessarily a bad thing by advocating and investing. What's happening with the Cloud? Is AWS just running into the law, large numbers? Do you think we can actually see a re-acceleration like we have in the past with AWS Cloud? Azure, we predicted is going to be 75% of AWS IAS revenues. You know, we try to estimate IAS. >> Yeah. >> Even though they don't share that with us. That's a huge milestone. You'd think-- There's some people who have, I think, Bob Evans predicted a while ago that Microsoft would surpass AWS in terms of size. You know, what do you think? >> Yeah, I think that Azure's going to keep to-- Keep growing at a pretty good clip. I think that for Azure, they still have really great account control, even though people like to hate Microsoft. The Microsoft sellers that are out there making those companies successful day after day have really done a good job of being in those accounts and helping people. I was recently over in the UK. And the UK market between AWS and Azure is pretty amazing, how much Azure there is. And it's growing within Europe in general. In the states, it's, you know, I think it's growing well. I think it's still growing, probably not as fast as it is outside the U.S. But, you go down to someplace like Australia, it's also Azure. You hear about Azure all the time. >> Why? Is that just because of the Microsoft's software state? It's just so convenient. >> I think it has to do with, you know, and you can go with the reasoning they don't break out, you know, Office 365 and all of that out of their numbers is because they have-- They're in all of these accounts because the office suite is so pervasive in there. So, they always have reasons to go back in and, oh by the way, you're on these old SQL licenses. Let us move you up here and we'll be able to-- We'll support you on the old version, you know, with security and all of these things. And be able to move you forward. So, they have a lot of, I guess you could say, levers to stay in those accounts and be interesting. At least as part of the Cloud estate. I think Amazon, you know, is hitting, you know, the large number. Laws of large numbers. But I think that they're also going through, and I think this was seen in the layoffs that they were making, that they're looking to understand and have profitability in more of those services that they have. You know, over 350 odd services that they have. And you know, as somebody who went there and helped to start yet a new one, while I was there. And finally, it went to beta back in September, you start to look at the fact that, that number of services, people, their own sellers don't even know all of their services. It's impossible to comprehend and sell that many things. So, I think what they're going through is really looking to rationalize a lot of what they're doing from a services perspective going forward. They're looking to focus on more profitable services and bringing those in. Because right now it's built like a layer cake where you have, you know, S3 EBS and EC2 on the bottom of the layer cake. And then maybe you have, you're using IAM, the authorization and authentication in there and you have all these different services. And then they call it EMR on top. And so, EMR has to pay for that entire layer cake just to go and compete against somebody like Mongo or something like that. So, you start to unwind the costs of that. Whereas Azure, went and they build basically ground up services for the most part. And Google kind of falls somewhere in between in how they build their-- They're a sort of layer cake type effect, but not as many layers I guess you could say. >> I feel like, you know, Amazon's trying to be a platform for the ecosystem. Yes, they have their own products and they're going to sell. And that's going to drive their profitability cause they don't have to split the pie. But, they're taking a piece of-- They're spinning the meter, as Ziyas Caravalo likes to say on every time Snowflake or Databricks or Mongo or Atlas is, you know, running on their system. They take a piece of the action. Now, Microsoft does that as well. But, you look at Microsoft and security, head-to-head competitors, for example, with a CrowdStrike or an Okta in identity. Whereas, it seems like at least for now, AWS is a more friendly place for the ecosystem. At the same time, you do a lot of business in Microsoft. >> Yeah. And I think that a lot of companies have always feared that Amazon would just throw, you know, bodies at it. And I think that people have come to the realization that a two pizza team, as Amazon would call it, is eight people. I think that's, you know, two slices per person. I'm a little bit fat, so I don't know if that's enough. But, you start to look at it and go, okay, if they're going to start out with eight engineers, if I'm a startup and they're part of my ecosystem, do I really fear them or should I really embrace them and try to partner closer with them? And I think the smart people and the smart companies are partnering with them because they're realizing, Amazon, unless they can see it to, you know, a hundred million, $500 million market, they're not going to throw eight to 16 people at a problem. I think when, you know, you could say, you could look at the elastic with OpenSearch and what they did there. And the licensing terms and the battle they went through. But they knew that Elastic had a huge market. Also, you had a number of ecosystem companies building on top of now OpenSearch, that are now domain on top of Amazon as well. So, I think Amazon's being pretty strategic in how they're doing it. I think some of the-- It'll be interesting. I think this year is a payout year for the cuts that they're making to some of the services internally to kind of, you know, how do we take the fat off some of those services that-- You know, you look at Alexa. I don't know how much revenue Alexa really generates for them. But it's a means to an end for a number of different other services and partners. >> What do you make of this ChatGPT? I mean, Microsoft obviously is playing that card. You want to, you want ChatGPT in the Cloud, come to Azure. Seems like AWS has to respond. And we know Google is, you know, sharpening its knives to come up with its response. >> Yeah, I mean Google just went and talked about Bard for the first time this week and they're in private preview or I guess they call it beta, but. Right at the moment to select, select AI users, which I have no idea what that means. But that's a very interesting way that they're marketing it out there. But, I think that Amazon will have to respond. I think they'll be more measured than say, what Google's doing with Bard and just throwing it out there to, hey, we're going into beta now. I think they'll look at it and see where do we go and how do we actually integrate this in? Because they do have a lot of components of AI and ML underneath the hood that other services use. And I think that, you know, they've learned from that. And I think that they've already done a good job. Especially for media and entertainment when you start to look at some of the ways that they use it for helping do graphics and helping to do drones. I think part of their buy of iRobot was the fact that iRobot was a big user of RoboMaker, which is using different models to train those robots to go around objects and things like that, so. >> Quick touch on Kubernetes, the whole DevOps World we just covered. The Cloud Native Foundation Security, CNCF. The security conference up in Seattle last week. First time they spun that out kind of like reinforced, you know, AWS spins out, reinforced from reinvent. Amsterdam's coming up soon, the CubeCon. What should we expect? What's hot in Cubeland? >> Yeah, I think, you know, Kubes, you're going to be looking at how OpenShift keeps growing and I think to that respect you get to see the momentum with people like Red Hat. You see others coming up and realizing how OpenShift has gone to market as being, like you were saying, partnering with those Clouds and really making it simple. I think the simplicity and the manageability of Kubernetes is going to be at the forefront. I think a lot of the investment is still going into, how do I bring observability and DevOps and AIOps and MLOps all together. And I think that's going to be a big place where people are going to be looking to see what comes out of CubeCon in Amsterdam. I think it's that manageability ease of use. >> Well Rob, I look forward to working with you on behalf of the whole Cube team. We're going to do more of these and go out to some shows extract the signal from the noise. Really appreciate you coming into our studio. >> Well, thank you for having me on. Really appreciate it. >> You're really welcome. All right, keep it right there, or thanks for watching. This is Dave Vellante for the Cube. And we'll see you next time. (light music)
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I'm really pleased to It's always great to be here. and I think we can have the number of Clouds that they have, contract to start with those make sense to you And, I think when you look in terms of, you know, the outlook. And they're looking to My sense is they still, you know, in how they go to market And he said to this audience, is it the best place for me to go? You do strategy, you do messaging. and it's, you know, And I think when you start Even Oracle, you know, since they started to to be 75% of AWS IAS revenues. You know, what do you think? it's, you know, I think it's growing well. Is that just because of the And be able to move you forward. I feel like, you know, I think when, you know, you could say, And we know Google is, you know, And I think that, you know, you know, AWS spins out, and I think to that respect forward to working with you Well, thank you for having me on. And we'll see you next time.
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Breaking Analysis: Cloud players sound a cautious tone for 2023
>> From the Cube Studios in Palo Alto in Boston bringing you data-driven insights from the Cube and ETR. This is Breaking Analysis with Dave Vellante. >> The unraveling of market enthusiasm continued in Q4 of 2022 with the earnings reports from the US hyperscalers, the big three now all in. As we said earlier this year, even the cloud is an immune from the macro headwinds and the cracks in the armor that we saw from the data that we shared last summer, they're playing out into 2023. For the most part actuals are disappointing beyond expectations including our own. It turns out that our estimates for the big three hyperscaler's revenue missed by 1.2 billion or 2.7% lower than we had forecast from even our most recent November estimates. And we expect continued decelerating growth rates for the hyperscalers through the summer of 2023 and we don't think that's going to abate until comparisons get easier. Hello and welcome to this week's Wikibon Cube Insights powered by ETR. In this Breaking Analysis, we share our view of what's happening in cloud markets not just for the hyperscalers but other firms that have hitched a ride on the cloud. And we'll share new ETR data that shows why these trends are playing out tactics that customers are employing to deal with their cost challenges and how long the pain is likely to last. You know, riding the cloud wave, it's a two-edged sword. Let's look at the players that have gone all in on or are exposed to both the positive and negative trends of cloud. Look the cloud has been a huge tailwind for so many companies like Snowflake and Databricks, Workday, Salesforce, Mongo's move with Atlas, Red Hats Cloud strategy with OpenShift and so forth. And you know, the flip side is because cloud is elastic what comes up can also go down very easily. Here's an XY graphic from ETR that shows spending momentum or net score on the vertical axis and market presence in the dataset on the horizontal axis provision or called overlap. This is data from the January 2023 survey and that the red dotted lines show the positions of several companies that we've highlighted going back to January 2021. So let's unpack this for a bit starting with the big three hyperscalers. The first point is AWS and Azure continue to solidify their moat relative to Google Cloud platform. And we're going to get into this in a moment, but Azure and AWS revenues are five to six times that of GCP for IaaS. And at those deltas, Google should be gaining ground much faster than the big two. The second point on Google is notice the red line on GCP relative to its starting point. While it appears to be gaining ground on the horizontal axis, its net score is now below that of AWS and Azure in the survey. So despite its significantly smaller size it's just not keeping pace with the leaders in terms of market momentum. Now looking at AWS and Microsoft, what we see is basically AWS is holding serve. As we know both Google and Microsoft benefit from including SaaS in their cloud numbers. So the fact that AWS hasn't seen a huge downward momentum relative to a January 2021 position is one positive in the data. And both companies are well above that magic 40% line on the Y-axis, anything above 40% we consider to be highly elevated. But the fact remains that they're down as are most of the names on this chart. So let's take a closer look. I want to start with Snowflake and Databricks. Snowflake, as we reported from several quarters back came down to Earth, it was up in the 80% range in the Y-axis here. And it's still highly elevated in the 60% range and it continues to move to the right, which is positive but as we'll address in a moment it's customers can dial down consumption just as in any cloud. Now, Databricks is really interesting. It's not a public company, it never made it to IPO during the sort of tech bubble. So we don't have the same level of transparency that we do with other companies that did make it through. But look at how much more prominent it is on the X-axis relative to January 2021. And it's net score is basically held up over that period of time. So that's a real positive for Databricks. Next, look at Workday and Salesforce. They've held up relatively well, both inching to the right and generally holding their net scores. Same from Mongo, which is the brown dot above its name that says Elastic, it says a little gets a little crowded which Elastic's actually the blue dot above it. But generally, SaaS is harder to dial down, Workday, Salesforce, Oracles, SaaS and others. So it's harder to dial down because commitments have been made in advance, they're kind of locked in. Now, one of the discussions from last summer was as Mongo, less discretionary than analytics i.e. Snowflake. And it's an interesting debate but maybe Snowflake customers, you know, they're also generally committed to a dollar amount. So over time the spending is going to be there. But in the short term, yeah maybe Snowflake customers can dial down. Now that highlighted dotted red line, that bolded one is Datadog and you can see it's made major strides on the X-axis but its net score has decelerated quite dramatically. Openshift's momentum in the survey has dropped although IBM just announced that OpenShift has a a billion dollar ARR and I suspect what's happening there is IBM consulting is bundling OpenShift into its modernization projects. It's got a, that sort of captive base if you will. And as such it's probably not as top of mind to the respondents but I'll bet you the developers are certainly aware of it. Now the other really notable call out here is CloudFlare, We've reported on them earlier. Cloudflare's net score has held up really well since January of 2021. It really hasn't seen the downdraft of some of these others, but it's making major major moves to the right gaining market presence. We really like how CloudFlare is performing. And the last comment is on Oracle which as you can see, despite its much, much lower net score continues to gain ground in the market and thrive from a profitability standpoint. But the data pretty clearly shows that there's a downdraft in the market. Okay, so what's happening here? Let's dig deeper into this data. Here's a graphic from the most recent ETR drill down asking customers that said they were going to cut spending what technique they're using to do so. Now, as we've previously reported, consolidating redundant vendors is by far the most cited approach but there's two key points we want to make here. One is reducing excess cloud resources. As you can see in the bars is the second most cited technique and it's up from the previous polling period. The second we're not showing, you know directly but we've got some red call outs there. Reducing cloud costs jumps to 29% and 28% respectively in financial services and tech telco. And it's much closer to second. It's basically neck and neck with consolidating redundant vendors in those two industries. So they're being really aggressive about optimizing cloud cost. Okay, so as we said, cloud is great 'cause you can dial it up but it's just as easy to dial down. We've identified six factors that customers tell us are affecting their cloud consumption and there are probably more, if you got more we'd love to hear them but these are the ones that are fairly prominent that have hit our radar. First, rising mortgage rates mean banks are processing fewer loans means less cloud. The crypto crash means less trading activity and that means less cloud resources. Third lower ad spend has led companies to reduce not only you know, their ad buying but also their frequency of running their analytics and their calculations. And they're also often using less data, maybe compressing the timeframe of the corpus down to a shorter time period. Also very prominent is down to the bottom left, using lower cost compute instances. For example, Graviton from AWS or AMD chips and tiering storage to cheaper S3 or deep archived tiers. And finally, optimizing based on better pricing plans. So customers are moving from, you know, smaller companies in particular moving maybe from on demand or other larger companies that are experimenting using on demand or they're moving to spot pricing or reserved instances or optimized savings plans. That all lowers cost and that means less cloud resource consumption and less cloud revenue. Now in the days when everything was on prem CFOs, what would they do? They would freeze CapEx and IT Pros would have to try to do more with less and often that meant a lot of manual tasks. With the cloud it's much easier to move things around. It still takes some thinking and some effort but it's dramatically simpler to do so. So you can get those savings a lot faster. Now of course the other huge factor is you can cut or you can freeze. And this graphic shows data from a recent ETR survey with 159 respondents and you can see the meaningful uptick in hiring freezes, freezing new IT deployments and layoffs. And as we've been reporting, this has been trending up since earlier last year. And note the call out, this is especially prominent in retail sectors, all three of these techniques jump up in retail and that's a bit of a concern because oftentimes consumer spending helps the economy make a softer landing out of a pullback. But this is a potential canary in the coal mine. If retail firms are pulling back it's because consumers aren't spending as much. And so we're keeping a close eye on that. So let's boil this down to the market data and what this all means. So in this graphic we show our estimates for Q4 IaaS revenues compared to the "actual" IaaS revenues. And we say quote because AWS is the only one that reports, you know clean revenue and IaaS, Azure and GCP don't report actuals. Why would they? Because it would make them look even, you know smaller relative to AWS. Rather, they bury the figures in overall cloud which includes their, you know G-Suite for Google and all the Microsoft SaaS. And then they give us little tidbits about in Microsoft's case, Azure, they give growth rates. Google gives kind of relative growth of GCP. So, and we use survey data and you know, other data to try to really pinpoint and we've been covering this for, I don't know, five or six years ever since the cloud really became a thing. But looking at the data, we had AWS growing at 25% this quarter and it came in at 20%. So a significant decline relative to our expectations. AWS announced that it exited December, actually, sorry it's January data showed about a 15% mid-teens growth rate. So that's, you know, something we're watching. Azure was two points off our forecast coming in at 38% growth. It said it exited December in the 35% growth range and it said that it's expecting five points of deceleration off of that. So think 30% for Azure. GCP came in three points off our expectation coming in 35% and Alibaba has yet to report but we've shaved a bid off that forecast based on some survey data and you know what maybe 9% is even still not enough. Now for the year, the big four hyperscalers generated almost 160 billion of revenue, but that was 7 billion lower than what what we expected coming into 2022. For 2023, we're expecting 21% growth for a total of 193.3 billion. And while it's, you know, lower, you know, significantly lower than historical expectations it's still four to five times the overall spending forecast that we just shared with you in our predictions post of between 4 and 5% for the overall market. We think AWS is going to come in in around 93 billion this year with Azure closing in at over 71 billion. This is, again, we're talking IaaS here. Now, despite Amazon focusing investors on the fact that AWS's absolute dollar growth is still larger than its competitors. By our estimates Azure will come in at more than 75% of AWS's forecasted revenue. That's a significant milestone. AWS is operating margins by the way declined significantly this past quarter, dropping from 30% of revenue to 24%, 30% the year earlier to 24%. Now that's still extremely healthy and we've seen wild fluctuations like this before so I don't get too freaked out about that. But I'll say this, Microsoft has a marginal cost advantage relative to AWS because one, it has a captive cloud on which to run its massive software estate. So it can just throw software at its own cloud and two software marginal costs. Marginal economics despite AWS's awesomeness in high degrees of automation, software is just a better business. Now the upshot for AWS is the ecosystem. AWS is essentially in our view positioning very smartly as a platform for data partners like Snowflake and Databricks, security partners like CrowdStrike and Okta and Palo Alto and many others and SaaS companies. You know, Microsoft is more competitive even though AWS does have competitive products. Now of course Amazon's competitive to retail companies so that's another factor but generally speaking for tech players, Amazon is a really thriving ecosystem that is a secret weapon in our view. AWS happy to spin the meter with its partners even though it sells competitive products, you know, more so in our view than other cloud players. Microsoft, of course is, don't forget is hyping now, we're hearing a lot OpenAI and ChatGPT we reported last week in our predictions post. How OpenAI is shot up in terms of market sentiment in ETR's emerging technology company surveys and people are moving to Azure to get OpenAI and get ChatGPT that is a an interesting lever. Amazon in our view has to have a response. They have lots of AI and they're going to have to make some moves there. Meanwhile, Google is emphasizing itself as an AI first company. In fact, Google spent at least five minutes of continuous dialogue, nonstop on its AI chops during its latest earnings call. So that's an area that we're watching very closely as the buzz around large language models continues. All right, let's wrap up with some assumptions for 2023. We think SaaS players are going to continue to be sticky. They're going to be somewhat insulated from all these downdrafts because they're so tied in and customers, you know they make the commitment up front, you've got the lock in. Now having said that, we do expect some backlash over time on the onerous and generally customer unfriendly pricing models of most large SaaS companies. But that's going to play out over a longer period of time. Now for cloud generally and the hyperscalers specifically we do expect accelerating growth rates into Q3 but the amplitude of the demand swings from this rubber band economy, we expect to continue to compress and become more predictable throughout the year. Estimates are coming down, CEOs we think are going to be more cautious when the market snaps back more cautious about hiring and spending and as such a perhaps we expect a more orderly return to growth which we think will slightly accelerate in Q4 as comps get easier. Now of course the big risk to these scenarios is of course the economy, the FED, consumer spending, inflation, supply chain, energy prices, wars, geopolitics, China relations, you know, all the usual stuff. But as always with our partners at ETR and the Cube community, we're here for you. We have the data and we'll be the first to report when we see a change at the margin. Okay, that's a wrap for today. I want to thank Alex Morrison who's on production and manages the podcast, Ken Schiffman as well out of our Boston studio getting this up on LinkedIn Live. Thank you for that. Kristen Martin also and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our Editor-in-Chief over at siliconangle.com. He does some great editing for us. Thank you all. Remember all these episodes are available as podcast. Wherever you listen, just search Breaking Analysis podcast. I publish each week on wikibon.com, at siliconangle.com where you can see all the data and you want to get in touch. Just all you can do is email me david.vellante@siliconangle.com or DM me @dvellante if you if you got something interesting, I'll respond. If you don't, it's either 'cause I'm swamped or it's just not tickling me. You can comment on our LinkedIn post as well. And please check out ETR.ai for the best survey data in the enterprise tech business. This is Dave Vellante for the Cube Insights powered by ETR. Thanks for watching and we'll see you next time on Breaking Analysis. (gentle upbeat music)
SUMMARY :
From the Cube Studios and how long the pain is likely to last.
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Brian Gracely, The Cloudcast | Does the World Really Need Supercloud?
(upbeat music) >> Welcome back to Supercloud 2 this is Dave Vellante. We're here exploring the intersection of data and analytics and the future of cloud. And in this segment, we're going to look at the evolution of cloud, and try to test some of the Supercloud concepts and assumptions with Brian Gracely, is the founder and co-host along with Aaron Delp of the popular Cloudcast program. Amazing series, if you're not already familiar with it. The Cloudcast is one of the best ways to keep up with so many things going on in our industry. Enterprise tech, platform engineering, business models, obviously, cloud developer trends, crypto, Web 3.0. Sorry Brian, I know that's a sore spot, but Brian, thanks for coming >> That's okay. >> on the program, really appreciate it. >> Yeah, great to be with you, Dave. Happy New Year, and great to be back with everybody with SiliconANGLE again this year. >> Yeah, we love having you on. We miss working with you day-to-day, but I want to start with Gracely's theorem, which basically says, I'm going to paraphrase. For the most part, nothing new gets introduced in the enterprise tech business, patterns repeat themselves, maybe get applied in new ways. And you know this industry well, when something comes out that's new, if you take virtualization, for example, been around forever with mainframes, but then VMware applied it, solve a real problem in the client service system. And then it's like, "Okay, this is awesome." We get really excited and then after a while we pushed the architecture, we break things, introduce new things to fix the things that are broken and start adding new features. And oftentimes you do that through acquisitions. So, you know, has the cloud become that sort of thing? And is Supercloud sort of same wine, new bottle, following Gracely's theorem? >> Yeah, I think there's some of both of it. I hate to be the sort of, it depends sort of answer but, I think to a certain extent, you know, obviously Cloud in and of itself was, kind of revolutionary in that, you know, it wasn't that you couldn't rent things in the past, it was just being able to do it at scale, being able to do it with such amazing self-service. And then, you know, kind of proliferation of like, look at how many services I can get from, from one cloud, whether it was Amazon or Azure or Google. And then, you know, we, we slip back into the things that we know, we go, "Oh, well, okay, now I can get computing on demand, but, now it's just computing." Or I can get database on demand and it's, you know, it's got some of the same limitations of, of say, of database, right? It's still, you know, I have to think about IOPS and I have to think about caching, and other stuff. So, I think we do go through that and then we, you know, we have these sort of next paradigms that come along. So, you know, serverless was another one of those where it was like, okay, it seems sort of new. I don't have to, again, it was another level of like, I don't have to think about anything. And I was able to do that because, you know, there was either greater bandwidth available to me, or compute got cheaper. And what's been interesting is not the sort of, that specific thing, serverless in and of itself is just another way of doing compute, but the fact that it now gets applied as, sort of a no-ops model to, you know, again, like how do I provision a database? How do I think about, you know, do I have to think about the location of a service? Does that just get taken care of for me? So I think the Supercloud concept, and I did a thing and, and you and I have talked about it, you know, behind the scenes that maybe the, maybe a better name is Super app for something like Snowflake or other, but I think we're, seeing these these sort of evolutions over and over again of what were the big bottlenecks? How do we, how do we solve those bottlenecks? And I think the big thing here is, it's never, it's very rarely that you can take the old paradigm of what the thing was, the concept was, and apply it to the new model. So, I'll just give you an example. So, you know, something like VMware, which we all know, wildly popular, wildly used, but when we apply like a Supercloud concept of VMware, the concept of VMware has always been around a cluster, right? It's some finite number of servers, you sort of manage it as a cluster. And when you apply that to the cloud and you say, okay, there's, you know, for example, VMware in the cloud, it's still the same concept of a cluster of VMware. But yet when you look at some of these other services that would fit more into the, you know, Supercloud kind of paradigm, whether it's a Snowflake or a MongoDB Atlas or maybe what CloudFlare is doing at the edge, those things get rid of some of those old paradigms. And I think that's where stuff, you start to go, "Oh, okay, this is very different than before." Yes, it's still computing or storage, or data access, but there's a whole nother level of something that we didn't carry forward from the previous days. And that really kind of breaks the paradigm. And so that's the way I think I've started to think about, are these things really brand new? Yes and no, but I think it's when you can see that big, that thing that you didn't leave behind isn't there anymore, you start to get some really interesting new innovation come out of it. >> Yeah. And that's why, you know, lift and shift is okay, when you talk to practitioners, they'll say, "You know, I really didn't change my operating model. And so I just kind of moved it into the cloud. there were some benefits, but it was maybe one zero not three zeros that I was looking for." >> Right. >> You know, we always talk about what's great about cloud, the agility, and all the other wonderful stuff that we know, what's not working in cloud, you know, tie it into multi-cloud, you know, in terms of, you hear people talk about multi-cloud by accident, okay, that's true. >> Yep. >> What's not great about cloud. And then I want to get into, you know, is multi-cloud really a problem or is it just sort of vendor hype? But, but what's not working in cloud? I mean, you mentioned serverless and serverless is kind of narrow, right, for a lot of stateless apps, right? But, what's not great about cloud? >> Well, I think there's a few things that if you ask most people they don't love about cloud. I think, we can argue whether or not sort of this consolidation around a few cloud providers has been a good thing or a bad thing. I think, regardless of that, you know, we are seeing, we are hearing more and more people that say, look, you know, the experience I used to have with cloud when I went to, for example, an Amazon and there was, you know, a dozen services, it was easy to figure out what was going on. It was easy to figure out what my billing looked like. You know, now they've become so widespread, the number of services they have, you know, the number of stories you just hear of people who went, "Oh, I started a service over in US West and I can't find it anymore 'cause it's on a different screen. And I, you know, I just got billed for it." Like, so I think the sprawl of some of the clouds has gotten, has created a user experience that a lot of people are frustrated with. I think that's one thing. And we, you know, we see people like Digital Ocean and we see others who are saying, "Hey, we're going to be that simplified version." So, there's always that yin and yang. I think people are super frustrated at network costs, right? So, you know, and that's kind of at a lot of, at the center of maybe why we do or don't see more of these Supercloud services is just, you know, in the data center as an application owner, I didn't have to think about, well where, where does this go to? Where are my users? Yes, somebody took care of it, but when those things become front and center, that's super frustrating. That's the one area that we've seen absolutely no cost savings, cost reduction. So I think that frustrates people a lot. And then I think the third piece is just, you know, we're, we went from super centralized IT organizations, which, you know, for decades was how it worked. It was part of the reason why the cloud expanded and became a thing, right? Sort of shadow IT and I can't get things done. And then, now what we've seen is sort of this proliferation of little pockets of groups that are your IT, for lack of a better thing, whether they're called platform engineering or SRE or DevOps. But we have this, expansion, explosion if you will, of groups that, if I'm an app dev team, I go, "Hey, you helped me make this stuff run, but then the team next to you has another group and they have another group." And so you see this explosion of, you know, we don't have any standards in the company anymore. And, so sort of self-service has created its own nightmare to a certain extent for a lot of larger companies. >> Yeah. Thank you for that. So, you know, I want, I want to explore this multi-cloud, you know, by accident thing and is a real problem. You hear that a lot from vendors and we've been talking about Supercloud as this unifying layer across cloud. You know, but when you talk to customers, a lot of them are saying, "Yes, we have multiple clouds in our organization, but my group, we have mono cloud, we know the security, edicts, we know how to, you know, deal with the primitives, whether it's, you know, S3 or Azure Blob or whatever it is. And we're very comfortable with this." It's, that's how we're simplifying. So, do you think this is really a problem? Does it have merit that we need that unifying layer across clouds, or is it just too early for that? >> I think, yeah, I think what you, what you've laid out is basically how the world has played out. People have picked a cloud for a specific application or a series of applications. Yeah, and I think if you talk to most companies, they would tell you, you know, holistically, yes, we're multi-cloud, not, maybe not necessarily on, I don't necessarily love the phrase where people say like, well it happened by accident. I think it happened on purpose, but we got to multi-cloud, not in the way that maybe that vendors, you know, perceived, you know, kind of laid out a map for. So it was, it was, well you will lay out this sort of Supercloud framework. We didn't call it that back then, we just called it sort of multi-cloud. Maybe it was Kubernetes or maybe it was whatever. And different groups, because central IT kind of got disbanded or got fragmented. It turned into, go pick the best cloud for your application, for what you need to do for the business. And then, you know, multiple years later it was like, "Oh, hold on, I've got 20% in Google and 50% in AWS and I've got 30% in Azure. And, you know, it's, yeah, it's been evolution. I don't know that it's, I don't know if it's a mistake. I think it's now groups trying to figure out like, should I make sense of it? You know, should I try and standardize and I backwards standardize some stuff? I think that's going to be a hard thing for, for companies to do. 'cause I think they feel okay with where the applications are. They just happen to be in multiple clouds. >> I want to run something by you, and you guys, you and Aaron have talked about this. You know, still depending on who, which keynote you listen to, small percentage of the workloads are actually in cloud. And when you were with us at Wikibon, I think we called it true private cloud, and we looked at things like Nutanix and there were a lot of other examples of companies that were trying to replicate the hyperscale experience on Prem. >> Yeah. >> And, we would evaluate that, you know, beyond virtualization, and so we sort of defined that and, but I think what's, maybe what's more interesting than Supercloud across clouds is if you include that, that on Prem estate, because that's where most of the work is being done, that's where a lot of the proprietary tools have been built, a lot of data, a lot of software. So maybe there's this concept of sending that true private cloud to true hybrid cloud. So I actually think hybrid cloud in some cases is the more interesting use case for so-called Supercloud. What are your thoughts on that? >> Yeah, I think there's a couple aspects too. I think, you know, if we were to go back five or six years even, maybe even a little further and look at like what a data center looked like, even if it was just, "Hey we're a data center that runs primarily on VMware. We use some of their automation". Versus what you can, even what you can do in your data center today. The, you know, the games that people have seen through new types of automation through Kubernetes, through get ops, and a number of these things, like they've gotten significantly further along in terms of I can provision stuff really well, I can do multi-tenancy, I can do self-service. Is it, you know, is it still hard? Yeah. Because those things are hard to do, but there's been significant progress there. I don't, you know, I still look for kind of that, that killer application, that sort of, you know, lighthouse use case of, hybrid applications, you know, between data center and between cloud. I think, you know, we see some stuff where, you know, backup is a part of it. So you use the cloud for storage, maybe you use the cloud for certain kinds of resiliency, especially on maybe front end load balancing and stuff. But I think, you know, I think what we get into is, this being hung up on hybrid cloud or multi-cloud as a term and go like, "Look, what are you trying to measure? Are you trying to measure, you know, efficiency of of of IT usage? Are you trying to measure how quickly can I give these business, you know, these application teams that are part of a line of business resources that they need?" I think if we start measuring that way, we would look at, you know, you'd go, "Wow, it used to be weeks and months. Now we got rid of these boards that have to review everything every time I want to do a change management type of thing." We've seen a lot more self-service. I think those are the things we want to measure on. And then to your point of, you know, where does, where do these Supercloud applications fit in? I think there are a bunch of instances where you go, "Look, I have a, you know, global application, I have a thing that has to span multiple regions." That's where the Supercloud concept really comes into play. We used to do it in the data center, right? We'd had all sorts of technologies to help with that, I think you can now start to do it in the cloud. >> You know, one of the other things, trying to understand, your thoughts on this, do you think that you, you again have talked about this, like I'm with you. It's like, how is it that Google's losing, you know, 3 billion dollars a year, whatever. I mean, because when you go back and look at Amazon, when they were at that level of revenue where Google is today, they were making money, you know, and they were actually growing faster, by the way. So it's kind of interesting what's happened with Google. But, the reason I bring that up is, trying to understand if you think the hyperscalers will ever be motivated to create standards across clouds, and that may be a play for Google. I mean, obviously with Kubernetes it was like a Hail Mary and kind of made them relevant. Where would Google be without Kubernetes? But then did it achieve the objectives? We could have that conversation some other time, but do you think the hyperscalers will actually say, "Okay, we're going to lean in and create these standards across clouds." Because customers would love that, I would think, but it would sub-optimize their competitive advantage. What are your thoughts? >> I think, you know, on the surface, I would say they, they probably aren't. I think if you asked 'em the question, they would say, "Well, you know, first and foremost, you know, we do deliver standards, so we deliver a, you know, standard SQL interface or a SQL you know, or a standard Kubernetes API or whatever. So, in that, from that perspective, you know, we're not locking you into, you know, an Amazon specific database, or a Google specific database." You, you can argue about that, but I think to a certain extent, like they've been very good about, "Hey, we're going to adopt the standards that people want." A lot of times the open source standards. I think the problem is, let's say they did come up with a standard for it. I think you still have the problem of the costs of migration and you know, the longer you've, I think their bet is basically the longer you've been in some cloud. And again, the more data you sort of compile there, the data gravity concept, there's just going to be a natural thing that says, okay, the hurdle to get over to say, "Look, we want to move this to another cloud", becomes so cost prohibitive that they don't really have to worry about, you know, oh, I'm going to get into a war of standards. And so far I think they sort of realize like that's the flywheel that the cloud creates. And you know, unless they want to get into a world where they just cut bandwidth costs, like it just kind of won't happen. You know, I think we've even seen, and you know, the one example I'll use, and I forget the name of it off the top of my head, but there's a, there's a Google service. I think it's like BigQuery external or something along those lines, that allows you to say, "Look, you can use BigQuery against like S3 buckets and against other stuff." And so I think the cloud providers have kind of figured out, I'm never going to get the application out of that other guy's cloud or you know, the other cloud. But maybe I'm going to have to figure out some interesting ways to sort of work with it. And, you know, it's a little bit, it's a little janky, but that might be, you know, a moderate step that sort of gets customers where they want to be. >> Yeah. Or you know, it'd be interesting if you ever see AWS for example, running its database in other clouds, you started, even Oracle is doing that with, with with Azure, which is a form of Supercloud. My last question for you is, I want to get you thinking about sort of how the future plays out. You know, think about some of the companies that we've put forth this Supercloud, and by the way, this has been a criticism of the concept. Charles Fitzer, "Everything is Supercloud!" Which if true would defeat the purpose of course. >> Right. >> And so right with the community effort, we really tried to put some guardrails down on the essential characteristics, the deployment models, you know, so for example, running across multiple clouds with a purpose build pass, creating a common experience, metadata intelligence that solves a specific problem. I mean, the example I often use is Snowflake's governed data sharing. But yeah, Snowflake, Databricks, CloudFlare, Cohesity, you know, I just mentioned Oracle and Azure, these and others, they certainly claim to have that common experience across clouds. But my question is, again, I come back to, do customers need this capability? You know, is Mono Cloud the way to solve that problem? What's your, what are your thoughts on how this plays out in the future of, I guess, PAs, apps and cloud? >> Yeah, I think a couple of things. So, from a technology perspective, I think, you know, the companies you name, the services you've named, have sort of proven that the concept is viable and it's viable at a reasonable size, right? These aren't completely niche businesses, right? They're multi-billion dollar businesses. So, I think there's a subset of applications that, you know, maybe a a bigger than a niche set of applications that are going to use these types of things. A lot of what you talked about is very data centric, and that's, that's fine. That's that layer is, figuring that out. I think we'll see messaging types of services, so like Derek Hallison's, Caya Company runs a, sort of a Supercloud for messaging applications. So I think there'll be places where it makes a ton of sense. I think, the thing that I'm not sure about, and because again, we've been now 10 plus years of sort of super low, you know, interest rates in terms of being able to do things, is a lot of these things come out of research that have been done previously. Then they get turned into maybe somewhat of an open source project, and then they can become something. You know, will we see as much investment into the next Snowflake if, you know, the interest rates are three or four times that they used to be, do we, do we see VCs doing it? So that's the part that worries me a little bit, is I think we've seen what's possible. I think, you know, we've seen companies like what those services are. I think I read yesterday Snowflake was saying like, their biggest customers are growing at 30, like 50 or 60%. Like the, value they get out of it is becoming exponential. And it's just a matter of like, will the economics allow the next big thing to happen? Because some of these things are pretty, pretty costly, you know, expensive to get started. So I'm bullish on the idea. I don't know that it becomes, I think it's okay that it's still sort of, you know, niche plus, plus in terms of the size of it. Because, you know, if we think about all of IT it's still, you know, even microservices is a small part of bigger things. But I'm still really bullish on the idea. I like that it's been proven. I'm a little wary, like a lot of people have the economics of, you know, what might slow things down a little bit. But yeah, I, think the future is going to involve Supercloud somewhere, whatever people end up calling it. And you and I discussed that. (laughs) But I don't, I don't think it goes away. I don't think it's, I don't think it's a fad. I think it is something that people see tremendous value and it's just, it's got to be, you know, for what you're trying to do, your application specific thing. >> You're making a great point on the funding of innovation and we're entering a new era of public policy as well. R and D tax credit is now is shifting. >> Yeah. >> You know, you're going to have to capitalize that over five years now. And that's something that goes back to the 1950s and many people would argue that's at least in part what has helped the United States be so, you know, competitive in tech. But Brian, always great to talk to you. Thanks so much for participating in the program. Great to see you. >> Thanks Dave, appreciate it. Good luck with the rest of the show. >> Thank you. All right, this is Dave Vellante for John Furrier, the entire Cube community. Stay tuned for more content from Supercloud2.
SUMMARY :
of the popular Cloudcast program. Yeah, great to be with you, Dave. So, you know, has the cloud I think to a certain extent, you know, when you talk to cloud, you know, tie it into you know, is multi-cloud And we, you know, So, you know, I want, I want And then, you know, multiple you and Aaron have talked about this. And, we would evaluate that, you know, But I think, you know, I money, you know, and I think, you know, on the is, I want to get you Cohesity, you know, I just of sort of super low, you know, on the funding of innovation the United States be so, you Good luck with the rest of the show. the entire Cube community.
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Dev Ittycheria, MongoDB | AWS re:Invent 2022
>>Hello and run. Welcome back to the Cube's live coverage here. Day three of Cube's coverage, two sets, wall to wall coverage. Third set upstairs in the Executive Briefing Center. I'm John Furry, host of the Cube with Dave Alon. Two other hosts here. Lot of action. Dave. The cheer here is the CEO of MongoDB, exclusive post on Silicon Angle for your prior to the event. Thanks for doing that. Great to see >>You. Likewise. Nice to see you >>Coming on. See you David. So it's great to catch up. Prior to the event for that exclusive story on ecosystem, your perspective that resonated with a lot of the people. The traffic on that post and comments have been off the charts. I think we're seeing a ecosystem kind of surge and not change over, but like a an and ISV and new platform. So I really appreciate your perspective as a platform ISV for aws. What's it like? What's this event like? What's your learnings? What's your takeaway from your customers here this year? What's the most important story going on? >>First of all, I think being here is important for us because we have so many customers and partners here. In fact, if you look at the customers that Amazon themselves announced about two thirds of those customers or MongoDB customers. So we have a huge overlap in customers here. So just connecting with customers and partners has been important. Obviously a lot of them are thinking about their plans going to next year. So we're kind of meeting with them to think about what their priorities are and how we can help. And also we're sharing a little bit of our product roadmap in terms of where we're going and helping them think through like how they can best use Mongadi B as they think about their data strategy, you know, going to next year. So it's been a very productive end. We have a lot of people here, a lot of sales people, a lot of product people, and there's tons of customers here. So we can get a lot accomplished in a few days. >>Dave and I always talk on the cube. Well, Dave always goes to the TAM expansion question. Expanding your total stressful market, the market is changing and you guys have a great position growing positioned. How do you look at the total addressable market for Mongo changing? Where's the growth gonna come from? How do you see your role in the market and how does that impact your current business model? >>Yeah, our whole goal is to really enable developers to think about Mongo, to be first when they're building modern applications. So what we've done is first built a fir, a first class transactional platform and now we've kind expanding the platform to do things like search and analytics, right? And so we are really offering a broad set of capabilities. Now our primary focus is the developer and helping developers build these amazing applications and giving them tools to really do so in a very quick way. So if you think about customers like Intuit, customers like Canva, customers like, you know, Verizon, at and t, you know, who are just using us to really transform their business. It's either to build new applications quickly to do things at a certain level of performance of scale they've never done before. And so really enabling them to do so much more in building these next generation applications that they can build anywhere else. >>So I was listening to McDermott, bill McDermott this morning. Yeah. And you listen to Bill, you just wanna buy from the guy, right? He's amazing. But he was basically saying, look, companies like he was talking about ServiceNow that could help organizations digitally transform, et cetera, but make money or save money or in a good position. And I said, right, Mongo's definitely one of those companies. What are those conversations like here? I know you've been meeting with customers, it's a different environment right now. There's a lot of uncertainty. I, I was talking to one of your customers said, yeah, I'm up for renewal. I love Mongo. I'm gonna see if they can stage my payments a little bit. You know, things like that. Are those conversations? Yeah, you know, similar to what >>You having, we clearly customers are getting a little bit more prudent, but we haven't seen any kind of like slow down terms of deal cycles or, or elongated sales cycles. I mean, obviously different customers in different sectors are going through different issues. What we are seeing customers think about is like how can I, you know, either drive more efficiency in my business like and big part of that is modernization of my existing legacy tech stack. How can maybe consolidate to a fewer set of vendors? I think they like our broad platform story. You know, rather than using three or four different databases, they can use MongoDB to do everything. So that that resonates with customers and the fact that they can move fast, right? Developer productivity is a proxy for innovation. And so being able to move fast to either seize new opportunities or respond to new threats is really, you know, top of mind for still C level executive. >>So can your software, you're right, consolidation is the number one way in which people are save money. Can your software be deflationary? I mean, I mean that in a good way. So >>I was just meeting with a customer who was thinking about Mongo for their transactional platform, elastic for the search platform and like a graph database for a special use case. And, and we said you can do all that on MongoDB. And he is like, oh my goodness, I can consolidate everything. Have one elegant developer interface. I can keep all the data in one place. I can easily access that data. And that makes so much more sense than having to basically use a bunch of peace parts. And so that's, that's what we're seeing more and more interest from customers about. >>So one of the things I want to get your reaction to is, I was saying on the cube, now you can disagree with me if you want, but at, in the cloud native world at Cuban and Kubernetes was going through its hype cycle. The conversation went to it's getting boring. And that's good cause they want it to be boring. They don't want people to talk about the run time. They want it to be working. Working is boring. That's invisible. It's good, it's sticky, it's done. As you guys have such a great sticky business model, you got a great install base. Mongo works, people are happy, they like the product. So it's kind of working, I won't wanna say boring cuz that's, it's irrelevant. What's the exciting things that Mongo's bringing on top of the existing base of product that is gonna really get your clients and prospects enthused about the innovation from Mongo? What's what cuz it's, it's almost like electricity in a way. You guys are very utility in, in the way you do, but it's growing. But is there an exciting element coming that you see that they should pay attention to? What's, what's your >>Vision that, right, so if you look back over the last 10, 15 years, there's been big two big platform shifts, mobile and cloud. I think the next big platform shift is from what I call dumb apps to smart apps. So building more intelligence into applications. And what that means is automating human decision making and embedding that into applications. So we believe that to be a fundamentally a developer problem to solve, yes, you need data scientist to build the machine learning algorithms to train the models. Yeah. But ultimately you can't really deploy, deployed at scale unless you give developers the tools to build those smart applications that what we focused on. And a big part of that is what we call application driven analytics where people or can, can embed that intelligence into applications so that they can instead rather having humans involved, they can make decisions faster, drive to businesses more quickly, you know, shorten it's short and time to market, et cetera. >>And so your strategy to implement those smart apps is to keep targeting the developer Yes. And build on that >>Base. Correct. Exactly. So we wanna essentially democratize the ability for any customer to use our tools to build a smart applications where they don't have the resources of a Google or you know, a large tech company. And that's essentially resonating with our customer base. >>We, we were talking about this earlier after Swami's keynote, is most companies struggle to put data at the core of their business. And I don't mean centralizing it all in a single place as data's everywhere, but, but really organizing their company and democratizing data so people can make data decisions. So I think what you're saying, essentially Atlas is the platform that you're gonna inject intelligence into and allow developers to then build applications that are, you know, intelligent, smart with ai, machine intelligence, et cetera. And that's how the ones that don't have the resources of a Google or an Amazon become correct the, that kind of AI company if >>You, and that's, that's the whole purpose of a developer data platform is to enable them to have the tools, you know, to have very sophisticated analytics, to have the ability to do very sophisticated indexes, optimized for analytics, the ability to use data lakes for very efficient storage and retrieval of data to leverage, you know, edge devices to be able to capture and synchronize data. These are all critical elements to build these next generation applications. And you have to do that, but you don't want to stitch together a thousand primitives. You want to have a platform to do that. And that's where we really focus. >>You know, Dave, Dave and I, three, two days, Dave and I, Dave Ante and I have been talking a lot about developer productivity. And one observation that's now validated is that developers are setting the pace for innovation. Correct? And if you look at the how they, the language that they speak, it's not the same language as security departments, right? They speak almost like different languages, developer and security, and then you got data language. But the developers are making choices of self-service. They can accelerate, they're driving the behavior behavior into the organizations. And this is one of the things I wrote about on Friday last week was the organizational changes are changing cuz the developers set the pace. You can't force tooling down their throat. They're gonna go with what's easy, what's workable. If you believe that to be true, then all the security's gonna be in the developer pipeline. All the innovations we've driven off that high velocity developer site, we're seeing success of security being embedded there with the developers. What are you gonna bring up to that developer layer that's going to help with security, help with maybe even new things, >>Right? So, you know, it's, it's almost a cliche to say now software is in the world, right? Because every company's value props is driven by, it's either enabled to find or created through software. What that really means is that developers are eating all the work, right? And you're seeing, you saw in DevOps, right? Where developers basically enro encroach into the ops world and made infrastructure a programmable interface. You see developers, to your point, encroaching in security, embedding more and more security features into their applications. We believe the same thing's gonna happen with data scientists and business analysts where developers are gonna embed that functionality that was done by different domains in the Alex world and embed that capability into apps themselves. So these applications are just naturally smarter. So you don't need someone to look at a dashboard and say, aha, there's some insight here now I need to go make a decision. The application will do that for you and actually make that decision for you so you can move that much more quickly to run your business either more efficiently or to drive more, you know, revenue. >>Well the interesting thing about your business is cuz you know, you got a lot of transactional activity going on and the data, the way I would say what you just described is the data stack and the application stacks are coming together, right? And you're in a really good position, I think to really affect that. You think about we've, we've operationalized so many systems, we really haven't operationalized our data systems. And, and particularly as you guys get more into analytics, it becomes an interesting, you know, roadmap for Mongo and your customers. How do you see that? >>Yeah, so I wanna be clear, we're not trying to be a data warehouse, I get it. We're not trying to be like, you know, go compete. In fact, we have nice partnership with data bricks and so forth. What we are really trying to do is enable developers to instrument and build these applications that embed analytics. Like a good analogy I'd use is like Google Maps. You think about how sophisticated Google Maps has, and I use that because everyone has used Google Maps. Yeah. Like in the old, I was old enough to print out the directions, map quest exactly, put it on my lap and drive and look down. Now have this device that tells me, you know, if there's a traffic, if there's an accident, if there's something you know, going will reroute me automatically. And what that app is doing is embedding real time data into, into its decision making and making the decision for you so that you don't have to think about which road to take. Right? You, you're gonna see that happen across almost every application over the next X number of years where these applications are gonna become so much smarter and make these decisions for you. So you can just move so much more quickly. >>Yeah. Talk about the company, what status of the company, your growth plans. Obviously you're seeing a lot of news and Salesforce co CEO just resigned, layoffs at cnn, layoffs at DoorDash. You know, tech unfortunately is not impacted, thank God. I'm not that too bad. Certainly in cloud's not impacted it is impacting some of the buying behavior. We talked about that. What's going on with the company head count? What's your goals? How's the team doing? What are your priorities? >>Right? So we we're going after a big, big opportunity. You know, we recognize, obviously the market's a little choppy right now, but our long term, we're very bullish on the opportunity. We believe that we can be the modern developer data platform to build these next generation applications in terms of costs. We're obviously being a little bit more judicious about where we're investing, but we see big, big opportunities for us. And so our overall cost base will grow next year. But obviously we also recognize that there's ways to drive more efficiency. We're at a scale now. We're a 1.2 billion business. We're gonna announce our Q3 results next week. So we'll talk a little bit more about, you know, what we're seeing in the business next week. But we, we think we're a business that's growing fast. You know, we grew, you know, over 50, 50% and so, so we're pretty fast growing business. Yeah. You see? >>Yeah, Tuesday, December 6th you guys announce Exactly. Course is a big, we always watch and love it. So, so what I'm hearing is you're not, you're not stepping on the brakes, you're still accelerating growth, but not at all costs. >>Correct. The term we're using is profitable growth. We wanna, you know, you know, drive the business in a way that we think continues to seize the opportunity. But we also, we always exercise discipline. You know, I, I'm old enough where I had to deal with 2000 and 2008, so, you know, seen the movie before, I'm not 28 and have not seen these markets. And so obviously some are, you know, emerging leaders have not seen these kinds of markets before. So we're kind of helping them think about how to continue to be disciplined. And >>I like that reference to two thousand.com bubble and the financial crisis of 2008. I mentioned this to you when we chat, I'd love to get your thoughts. Now looking back for reinvent, Amazon wasn't a force in, in 2008. They weren't really that big debt yet. Know impact agility, wasn't it? They didn't hit that, they didn't hit that cruising altitude of the value pro cloud agility, time of value moving fast. Now they are. So this is the first time that they're a part of the economic equation. You're on, you're on in the middle of it with Amazon. They could be a catalyst to recover faster if plan properly. What's your CEO take on just that general and other CEOs might be watching and saying, Hey, you know, if I play this right, I could leverage the cloud. You know, Adams is leading into the cloud during a recession. Okay, I get that. But specifically there might be a tactic. What's your view on >>That? I mean, what, what we're seeing the, the hyperscalers do is really continue to kind of compete at the raw infrastructure level on storage, on compute, on network performance, on security to provide the, the kind of the building blocks for companies like Monga Beach really build on. So we're leveraging that price performance curve that they're pushing. You know, they obviously talk about Graviton three, they're talking about their training model chip sets and their inference model chip sets and their security chip sets. Which is great for us because we can leverage those capabilities to build upon that. And I think, you know, if you had asked me, you know, in 2008, would we be talking about chip sets in 2022? I'd probably say, oh, we're way beyond that. But what it really speaks to is those things are still so profoundly important. And I think that's where you can see Amazon and Google and Microsoft compete to provide the best underlying infrastructure where companies like mongadi we can build upon and we can help customers leverage that to really build the next generation. >>I'm not saying it's 2008 all over again, but we have data from 2008 that was the first major tailwind for the cloud. Yeah. When the CFO said we're going from CapEx to opex. So we saw that. Now it's a lot different now it's a lot more mature >>I think. I think there's a fine tuning trend going on where people are right sizing, fine tuning, whatever you wanna call it. But a craft is coming. A trade craft of cloud management, cloud optimization, managing the cost structures, tuning, it's a crafting, it's more of a craft. It's kind of seems like we're >>In that era, I call it cost optimization, that people are looking to say like, I know I'm gonna invest but I wanna be rational and more thoughtful about where I invest and why and with whom I invest with. Versus just like, you know, just, you know, everyone getting a 30% increase in their opex budgets every year. I don't think that's gonna happen. And so, and that's where we feel like it's gonna be an opportunity for us. We've kind of hit scap velocity. We've got the developer mind share. We have 37,000 customers of all shapes and sizes across the world. And that customer crown's only growing. So we feel like we're a place where people are gonna say, I wanna standardize among the >>Db. Yeah. And so let's get a great quote in his keynote, he said, if you wanna save money, the place to do it is in the cloud. >>You tighten the belt, which belt you tightening? The marketplace belt, the wire belt. We had a whole session on that. Tighten your belt thing. David Chair, CEO of a billion dollar company, MongoDB, continue to grow and grow and continue to innovate. Thanks for coming on the cube and thanks for participating in our stories. >>Thanks for having me. Great to >>Be here. Thank. Okay, I, Dave ante live on the show floor. We'll be right back with our final interview of the day after this short break, day three coming to close. Stay with us. We'll be right back.
SUMMARY :
host of the Cube with Dave Alon. Nice to see you So it's great to catch up. can best use Mongadi B as they think about their data strategy, you know, going to next year. How do you see your role in the market and how does that impact your current customers like Canva, customers like, you know, Verizon, at and t, you know, And you listen to Bill, you just wanna buy from the guy, able to move fast to either seize new opportunities or respond to new threats is really, you know, So can your software, you're right, consolidation is the number one way in which people are save money. And, and we said you can do all that on MongoDB. So one of the things I want to get your reaction to is, I was saying on the cube, now you can disagree with me if you want, they can make decisions faster, drive to businesses more quickly, you know, And so your strategy to implement those smart apps is to keep targeting the developer Yes. of a Google or you know, a large tech company. And that's how the ones that don't have the resources of a Google or an Amazon data to leverage, you know, edge devices to be able to capture and synchronize data. And if you look at the how they, the language that they speak, it's not the same language as security So you don't need someone to look at a dashboard and say, aha, there's some insight here now I need to go make a the data, the way I would say what you just described is the data stack and the application stacks are coming together, into its decision making and making the decision for you so that you don't have to think about which road to take. Certainly in cloud's not impacted it is impacting some of the buying behavior. You know, we grew, you know, over 50, Yeah, Tuesday, December 6th you guys announce Exactly. And so obviously some are, you know, emerging leaders have not seen these kinds of markets before. I mentioned this to you when we chat, I'd love to get your thoughts. And I think, you know, if you had asked me, you know, in 2008, would we be talking about chip sets in When the CFO said we're going from CapEx to opex. fine tuning, whatever you wanna call it. Versus just like, you know, just, you know, everyone getting a 30% increase in their You tighten the belt, which belt you tightening? Great to of the day after this short break, day three coming to close.
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Dev Ittycheria, MongoDB | Cube Conversation: Partner Exclusive
>>Hi, I'm John Ferry with the Cube. We're here for a special exclusive conversation with David Geria, the CEO of Mongo MongoDB. Well established leading platform. It's been around for, I mean, decades. So continues to become the platform of choice for high performance data. This modern data stack that's emerging, a big part of the story here at a reinvent 2022 on top of an already performing a cloud with, you know, chips and silicon specialized instances, the world's gonna be getting faster, smaller, higher performance, lower cost specialized. Dave, thanks for taking the time with me today, >>John. It's great to be here. Thank you for having me. >>Do you see yourself as a ISV or you just go with that, because that's kind of a nomenclature >>When, when I think of the term isv, I think of the notion of someone building an end solution for customer to get something done. Or what we're building is essentially a developer data platform and we have thousands of ISVs who build software applications on our platform. So how could we be an isv? Because by definition I, you know, we enable people to do so many different things and you know, they can be the, you know, the largest companies of the world trying to transform their business or startups who are trying to disrupt either existing industries or create new ones. And so that's, and, and that's how our customers view MongoDB and, and the whole Atlas platform basically enables them to do some amazing things. The reason for that is, you know, you know, we believe that what we are enabling developers to do is be able to reduce the friction and the work required to build modern applications through the document model, which is really intuitive to the way developers think and code through the distributed nature of platforms. >>So, you know, things like charting no other company on the planet offers the capabilities we do to enable people to build the most highly performant and scalable applications. And also what we also do is enable people to, you know, run different types of workloads on our platform. So we have obviously transactional, we have search, we have time series, we enable people to do things like sophisticated device synchronization from Edge to the back end. We do graph, we do real time analytics. So being able to consolidate all that with developers on one elegant unified platform really makes, you know, it attractive for developers to build on long >>Db. You know, you guys are a feature partner of aws and I would speculate, I don't know if you can comment on this, but I would imagine that you probably produce a lot of revenue for Amazon because you really can't turn off EC two when you do a database work. So, you know, you kind of crank it all the time. You guys are a top partner. How long have you guys been a partner with aws? What's the relationship? >>The relationship's been strong, actually, Amazon spoke at one of our first user conferences in 2013. And since then we've been working together. We've been at reinvent since essentially 2015. And we've been a premier partner, an Emerald sponsor for the last Nu you know, I think four or five years. And so we're very committed to the relationship and I think there's some things that we have a lot, we have a lot of things in common. We care a lot about customers and for us, our customers, our developers, we care a lot about removing friction from their day to day work to move, be able to move fast and be able to, in order to seize new opportunities and respond to new threats. And so consequently, I think the partnership, obviously by nature of our, our common objectives has really come together. >>Talk about the journey of Mongo. I mean, you look back at the history, I, you go back the old lamp stack days, right? So you know, the day developer traction is just really kind of stuck at the none. I mean, it's, it's really well known. And I remember over the conversations, Dave Mongo doesn't scale. I mean, every year we heard something along those lines cuz it just kept scaling. I heard the same thing with AWS back in 2013 timeframe. You, oh, it's just, it's really not for a real prime time. It's, it's for hobbyists, not so much builders, maybe startup cloud, but that developer traction is translated. Can you take us through the journey of Mongo where it is now and, and kinda look back and, and, and take us through what's the state of the art now, >>Right? So just for those of you who, who, those, you know, those in your audience who don't know too much about Mon Be I'll just, you know, start with the background. The company was astounded by developers. It was basically the CTO and some key developers from Double Click who really saw the challenges and the limitations of the relational database architecture because they're trying to serve billions of ads per day and they constantly need to work on the constraints and relational database. And so they essentially decided, why don't we just build a database that we'd want to use? And that was a catalyst to starting MongoDB. The first thing they focused on was, rather than having a tabler data structure, they focused on a document data structure. Why documents? Because there's much more natural and intuitive to work with data and documents in terms of you can set parent child relationships and how you just think about the relationship with data is much more natural in a document than trying to connect data in a, you know, in hundreds of different tables. >>And so that enabled developers to just move so much faster. The second thing they focused on was building a truly distributed architecture, not kind of some adjunct, you know, you know, architecture that maybe made the existing architecture a little bit more scalable. They really took from the ground up a truly distributed architecture. So where you can do native replication, you can do charting and you can do it on a global basis. And so that was the, the other profound, you know, thing that they did. And then since then, what we've also done is, you know, the document model is truly a super set of other models. So we enabled other capabilities like search you can do joins, so you can do very transaction intensive use case among be where fully asset compliant. So you have the highest forms of data guarantees you can do very sophisticated things like time series, you can do device synchronization, you can do real time analytics because we can carve off read only nodes to be able to read and query data in real time rather than have to offload that data into a data warehouse. >>And so that enables developers to just build a wide variety of, of application longing to be, and they get one unified developer interface. It's highly elegant and seamless. And so essentially the cost and tax of matching multiple point tools goes away when, when I think of the term isv, I think of the notion of someone building an end solution for a customer to get something done. Or what we're building is essentially a developer data platform and we have thousands of ISVs who build software applications on our platform. So how could we be an isv? Because by definition I, you know, we enable people to do so many different things and you know, they can be the, you know, the largest companies in the world trying to transform their business or startups or trying to disrupt either existing industries or create new ones. And so that's, and and that's how our customers view MongoDB and, and the whole Atlas platform basically enables them to do some amazing things. >>Yeah, we're seeing a lot of activity on the Atlas. Do you see yourself as a ISV or you just go with that because that's kind of a nomenclature? >>No, we don't view ourselves as ISV at all. We view ourselves as a developer data platform. And the reason for that is, you know, you know, we believe that what we are enabling developers to do is be able to reduce the friction and the work required to build modern applications through the document model, which is really intuitive to the way developers think and code through the distributed nature of platforms. So, you know, things like sharding, no other company on the planet offers the capabilities we do to enable people to build the most highly performant and scalable applications. And also what we also do is enable people to, you know, run different types of workflows on our platform. So we have obviously transactional, we have search, we have time series, we enable people to do things like sophisticated device synchronization from Edge to the back end. We do graph, we do real time analytics. So being able to consolidate all that with developers on one elegant unified platform really makes, you know, it attractive for developers to build on long ndb. >>You know, the cloud adoption really is putting a lot of pressure on these systems and you're seeing companies in the ecosystem and AWS stepping up, you guys are doing great job, but we're seeing a lot more acceleration around it, on staying on premise for certain use cases. Yet you got the cloud as well growing for workloads and, and you get this hybrid steady state as an operational mode. I call that 10 of the classic cloud adoption track record. You guys are an example of multiple iterations in cloud. You're doing a lot more, we're starting to see this tipping point with others and customers coming kind of on that same pattern. Building platforms on top of aws on top of the primitives, more horsepower, higher level services, industry specific capabilities with data. I mean this is a new kind of cloud, kind of a next generation, you knows next gen you got the classic high performance infrastructure, it's getting better and better, but now you've got this new application platform, you know, reminds me of the old asp, you know, if you will. I mean, so are you seeing customers doing things differently? Can you share your, your reaction to this role of, you know, this new kind of SaaS platform that just isn't an application, it's, it's more, it's deeper than that. What's going on here? We call it super cloud, but >>Like what? Yeah, so essentially what what, you know, a lot of our customers doing, and by the way we have over 37,000 customers of all shapes and sizes from the largest companies in the world to cutting edge startups who are building applications among B, why do they choose MongoDB? Because essentially it's the, you know, the fastest way to innovate and the reason it's the fastest way to innovate is because they can work with data so much easier than working with data on other types of architecture. So the document model is profoundly a breakthrough way to work with data to make it very, very easy. So customers are essentially building these modern applications, you know, applications built on microservices, event driven architectures, you know, addressing sophisticated use cases like time series to, and then ultimately now they're getting into machine learning. We have a bunch of companies building machine learning applications on top of MongoDB. And the reason they're doing that is because one, they get the benefits of being able to, you know, build and work with, with data so much easier than any other platform. And it's highly scale and performant in a way that no other platform is. So literally they can run their, you know, workloads both locally and one, you know, autonomous zone or they can basically be or available zone or they could be basically, you know, anywhere in the world. And we also offer multicloud capabilities, which I can get into later. >>Let's talk about the performance side. I know I was speaking with some Amazon folks every year it's the same story. They're really working on the physics, they're getting the chips, they wanna squeeze as much energy out of that. I've never met a developer that said they wanna run their workload on a slower platform or slower hardware. We know said no developer, right? No one wants to do that. >>Correct. >>So you guys have a lot of experience tuning in with Graviton instances, we're seeing a lot more AWS EC two instances, we're seeing a lot more kind of integrated end to end stories. Data is now security, it's tied into data stacks or data modern kind of data hybrid stack. A lot going on around the hardware performance specialization, the role of data, kind of a modern data stack emerging. What, what's your thoughts on the that that Yeah, >>I, I think if you had asked me, you know, when the cloud started going vogue, like you know, the, you know, the, the later part of the last decade and told me, you know, sitting here 12, 15 years later, would you know, would we be talking about, you know, chip processing speeds? I'd probably thought, nah, we would've moved on by then. But what's really clear is that customers, to your point, customers care about performance, they care about price performance, right? So AWS's investments in Graviton, we have actually deployed a significant portion of our at fleet on Amazon now runs on Graviton. You know, they've built other chip sets like train and, and inferential for like, you know, training models and running inferences. They're doing things like Nitro. And so what that really speaks to is that the cloud providers are focusing on the price performance of their, as you call it, their primitives and their infrastructure and the infrastructure layer that are still very, very important. >>And, and you know, if you look at their revenue, about 60 to 70% of the revenue comes from that pure infrastructure. So to your point, they can't offer a second class solution and still win. So given that now they're seeing a lot of competition from Azure, Azure's building their own chip sets, Google's already obviously doing that and and building specialized chip sets for machine learning. You're seeing these cloud providers compete. So they have to really compete to make their platform the most performant, the most price competitive in the marketplace. Which gives us a great platform to build on to enable developers to build these incredibly highly performant applications that customers are now demand. >>I think that's a really great point. I mean, you know, it's so funny Dave, because you know, I remember those, we don't talk speeds and feeds anymore. We're not talking about boxes. I mean that's old kind of school thinking because it was a data center mentality, speeds and feeds and that was super important. But we're kind of coming back to that in the cloud now in distributed architecture, as you put your platforms out there for developers, you have to run fast. You gotta, you can't give the developer subpar or any kind of performance that's, they'll, they'll go somewhere else. I mean that's the reality of what developers, no one, again, no one says I wanna go on the slower platform unless it's some sort of policy based on price or some sort of thing. But, but for the most part it's gotta run fast. So you got the tail of two clouds going on here, you got Amazon classic ias, keep making it faster under the hood. >>And then you got the new abstraction layers of the higher level services. That's where you guys are bridging this new, new generational shift where it's like, hey, you know what? I can go, I can run a headless application, I can run a SAS app that's refactored with data. So you've seen a lot more innovation with developers, you know, running stuff in, in the C I C D pipeline that was once it, and you're seeing security and data operations kind of emerging as a structural change of how companies are, are are transforming on the business side. What's your reaction to that business transformation and the role of the developer? >>Right, so I mean I have to obviously give amazing kudos to the, you know, to AWS and the Amazon team for what they've built. Obviously they're the ones who kind of created the cloud industry and they continue to push the innovation in the space. I mean today they have over 300 services and you know, obviously, you know, no star today is building anything not on the cloud because they have so many building blocks to start with. But what we though have found from our talking to our customers is that in some ways there is still, you know, the onus is on the customer to figure out which building block to use to be able to stitch together the applications and solutions they wanna build. And what we have done is taken essentially an opinionated point of view and said we will enable you to do that. >>You know, using one data model. You know, Amazon today offers I think 17 or 18 different types of databases. We don't think like, you know, having a tool for every job makes sense because over time the tax and cost of learning, managing and supporting those different applications just don't make a lot of sense or just become cost prohibitive. And so we think offering one data model, one, you know, elegant user experience, you know, one way to address the broadest set of of use cases is that we think is a better way. But clearly customers have choice. They can use Amazon's primitives and those second layer services as you as you described, or they can use us. Unfortunately we've seen a lot of customers come to us with our approach and so does Amazon. And I have to give obviously again kudos and Amazon is very customer obsessed and so we have a great relationship with them, both technically in terms of the product integrations we do as well as working with 'em in the field, you know, on joint customer opportunities. >>Speaking of, while you mentioned that, I wanna just ask you, how is that marketplace relationship going with aws? Some of the partners are really seeing great economic and joint selling or them selling your, your stuff. So there's a real revenue pop there in that religion. Can you comment on that? >>So we had been working the partner in the marketplace for many years now, more from a field point of view where customers could leverage their existing commitments to AWS and leverage essentially, you know, using Atlas and applying in an atlas towards their commits. There was also some sales incentives for people in the field to basically work together so that, you know, everyone won should we collectively win a customer? What we recently announced is as pay as you Go initiative, where literally a customer on the Amazon marketplace can basically turn up, you know, an Alice instance with no commitment. So it's so easy. So we're just pushing the envelope to just reduce the friction for people to use Atlas on aws. And it's working really very well. The uptake has been been very strong and and we feel like we're just getting started because we're so excited about the results we're >>Seeing. You know, one of the things that's kind of not core in the keynote theme, but I think it's underlying message is clear in the industry, is the developer productivity. You said making things easy is a big deal, self-service, getting in and trying, these are what developer friendly tools are like and platform. So I have to ask you, cuz this comes up a lot in our kind of business conversation, is, is if you take digital transformation concept to its completion, assuming now you know, as a thought exercise, you completely transform a company with technology that's, that is the business transformation outcome. Take it to completion. What does that look like? I mean, if you go there you'd say, okay, the company is the app, the company is the data, it's not a department serving the business, it's the business. And so I think this is kind of what we're seeing as the next big mountain climb, which is companies that do transform there, they are technology companies, they're not a department like it. So I think a lot of companies are kind of saying, wait a minute, why would we have a department? It should be the company. What's your your your view on this because this >>Yeah, so I I've had the for good fortune of being able to talk to thousand customers all over the world. And you know, one thing John, they never tell me, they never tell me that they're innovating too quickly. In fact, they always tell me the reverse. They tell me all the obstacles and impediments they have to be able to be able to be able to move fast. So one of the reasons they gravitate to MongoDB is just the speed that they wish they can build applications to, to your point, developer productivity. And by definition, developer productivity is a proxy for innovation. The faster you can make your developers, you know, move, the faster they can push out code, the faster they can iterate and build new solutions or add more capabilities on the existing applications, the faster you can innovate either to, again, seize new opportunities or to respond to new threats in your business. >>And so that resonates with every C level executive. And to your point, the developers not some side hustle that they kind of think about once in a while. It's core to the business. So developers have amassed enormous amount of power and influence. You know, their, their, their engineering teams are front and center in terms of how they think about building capabilities and and building their business. And that's also obviously enabled, you know, to your point, every software company, every company's not becoming a software company because it all starts with softwares, software enables, defines or creates almost every company's value proposition. >>You know, it makes me smile because I love operating systems as one of my hobbies in college was, you know, systems programming and I remember those network kind of like the operating systems, the cloud. So, you know, everything's got specialized capabilities and that's a big theme here at Reinvent. If you look at the announcements Monday night with Peter DeSantis, you got, you got new instances, new chips. So this whole engine kind of specialized component is like an engine. You got a core and you got other subsystems. This is gonna be an integral part of how companies architect their platform or you know, Adam calls it the landing zone or whatever they wanna call it. But you gotta start seeing a new architectural thinking for companies. What's your, can you share your experience on how companies should look at this opportunity as a plethora of more goodness on the hardware? On hardware, but like chips and instances? Cause now you can mix and match. You've got, you've got, you got everything you need to kind of not roll your own but like really build foundational high performance capabilities. >>Yeah, so I I, so I think this is where I think Amazon is really enabling all companies, including, you know, companies like Mon db, you know, push the envelope and innovation. So for example, you know, the, the next big hurdle for us, I think we've seen two big platform shifts over the last 15 years of platform shifts, you know, to mobile and the platform shift to cloud. I believe the next big platform shift is going from dumb apps to smart apps, which you're building in, you know, machine learning and you know, AI and just very sophisticated automation. And when you start automating human decision making, rather than, you know, looking at a dashboard and saying, okay, I see the data now, now I have to do this. You can automate that into your applications and make your applications leveraging real time data become that much more smart. And that ultimately then becomes a developer challenge. And so we feel really good about our position in taking advantage of those next big trends and software leveraging the price performance curves that, you know, Amazon continues to push in terms of their hardware performance, networking performance, you know, you know, price, performance and storage to build those next generation of modern applications. >>Okay, so let me get this straight. You have next generation intelligent smart apps and you have AI generative solutions coming out around the corner. This is like pretty good position for Mongo to be in with data. I mean, this is what you do, you're in that exactly of the action. What's it like? I mean, you must be like trying to shake the world and wake up. The world's starting to wake up now through this. So what's, what's it like? >>Well, I mean we're really excited and bullish about the future. We think that we're well positioned because we know as to your point, you know, we have amassed amazing amount of developer mindshare. We are the most popular modern data platform out there in the world. There's developers in almost every corner of the planet using us to do something. And to your point, leveraging data and these advances in machine learning ai. And we think the more AI becomes democratized, not, you know, done by a bunch of data scientists sitting in some corner office, but essentially enabling developers to have the tools to build these very, very sophisticated, smart applications will, you know, will position as well. So that's, you know, obviously gonna be a focus for us over the, frankly, I think this is gonna be like a 10 year, 10 15 year run and we're just getting started in this whole >>Area. I think you guys are really well positioned. I think that's a great point. And Adam mentioned to me and, and Mike interviewed, he said on stage talk about it, the role of a data analyst kind of goes away. Everyone's a data analyst, right? You'll still see specialization on, on core data engineering, which is kind of like an SRE role for data. So data ops and data as code is a big deal making data applications. So again, exciting times and you guys are well positioned. If you had to bumper sticker the event this week here at Reinvent, what would you, how would you categorize this this point in time? I mean, Adam's great leader, he is gonna help educate customers how to use technology to, for business advantage and transformation. You know, Andy did a great job making technology great and innovative and setting the table, Adam's gotta bring it to the enterprises and businesses. So it's gonna be an interesting point in time we're in now. What, how would you categorize this year's reinvent, >>Right? I think the, the, the tech world is pivoting towards what I'd call rationalization or cost optimization. I think people obviously in, you know, the last 10 years have, you know, it's all about speed, speed, speed. And I think people still value speed, but they wanna do it at some sort of predictable cost model. And I think you're gonna see a lot more focus around cost and cost optimization. That's where we think having one platform is by definition of vendor consolidation way for people to cut costs so that they can basically, you know, still move fast but don't have to incur the tax of using a whole bunch of different point tools. And so we think we're well positioned. So the bumper sticker I think about is essentially, you know, do more for less with MongoDB. >>Yeah. And the developers on the front lines. Great stuff. You guys are great partner, a top partner at AWS and great reflection on, on where you guys been, but really where you are now and great opportunity. David Didier, thank you so much for spending the time and it's been great following Mongo and the continued rise of, of developers of the on the front lines really driving the business and that, and they are, I know, driving the business, so, and I think they're gonna continue Smart apps, intelligent apps, ai, generative apps are coming. I mean this is real. >>Thanks John. It's great speaking with >>You. Yeah, thanks. Thanks so much. Okay.
SUMMARY :
of an already performing a cloud with, you know, chips and silicon specialized instances, Thank you for having me. I, you know, we enable people to do so many different things and you know, they can be the, And also what we also do is enable people to, you know, run different types So, you know, you kind of crank it all the time. an Emerald sponsor for the last Nu you know, I think four or five years. So you know, the day developer traction is just really kind of stuck at the So just for those of you who, who, those, you know, those in your audience who don't know too much about Mon And so that was the, the other profound, you know, things and you know, they can be the, you know, the largest companies in the world trying to transform Do you see yourself as a ISV or you you know, you know, we believe that what we are enabling developers to do is be able to reduce know, reminds me of the old asp, you know, if you will. Yeah, so essentially what what, you know, a lot of our customers doing, and by the way we have over 37,000 Let's talk about the performance side. So you guys have a lot of experience tuning in with Graviton instances, we're seeing a lot like you know, the, you know, the, the later part of the last decade and told me, you know, And, and you know, if you look at their revenue, about 60 to 70% I mean, you know, it's so funny Dave, because you know, I remember those, And then you got the new abstraction layers of the higher level services. to the, you know, to AWS and the Amazon team for what they've built. And so we think offering one data model, one, you know, elegant user experience, Can you comment on that? can basically turn up, you know, an Alice instance with no commitment. is, is if you take digital transformation concept to its completion, assuming now you And you know, one thing John, they never tell me, they never tell me that they're innovating too quickly. you know, to your point, every software company, every company's not becoming a software company because or you know, Adam calls it the landing zone or whatever they wanna call it. So for example, you know, the, the next big hurdle for us, I think we've seen two big platform shifts over the I mean, this is what you do, So that's, you know, you guys are well positioned. I think people obviously in, you know, the last 10 years have, on where you guys been, but really where you are now and great opportunity. Thanks so much.
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Kim Leyenaar, Broadcom | SuperComputing 22
(Intro music) >> Welcome back. We're LIVE here from SuperComputing 22 in Dallas Paul Gillin, for Silicon Angle in theCUBE with my guest host Dave... excuse me. And our, our guest today, this segment is Kim Leyenaar who is a storage performance architect at Broadcom. And the topic of this conversation is, is is networking, it's connectivity. I guess, how does that relate to the work of a storage performance architect? >> Well, that's a really good question. So yeah, I have been focused on storage performance for about 22 years. But even, even if we're talking about just storage the entire, all the components have a really big impact on ultimately how quickly you can access your data. So, you know, the, the switches the memory bandwidth, the, the expanders the just the different protocols that you're using. And so, and the big part of is actually ethernet because as you know, data's not siloed anymore. You have to be able to access it from anywhere in the world. >> Dave: So wait, so you're telling me that we're just not living in a CPU centric world now? >> Ha ha ha >> Because it is it is sort of interesting. When we talk about supercomputing and high performance computing we're always talking about clustering systems. So how do you connect those systems? Isn't that, isn't that kind of your, your wheelhouse? >> Kim: It really is. >> Dave: At Broadcom. >> It's, it is, it is Broadcom's wheelhouse. We are all about interconnectivity and we own the interconnectivity. You know, you know, years ago it was, 'Hey, you know buy this new server because, you know, we we've added more cores or we've got better memory.' But now you've got all this siloed data and we've got you know, we've got this, this stuff or defined kind of environment now this composable environments where, hey if you need more networking, just plug this in or just go here and just allocate yourself more. So what we're seeing is these silos really of, 'hey here's our compute, here's your networking, here's your storage.' And so, how do you put those all together? The thing is interconnectivity. So, that's really what we specialize in. I'm really, you know, I'm really happy to be here to talk about some of the things that that we do to enable high performance computing. >> Paul: Now we're seeing, you know, new breed of AI computers being built with multiple GPUs very large amounts of data being transferred between them. And the internet really has become a, a bottleneck. The interconnect has become a bottle, a bottleneck. Is that something that Broadcom is working on alleviating? >> Kim: Absolutely. So we work with a lot of different, there's there's a lot of different standards that we work with to define so that we can make sure that we work everywhere. So even if you're just a dentist's office that's deploying one server, or we're talking about these hyperscalers that are, you know that have thousands or, you know tens of thousands of servers, you know, we're working on making sure that the next generation is able to outperform the previous generation. Not only that, but we found that, you know with these siloed things, if, if you add more storage but that means we're going to eat up six cores using that it's not really as useful. So Broadcom's really been focused on trying to offload the CPU. So we're offloading it from, you know data security, data protection, you know, we're we do packet sniffing ourselves and things like that. So no longer do we rely on the CPU to do that kind of processing for us but we become very smart devices all on our own so that they work very well in these kind of environments. >> Dave: So how about, give, give us an example. I know a lot of the discussion here has been around using ethernet as the connectivity layer. >> Yes. >> You know, in in, in the past, people would think about supercomputing as exclusively being InfiniBand based. >> Ha ha ha. >> But give, give us an idea of what Broadcom is doing in the ethernet space. What, you know, what's what are the advantages of using ethernet? >> Kim: So we've made two really big announcements. The first one is our Tomahawk five ethernet switch. So it's a 400 gigi ethernet switch. And the other thing we announced too was our Thor. So we have, these are our network controllers that also support up to 400 gigi each as well. So, those two alone, it just, it's amazing to me how much data we're able to transfer with those. But not only that, but they're super super intelligent controllers too. And then we realized, you know, hey, we're we're managing all this data, let's go ahead and offload the CPU. So we actually adopted the Rocky Standards. So that's one of the things that puts us above InfiniBand is that ethernet is ubiquitous, it's everywhere. And InfiniBand is primarily just owned by one or two companies. And, and so, and it's also a lot more expensive. So ethernet is just, it's everywhere. And now with the, with the Rocky standards, we're working along with, it's, it's, it does what you're talking about much better than, you know predecessors. >> Tell us about the Rocky Standards. I'm not familiar with it. I'm sure some of our listeners are not. What is the Rocky standard? >> Kim: Ha ha ha. So it's our DNA over converged to ethernet. I'm not a Rocky expert myself but I am an expert on how to offload the CPU. And so one of the things it does is instead of using the CPU to transfer the data from, you know the user space over to the next, you know server when you're transferring it we actually will do it ourselves. So we'll handle it ourselves. We will take it, we will move it across the wire and we will put it in that remote computer. And we don't have to ask the CPU to do anything to get involved in that. So big, you know, it's a big savings. >> Yeah, I mean in, in a nutshell, because there are parts of the InfiniBand protocol that are essentially embedded in RDMA over converged ethernet. So... >> Right. >> So if you can, if you can leverage kind of the best of both worlds, but have it in an ethernet environment which is already ubiquitous, it seems like it's, kind of democratizing supercomputing and, and HPC and I know you guys are big partners with Dell as an example, you guys work with all sorts of other people. >> Kim: Yeah. >> But let's say, let's say somebody is going to be doing ethernet for connectivity, you also offer switches? >> Kim: We do, actually. >> So is that, I mean that's another piece of the puzzle. >> That's a big piece of the puzzle. So we just released our, our Atlas 2 switch. It is a PCIE Gen Five switch. And... >> Dave: What does that mean? What does Gen five, what does that mean? >> Oh, Gen Five PCIE, it's it's a magic connectivity right now. So, you know, we talk about the Sapphire Rapids release as well as the GENUWA release. I know that those, you know those have been talked about a lot here. I've been walking around and everybody's talking about it. Well, those enable the Gen Five PCIE interfaces. So we've been able to double the bandwidth from the Gen Four up to the Gen Five. So, in order to, to support that we do now have our Atlas two PCIE Gen Five switch. And it allows you to connect especially around here we're talking about, you know artificial intelligence and machine learning. A lot of these are relying on the GPU and the DPU that you see, you know a lot of people talking about enabling. So by in, you know, putting these switches in the servers you can connect multitudes of not only NVME devices but also these GPUs and these, these CPUs. So besides that we also have the storage component of it too. So to support that, we we just recently have released our 9,500 series HBAs which support 24 gig SAS. And you know, this is kind of a, this is kind of a big deal for some of our hyperscalers that say, Hey, look our next generation, we're putting a hundred hard drives in. So we're like, you know, so a lot of it is maybe for cold storage, but by giving them that 24 gig bandwidth and by having these mass 24 gig SAS expanders that allows these hyperscalers to build up their systems. >> Paul: And how are you supporting the HPC community at large? And what are you doing that's exclusively for supercomputing? >> Kim: Exclusively for? So we're doing the interconnectivity really for them. You know, you can have as, as much compute power as you want, but these are very data hungry applications and a lot of that data is not sitting right in the box. A lot of that data is sitting in some other country or in some other city, or just the box next door. So to be able to move that data around, you know there's a new concept where they say, you know do the compute where the data is and then there's another kind of, you know the other way is move the data around which is a lot easier kind of sometimes, but so we're allowing us to move that data around. So for that, you know, we do have our our tomahawk switches, we've got our Thor NICS and of course we got, you know, the really wide pipe. So our, our new 9,500 series HBA and RAID controllers not only allow us to do, so we're doing 28 gigabytes a second that we can trans through the one controller, and that's on protected data. So we can actually have the high availability protected data of RAID 5 or RAID 6, or RAID 10 in the box giving in 27 gigabytes a second. So it's, it's unheard of the latency that we're seeing even off of this too, we have a right cash latency that is sub 8 microseconds that is lower than most of the NVME drives that you see, you know that are available today. So, so you know we're able to support these applications that require really low latency as well as data protection. >> Dave: So, so often when we talk about the underlying hardware, it's a it's a game of, you know, whack-a-mole chase the bottleneck. And so you've mentioned PCIE five, a lot of folks who will be implementing five, gen five PCIE five are coming off of three, not even four. >> Kim: I know. >> So make, so, so they're not just getting a last generation to this generation bump but they're getting a two generations, bump. >> Kim: They are. >> How does that, is it the case that it would never make sense to use a next gen or a current gen card in an older generation bus because of the mismatch and performance? Are these things all designed to work together? >> Uh... That's a really tough question. I want to say, no, it doesn't make sense. It, it really makes sense just to kind of move things forward and buy a card that's made for the bus it's in. However, that's not always the case. So for instance, our 9,500 controller is a Gen four PCIE but what we did, we doubled the PCIE so it's a by 16, even though it's a gen four, it's a by 16. So we're getting really, really good bandwidth out of it. As I said before, you know, we're getting 28, 27.8 or almost 28 gigabytes a second bandwidth out of that by doubling the PCIE bus. >> Dave: But they worked together, it all works together? >> All works together. You can put, you can put our Gen four and a Gen five all day long and they work beautifully. Yeah. We, we do work to validate that. >> We're almost out our time. But I, I want to ask you a more, nuts and bolts question, about storage. And we've heard for, you know, for years of the aerial density of hard disk has been reached and there's really no, no way to excel. There's no way to make the, the dish any denser. What is the future of the hard disk look like as a storage medium? >> Kim: Multi actuator actually, we're seeing a lot of multi-actuator. I was surprised to see it come across my desk, you know because our 9,500 actually does support multi-actuator. And, and, and so it was really neat after I've been working with hard drives for 22 years and I remember when they could do 30 megabytes a second, and that was amazing. That was like, wow, 30 megabytes a second. And then, about 15 years ago, they hit around 200 to 250 megabytes a second, and they stayed there. They haven't gone anywhere. What they have done is they've increased the density so that you can have more storage. So you can easily go out and buy 15 to 30 terabyte drive, but you're not going to get any more performance. So what they've done is they've added multiple actuators. So each one of these can do its own streaming and each one of these can actually do their own seeking. So you can get two and four. And I've even seen a talk about, you know eight actuator per disc. I, I don't think that, I think that's still theory, but but they could implement those. So that's one of the things that we're seeing. >> Paul: Old technology somehow finds a way to, to remain current. >> It does. >> Even it does even in the face of new alternatives. Kim Leyenaar, Storage Architect, Storage Performance Architect at Broadcom Thanks so much for being here with us today. Thank you so much for having me. >> This is Paul Gillin with Dave Nicholson here at SuperComputing 22. We'll be right back. (Outro music)
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And the topic of this conversation is, is So, you know, the, the switches So how do you connect those systems? buy this new server because, you know, we you know, new breed So we're offloading it from, you know I know a lot of the You know, in in, in the What, you know, what's And then we realized, you know, hey, we're What is the Rocky standard? the data from, you know of the InfiniBand protocol So if you can, if you can So is that, I mean that's So we just released So we're like, you know, So for that, you know, we do have our it's a game of, you know, So make, so, so they're not out of that by doubling the PCIE bus. You can put, you can put And we've heard for, you know, for years so that you can have more storage. to remain current. Even it does even in the with Dave Nicholson here
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Winning Cloud Models - De facto Standards or Open Clouds | Supercloud22
(bright upbeat music) >> Welcome back, everyone, to the "Supercloud 22." I'm John Furrier, host of "The Cube." This is the Cloud-erati panel, the distinguished experts who have been there from day one, watching the cloud grow, from building clouds, and all open source stuff as well. Just great stuff. Good friends of "The Cube," and great to introduce back on "The Cube," Adrian Cockcroft, formerly with Netflix, formerly AWS, retired, now commentating here in "The Cube," as well as other events. Great to see you back out there, Adrian. Lori MacVittie, Cloud Evangelist with F5, also wrote a great blog post on supercloud, as well as Dave Vellante as well, setting up the supercloud conversation, which we're going to get into, and Chris Hoff, who's the CTO and CSO of LastPass who's been building clouds, and we know him from "The Cube" before with security and cloud commentary. Welcome, all, back to "The Cube" and supercloud. >> Thanks, John. >> Hi. >> All right, Lori, we'll start with you to get things going. I want to try to sit back, as you guys are awesome experts, and involved from building, and in the trenches, on the front lines, and Adrian's coming out of retirement, but Lori, you wrote the post setting the table on supercloud. Let's start with you. What is supercloud? What is it evolving into? What is the north star, from your perspective? >> Well, I don't think there's a north star yet. I think that's one of the reasons I wrote it, because I had a clear picture of this in my mind, but over the past, I don't know, three, four years, I keep seeing, in research, my own and others', complexity, multi-cloud. "We can't manage it. They're all different. "We have trouble. What's going on? "We can't do anything right." And so digging into it, you start looking into, "Well, what do you mean by complexity?" Well, security. Migration, visibility, performance. The same old problems we've always had. And so, supercloud is a concept that is supposed to overlay all of the clouds and normalize it. That's really what we're talking about, is yet another abstraction layer that would provide some consistency that would allow you to do the same security and monitor things correctly. Cornell University actually put out a definition way back in 2016. And they said, "It's an architecture that enables migration "across different zones or providers," and I think that's important, "and provides interfaces to everything, "makes it consistent, and normalizes the network," basically brings it all together, but it also extends to private clouds. Sometimes we forget about that piece of it, and I think that's important in this, so that all your clouds look the same. So supercloud, big layer on top, makes everything wonderful. It's unicorns again. >> It's interesting. We had multiple perspectives. (mumbles) was like Snowflake, who built on top of AWS. Jerry Chan, who we heard from earlier today, Greylock Penn's "Castles in the Cloud" saying, "Hey, you can have a moat, "you can build an advantage and have differentiation," so startups are starting to build on clouds, that's the native cloud view, and then, of course, they get success and they go to all the other clouds 'cause they got customers in the ecosystem, but it seems that all the cloud players, Chris, you commented before we came on today, is that they're all fighting for the customer's workloads on their infrastructure. "Come bring your stuff over to here, "and we'll make it run better." And all your developers are going to be good. Is there a problem? I mean, or is this something else happening here? Is there a real problem? >> Well, I think the north star's over there, by the way, Lori. (laughing) >> Oh, there it is. >> Right there. The supercloud north star. So indeed I think there are opportunities. Whether you call them problems or not, John, I think is to be determined. Most companies have, especially if they're a large enterprise, whether or not they've got an investment in private cloud or not, have spent time really trying to optimize their engineering and workload placement on a single cloud. And that, regardless of your choice, as we take the big three, whether it's Amazon, Google, or Microsoft, each of them have their pros and cons for various types of workloads. And so you'll see a lot of folks optimizing for a particular cloud, and it takes a huge effort up and down the stack to just get a single cloud right. That doesn't take into consideration integrations with software as a service, instantiated, oftentimes, on top of infrastructure of the service that you need to supplement where the obstruction layer ends in infrastructure of the service. You've seen most IS players starting to now move up-chain, as we predicted years ago, to platform as a service, but platforms of various types. So I definitely see it as an opportunity. Previous employers have had multiple clouds, but they were very specifically optimized for the types of workloads, for example, in, let's say, AWS versus GCP, based on the need for different types and optimized compute platforms that each of those providers ran. We never, in that particular case, thought about necessarily running the same workloads across both clouds, because they had different pricing models, different security models, et cetera. And so the challenge is really coming down to the fact that, what is the cost benefit analysis of thinking about multi-cloud when you can potentially engineer the resiliency or redundancy, all the in-season "ilities" that you might need to factor into your deployments on a single cloud, if they are investing at the pace in which they are? So I think it's an opportunity, and it's one that continues to evolve, but this just reminds me, your comments remind me, of when we were talking about OpenStack versus AWS. "Oh, if there were only APIs that existed "that everybody could use," and you saw how that went. So I think that the challenge there is, what is the impetus for a singular cloud provider, any of the big three, deciding that they're going to abstract to a single abstraction layer and not be able to differentiate from the competitors? >> Yeah, and that differentiation's going to be big. I mean, assume that the clouds aren't going to stay still like AWS and just not stop innovating. We see the devs are doing great, Adrian, open source is bigger and better than ever, but now that's been commercialized into enterprise. It's an ops problem. So to Chris's point, the cost benefit analysis is interesting, because do companies have to spin up multiple operations teams, each with specialized training and tooling for the clouds that they're using, and does that open up a can of worms, or is that a good thing? I mean, can you design for this? I mean, is there an architecture or taxonomy that makes it work, or is it just the cart before the horse, the solution before the problem? >> Yeah, well, I think that if you look at any large vendor... Sorry, large customer, they've got a bit of everything already. If you're big enough, you've bought something from everybody at some point. So then you're trying to rationalize that, and trying to make it make sense. And I think there's two ways of looking at multi-cloud or supercloud, and one is that the... And practically, people go best of breed. They say, "Okay, I'm going to get my email "from Google or Microsoft. "I'm going to run my applications on AWS. "Maybe I'm going to do some AI machine learning on Google, "'cause those are the strengths of the platforms." So people tend to go where the strength is. So that's multi-cloud, 'cause you're using multiple clouds, and you still have to move data and make sure they're all working together. But then what Lori's talking about is trying to make them all look the same and trying to get all the security architectures to be the same and put this magical layer, this unicorn magical layer that, "Let's make them all look the same." And this is something that the CIOs have wanted for years, and they keep trying to buy it, and you can sell it, but the trouble is it's really hard to deliver. And I think, when I go back to some old friends of ours at Enstratius who had... And back in the early days of cloud, said, "Well, we'll just do an API that abstracts "all the cloud APIs into one layer." Enstratius ended up being sold to Dell a few years ago, and the problem they had was that... They didn't have any problem selling it. The problem they had was, a year later, when it came up for renewal, the developers all done end runs around it were ignoring it, and the CIOs weren't seeing usage. So you can sell it, but can you actually implement it and make it work well enough that it actually becomes part of your core architecture without, from an operations point of view, without having the developers going directly to their favorite APIs around them? And I'm not sure that you can really lock an organization down enough to get them onto a layer like that. So that's the way I see it. >> You just defined- >> You just defined shadow shadow IT. (laughing) That's pretty- (crosstalk) >> Shadow shadow IT, yeah. >> Yeah, shadow shadow it. >> Yeah. >> Yeah. >> I mean, this brings up the question, I mean, is there really a problem? I mean, I guess we'll just jump to it. What is supercloud? If you can have the magic outcome, what is it? Enstratius rendered in with automation? The security issues? Kubernetes is hot. What is the supercloud dream? I guess that's the question. >> I think it's got easier than it was five, 10 years ago. Kubernetes gives you a bunch of APIs that are common across lots of different areas, things like Snowflake or MongoDB Atlas. There are SaaS-based services, which are across multiple clouds from vendors that you've picked. So it's easier to build things which are more portable, but I still don't think it's easy to build this magic API that makes them all look the same. And I think that you're going to have leaky abstractions and security being... Getting the security right's going to be really much more complex than people think. >> What about specialty superclouds, Chris? What's your view on that? >> Yeah, I think what Adrian is alluding to, those leaky abstractions, are interesting, especially from the security perspective, 'cause I think what you see is if you were to happen to be able to thin slice across a set of specific types of workloads, there is a high probability given today that, at least on two of the three major clouds, you could get SaaS providers that sit on those same infrastructure of the service clouds for you, string them together, and have a service that technically is abstracted enough from the things you care about to work on one, two, or three, maybe not all of them, but most SaaS providers in the security space, or identity space, data space, for example, coexist on at least Microsoft and AWS, if not all three, with Google. And so you could technically abstract a service to the point that you let that level of abstract... Like Lori said, no computer science problem could not be... So, no computer science problem can't be solved with more layers of abstraction or misdirection... Or redirection. And in that particular case, if you happen to pick the right vendors that run on all three clouds, you could possibly get close. But then what that really talks about is then, if you built your seven-layer dip model, then you really have specialty superclouds spanning across infrastructure of the service clouds. One for your identity apps, one for data and data layers, to normalize that, one for security, but at what cost? Because you're going to be charged not for that service as a whole, but based on compute resources, based on how these vendors charge across each cloud. So again, that cost-benefit ratio might start being something that is rather imposing from a budgetary perspective. >> Lori, weigh in on this, because the enterprise people love to solve complexity with more complexity. Here, we need to go the other way. It's a commodity. So there has to be a better way. >> I think I'm hearing two fundamental assumptions. One, that a supercloud would force the existing big three to implement some sort of equal API. Don't agree with that. There's no business case for that. There's no reason that could compel them to do that. Otherwise, we would've convinced them to do that, what? 10, 15 years ago when we said we need to be interoperable. So it's not going to happen there. They don't have a good reason to do that. There's no business justification for that. The other presumption, I think, is that we would... That it's more about the services, the differentiated services, that are offered by all of these particular providers, as opposed to treating the core IaaS as the commodity it is. It's compute, it's some storage, it's some networking. Look at that piece. Now, pull those together by... And it's not OpenStack. That's not the answer, it wasn't the answer, it's not the answer now, but something that can actually pull those together and abstract it at a different layer. So cloud providers don't have to change, 'cause they're not going to change, but if someone else were to build that architecture to say, "all right, I'm going to treat all of this compute "so you can run your workloads," as Chris pointed out, "in the best place possible. "And we'll help you do that "by being able to provide those cost benefit analysis, "'What's the best performance, what are you doing,' "And then provide that as a layer." So I think that's really where supercloud is going, 'cause I think that's what a lot of the market actually wants in terms of where they want to run their workloads, because we're seeing that they want to run workloads at the edge, "a lot closer to me," which is yet another factor that we have to consider, and how are you going to be moving individual workloads around? That's the holy grail. Let's move individual workloads to where they're the best performance, the security, cost optimized, and then one layer up. >> Yeah, I think so- >> John Considine, who ultimately ran CloudSwitch, that sold to Verizon, as well as Tom Gillis, who built Bracket, are both rolling in their graves, 'cause what you just described was exactly that. (Lori laughing) Well, they're not even dead yet, so I can't say they're rolling in their graves. Sorry, Tom. Sorry, John. >> Well, how do hyperscalers keep their advantage with all this? I mean, to that point. >> Native services and managed services on top of it. Look how many flavors of managed Kubernetes you have. So you have a choice. Roll your own, or go with a managed service, and then differentiate based on the ability to take away and simplify some of that complexity. Doesn't mean it's more secure necessarily, but I do think we're seeing opportunities where those guys are fighting tooth and nail to keep you on a singular cloud, even though, to Lori's point, I agree, I don't think it's about standardized APIs, 'cause I think that's never going to happen. I do think, though, that SaaS-y supercloud model that we were talking about, layering SaaS that happens to span all the three infrastructure of the service are probably more in line with what Lori was talking about. But I do think that portability of workload is given to you today within lots of ways. But again, how much do you manage, and how much performance do you give up by running additional abstraction layers? And how much security do you give up by having to roll your own and manage that? Because the whole point was, in many cases... Cloud is using other people's computers, so in many cases, I want to manage as little of it as I possibly can. >> I like this whole SaaS angle, because if you had the old days, you're on Amazon Web Services, hey, if you build a SaaS application that runs on Amazon, you're all great, you're born in the cloud, just like that generations of startups. Great. Now when you have this super pass layer, as Dave Vellante was riffing on his analysis, and Lori, you were getting into this pass layer that's kind of like SaaS-y, what's the SaaS equation look like? Because that, to me, sounds like a supercloud version of saying, "I have a workload that runs on all the clouds equally." I just don't think that's ever going to happen. I agree with you, Chris, on that one. But I do see that you can have an abstraction that says, "Hey, I don't really want to get in the weeds. "I don't want to spend a lot of ops time on this. "I just want it to run effectively, and magic happens," or, as you said, some layer there. How does that work? How do you see this super pass layer, if anything, enabling a different SaaS game? >> I think you hit on it there. The last like 10 or so years, we've been all focused on developers and developer productivity, and it's all about the developer experience, and it's got to be good for them, 'cause they're the kings. And I think the next 10 years are going to be very focused on operations, because once you start scaling out, it's not about developers. They can deliver fast or slow, it doesn't matter, but if you can't scale it out, then you've got a real problem. So I think that's an important part of it, is really, what is the ops experience, and what is the best way to get those costs down? And this would serve that purpose if it was done right, which, we can argue about whether that's possible or not, but I don't have to implement it, so I can say it's possible. >> Well, are we going to be getting into infrastructure as code moves into "everything is code," security, data, (laughs) applications is code? I mean, "blank" is code, fill in the blank. (Lori laughing) >> Yeah, we're seeing more of that with things like CDK and Pulumi, where you are actually coding up using a real language rather than the death by YAML or whatever. How much YAML can you take? But actually having a real language so you're not trying to do things in parsing languages. So I think that's an interesting trend. You're getting some interesting templates, and I like what... I mean, the counterexample is that if you just go deep on one vendor, then maybe you can go faster and it is simpler. And one of my favorite vendor... Favorite customers right now that I've been talking to is Liberty Mutual. Went very deep and serverless first on AWS. They're just doing everything there, and they're using CDK Patterns to do it, and they're going extremely fast. There's a book coming out called "The Value Flywheel" by Dave Anderson, it's coming out in a few months, to just detail what they're doing, but that's the counterargument. If you could pick one vendor, you can go faster, you can get that vendor to do more for you, and maybe get a bigger discount so you're not splitting your discounts across vendors. So that's one aspect of it. But I think, fundamentally, you're going to find the CIOs and the ops people generally don't like sitting on one vendor. And if that single vendor is a horizontal platform that's trying to make all the clouds look the same, now you're locked into whatever that platform was. You've still got a platform there. There's still something. So I think that's always going to be something that the CIOs want, but the developers are always going to just pick whatever the best tool for building the thing is. And a analogy here is that the developers are dating and getting married, and then the operations people are running the family and getting divorced. And all the bad parts of that cycle are in the divorce end of it. You're trying to get out of a vendor, there's lawyers, it's just a big mess. >> Who's the lawyer in this example? (crosstalk) >> Well... (laughing) >> Great example. (crosstalk) >> That's why ops people don't like lock-in, because they're the ones trying to unlock. They aren't the ones doing the lock-in. They're the ones unlocking, when developers, if you separate the two, are the ones who are going, picking, having the fun part of it, going, trying a new thing. So they're chasing a shiny object, and then the ops people are trying to untangle themselves from the remains of that shiny object a few years later. So- >> Aren't we- >> One way of fixing that is to push it all together and make it more DevOps-y. >> Yeah, that's right. >> But that's trying to put all the responsibilities in one place, like more continuous improvement, but... >> Chris, what's your reaction to that? Because you're- >> No, that's exactly what I was going to bring up, yeah, John. And 'cause we keep saying "devs," "dev," and "ops" and I've heard somewhere you can glue those two things together. Heck, you could even include "sec" in the middle of it, and "DevSecOps." So what's interesting about what Adrian's saying though, too, is I think this has a lot to do with how you structure your engineering teams and how you think about development versus operations and security. So I'm building out a team now that very much makes use of, thanks to my brilliant VP of Engineering, a "Team Topologies" approach, which is a very streamlined and product oriented way of thinking about, for example, in engineering, if you think about team structures, you might have people that build the front end, build the middle tier, and the back end, and then you have a product that needs to make use of all three components in some form. So just from getting stuff done, their ability then has to tie to three different groups, versus building a team that's streamlined that ends up having front end, middleware, and backend folks that understand and share standards but are able to uncork the velocity that's required to do that. So if you think about that, and not just from an engineering development perspective, but then you couple in operations as a foundational layer that services them with embedded capabilities, we're putting engineers and operations teams embedded in those streamlined teams so that they can run at the velocity that they need to, they can do continuous integration, they can do continuous deployment. And then we added CS, which is continuously secure, continuous security. So instead of having giant, centralized teams, we're thinking there's a core team, for example, a foundational team, that services platform, makes sure all the trains are running on time, that we're doing what we need to do foundationally to make the environments fully dev and operator and security people functional. But then ultimately, we don't have these big, monolithic teams that get into turf wars. So, to Adrian's point about, the operators don't like to be paned in, well, they actually have a say, ultimately, in how they architect, deploy, manage, plan, build, and operate those systems. But at the same point in time, we're all looking at that problem across those teams and go... Like if one streamline team says, "I really want to go run on Azure, "because I like their services better," the reality is the foundational team has a larger vote versus opinion on whether or not, functionally, we can satisfy all of the requirements of the other team. Now, they may make a fantastic business case and we play rock, paper, scissors, and we do that. Right now, that hasn't really happened. We look at the balance of AWS, we are picking SaaS-y, supercloud vendors that will, by the way, happen to run on three platforms, if we so choose to expand there. So we have a similar interface, similar capability, similar processes, but we've made the choice at LastPass to go all in on AWS currently, with respect to how we deliver our products, for all the reasons we just talked about. But I do think that operations model and how you build your teams is extremely important. >> Yeah, and to that point- >> And has the- (crosstalk) >> The vendors themselves need optionality to the customer, what you're saying. So, "I'm going to go fast, "but I need to have that optionality." I guess the question I have for you guys is, what is today's trade-off? So if the decision point today is... First of all, I love the go-fast model on one cloud. I think that's my favorite when I look at all this, and then with the option, knowing that I'm going to have the option to go to multiple clouds. But everybody wants lock-in on the vendor side. Is that scale, is that data advantage? I mean, so the lock-in's a good question, and then also the trade-offs. What do people have to do today to go on a supercloud journey to have an ideal architecture and taxonomy, and what's the right trade-offs today? >> I think that the- Sorry, just put a comment and then let Lori get a word in, but there's a lot of... A lot of the market here is you're building a product, and that product is a SaaS product, and it needs to run somewhere. And the customers that you're going to... To get the full market, you need to go across multiple suppliers, most people doing AWS and Azure, and then with Google occasionally for some people. But that, I think, has become the pattern that most of the large SaaS platforms that you'd want to build out of, 'cause that's the fast way of getting something that's going to be stable at scale, it's got functionality, you'd have to go invest in building it and running it. Those platforms are just multi-cloud platforms, they're running across them. So Snowflake, for example, has to figure out how to make their stuff work on more than one cloud. I mean, they started on one, but they're going across clouds. And I think that that is just the way it's going to be, because you're not going to get a broad enough view into the market, because there isn't a single... AWS doesn't have 100% of the market. It's maybe a bit more than them, but Azure has got a pretty solid set of markets where it is strong, and it's market by market. So in some areas, different people in some places in the world, and different vertical markets, you'll find different preferences. And if you want to be across all of them with your data product, or whatever your SaaS product is, you're just going to have to figure this out. So in some sense, the supercloud story plays best with those SaaS providers like the Snowflakes of this world, I think. >> Lori? >> Yeah, I think the SaaS product... Identity, whatever, you're going to have specialized. SaaS, superclouds. We already see that emerging. Identity is becoming like this big SaaS play that crosses all clouds. It's not just for one. So you get an evolution going on where, yes, I mean, every vendor who provides some kind of specific functionality is going to have to build out and be multi-cloud, as it were. It's got to work equally across them. And the challenge, then, for them is to make it simple for both operators and, if required, dev. And maybe that's the other lesson moving forward. You can build something that is heaven for ops, but if the developers won't use it, well, then you're not going to get it adopted. But if you make it heaven for the developers, the ops team may not be able to keep it secure, keep everything. So maybe we have to start focusing on both, make it friendly for both, at least. Maybe it won't be the perfect experience, but gee, at least make it usable for both sides of the equation so that everyone can actually work in concert, like Chris was saying. A more comprehensive, cohesive approach to delivery and deployment. >> All right, well, wrapping up here, I want to just get one final comment from you guys, if you don't mind. What does supercloud look like in five years? What's the Nirvana, what's the steady state of supercloud in five to 10 years? Or say 10 years, make it easier. (crosstalk) Five to 10 years. Chris, we'll start with you. >> Wow. >> Supercloud, what's it look like? >> Geez. A magic pane, a single pane of glass. (laughs) >> Yeah, I think- >> Single glass of pain. >> Yeah, a single glass of pain. Thank you. You stole my line. Well, not mine, but that's the one I was going to use. Yeah, I think what is really fascinating is ultimately, to answer that question, I would reflect on market consolidation and market dynamics that happens even in the SaaS space. So we will see SaaS companies combining in focal areas to be able to leverage the positions, let's say, in the identity space that somebody has built to provide a set of compelling services that help abstract that identity problem or that security problem or that instrumentation and observability problem. So take your favorite vendors today. I think what we'll end up seeing is more consolidation in SaaS offerings that run on top of infrastructure of the service offerings to where a supercloud might look like something I described before. You have the combination of your favorite interoperable identity, observability, security, orchestration platforms run across them. They're sold as a stack, whether it be co-branded by an enterprise vendor that sells all of that and manages it for you or not. But I do think that... You talked about, I think you said, "Is this an innovator's dilemma?" No, I think it's an integrator's dilemma, as it has always ultimately been. As soon as you get from Genesis to Bespoke Build to product to then commoditization, the cycle starts anew. And I think we've gotten past commoditization, and we're looking at niche areas. So I see just the evolution, not necessarily a revolution, of what we're dealing with today as we see more consolidation in the marketplace. >> Lori, what's your take? Five years, 10 years, what does supercloud look like? >> Part of me wants to take the pie in the sky unicorn approach. "No, it will be beautiful. "One button, and things will happen," but I've seen this cycle many times before, and that's not going to happen. And I think Chris has got it pretty close to what I see already evolving. Those different kinds of super services, basically. And that's really what we're talking about. We call them SaaS, but they're... X is a service. Everything is a service, and it's really a supercloud that can run anywhere, but it presents a different interface, because, well, it's easier. And I think that's where we're going to go, and that's just going to get more refined. And yes, a lot of consolidation, especially on the observability side, but that's also starting to consume the security side, which is really interesting to watch. So that could be a little different supercloud coming on there that's really focused on specific types of security, at least, that we'll layer across, and then we'll just hook them all together. It's an API first world, and it seems like that's going to be our standard for the next while of how we integrate everything. So superclouds or APIs. >> Awesome. Adrian... Adrian, take us home. >> Yeah, sure. >> What's your- I think, and just picking up on Lori's point that these are web services, meaning that you can just call them from anywhere, they don't have to run everything in one place, they can stitch it together, and that's really meant... It's somewhat composable. So in practice, people are going to be composable. Can they compose their applications on multiple platforms? But I think the interesting thing here is what the vendors do, and what I'm seeing is vendors running software on other vendors. So you have Google building platforms that, then, they will support on AWS and Azure and vice versa. You've got AWS's distro of Kubernetes, which they now give you as a distro so you can run it on another platform. So I think that trend's going to continue, and it's going to be, possibly, you pick, say, an AWS or a Google software stack, but you don't run it all on AWS, you run it in multiple places. Yeah, and then the other thing is the third tier, second, third tier vendors, like, I mean, what's IBM doing? I think in five years time, IBM is going to be a SaaS vendor running on the other clouds. I mean, they're already halfway there. To be a bit more controversial, I guess it's always fun to... Like I don't work for a corporate entity now. No one tells me what I can say. >> Bring it on. >> How long can Google keep losing a billion dollars a quarter? They've either got to figure out how to make money out of this thing, or they'll end up basically being a software stack on another cloud platform as their, likely, actual way they can make money on it. Because you've got to... And maybe Oracle, is that a viable cloud platform that... You've got to get to some level of viability. And I think the second, third tier of vendors in five, 10 years are going to be running on the primary platform. And I think, just the other final thing that's really driving this right now. If you try and place an order right now for a piece of equipment for your data center, key pieces of equipment are a year out. It's like trying to buy a new fridge from like Sub-Zero or something like that. And it's like, it's a year. You got to wait for these things. Any high quality piece of equipment. So you go to deploy in your data center, and it's like, "I can't get stuff in my data center. "Like, the key pieces I need, I can't deploy a whole system. "We didn't get bits and pieces of it." So people are going to be cobbling together, or they're going, "No, this is going to cloud, because the cloud vendors "have a much stronger supply chain to just be able "to give you the system you need. "They've got the capacity." So I think we're going to see some pandemic and supply chain induced forced cloud migrations, just because you can't build stuff anymore outside the- >> We got to accelerate supercloud, 'cause they have the supply. They are the chain. >> That's super smart. That's the benefit of going last. So I'm going to scoop in real quick. I can't believe we can call this "Web3 Supercloud," because none of us said "Web3." Don't forget DAO. (crosstalk) (indistinct) You have blockchain, blockchain superclouds. I mean, there's some very interesting distributed computing stuff there, but we'll have to do- >> (crosstalk) We're going to call that the "Cubeverse." The "Cubeverse" is coming. >> Oh, the "Cubeverse." All right. >> We will be... >> That's very meta. >> In the metaverse, Cubeverse soon. >> "Stupor cloud," perhaps. But anyway, great points, Adrian and Lori. Loved it. >> Chris, great to see you. Adrian, Lori, thanks for coming on. We've known each other for a long time. You guys are part of the cloud-erati, the group that has been in there from day one, and watched it evolve, and you get the scar tissue to prove it, and the experience. So thank you so much for sharing your commentary. We'll roll this up and make it open to everybody as additional content. We'll call this the "outtakes," the longer version. But really appreciate your time, thank you. >> Thank you. >> Thanks so much. >> Okay, we'll be back with more "Supercloud 22" right after this. (bright upbeat music)
SUMMARY :
Great to see you back out there, Adrian. and in the trenches, some consistency that would allow you are going to be good. by the way, Lori. and it's one that continues to evolve, I mean, assume that the and the problem they had was that... You just defined shadow I guess that's the question. Getting the security right's going to be the things you care about So there has to be a better way. build that architecture to say, that sold to Verizon, I mean, to that point. is given to you today within lots of ways. But I do see that you can and it's got to be good for code, fill in the blank. And a analogy here is that the developers (crosstalk) are the ones who are going, is to push it all together all the responsibilities the operators don't like to be paned in, the option to go to multiple clouds. and it needs to run somewhere. And maybe that's the other of supercloud in five to 10 years? A magic pane, a single that happens even in the SaaS space. and that's just going to get more refined. Adrian, take us home. and it's going to be, So people are going to be cobbling They are the chain. So I'm going to scoop in real quick. call that the "Cubeverse." Oh, the "Cubeverse." In the metaverse, But anyway, great points, Adrian and Lori. and you get the scar tissue to with more "Supercloud
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Erik Bradley | AWS Summit New York 2022
>>Hello, everyone. Welcome to the cubes coverage here. New York city for AWS Amazon web services summit 2022. I'm John furrier, host of the cube with Dave ante. My co-host. We are breaking it down, getting an update on the ecosystem. As the GDP drops, inflations up gas prices up the enterprise continues to grow. We're seeing exceptional growth. We're here on the ground floor. Live at the Summit's packed house, 10,000 people. Eric Bradley's here. Chief STR at ETR, one of the premier enterprise research firms out there, partners with the cube and powers are breaking analysis that Dave does check that out as the hottest podcast in enterprise. Eric. Great to have you on the cube. Thanks for coming on. >>Thank you so much, John. I really appreciate the collaboration always. >>Yeah. Great stuff. Your data's amazing ETR folks watching check out ETR. They have a unique formula, very accurate. We love it. It's been moving the market. Congratulations. Let's talk about the market right now. This market is booming. Enterprise is the hottest thing, consumers kind of in the toilet. Okay. I said that all right, back out devices and, and, and consumer enterprise is still growing. And by the way, this first downturn, the history of the world where hyperscalers are on full pumping on all cylinders, which means they're still powering the revolution. >>Yeah, it's true. The hyperscalers were basically at this two sun system when Microsoft and an AWS first came around and everything was orbiting around it. And we're starting to see that sun cool off a little bit, but we're talking about a gradient here, right? When we say cool off, we're not talking to shutdown, it's still burning hot. That's for sure. And I can get it to some of the macro data in a minute, if that's all right. Or do you want me to go right? No, go go. Right. Yeah. So right now we just closed our most recent survey and that's macro and vendor specific. We had 1200 people talk to us on the macro side. And what we're seeing here is a cool down in spending. We originally had about 8.5% increase in budgets. That's cool down is 6.5 now, but I'll say with the doom and gloom and the headlines that we're seeing every day, 6.5% growth coming off of what we just did the last couple of years is still pretty fantastic as a backdrop. >>Okay. So you, you started to see John mentioned consumer. We saw that in Snowflake's earnings. For example, we, we certainly saw, you know, Walmart, other retailers, the FA Facebooks of the world where consumption was being dialed down, certain snowflake customers. Not necessarily, they didn't have mentioned any customers, but they were able to say, all right, we're gonna dial down, consumption this quarter, hold on until we saw some of that in snowflake results and other results. But at the same time, the rest of the industry is booming. But your data is showing softness within the fortune 500 for AWS, >>Not only AWS, but fortune 500 across the board. Okay. So going back to that larger macro data, the biggest drop in spending that we captured is fortune 500, which is surprising. But at the same time, these companies have a better purview into the economy. In general, they tend to see things further in advance. And we often remember they spend a lot of money, so they don't need to play catch up. They'll easily more easily be able to pump the brakes a little bit in the fortune 500. But to your point, when we get into the AWS data, the fortune 500 decrease seems to be hitting them a little bit more than it is Azure and GCP. I >>Mean, we're still talking about a huge business, right? >>I mean, they're catching up. I mean, Amazon has been transforming from owning the developer cloud startup cloud decade ago to really putting a dent on the enterprise as being number one cloud. And I still contest that they're number one by a long ways, but Azure kicking ass and catching up. Okay. You seeing people move to Azure, you got Charlie bell over there, Sean, by former Amazonians, Theresa Carlson, people are going over there, there there's lift over at Azure. >>There certainly is. >>Is there kinks in the arm or for AWS? There's >>A couple of kinks, but I think your point is really good. We need to take a second there. If you're talking about true pass or infrastructure is a service true cloud compute. I think AWS still is the powerhouse. And a lot of times the, the data gets a little muddied because Azure is really a hosted platform for applications. And you're not really sure where that line is drawn. And I think that's an important caveat to make, but based on the data, yes, we are seeing some kinks in the armor for AWS. Yes. Explain. So right now, a first of all caveat, 40% net score, which is our proprietary spending metric across the board. So we're not like raising any alarms here. It's still strong that said there are declines and there are declines pretty much across the board. The only spot we're not seeing a decline at all is in container, spend everything else is coming down specifically. We're seeing it come down in data analytics, data warehousing, and M I, which is a little bit of a concern because that, that rate of decline is not the same with Azure. >>Okay. So I gotta ask macro, I see the headwinds on the macro side, you pointed that out. Is there any insight into any underlying conditions that might be there on AWS or just a chronic kind of situational thing >>Right now? It seems situational. Other than that correlation between their big fortune 500, you know, audience and that being our biggest decline. The other aspect of the macro survey is we ask people, if you are planning to decline spend, how do you plan on doing it? And the number two answer is taking a look at our cloud spend and auditing it. So they're kind say, all right, you know, for the last 10 years it's been drunken, sail or spend, I >>Was gonna use that same line, you know, >>Cloud spend, just spend and we'll figure it out later, who cares? And then right now it's time to tighten the belts a little bit, >>But this is part of the allure of cloud at some point. Yeah. You, you could say, I'm gonna, I'm gonna dial it down. I'm gonna rein it in. So that's part of the reason why people go to the cloud. I want to, I wanna focus in on the data side of things and specifically the database. Let, just to give some context if, and correct me if I'm, I'm a little off here, but snowflake, which hot company, you know, on the planet, their net score was up around 80% consistently. It it's dropped down the last, you know, quarter, last survey to 60%. Yeah. So still highly, highly elevated, but that's relative to where Amazon is much larger, but you're saying they're coming down to the 40% level. Is that right? >>Yeah, they are. And I remember, you know, when I first started doing this 10 years ago, AWS at a 70%, you know, net score as well. So what's gonna happen over time is those adoptions are gonna get less and you're gonna see more flattening of spend, which ultimately is going to lower the score because we're looking for expansion rates. We wanna see adoption and increase. And when you see flattening a spend, it starts to contract a little bit. And you're right. Snowflake also was in the stratosphere that cooled off a little bit, but still, you know, very strong and AWS is coming down. I think the reason why it's so concerning is because a it's within the fortune 500 and their rate of decline is more than Azure right >>Now. Well, and, and one of the big trends you're seeing in database is this idea of converging function. In other words, bringing transaction and analytics right together at snowflake summit, they added the capability to handle transaction data, Mongo DB, which is largely mostly transactions added the capability in June to bring in analytic data. You see data bricks going from data engineering and data science now getting into snowflake space and analytics. So you're seeing that convergence Oracle is converging with my SQL heat wave and their core databases, couch base couch base is doing the same. Maria do virtually all these database companies are, are converging their platforms with the exception of AWS. AWS is still the right tool for the right job. So they've got Aurora, they've got RDS, they've got, you know, a dynamo DV, they've got red, they've got, you know, going on and on and on. And so the question everybody's asking is will that change? Will they start to sort of cross those swim lanes? We haven't seen it thus far. How is that affecting the data >>Performance? I mean, that's fantastic analysis. I think that's why we're seeing it because you have to be in the AWS ecosystem and they're really not playing nicely with others in the sandbox right now that now I will say, oh, Amazon's not playing nicely. Well, no, no. Simply to your point though, that there, the other ones are actually bringing in others at consolidating other different vendor types. And they're really not. You know, if you're in AWS, you need to stay within AWS. Now I will say their tools are fantastic. So if you do stay within AWS, they have a tool for every job they're advanced. And they're incredible. I think sometimes the complexity of their tools hurts them a little bit. Cause to your point earlier, AWS started as a developer-centric type of cloud. They have moved on to enterprise cloud and it's a little bit more business oriented, but their still roots are still DevOps friendly. And unless you're truly trained, AWS can be a little scary. >>So a common use case is I'm gonna be using Aurora for my transaction system and then I'm gonna ETL it into Redshift. Right. And, and I, now I have two data stores and I have two different sets of APIs and primitives two different teams of skills. And so that is probably causing some friction and complexity in the customer base that again, the question is, will they begin to expand some of those platforms to minimize some of that friction? >>Well, yeah, this is the question I wanted to ask on that point. So I've heard from people inside Amazon don't count out Redshift, we're making, we're catching up. I think that's my word, but they were kind of saying that right. Cuz Redshift is good, good database, but they're adding a lot more. So you got snowflake success. I think it's a little bit of a jealousy factor going on there within Redshift team, but then you got Azure synapse with the Synap product synapse. Yep. And then you got big query from Google big >>Query. Yep. >>What's the differentiation. What are you seeing for the data for the data warehouse or the data clouds that are out there for the customers? What's the data say, say to us? >>Yeah, unfortunately the data's showing that they're dropping a little bit whose day AWS is dropping a little bit now of their data products, Redshift and RDS are still the two highest of them, but they are starting to decline. Now I think one of the great data points that we have, we just closed the survey is we took a comparison of the legacy data. Now please forgive me for the word legacy. We're gonna anger a few people, but we Gotter data Oracle on-prem, we've got IBM. Some of those more legacy data warehouse type of names. When we look at our art survey takers that have them where their spend is going, that spends going to snowflake first, and then it's going to Google and then it's going to Microsoft Azure and, and AWS is actually declining in there. So when you talk about who's taking that legacy market share, it's not AWS right now. >>So legacy goes to legacy. So Microsoft, >>So, so let's work through in a little context because Redshift really was the first to take, you know, take the database to the cloud. And they did that by doing a one time license deal with par XL, which was an on-prem database. And then they re-engineered it, they did a fantastic job, but it was still engineered for on-prem. Then you along comes snowflake a couple years later and true cloud native, same thing with big query. Yep. True cloud native architecture. So they get a lot of props. Now what, what Amazon did, they took a page outta of the snowflake, for example, separating compute from storage. Now of course what's what, what Amazon did is actually not really completely separating like snowflake did they couldn't because of the architecture, they created a tearing system that you could dial down the compute. So little nuances like that. I understand. But at the end of the day, what we're seeing from snowflake is the gathering of an ecosystem in this true data cloud, bringing in different data types, they got to the public markets, data bricks was not able to get to the public markets. Yeah. And think is, is struggling >>And a 25 billion evaluation. >>Right. And so that's, that's gonna be dialed down, struggling somewhat from a go to market standpoint where snowflake has no troubles from a go to market. They are the masters at go to market. And so now they've got momentum. We talked to Frank sluman at the snowflake. He basically said, I'm not taking the foot off the gas, no way. Yeah. We, few of our large, you know, consumer customers dialed things down, but we're going balls to the >>Wall. Well, if you look at their show before you get in the numbers, you look at the two shows. Snowflake had their summit in person in Vegas. Data bricks has had their show in San Francisco. And if you compare the two shows, it's clear, who's winning snowflake is blew away from a, from a market standpoint. And we were at snowflake, but we weren't at data bricks, but there was really nothing online. I heard from sources that it was like less than 3000 people. So >>Snowflake was 1900 people in 2019, nearly 10,000. Yeah. In 2020, >>It's gonna be fun to sort of track that as a, as an odd caveat to say, okay, let's see what that growth is. Because in fairness, data, bricks, you know, a little bit younger, Snowflake's had a couple more years. So I'd be curious to see where they are. Their, their Lakehouse paradigm is interesting. >>Yeah. And I think it's >>And their product first company, yes. Their go to market might be a little bit weak from our analysis, but that, but they'll figure it out. >>CEO's pretty smart. But I think it's worth pointing out. It's like two different philosophies, right? It is. Snowflake is come into our data cloud. That's their proprietary environment. They're the, they think of the iPhone, right? End to end. We, we guarantee it's all gonna work. And we're in control. Snowflake is like, Hey, open source, no, bring in data bricks. I mean data bricks, open source, bring in this tool that too, now you are seeing snowflake capitulate a little bit. They announce, for instance, Apache iceberg support at their, at the snowflake summit. So they're tipping their cap to open source. But at the end of the day, they're gonna market and sell the fact that it's gonna run better in native snowflake. Whereas data bricks, they're coming at it from much more of an open source, a mantra. So that's gonna, you know, we'll see who look at, you had windows and you had apple, >>You got, they both want, you got Cal and you got Stanford. >>They both >>Consider, I don't think it's actually there yet. I, I find the more interesting dynamic right now is between AWS and snowflake. It's really a fun tit for tat, right? I mean, AWS has the S three and then, you know, snowflake comes right on top of it and announces R two, we're gonna do one letter, one number better than you. They just seem to have this really interesting dynamic. And I, and it is SLT and no one's betting against him. I mean, this guy's fantastic. So, and he hasn't used his war chest yet. He's still sitting on all that money that he raised to your point, that data bricks five, their timing just was a little off >>5 billion in >>Capital when Slootman hasn't used that money yet. So what's he gonna do? What can he do when he turns that on? He finds the right. >>They're making some acquisitions. They did the stream lit acquisitions stream. >>Fantastic >>Problem. With data bricks, their valuation is underwater. Yes. So they're recruiting and their MNAs. Yes. In the toilet, they cannot make the moves because they don't have the currency until they refactor the multiple, let the, this market settle. I I'm, I'm really nervous that they have to over factor the >>Valuation. Having said that to your point, Eric, the lake house architecture is definitely gaining traction. When you talk to practitioners, they're all saying, yeah, we're building data lakes, we're building lake houses. You know, it's a much, much smaller market than the enterprise data warehouse. But nonetheless, when you talk to practitioners that are actually doing things like self serve data, they're building data lakes and you know, snow. I mean, data bricks is right there. And as a clear leader in, in ML and AI and they're ahead of snowflake, right. >>And I was gonna say, that's the thing with data bricks. You know, you're getting that analytics at M I built into it. >>You know, what's ironic is I remember talking to Matt Carroll, who's CEO of auDA like four or five years ago. He came into the office in ma bro. And we were in temporary space and we were talking about how there's this new workload emerging, which combines AWS for cloud infrastructure, snowflake for the simple data warehouse and data bricks for the ML AI, and then all now all of a sudden you see data bricks yeah. And snowflake going at it. I think, you know, to your point about the competition between AWS and snowflake, here's what I think, I think the Redshift team is, you know, doesn't like snowflake, right. But I think the EC two team loves it. Loves it. Exactly. So, so I think snowflake is driving a lot of, >>Yeah. To John's point, there is plenty to go around. And I think I saw just the other day, I saw somebody say less than 40% of true global 2000 organizations believe that they're at real time data analytics right now. They're not really there yet. Yeah. Think about how much runway is left and how many tools you need to get to real time streaming use cases. It's complex. It's not easy. >>It's gonna be a product value market to me, snowflake in data bricks. They're not going away. Right. They're winning architectures. Yeah. In the cloud, what data bricks did would spark and took over the Haddo market. Yeah. To your point. Now that big data, market's got two players, in my opinion, snow flicking data, bricks converging. Well, Redshift is sitting there behind the curtain, their wild card. Yeah. They're wild card, Dave. >>Okay. I'm gonna give one more wild card, which is the edge. Sure. Okay. And that's something that when you talk about real time analytics and AI referencing at the edge, there aren't a lot of database companies in a position to do that. You know, Amazon trying to put outposts out there. I think it runs RDS. I don't think it runs any other database. Right. Snowflake really doesn't have a strong edge strategy when I'm talking the far edge, the tiny edge. >>I think, I think that's gonna be HPE or Dell's gonna own the outpost market. >>I think you're right. I'll come back to that. Couch base is an interesting company to watch with Capella Mongo. DB really doesn't have a far edge strategy at this point, but couch base does. And that's one to watch. They're doing some really interesting things there. And I think >>That, but they have to leapfrog bongo in my >>Opinion. Yeah. But there's a new architecture emerging at the edge and it's gonna take a number of years to develop, but it could eventually from an economic standpoint, seep back into the enterprise arm base, low end, take a look at what couch base is >>Doing. They hired an Amazon guard system. They have to leapfrog though. They need to, they can't incrementally who's they who >>Couch >>Base needs to needs to make a big move in >>Leap frog. Well, think they're trying to, that's what Capella is all about was not only, you know, their version of Atlas bringing to the cloud couch base, but it's also stretching it out to the edge and bringing converged database analytics >>Real quick on the numbers. Any data on CloudFlare, >>I was, I've been sitting here trying to get the word CloudFlare out my mouth the whole time you guys were talking, >>Is this another that's innovated in the ecosystem. So >>Platform, it was really simple for them early on, right? They're gonna get that edge network out there and they're gonna steal share from Akamai. Then they started doing exactly what Akamai did. We're gonna start rolling out some security. Their security is fantastic. Maybe some practitioners are saying a little bit too much, cuz they're not focused on one thing or another, but they are doing extremely well. And now they're out there in the cloud as well. You >>Got S3 compare. They got two, they got an S3 competitor. >>Exactly. So when I'm listening to you guys talk about, you know, a, a couch base I'm like, wow, those two would just be an absolute fantastic, you know, combination between the two of them. You mean >>CloudFlare >>Couch base. Yeah. >>I mean you got S3 alternative, right? You got a Mongo alternative basically in my >>Opinion. And you're going and you got the edge and you got the edge >>Network with security security, interesting dynamic. This brings up the super cloud date. I wanna talk about Supercloud because we're seeing a trend on we're reporting this since last year that basically people don't have to spend the CapEx to be cloud scale. And you're seeing Amazon enable that, but snowflake has become a super cloud. They're on AWS. Now they're on Azure. Why not tan expansion expand the market? Why not get that? And then it'll be on Google next, all these marketplaces. So the emergence of this super cloud, and then the ability to make that across a substrate across multiple clouds is a strategy we're seeing. What do you, what do you think? >>Well, honestly, I'm gonna be really Frank here. The, everything I know about the super cloud I know from this guy. So I've been following his lead on this and I'm looking forward to you guys doing that conference and that summit coming up from a data perspective. I think what you're saying is spot on though, cuz those are the areas we're seeing expansion in without a doubt. >>I think, you know, when you talk about things like super cloud and you talk about things like metaverse, there's, there's a, there, there look every 15 or 20 years or so this industry reinvents itself and a new disruption comes out and you've got the internet, you've got the cloud, you've got an AI and VR layer. You've got, you've got machine intelligence. You've got now gaming. There's a new matrix, emerging, super cloud. Metaverse there's something happening out there here. That's not just your, your father's SAS or is or pass. Well, >>No, it's also the spend too. Right? So if I'm a company like say capital one or Goldman Sachs, my it spend has traditionally been massive every year. Yes. It's basically like tons of CapEx comes the cloud. It's an operating expense. Wait a minute, Amazon has all the CapEx. So I'm not gonna dial down my budget. I want a competitive advantage. So next thing they know they have a super cloud by default because they just pivoted their, it spend into new capabilities that they then can sell to the market in FinTech makes total sense. >>Right? They're building out a digital platform >>That would, that was not possible. Pre-cloud >>No, it wasn't cause you weren't gonna go put all that money into CapEx expenditure to build that out. Not knowing whether or not the market was there, but the scalability, the ability to spend, reduce and be flexible with it really changes that paradigm entire. >>So we're looking at this market now thinking about, okay, it might be Greenfield in every vertical. It might have a power law where you have a head of the long tail. That's a player like a capital one, an insurance. It could be Liberty mutual or mass mutual that has so much it and capital that they're now gonna scale it into a super cloud >>And they have data >>And they have the data tools >>And the tools. And they're gonna bring that to their constituents. Yes, yes. And scale it using >>Cloud. So that means they can then service the entire vertical as a service provider. >>And the industry cloud is becoming bigger and bigger and bigger. I mean, that's really a way that people are delivering to market. So >>Remember in the early days of cloud, all the banks thought they could build their own cloud. Yeah. Yep. Well actually it's come full circle. They're like, we can actually build a cloud on top of the cloud. >>Right. And by the way, they can have a private cloud in their super cloud. Exactly. >>And you know, it's interesting cause we're talking about financial services insurance, all the people we know spend money in our macro survey. Do you know the, the sector that's spending the most right now? It's gonna shock you energy utilities. Oh yeah. I was gonna, the energy utilities industry right now is the one spending the most money I saw largely cuz they're playing ketchup. But also because they don't have these type of things for their consumers, they need the consumer app. They need to be able to do that delivery. They need to be able to do metrics. And they're the they're, they're the one spending right >>Now it's an arms race, but the, the vector shifts to value creation. So >>It's it just goes back to your post when it was a 2012, the trillion dollar baby. Yeah. It's a multi-trillion dollar baby that they, >>The world was going my chassis post on Forbes, headline trillion dollar baby 2012. You know, I should add it's happening. That's >>On the end. Yeah, exactly. >>Trillions of babies, Eric. Great to have you on the key. >>Thank you so much guys. >>Great to bring the data. Thanks for sharing. Check out ETR. If you're into the enterprise, want to know what's going on. They have a unique approach, very accurate in their survey data. They got a great market basket of, of, of, of, of data questions and people and community. Check it out. Thanks for coming on and sharing with. >>Thank you guys. Always enjoy. >>We'll be back with more coverage here in the cube in New York city live at summit 22. I'm John fur with Dave ante. We'll be right back.
SUMMARY :
Great to have you on the cube. I really appreciate the collaboration always. And by the way, And I can get it to some of the macro data in a minute, if that's all right. For example, we, we certainly saw, you know, Walmart, other retailers, So going back to that larger macro data, You seeing people move to Azure, you got Charlie bell over there, And I think that's an important caveat to make, Is there any insight into any underlying conditions that might be there on AWS And the number two answer the last, you know, quarter, last survey to 60%. And I remember, you know, when I first started doing this 10 years ago, AWS at a 70%, And so the question everybody's asking is will that change? I think that's why we're seeing it because you have to be in And so that is probably causing some friction and complexity in the customer base that again, And then you got big query from Google big Yep. What's the data say, say to us? So when you talk about who's taking that legacy market So legacy goes to legacy. But at the end of the day, what we're seeing from snowflake They are the masters at go to market. And if you compare the two shows, it's clear, who's winning snowflake is blew away Yeah. So I'd be curious to see where they are. And their product first company, yes. I mean data bricks, open source, bring in this tool that too, now you are seeing snowflake capitulate I mean, AWS has the S three and then, He finds the right. They did the stream lit acquisitions stream. I'm really nervous that they have to over factor the they're building data lakes and you know, snow. And I was gonna say, that's the thing with data bricks. I think, you know, to your point about the competition between AWS And I think I saw just the other day, In the cloud, what data bricks did would spark And that's something that when you talk about real time And I think but it could eventually from an economic standpoint, seep back into the enterprise arm base, They have to leapfrog though. Well, think they're trying to, that's what Capella is all about was not only, you know, Real quick on the numbers. So And now they're out there in the cloud as well. They got two, they got an S3 competitor. wow, those two would just be an absolute fantastic, you know, combination between the two of them. Yeah. And you're going and you got the edge and you got the edge So the emergence of this super So I've been following his lead on this and I'm looking forward to you guys doing that conference and that summit coming up from a I think, you know, when you talk about things like super cloud and you talk about things like metaverse, Wait a minute, Amazon has all the CapEx. No, it wasn't cause you weren't gonna go put all that money into CapEx expenditure to build that out. It might have a power law where you have a head of the long tail. And they're gonna bring that to their constituents. So that means they can then service the entire vertical as a service provider. And the industry cloud is becoming bigger and bigger and bigger. Remember in the early days of cloud, all the banks thought they could build their own cloud. And by the way, they can have a private cloud in their super cloud. And you know, it's interesting cause we're talking about financial services insurance, all the people we know spend money in So It's it just goes back to your post when it was a 2012, the trillion dollar baby. You know, I should add it's happening. On the end. Great to bring the data. Thank you guys. We'll be back with more coverage here in the cube in New York city live at summit 22.
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Breaking Analysis: Answering the top 10 questions about SuperCloud
>> From the theCUBE studios in Palo Alto in Boston, bringing you data driven insights from theCUBE and ETR. This is "Breaking Analysis" with Dave Vellante. >> Welcome to this week's Wikibon, theCUBE's insights powered by ETR. As we exited the isolation economy last year, supercloud is a term that we introduced to describe something new that was happening in the world of cloud. In this Breaking Analysis, we address the 10 most frequently asked questions we get around supercloud. Okay, let's review these frequently asked questions on supercloud that we're going to try to answer today. Look at an industry that's full of hype and buzzwords. Why the hell does anyone need a new term? Aren't hyperscalers building out superclouds? We'll try to answer why the term supercloud connotes something different from hyperscale clouds. And we'll talk about the problems that superclouds solve specifically. And we'll further define the critical aspects of a supercloud architecture. We often get asked, isn't this just multi-cloud? Well, we don't think so, and we'll explain why in this Breaking Analysis. Now in an earlier episode, we introduced the notion of super PaaS. Well, isn't a plain vanilla PaaS already a super PaaS? Again, we don't think so, and we'll explain why. Who will actually build and who are the players currently building superclouds? What workloads and services will run on superclouds? And 8-A or number nine, what are some examples that we can share of supercloud? And finally, we'll answer what you can expect next from us on supercloud? Okay, let's get started. Why do we need another buzzword? Well, late last year, ahead of re:Invent, we were inspired by a post from Jerry Chen called "Castles in the Cloud." Now in that blog post, he introduced the idea that there were sub-markets emerging in cloud that presented opportunities for investors and entrepreneurs that the cloud wasn't going to suck the hyperscalers. Weren't going to suck all the value out of the industry. And so we introduced this notion of supercloud to describe what we saw as a value layer emerging above the hyperscalers CAPEX gift, we sometimes call it. Now it turns out, that we weren't the only ones using the term as both Cornell and MIT have used the phrase in somewhat similar, but different contexts. The point is something new was happening in the AWS and other ecosystems. It was more than IaaS and PaaS, and wasn't just SaaS running in the cloud. It was a new architecture that integrates infrastructure, platform and software as services to solve new problems that the cloud vendors in our view, weren't addressing by themselves. It seemed to us that the ecosystem was pursuing opportunities across clouds that went beyond conventional implementations of multi-cloud. And we felt there was a structural change going on at the industry level, the supercloud, metaphorically was highlighting. So that's the background on why we felt a new catch phrase was warranted, love it or hate it. It's memorable and it's what we chose. Now to that last point about structural industry transformation. Andy Rappaport is sometimes and often credited with identifying the shift from the vertically integrated IBM mainframe era to the fragmented PC microprocesor-based era in his HBR article in 1991. In fact, it was David Moschella, who at the time was an IDC Analyst who first introduced the concept in 1987, four years before Rappaport's article was published. Moschella saw that it was clear that Intel, Microsoft, Seagate and others would replace the system vendors, and put that forth in a graphic that looked similar to the first two on this chart. We don't have to review the shift from IBM as the center of the industry to Wintel, that's well understood. What isn't as well known or accepted is what Moschella put out in his 2018 book called "Seeing Digital" which introduced the idea of "The Matrix" that's shown on the right hand side of this chart. Moschella posited that new services were emerging built on top of the internet and hyperscale clouds that would integrate other innovations and would define the next era of computing. He used the term Matrix because the conceptual depiction included not only horizontal technology rose like the cloud and the internet, but for the first time included connected industry verticals, the columns in this chart. Moschella pointed out that whereas historically, industry verticals had a closed value chain or stack and ecosystem of R&D, and production, and manufacturing, and distribution. And if you were in that industry, the expertise within that vertical generally stayed within that vertical and was critical to success. But because of digital and data, for the first time, companies were able to traverse industries, jump across industries and compete because data enabled them to do that. Examples, Amazon and content, payments, groceries, Apple, and payments, and content, and so forth. There are many examples. Data was now this unifying enabler and this marked a change in the structure of the technology landscape. And supercloud is meant to imply more than running in hyperscale clouds, rather it's the combination of multiple technologies enabled by CloudScale with new industry participants from those verticals, financial services and healthcare, manufacturing, energy, media, and virtually all in any industry. Kind of an extension of every company is a software company. Basically, every company now has the opportunity to build their own cloud or supercloud. And we'll come back to that. Let's first address what's different about superclouds relative to hyperscale clouds? You know, this one's pretty straightforward and obvious, I think. Hyperscale clouds, they're walled gardens where they want your data in their cloud and they want to keep you there. Sure, every cloud player realizes that not all data will go to their particular cloud so they're meeting customers where their data lives with initiatives like Amazon Outposts and Azure Arc, and Google Anthos. But at the end of the day, the more homogeneous they can make their environments, the better control, security, cost, and performance they can deliver. The more complex the environment, the more difficult it is to deliver on their brand promises. And of course, the lesser margin that's left for them to capture. Will the hyperscalers get more serious about cross-cloud services? Maybe, but they have plenty of work to do within their own clouds and within enabling their own ecosystems. They had a long way to go a lot of runway. So let's talk about specifically, what problems superclouds solve? We've all seen the stats from IDC or Gartner, or whomever the customers on average use more than one cloud. You know, two clouds, three clouds, five clouds, 20 clouds. And we know these clouds operate in disconnected silos for the most part. And that's a problem because each cloud requires different skills because the development environment is different as is the operating environment. They have different APIs, different primitives, and different management tools that are optimized for each respective hyperscale cloud. Their functions and value props don't extend to their competitors' clouds for the most part. Why would they? As a result, there's friction when moving between different clouds. It's hard to share data, it's hard to move work. It's hard to secure and govern data. It's hard to enforce organizational edicts and policies across these clouds, and on-prem. Supercloud is an architecture designed to create a single environment that enables management of workloads and data across clouds in an effort to take out complexity, accelerate application development, streamline operations and share data safely, irrespective of location. It's pretty straightforward, but non-trivial, which is why I always ask a company's CEO and executives if stock buybacks and dividends will yield as much return as building out superclouds that solve really specific and hard problems, and create differential value. Okay, let's dig a bit more into the architectural aspects of supercloud. In other words, what are the salient attributes of supercloud? So first and foremost, a supercloud runs a set of specific services designed to solve a unique problem and it can do so in more than one cloud. Superclouds leverage the underlying cloud native tooling of a hyperscale cloud, but they're optimized for a specific objective that aligns with the problem that they're trying to solve. For example, supercloud might be optimized for lowest cost or lowest latency, or sharing data, or governing, or securing that data, or higher performance for networking, for example. But the point is, the collection of services that is being delivered is focused on a unique value proposition that is not being delivered by the hyperscalers across clouds. A supercloud abstracts the underlying and siloed primitives of the native PaaS layer from the hyperscale cloud and then using its own specific platform as a service tooling, creates a common experience across clouds for developers and users. And it does so in a most efficient manner, meaning it has the metadata knowledge and management capabilities that can optimize for latency, bandwidth, or recovery, or data sovereignty, or whatever unique value that supercloud is delivering for the specific use case in their domain. And a supercloud comprises a super PaaS capability that allows ecosystem partners through APIs to add incremental value on top of the supercloud platform to fill gaps, accelerate features, and of course innovate. The services can be infrastructure-related, they could be application services, they could be data services, security services, user services, et cetera, designed and packaged to bring unique value to customers. Again, that hyperscalers are not delivering across clouds or on-premises. Okay, so another common question we get is, isn't that just multi-cloud? And what we'd say to that is yes, but no. You can call it multi-cloud 2.0, if you want, if you want to use it, it's kind of a commonly used rubric. But as Dell's Chuck Whitten proclaimed at Dell Technologies World this year, multi-cloud by design, is different than multi-cloud by default. Meaning to date, multi-cloud has largely been a symptom of what we've called multi-vendor or of M&A, you buy a company and they happen to use Google Cloud, and so you bring it in. And when you look at most so-called, multi-cloud implementations, you see things like an on-prem stack, which is wrapped in a container and hosted on a specific cloud or increasingly a technology vendor has done the work of building a cloud native version of their stack and running it on a specific cloud. But historically, it's been a unique experience within each cloud with virtually no connection between the cloud silos. Supercloud sets out to build incremental value across clouds and above hyperscale CAPEX that goes beyond cloud compatibility within each cloud. So if you want to call it multi-cloud 2.0, that's fine, but we chose to call it supercloud. Okay, so at this point you may be asking, well isn't PaaS already a version of supercloud? And again, we would say no, that supercloud and its corresponding superPaaS layer which is a prerequisite, gives the freedom to store, process and manage, and secure, and connect islands of data across a continuum with a common experience across clouds. And the services offered are specific to that supercloud and will vary by each offering. Your OpenShift, for example, can be used to construct a superPaaS, but in and of itself, isn't a superPaaS, it's generic. A superPaaS might be developed to support, for instance, ultra low latency database work. It would unlikely again, taking the OpenShift example, it's unlikely that off-the-shelf OpenShift would be used to develop such a low latency superPaaS layer for ultra low latency database work. The point is supercloud and its inherent superPaaS will be optimized to solve specific problems like that low latency example for distributed databases or fast backup and recovery for data protection, and ransomware, or data sharing, or data governance. Highly specific use cases that the supercloud is designed to solve for. Okay, another question we often get is who has a supercloud today and who's building a supercloud, and who are the contenders? Well, most companies that consider themselves cloud players will, we believe, be building or are building superclouds. Here's a common ETR graphic that we like to show with Net Score or spending momentum on the Y axis and overlap or pervasiveness in the ETR surveys on the X axis. And we've randomly chosen a number of players that we think are in the supercloud mix, and we've included the hyperscalers because they are enablers. Now remember, this is a spectrum of maturity it's a maturity model and we've added some of those industry players that we see building superclouds like CapitalOne, Goldman Sachs, Walmart. This is in deference to Moschella's observation around The Matrix and the industry structural changes that are going on. This goes back to every company, being a software company and rather than pattern match an outdated SaaS model, we see new industry structures emerging where software and data, and tools, specific to an industry will lead the next wave of innovation and bring in new value that traditional technology companies aren't going to solve, and the hyperscalers aren't going to solve. You know, we've talked a lot about Snowflake's data cloud as an example of supercloud. After being at Snowflake Summit, we're more convinced than ever that they're headed in this direction. VMware is clearly going after cross-cloud services you know, perhaps creating a new category. Basically, every large company we see either pursuing supercloud initiatives or thinking about it. Dell showed project Alpine at Dell Tech World, that's a supercloud. Snowflake introducing a new application development capability based on their superPaaS, our term of course, they don't use the phrase. Mongo, Couchbase, Nutanix, Pure Storage, Veeam, CrowdStrike, Okta, Zscaler. Yeah, all of those guys. Yes, Cisco and HPE. Even though on theCUBE at HPE Discover, Fidelma Russo said on theCUBE, she wasn't a fan of cloaking mechanisms, but then we talked to HPE's Head of Storage Services, Omer Asad is clearly headed in the direction that we would consider supercloud. Again, those cross-cloud services, of course, their emphasis is connecting as well on-prem. That single experience, which traditionally has not existed with multi-cloud or hybrid. And we're seeing the emergence of companies, smaller companies like Aviatrix and Starburst, and Clumio and others that are building versions of superclouds that solve for a specific problem for their customers. Even ISVs like Adobe, ADP, we've talked to UiPath. They seem to be looking at new ways to go beyond the SaaS model and add value within their cloud ecosystem specifically, around data as part of their and their customers digital transformations. So yeah, pretty much every tech vendor with any size or momentum and new industry players are coming out of hiding, and competing. Building superclouds that look a lot like Moschella's Matrix, with machine intelligence and blockchains, and virtual realities, and gaming, all enabled by the internet and hyperscale cloud CAPEX. So it's moving fast and it's the future in our opinion. So don't get too caught up in the past or you'll be left behind. Okay, what about examples? We've given a number in the past, but let's try to be a little bit more specific. Here are a few we've selected and we're going to answer the two questions in one section here. What workloads and services will run in superclouds and what are some examples? Let's start with analytics. Our favorite example is Snowflake, it's one of the furthest along with its data cloud, in our view. It's a supercloud optimized for data sharing and governance, query performance, and security, and ecosystem enablement. When you do things inside of that data cloud, what we call a super data cloud. Again, our term, not theirs. You can do things that you could not do in a single cloud. You can't do this with Redshift, You can't do this with SQL server and they're bringing new data types now with merging analytics or at least accommodate analytics and transaction type data, and bringing open source tooling with things like Apache Iceberg. And so it ticks the boxes we laid out earlier. I would say that a company like Databricks is also in that mix doing it, coming at it from a data science perspective, trying to create that consistent experience for data scientists and data engineering across clouds. Converge databases, running transaction and analytic workloads is another example. Take a look at what Couchbase is doing with Capella and how it's enabling stretching the cloud to the edge with ARM-based platforms and optimizing for low latency across clouds, and even out to the edge. Document database workloads, look at MongoDB, a very developer-friendly platform that with the Atlas is moving toward a supercloud model running document databases very, very efficiently. How about general purpose workloads? This is where VMware comes into to play. Very clearly, there's a need to create a common operating environment across clouds and on-prem, and out to the edge. And I say VMware is hard at work on that. Managing and moving workloads, and balancing workloads, and being able to recover very quickly across clouds for everyday applications. Network routing, take a look at what Aviatrix is doing across clouds, industry workloads. We see CapitalOne, it announced its cost optimization platform for Snowflake, piggybacking on Snowflake supercloud or super data cloud. And in our view, it's very clearly going to go after other markets is going to test it out with Snowflake, running, optimizing on AWS and it's going to expand to other clouds as Snowflake's business and those other clouds grows. Walmart working with Microsoft to create an on-premed Azure experience that's seamless. Yes, that counts, on-prem counts. If you can create that seamless and continuous experience, identical experience from on-prem to a hyperscale cloud, we would include that as a supercloud. You know, we've written about what Goldman is doing. Again, connecting its on-prem data and software tooling, and other capabilities to AWS for scale. And we can bet dollars to donuts that Oracle will be building a supercloud in healthcare with its Cerner acquisition. Supercloud is everywhere you look. So I'm sorry, naysayers it's happening all around us. So what's next? Well, with all the industry buzz and debate about the future, John Furrier and I, have decided to host an event in Palo Alto, we're motivated and inspired to further this conversation. And we welcome all points of view, positive, negative, multi-cloud, supercloud, hypercloud, all welcome. So theCUBE on Supercloud is coming on August 9th, out of our Palo Alto studios, we'll be running a live program on the topic. We've reached out to a number of industry participants, VMware, Snowflake, Confluent, Sky High Security, Gee Rittenhouse's new company, HashiCorp, CloudFlare. We've hit up Red Hat and we expect many of these folks will be in our studios on August 9th. And we've invited a number of industry participants as well that we're excited to have on. From industry, from financial services, from healthcare, from retail, we're inviting analysts, thought leaders, investors. We're going to have more detail in the coming weeks, but for now, if you're interested, please reach out to me or John with how you think you can advance the discussion and we'll see if we can fit you in. So mark your calendars, stay tuned for more information. Okay, that's it for today. Thanks to Alex Myerson who handles production and manages the podcast for Breaking Analysis. And I want to thank Kristen Martin and Cheryl Knight, they help get the word out on social and in our newsletters. And Rob Hof is our editor in chief over at SiliconANGLE, who does a lot of editing and appreciate you posting on SiliconANGLE, Rob. Thanks to all of you. Remember, all these episodes are available as podcasts wherever you listen. All you got to do is search Breaking Analysis podcast. It publish each week on wikibon.com and siliconangle.com. You can email me directly at david.vellante@siliconangle.com or DM me @DVellante, or comment on my LinkedIn post. And please do check out ETR.ai for the best survey data. And the enterprise tech business will be at AWS NYC Summit next Tuesday, July 12th. So if you're there, please do stop by and say hello to theCUBE, it's at the Javits Center. This is Dave Vellante for theCUBE insights powered by ETR. Thanks for watching. And we'll see you next time on "Breaking Analysis." (bright music)
SUMMARY :
From the theCUBE studios and how it's enabling stretching the cloud
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Breaking Analysis: Answering the top 10 questions about supercloud
>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR. This is "Breaking Analysis" with Dave Vallante. >> Welcome to this week's Wikibon CUBE Insights powered by ETR. As we exited the isolation economy last year, Supercloud is a term that we introduced to describe something new that was happening in the world of cloud. In this "Breaking Analysis," we address the 10 most frequently asked questions we get around Supercloud. Okay, let's review these frequently asked questions on Supercloud that we're going to try to answer today. Look at an industry that's full of hype and buzzwords. Why the hell does anyone need a new term? Aren't hyperscalers building out Superclouds? We'll try to answer why the term Supercloud connotes something different from hyperscale clouds. And we'll talk about the problems that Superclouds solve specifically, and we'll further define the critical aspects of a Supercloud architecture. We often get asked, "Isn't this just multi-cloud?" Well, we don't think so, and we'll explain why in this "Breaking Analysis." Now, in an earlier episode, we introduced the notion of super PaaS. Well, isn't a plain vanilla PaaS already a super PaaS? Again, we don't think so, and we'll explain why. Who will actually build and who are the players currently building Superclouds? What workloads and services will run on Superclouds? And eight A or number nine, what are some examples that we can share of Supercloud? And finally, we'll answer what you can expect next from us on Supercloud. Okay, let's get started. Why do we need another buzzword? Well, late last year ahead of re:Invent, we were inspired by a post from Jerry Chen called castles in the cloud. Now, in that blog post, he introduced the idea that there were submarkets emerging in cloud that presented opportunities for investors and entrepreneurs. That the cloud wasn't going to suck the hyperscalers, weren't going to suck all the value out of the industry. And so we introduced this notion of Supercloud to describe what we saw as a value layer emerging above the hyperscalers CAPEX gift, we sometimes call it. Now, it turns out that we weren't the only ones using the term, as both Cornell and MIT, have used the phrase in somewhat similar, but different contexts. The point is, something new was happening in the AWS and other ecosystems. It was more than IS and PaaS, and wasn't just SaaS running in the cloud. It was a new architecture that integrates infrastructure, platform and software as services, to solve new problems that the cloud vendors, in our view, weren't addressing by themselves. It seemed to us that the ecosystem was pursuing opportunities across clouds that went beyond conventional implementations of multi-cloud. And we felt there was a structural change going on at the industry level. The Supercloud metaphorically was highlighting. So that's the background on why we felt a new catch phrase was warranted. Love it or hate it, it's memorable and it's what we chose. Now, to that last point about structural industry transformation. Andy Rapaport is sometimes and often credited with identifying the shift from the vertically integrated IBM mainframe era to the fragmented PC microprocesor based era in his HBR article in 1991. In fact, it was David Moschella, who at the time was an IDC analyst who first introduced the concept in 1987, four years before Rapaport's article was published. Moschella saw that it was clear that Intel, Microsoft, Seagate and others would replace the system vendors and put that forth in a graphic that looked similar to the first two on this chart. We don't have to review the shift from IBM as the center of the industry to Wintel. That's well understood. What isn't as well known or accepted is what Moschella put out in his 2018 book called "Seeing Digital" which introduced the idea of the matrix that's shown on the right hand side of this chart. Moschella posited that new services were emerging, built on top of the internet and hyperscale clouds that would integrate other innovations and would define the next era of computing. He used the term matrix, because the conceptual depiction included, not only horizontal technology rows, like the cloud and the internet, but for the first time included connected industry verticals, the columns in this chart. Moschella pointed out that, whereas historically, industry verticals had a closed value chain or stack and ecosystem of R&D and production and manufacturing and distribution. And if you were in that industry, the expertise within that vertical generally stayed within that vertical and was critical to success. But because of digital and data, for the first time, companies were able to traverse industries jump across industries and compete because data enabled them to do that. Examples, Amazon and content, payments, groceries, Apple and payments, and content and so forth. There are many examples. Data was now this unifying enabler and this marked a change in the structure of the technology landscape. And Supercloud is meant to imply more than running in hyperscale clouds. Rather, it's the combination of multiple technologies, enabled by cloud scale with new industry participants from those verticals; financial services, and healthcare, and manufacturing, energy, media, and virtually all and any industry. Kind of an extension of every company is a software company. Basically, every company now has the opportunity to build their own cloud or Supercloud. And we'll come back to that. Let's first address what's different about Superclouds relative to hyperscale clouds. Now, this one's pretty straightforward and obvious, I think. Hyperscale clouds, they're walled gardens where they want your data in their cloud and they want to keep you there. Sure, every cloud player realizes that not all data will go to their particular cloud. So they're meeting customers where their data lives with initiatives like Amazon Outposts and Azure Arc and Google Antos. But at the end of the day, the more homogeneous they can make their environments, the better control, security, costs, and performance they can deliver. The more complex the environment, the more difficult it is to deliver on their brand promises. And, of course, the less margin that's left for them to capture. Will the hyperscalers get more serious about cross cloud services? Maybe, but they have plenty of work to do within their own clouds and within enabling their own ecosystems. They have a long way to go, a lot of runway. So let's talk about specifically, what problems Superclouds solve. We've all seen the stats from IDC or Gartner or whomever, that customers on average use more than one cloud, two clouds, three clouds, five clouds, 20 clouds. And we know these clouds operate in disconnected silos for the most part. And that's a problem, because each cloud requires different skills, because the development environment is different as is the operating environment. They have different APIs, different primitives, and different management tools that are optimized for each respective hyperscale cloud. Their functions and value props don't extend to their competitors' clouds for the most part. Why would they? As a result, there's friction when moving between different clouds. It's hard to share data. It's hard to move work. It's hard to secure and govern data. It's hard to enforce organizational edicts and policies across these clouds and on-prem. Supercloud is an architecture designed to create a single environment that enables management of workloads and data across clouds in an effort to take out complexity, accelerate application development, streamline operations, and share data safely, irrespective of location. It's pretty straightforward, but non-trivial, which is why I always ask a company's CEO and executives if stock buybacks and dividends will yield as much return as building out Superclouds that solve really specific and hard problems and create differential value. Okay, let's dig a bit more into the architectural aspects of Supercloud. In other words, what are the salient attributes of Supercloud? So, first and foremost, a Supercloud runs a set of specific services designed to solve a unique problem, and it can do so in more than one cloud. Superclouds leverage the underlying cloud native tooling of a hyperscale cloud, but they're optimized for a specific objective that aligns with the problem that they're trying to solve. For example, Supercloud might be optimized for lowest cost or lowest latency or sharing data or governing or securing that data or higher performance for networking, for example. But the point is, the collection of services that is being delivered is focused on a unique value proposition that is not being delivered by the hyperscalers across clouds. A Supercloud abstracts the underlying and siloed primitives of the native PaaS layer from the hyperscale cloud, and then using its own specific platform as a service tooling, creates a common experience across clouds for developers and users. And it does so in the most efficient manner, meaning it has the metadata knowledge and management capabilities that can optimize for latency, bandwidth, or recovery or data sovereignty, or whatever unique value that Supercloud is delivering for the specific use case in their domain. And a Supercloud comprises a super PaaS capability that allows ecosystem partners through APIs to add incremental value on top of the Supercloud platform to fill gaps, accelerate features, and of course, innovate. The services can be infrastructure related, they could be application services, they could be data services, security services, user services, et cetera, designed and packaged to bring unique value to customers. Again, that hyperscalers are not delivering across clouds or on premises. Okay, so another common question we get is, "Isn't that just multi-cloud?" And what we'd say to that is yeah, "Yes, but no." You can call it multi-cloud 2.0, if you want. If you want to use, it's kind of a commonly used rubric. But as Dell's Chuck Whitten proclaimed at Dell Technologies World this year, multi-cloud, by design, is different than multi-cloud by default. Meaning, to date, multi-cloud has largely been a symptom of what we've called multi-vendor or of M&A. You buy a company and they happen to use Google cloud. And so you bring it in. And when you look at most so-called multi-cloud implementations, you see things like an on-prem stack, which is wrapped in a container and hosted on a specific cloud. Or increasingly, a technology vendor has done the work of building a cloud native version of their stack and running it on a specific cloud. But historically, it's been a unique experience within each cloud, with virtually no connection between the cloud silos. Supercloud sets out to build incremental value across clouds and above hyperscale CAPEX that goes beyond cloud compatibility within each cloud. So, if you want to call it multi-cloud 2.0, that's fine, but we chose to call it Supercloud. Okay, so at this point you may be asking, "Well isn't PaaS already a version of Supercloud?" And again, we would say, "No." That Supercloud and its corresponding super PaaS layer, which is a prerequisite, gives the freedom to store, process, and manage and secure and connect islands of data across a continuum with a common experience across clouds. And the services offered are specific to that Supercloud and will vary by each offering. OpenShift, for example, can be used to construct a super PaaS, but in and of itself, isn't a super PaaS, it's generic. A super PaaS might be developed to support, for instance, ultra low latency database work. It would unlikely, again, taking the OpenShift example, it's unlikely that off the shelf OpenShift would be used to develop such a low latency, super PaaS layer for ultra low latency database work. The point is, Supercloud and its inherent super PaaS will be optimized to solve specific problems like that low latency example for distributed databases or fast backup in recovery for data protection and ransomware, or data sharing or data governance. Highly specific use cases that the Supercloud is designed to solve for. Okay, another question we often get is, "Who has a Supercloud today and who's building a Supercloud and who are the contenders?" Well, most companies that consider themselves cloud players will, we believe, be building or are building Superclouds. Here's a common ETR graphic that we like to show with net score or spending momentum on the Y axis, and overlap or pervasiveness in the ETR surveys on the X axis. And we've randomly chosen a number of players that we think are in the Supercloud mix. And we've included the hyperscalers because they are enablers. Now, remember, this is a spectrum of maturity. It's a maturity model. And we've added some of those industry players that we see building Superclouds like Capital One, Goldman Sachs, Walmart. This is in deference to Moschella's observation around the matrix and the industry structural changes that are going on. This goes back to every company being a software company. And rather than pattern match and outdated SaaS model, we see new industry structures emerging where software and data and tools specific to an industry will lead the next wave of innovation and bring in new value that traditional technology companies aren't going to solve. And the hyperscalers aren't going to solve. We've talked a lot about Snowflake's data cloud as an example of Supercloud. After being at Snowflake Summit, we're more convinced than ever that they're headed in this direction. VMware is clearly going after cross cloud services, perhaps creating a new category. Basically, every large company we see either pursuing Supercloud initiatives or thinking about it. Dell showed Project Alpine at Dell Tech World. That's a Supercloud. Snowflake introducing a new application development capability based on their super PaaS, our term, of course. They don't use the phrase. Mongo, Couchbase, Nutanix, Pure Storage, Veeam, CrowdStrike, Okta, Zscaler. Yeah, all of those guys. Yes, Cisco and HPE. Even though on theCUBE at HPE Discover, Fidelma Russo said on theCUBE, she wasn't a fan of cloaking mechanisms. (Dave laughing) But then we talked to HPE's head of storage services, Omer Asad, and he's clearly headed in the direction that we would consider Supercloud. Again, those cross cloud services, of course, their emphasis is connecting as well on-prem. That single experience, which traditionally has not existed with multi-cloud or hybrid. And we're seeing the emergence of smaller companies like Aviatrix and Starburst and Clumio and others that are building versions of Superclouds that solve for a specific problem for their customers. Even ISVs like Adobe, ADP, we've talked to UiPath. They seem to be looking at new ways to go beyond the SaaS model and add value within their cloud ecosystem, specifically around data as part of their and their customer's digital transformations. So yeah, pretty much every tech vendor with any size or momentum, and new industry players are coming out of hiding and competing, building Superclouds that look a lot like Moschella's matrix, with machine intelligence and blockchains and virtual realities and gaming, all enabled by the internet and hyperscale cloud CAPEX. So it's moving fast and it's the future in our opinion. So don't get too caught up in the past or you'll be left behind. Okay, what about examples? We've given a number in the past but let's try to be a little bit more specific. Here are a few we've selected and we're going to answer the two questions in one section here. What workloads and services will run in Superclouds and what are some examples? Let's start with analytics. Our favorite example of Snowflake. It's one of the furthest along with its data cloud, in our view. It's a Supercloud optimized for data sharing and governance, and query performance, and security, and ecosystem enablement. When you do things inside of that data cloud, what we call a super data cloud. Again, our term, not theirs. You can do things that you could not do in a single cloud. You can't do this with Redshift. You can't do this with SQL server. And they're bringing new data types now with merging analytics or at least accommodate analytics and transaction type data and bringing open source tooling with things like Apache Iceberg. And so, it ticks the boxes we laid out earlier. I would say that a company like Databricks is also in that mix, doing it, coming at it from a data science perspective trying to create that consistent experience for data scientists and data engineering across clouds. Converge databases, running transaction and analytic workloads is another example. Take a look at what Couchbase is doing with Capella and how it's enabling stretching the cloud to the edge with arm based platforms and optimizing for low latency across clouds, and even out to the edge. Document database workloads, look at Mongo DB. A very developer friendly platform that where the Atlas is moving toward a Supercloud model, running document databases very, very efficiently. How about general purpose workloads? This is where VMware comes into play. Very clearly, there's a need to create a common operating environment across clouds and on-prem and out to the edge. And I say, VMware is hard at work on that, managing and moving workloads and balancing workloads, and being able to recover very quickly across clouds for everyday applications. Network routing, take a look at what Aviatrix is doing across clouds. Industry workloads, we see Capital One. It announced its cost optimization platform for Snowflake, piggybacking on Snowflake's Supercloud or super data cloud. And in our view, it's very clearly going to go after other markets. It's going to test it out with Snowflake, optimizing on AWS, and it's going to expand to other clouds as Snowflake's business and those other clouds grows. Walmart working with Microsoft to create an on-premed Azure experience that's seamless. Yes, that counts, on-prem counts. If you can create that seamless and continuous experience, identical experience from on-prem to a hyperscale cloud, we would include that as a Supercloud. We've written about what Goldman is doing. Again, connecting its on-prem data and software tooling, and other capabilities to AWS for scale. And you can bet dollars to donuts that Oracle will be building a Supercloud in healthcare with its Cerner acquisition. Supercloud is everywhere you look. So I'm sorry, naysayers, it's happening all around us. So what's next? Well, with all the industry buzz and debate about the future, John Furrier and I have decided to host an event in Palo Alto. We're motivated and inspired to further this conversation. And we welcome all points of view, positive, negative, multi-cloud, Supercloud, HyperCloud, all welcome. So theCUBE on Supercloud is coming on August 9th out of our Palo Alto studios. We'll be running a live program on the topic. We've reached out to a number of industry participants; VMware, Snowflake, Confluent, Skyhigh Security, G. Written House's new company, HashiCorp, CloudFlare. We've hit up Red Hat and we expect many of these folks will be in our studios on August 9th. And we've invited a number of industry participants as well that we're excited to have on. From industry, from financial services, from healthcare, from retail, we're inviting analysts, thought leaders, investors. We're going to have more detail in the coming weeks, but for now, if you're interested, please reach out to me or John with how you think you can advance the discussion, and we'll see if we can fit you in. So mark your calendars, stay tuned for more information. Okay, that's it for today. Thanks to Alex Myerson who handles production and manages the podcast for "Breaking Analysis." And I want to thank Kristen Martin and Cheryl Knight. They help get the word out on social and in our newsletters. And Rob Hof is our editor in chief over at SiliconANGLE, who does a lot of editing and appreciate you posting on SiliconANGLE, Rob. Thanks to all of you. Remember, all these episodes are available as podcasts wherever you listen. All you got to do is search, breaking analysis podcast. I publish each week on wikibon.com and siliconangle.com. Or you can email me directly at david.vellante@siliconangle.com. Or DM me @DVallante, or comment on my LinkedIn post. And please, do check out etr.ai for the best survey data in the enterprise tech business. We'll be at AWS NYC summit next Tuesday, July 12th. So if you're there, please do stop by and say hello to theCUBE. It's at the Javits Center. This is Dave Vallante for theCUBE Insights, powered by ETR. Thanks for watching. And we'll see you next time on "Breaking Analysis." (slow music)
SUMMARY :
This is "Breaking Analysis" stretching the cloud to the edge
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Breaking Analysis: H1 of ‘22 was ugly…H2 could be worse Here’s why we’re still optimistic
>> From theCUBE Studios in Palo Alto in Boston, bringing you data driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> After a two-year epic run in tech, 2022 has been an epically bad year. Through yesterday, The NASDAQ composite is down 30%. The S$P 500 is off 21%. And the Dow Jones Industrial average 16% down. And the poor holders at Bitcoin have had to endure a nearly 60% decline year to date. But judging by the attendance and enthusiasm, in major in-person tech events this spring. You'd never know that tech was in the tank. Moreover, walking around the streets of Las Vegas, where most tech conferences are held these days. One can't help but notice that the good folks of Main Street, don't seem the least bit concerned that the economy is headed for a recession. Hello, and welcome to this weeks Wiki Bond Cube Insights powered by ETR. In this Breaking Analysis we'll share our main takeaways from the first half of 2022. And talk about the outlook for tech going forward, and why despite some pretty concerning headwinds we remain sanguine about tech generally, but especially enterprise tech. Look, here's the bumper sticker on why many folks are really bearish at the moment. Of course, inflation is high, other than last year, the previous inflation high this century was in July of 2008, it was 5.6%. Inflation has proven to be very, very hard to tame. You got gas at $7 dollars a gallon. Energy prices they're not going to suddenly drop. Interest rates are climbing, which will eventually damage housing. Going to have that ripple effect, no doubt. We're seeing layoffs at companies like Tesla and the crypto names are also trimming staff. Workers, however are still in short supply. So wages are going up. Companies in retail are really struggling with the right inventory, and they can't even accurately guide on their earnings. We've seen a version of this movie before. Now, as it pertains to tech, Crawford Del Prete, who's the CEO of IDC explained this on theCUBE this very week. And I thought he did a really good job. He said the following, >> Matt, you have a great statistic that 80% of companies used COVID as their point to pivot into digital transformation. And to invest in a different way. And so what we saw now is that tech is now where I think companies need to focus. They need to invest in tech. They need to make people more productive with tech and it played out in the numbers. Now so this year what's fascinating is we're looking at two vastly different markets. We got gasoline at $7 a gallon. We've got that affecting food prices. Interesting fun fact recently it now costs over $1,000 to fill an 18 wheeler. All right, based on, I mean, this just kind of can't continue. So you think about it. >> Don't put the boat in the water. >> Yeah, yeah, yeah. Good luck if ya, yeah exactly. So a family has kind of this bag of money, and that bag of money goes up by maybe three, 4% every year, depending upon earnings. So that is sort of sloshing around. So if food and fuel and rent is taking up more, gadgets and consumer tech are not, you're going to use that iPhone a little longer. You're going to use that Android phone a little longer. You're going to use that TV a little longer. So consumer tech is getting crushed, really it's very, very, and you saw it immediately in ad spending. You've seen it in Meta, you've seen it in Facebook. Consumer tech is doing very, very, it is tough. Enterprise tech, we haven't been in the office for two and a half years. We haven't upgraded whether that be campus wifi, whether that be servers, whether that be commercial PCs as much as we would have. So enterprise tech, we're seeing double digit order rates. We're seeing strong, strong demand. We have combined that with a component shortage, and you're seeing some enterprise companies with a quarter of backlog, I mean that's really unheard of. >> And higher prices, which also profit. >> And therefore that drives up the prices. >> And this is a theme that we've heard this year at major tech events, they've really come roaring back. Last year, theCUBE had a huge presence at AWS Reinvent. The first Reinvent since 2019, it was really well attended. Now this was before the effects of the omicron variant, before they were really well understood. And in the first quarter of 2022, things were pretty quiet as far as tech events go But theCUBE'a been really busy this spring and early into the summer. We did 12 physical events as we're showing here in the slide. Coupa, did Women in Data Science at Stanford, Coupa Inspire was in Las Vegas. Now these are both smaller events, but they were well attended and beat expectations. San Francisco Summit, the AWS San Francisco Summit was a bit off, frankly 'cause of the COVID concerns. They were on the rise, then we hit Dell Tech World which was packed, it had probably around 7,000 attendees. Now Dockercon was virtual, but we decided to include it here because it was a huge global event with watch parties and many, many tens of thousands of people attending. Now the Red Hat Summit was really interesting. The choice that Red Hat made this year. It was purposefully scaled down and turned into a smaller VIP event in Boston at the Western, a couple thousand people only. It was very intimate with a much larger virtual presence. VeeamON was very well attended, not as large as previous VeeamON events, but again beat expectations. KubeCon and Cloud Native Con was really successful in Spain, Valencia, Spain. PagerDuty Summit was again a smaller intimate event in San Francisco. And then MongoDB World was at the new Javits Center and really well attended over the three day period. There were lots of developers there, lots of business people, lots of ecosystem partners. And then the Snowflake summit in Las Vegas, it was the most vibrant from the standpoint of the ecosystem with nearly 10,000 attendees. And I'll come back to that in a moment. Amazon re:Mars is the Amazon AI robotic event, it's smaller but very, very cool, a lot of innovation. And just last week we were at HPE Discover. They had around 8,000 people attending which was really good. Now I've been to over a dozen HPE or HPE Discover events, within Europe and the United States over the past decade. And this was by far the most vibrant, lot of action. HPE had a little spring in its step because the company's much more focused now but people was really well attended and people were excited to be there, not only to be back at physical events, but also to hear about some of the new innovations that are coming and HPE has a long way to go in terms of building out that ecosystem, but it's starting to form. So we saw that last week. So tech events are back, but they are smaller. And of course now a virtual overlay, they're hybrid. And just to give you some context, theCUBE did, as I said 12 physical events in the first half of 2022. Just to compare that in 2019, through June of that year we had done 35 physical events. Yeah, 35. And what's perhaps more interesting is we had our largest first half ever in our 12 year history because we're doing so much hybrid and virtual to compliment the physical. So that's the new format is CUBE plus digital or sometimes just digital but that's really what's happening in our business. So I think it's a reflection of what's happening in the broader tech community. So everyone's still trying to figure that out but it's clear that events are back and there's no replacing face to face. Or as I like to say, belly to belly, because deals are done at physical events. All these events we've been to, the sales people are so excited. They're saying we're closing business. Pipelines coming out of these events are much stronger, than they are out of the virtual events but the post virtual event continues to deliver that long tail effect. So that's not going to go away. The bottom line is hybrid is the new model. Okay let's look at some of the big themes that we've taken away from the first half of 2022. Now of course, this is all happening under the umbrella of digital transformation. I'm not going to talk about that too much, you've had plenty of DX Kool-Aid injected into your veins over the last 27 months. But one of the first observations I'll share is that the so-called big data ecosystem that was forming during the hoop and around, the hadoop infrastructure days and years. then remember it dispersed, right when the cloud came in and kind of you know, not wiped out but definitely dampened the hadoop enthusiasm for on-prem, the ecosystem dispersed, but now it's reforming. There are large pockets that are obviously seen in the various clouds. And we definitely see a ecosystem forming around MongoDB and the open source community gathering in the data bricks ecosystem. But the most notable momentum is within the Snowflake ecosystem. Snowflake is moving fast to win the day in the data ecosystem. They're providing a single platform that's bringing different data types together. Live data from systems of record, systems of engagement together with so-called systems of insight. These are converging and while others notably, Oracle are architecting for this new reality, Snowflake is leading with the ecosystem momentum and a new stack is emerging that comprises cloud infrastructure at the bottom layer. Data PaaS layer for app dev and is enabling an ecosystem of partners to build data products and data services that can be monetized. That's the key, that's the top of the stack. So let's dig into that further in a moment but you're seeing machine intelligence and data being driven into applications and the data and application stacks they're coming together to support the acceleration of physical into digital. It's happening right before our eyes in every industry. We're also seeing the evolution of cloud. It started with the SaaS-ification of the enterprise where organizations realized that they didn't have to run their own software on-prem and it made sense to move to SaaS for CRM or HR, certainly email and collaboration and certain parts of ERP and early IS was really about getting out of the data center infrastructure management business called that cloud 1.0, and then 2.0 was really about changing the operating model. And now we're seeing that operating model spill into on-prem workloads finally. We're talking about here about initiatives like HPE's Green Lake, which we heard a lot about last week at Discover and Dell's Apex, which we heard about in May, in Las Vegas. John Furrier had a really interesting observation that basically this is HPE's and Dell's version of outposts. And I found that interesting because outpost was kind of a wake up call in 2018 and a shot across the bow at the legacy enterprise infrastructure players. And they initially responded with these flexible financial schemes, but finally we're seeing real platforms emerge. Again, we saw this at Discover and at Dell Tech World, early implementations of the cloud operating model on-prem. I mean, honestly, you're seeing things like consoles and billing, similar to AWS circa 2014, but players like Dell and HPE they have a distinct advantage with respect to their customer bases, their service organizations, their very large portfolios, especially in the case of Dell and the fact that they have more mature stacks and knowhow to run mission critical enterprise applications on-prem. So John's comment was quite interesting that these firms are basically building their own version of outposts. Outposts obviously came into their wheelhouse and now they've finally responded. And this is setting up cloud 3.0 or Supercloud, as we like to call it, an abstraction layer, that sits above the clouds that serves as a unifying experience across a continuum of on-prem across clouds, whether it's AWS, Azure, or Google. And out to both the near and far edge, near edge being a Lowes or a Home Depot, but far edge could be space. And that edge again is fragmented. You've got the examples like the retail stores at the near edge. Outer space maybe is the far edge and IOT devices is perhaps the tiny edge. No one really knows how the tiny edge is going to play out but it's pretty clear that it's not going to comprise traditional X86 systems with a cool name tossed out to the edge. Rather, it's likely going to require a new low cost, low power, high performance architecture, most likely RM based that will enable things like realtime AI inferencing at that edge. Now we've talked about this a lot on Breaking Analysis, so I'm not going to double click on it. But suffice to say that it's very possible that new innovations are going to emerge from the tiny edge that could really disrupt the enterprise in terms of price performance. Okay, two other quick observations. One is that data protection is becoming a much closer cohort to the security stack where data immutability and air gaps and fast recovery are increasingly becoming a fundamental component of the security strategy to combat ransomware and recover from other potential hacks or disasters. And I got to say from our observation, Veeam is leading the pack here. It's now claiming the number one revenue spot in a statistical dead heat with the Dell's data protection business. That's according to Veeam, according to IDC. And so that space continues to be of interest. And finally, Broadcom's acquisition of Dell. It's going to have ripple effects throughout the enterprise technology business. And there of course, there are a lot of questions that remain, but the one other thing that John Furrier and I were discussing last night John looked at me and said, "Dave imagine if VMware runs better on Broadcom components and OEMs that use Broadcom run VMware better, maybe Broadcom doesn't even have to raise prices on on VMware licenses. Maybe they'll just raise prices on the OEMs and let them raise prices to the end customer." Interesting thought, I think because Broadcom is so P&L focused that it's probably not going to be the prevailing model but we'll see what happens to some of the strategic projects rather like Monterey and Capitola and Thunder. We've talked a lot about project Monterey, the others we'll see if they can make the cut. That's one of the big concerns because it's how OEMs like the ones that are building their versions of outposts are going to compete with the cloud vendors, namely AWS in the future. I want to come back to the comment on the data stack for a moment that we were talking about earlier, we talked about how the big data ecosystem that was once coalescing around hadoop dispersed. Well, the data value chain is reforming and we think it looks something like this picture, where cloud infrastructure lives at the bottom. We've said many times the cloud is expanding and evolving. And if companies like Dell and HPE can truly build a super cloud infrastructure experience then they will be in a position to capture more of the data value. If not, then it's going to go to the cloud players. And there's a live data layer that is increasingly being converged into platforms that not only simplify the movement in ELTing of data but also allow organizations to compress the time to value. Now there's a layer above that, we sometimes call it the super PaaS layer if you will, that must comprise open source tooling, partners are going to write applications and leverage platform APIs and build data products and services that can be monetized at the top of the stack. So when you observe the battle for the data future it's unlikely that any one company is going to be able to do this all on their own, which is why I often joke that the 2020s version of a sweaty Steve Bomber running around the stage, screaming, developers, developers developers, and getting the whole audience into it is now about ecosystem ecosystem ecosystem. Because when you need to fill gaps and accelerate features and provide optionality a list of capabilities on the left hand side of this chart, that's going to come from a variety of different companies and places, we're talking about catalogs and AI tools and data science capabilities, data quality, governance tools and it should be of no surprise to followers of Breaking Analysis that on the right hand side of this chart we're including the four principles of data mesh, which of course were popularized by Zhamak Dehghani. So decentralized data ownership, data as products, self-serve platform and automated or computational governance. Now whether this vision becomes a reality via a proprietary platform like Snowflake or somehow is replicated by an open source remains to be seen but history generally shows that a defacto standard for more complex problems like this is often going to emerge prior to an open source alternative. And that would be where I would place my bets. Although even that proprietary platform has to include open source optionality. But it's not a winner take all market. It's plenty of room for multiple players and ecosystem innovators, but winner will definitely take more in my opinion. Okay, let's close with some ETR data that looks at some of those major platform plays who talk a lot about digital transformation and world changing impactful missions. And they have the resources really to compete. This is an XY graphic. It's a view that we often show, it's got net score on the vertical access. That's a measure of spending momentum, and overlap or presence in the ETR survey. That red, that's the horizontal access. The red dotted line at 40% indicates that the platform is among the highest in terms of spending velocity. Which is why I always point out how impressive that makes AWS and Azure because not only are they large on the horizontal axis, the spending momentum on those two platforms rivals even that of Snowflake which continues to lead all on the vertical access. Now, while Google has momentum, given its goals and resources, it's well behind the two leaders. We've added Service Now and Salesforce, two platform names that have become the next great software companies. Joining likes of Oracle, which we show here and SAP not shown along with IBM, you can see them on this chart. We've also plotted MongoDB, which we think has real momentum as a company generally but also with Atlas, it's managed cloud database as a service specifically and Red Hat with trying to become the standard for app dev in Kubernetes environments, which is the hottest trend right now in application development and application modernization. Everybody's doing something with Kubernetes and of course, Red Hat with OpenShift wants to make that a better experience than do it yourself. The DYI brings a lot more complexity. And finally, we've got HPE and Dell both of which we've talked about pretty extensively here and VMware and Cisco. Now Cisco is executing on its portfolio strategy. It's got a lot of diverse components to its company. And it's coming at the cloud of course from a networking and security perspective. And that's their position of strength. And VMware is a staple of the enterprise. Yes, there's some uncertainty with regards to the Broadcom acquisition, but one thing is clear vSphere isn't going anywhere. It's entrenched and will continue to run lots of IT for years to come because it's the best platform on the planet. Now, of course, these are just some of the players in the mix. We expect that numerous non-traditional technology companies this is important to emerge as new cloud players. We've put a lot of emphasis on the data ecosystem because to us that's really going to be the main spring of digital, i.e., a digital company is a data company and that means an ecosystem of data partners that can advance outcomes like better healthcare, faster drug discovery, less fraud, cleaner energy, autonomous vehicles that are safer, smarter, more efficient grids and factories, better government and virtually endless litany of societal improvements that can be addressed. And these companies will be building innovations on top of cloud platforms creating their own super clouds, if you will. And they'll come from non-traditional places, industries, finance that take their data, their software, their tooling bring them to their customers and run them on various clouds. Okay, that's it for today. Thanks to Alex Myerson, who is on production and does the podcast for Breaking Analysis, Kristin Martin and Cheryl Knight, they help get the word out. And Rob Hoofe is our editor and chief over at Silicon Angle who helps edit our posts. Remember all these episodes are available as podcasts wherever you listen. All you got to do is search Breaking Analysis podcast. I publish each week on wikibon.com and siliconangle.com. You can email me directly at david.vellante@siliconangle.com or DM me at dvellante, or comment on my LinkedIn posts. And please do check out etr.ai for the best survey data in the enterprise tech business. This is Dave Vellante for theCUBE's Insights powered by ETR. Thanks for watching be well. And we'll see you next time on Breaking Analysis. (upbeat music)
SUMMARY :
This is Breaking Analysis that the good folks of Main Street, and it played out in the numbers. haven't been in the office And higher prices, And therefore that is that the so-called big data ecosystem
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Day One Wrap | HPE Discover 2022
>>The cube presents HPE discover 2022 brought to you by HPE. >>Hey everyone. Welcome back to the Cube's day one coverage of HPE discover 22 live from the Venetian in Las Vegas. I got a power panel here, Lisa Martin, with Dave Valante, John furrier, Holger Mueller also joins us. We are gonna wrap this, like you've never seen a rap before guys. Lot of momentum today, lot, lot of excitement, about 8,000 or so customers, partners, HPE leaders here. Holger. Let's go ahead and start with you. What are some of the things that you heard felt saw observed today on day one? >>Yeah, it's great to be back in person. Right? 8,000 people events are rare. Uh, I'm not sure. Have you been to more than 8,000? <laugh> yeah, yeah. Okay. This year, this year. I mean, historically, yes, but, um, >>Snowflake was 10. Yeah. >>So, oh, wow. Okay. So 8,000 was my, >>Cisco was, they said 15, >>But is my, my 8,000, my record, I let us down with 7,000 kind of like, but it's in the Florida swarm. It's not nicely. Like, and there's >>Usually what SFI, there's usually >>20, 20, 30, 40, 50. I remember 50 in the nineties. Right. That was a different time. But yeah. Interesting. Yeah. Interesting what people do and it depends how much time there is to come. Right. And know that it happens. Right. But yeah, no, I think it's interesting. We, we had a good two analyst track today. Um, interesting. Like HPE is kind of like back not being your grandfather's HPE to a certain point. One of the key stats. I know Dave always for the stats, right. Is what I found really interesting that over two third of GreenLake revenue is software and services. Now a love to know how much of that services, how much of that software. But I mean, I, I, I, provocate some, one to ones, the HP executives saying, Hey, you're a hardware company. Right. And they didn't even come back. Right. But Antonio said, no, two thirds is, uh, software and services. Right. That's interesting. They passed the one exabyte, uh, being managed, uh, as a, as a hallmark. Right. I was surprised only 120,000 users if I had to remember the number. Right, right. So that doesn't seem a terrible high amount of number of users. Right. So, but that's, that's, that's promising. >>So what software is in there, cuz it's gotta be mostly services. >>Right? Well it's the 70 plus cloud services, right. That everybody's talking about where the added eight of them shockingly back up and recovery, I thought that was done at launch. Right. >>Still who >>Keep recycling storage and you back. But now it's real. Yeah. >>But the company who knows the enterprise, right. HPE, what I've been doing before with no backup and recovery GreenLake. So that was kind of like, okay, we really want to do this now and nearly, and then say like, oh, by the way, we've been doing this all the time. Yeah. >>Oh, what's your take on the installed base of HP. We had that conversation, the, uh, kickoff or on who's their target, what's the target audience environment look like. It certainly is changing. Right? If it's software and services, GreenLake is resonating. Yeah. Um, ecosystems responding. What's their customers cuz managed services are up too Kubernetes, all the managed services what's what's it like what's their it transformation base look like >>Much of it is of course install base, right? The trusted 20, 30 plus year old HP customer. Who's keeping doing stuff of HP. Right. And call it GreenLake. They've been for so many name changes. It doesn't really matter. And it's kind of like nice that you get the consume pain only what you consume. Right. I get the cloud broad to me then the general markets, of course, people who still need to run stuff on premises. Right. And there's three reasons of doing this performance, right. Because we know the speed of light is relative. If you're in the Southern hemisphere and even your email servers in Northern hemisphere, it takes a moment for your email to arrive. It's a very different user experience. Um, local legislation for data, residency privacy. And then, I mean Charles Phillips who we all know, right. Former president of uh, info nicely always said, Hey, if the CIOs over 50, I don't have to sell qu. Right. So there is not invented. I'm not gonna do cloud here. And now I've kind of like clouded with something like HP GreenLake. That's the customers. And then of course procurement is a big friend, right? Yeah. Because when you do hardware refresh, right. You have to have two or three competitors who are the two or three competitors left. Right. There's Dell. Yeah. And then maybe Lenovo. Right? So, so like a >>Little bit channels, the strength, the procurement physicians of strength, of course install base question. Do you think they have a Microsoft opportunity where, what 365 was Microsoft had office before 365, but they brought in the cloud and then everything changed. Does HP have that same opportunity with kind of the GreenLake, you know, model with their existing stuff. >>It has a GreenLake opportunity, but there's not much software left. It's a very different situation like Microsoft. Right? So, uh, which green, which HP could bring along to say, now run it with us better in the cloud because they've been selling much of it. Most of it, of their software portfolio, which they bought as an HP in the past. Right. So I don't see that happening so much, but GreenLake as a platform itself course interesting because enterprise need a modern container based platform. >>I want, I want to double click on this a little bit because the way I see it is HP is going to its installed base. I think you guys are right on say, this is how we're doing business now. Yeah. You know, come on along. But my sense is, some customers don't want to do the consumption model. There are actually some customers that say, Hey, of course I got, I don't have a cash port problem. I wanna pay for it up front and leave me alone. >>I've been doing this since 50 years. Nice. As I changed it, now <laugh> two know >>Money's wants to do it. And I don't wanna rent because rental's more expensive and blah, blah, blah. So do you see that in the customer base that, that some are pushing back? >>Of course, look, I have a German accent, right? So I go there regularly and uh, the Germans are like worried about doing anything in the cloud. And if you go to a board in Germany and say, Hey, we can pay our usual hardware, refresh, CapEx as usual, or should we bug consumption? And they might know what we are running. <laugh> so not whole, no offense against the Germans out. The German parts are there, but many of them will say, Hey, so this is change with COVID. Right. Which is super interesting. Right? So the, the traditional boards non-technical have been hearing about this cloud variable cost OPEX to CapEx and all of a sudden there's so much CapEx, right. Office buildings, which are not being used truck fleets. So there's a whole new sensitivity by traditional non-technical boards towards CapEx, which now the light bulb went on and say, oh, that's the cloud thing about also. So we have to find a way to get our cost structure, to ramp up and ramp down as our business might be ramping up through COVID through now inflation fears, recession, fears, and so on. >>So, okay. HP's, HP's made the statement that anything you can do in the cloud you can do in GreenLake. Yes. And I've said you can't run on snowflake. You can't run Mongo Atlas, you can't run data bricks, but that's okay. That's fine. Let's be, I think they're talking about, there's >>A short list of things. I think they're talking about the, their >>Stuff, their, >>The operating experience. So we've got single sign on through a URL, right. Uh, you've got, you know, some level of consistency in terms of policy. It's unclear exactly what that is. You've got storage backup. Dr. What, some other services, seven other services. If you had to sort of take your best guess as to where HP is now and peg it toward where Amazon was in which year? >>20 14, 20 14. >>Yeah. Where they had their first conference or the second we invent here with 3000 people and they were thinking, Hey, we're big. Yeah. >>Yeah. And I think GreenLake is the building blocks. So they quite that's the >>Building. Right? I mean similar. >>Okay. Well, I mean they had E C, Q and S3 and SQS, right. That was the core. And then the rest of those services were, I mean, base stock was one of that first came in behind and >>In fairness, the industry has advanced since then, Kubernetes is further along. And so HPE can take advantage of that. But in terms of just the basic platform, I, I would agree. I think it's >>Well, I mean, I think, I mean the software, question's a big one. I wanna bring up because the question is, is that software is getting the world. Hardware is really software scales, everything, data, the edge story. I love their story. I think HP story is wonderful Aruba, you know, hybrid cloud, good story, edge edge. But if you look under the covers, it's weak, right? It's like, it's not software. They don't have enough software juice, but the ecosystem opportunity to me is where you plug and play. So HP knows that game. But if you look historically over the past 25 years, HP now HPE, they understand plug and play interoperability. So the question is, can they thread the needle >>Right. >>Between filling the gaps on the software? Yeah. With partners, >>Can they get the partners? Right. And which have been long, long time. Right. For a long time, HP has been the number one platform under ICP, right? Same thing. You get certified for running this. Right. I know from my own history, uh, I joined Oracle last century and the big thing was, let's get your eBusiness suite certified on HP. Right? Like as if somebody would buy H Oracle work for them, right. This 20 years ago, server >>The original exit data was HP. Oracle. >>Exactly. Exactly. So there's this thinking that's there. But I think the key thing is we know that all modern forget about the hardware form in the platforms, right? All modern software has to move to containers and snowflake runs in containers. You mentioned that, right? Yeah. If customers force snowflake and HPE to the table, right, there will be a way to make it work. Right. And which will help HPE to be the partner open part will bring the software. >>I, I think it's, I think that's an opportunity because that changes the game and agility and speed. If HP plays their differentiation, right. Which we asked on their opening segment, what's their differentiation. They got size scale channel, >>What to the enterprise. And then the big benefit is this workload portability thing. Right? You understand what is run in the public cloud? I need to run it local. For whatever reason, performance, local residency of data. I can move that. There that's the big benefit to the ISVs, the sales vendors as well. >>But they have to have a stronger data platform story in my that's right. Opinion. I mean, you can run Oracle and HPE, but there's no reason they shouldn't be able to do a deal with, with snowflake. I mean, we saw it with Dell. Yep. We saw it with, with, with pure and I, if our HPE I'd be saying, Hey, because the way the snowflake deal worked, you probably know this is your reading data into the cloud. The compute actually occurs in the cloud viral HB going snowflake saying we can separate compute and storage. Right. And we have GreenLake. We have on demand. Why don't we run the compute on-prem and make it a full class, first class citizen, right. For all of our customers data. And that would be really innovative. And I think Mongo would be another, they've got OnPrem. >>And the question is, how many, how many snowflake customers are telling snowflake? Can I run you on premise? And how much defo open years will they hear from that? Right? This is >>Why would they deal Dell? That >>Deal though, with that, they did a deal. >>I think they did that deal because the customer came to them and said, you don't exactly that deal. We're gonna spend the >>Snowflake >>Customers think crazy things happen, right? Even, even put an Oracle database in a Microsoft Azure data center, right. Would off who, what as >>Possible snowflake, >>Oracle. So on, Aw, the >>Snow, the snowflakes in the world have to make a decision. Dave on, is it all snowflake all the time? Because what the reality is, and I think, again, this comes back down to the, the track that HP could go up or down is gonna be about software. Open source is now the software industry. There's no such thing as proprietary software, in my opinion, relatively speaking, cloud scale and integrated, integrated integration software is proprietary. The workflows are proprietary. So if they can get that right with the partners, I would focus on that. I think they can tap open source, look at Amazon with open source. They sucked it up and they integrated it in. No, no. So integration is the deal, not >>Software first, but Snowflake's made the call. You were there, Lisa. They basically saying it's we have, you have to be in snowflake in order to get the governance and the scalability, all that other wonderful stuff. Oh, but we we'll do Apache iceberg. We'll we'll open it up. We'll do Python. Yeah. >>But you can't do it data clean room unless you are in snowflake. Exactly. Snowflake on snowflake. >>Exactly. >>But got it. Isn't that? What you heard from AWS all the time till they came out outposts, right? I mean, snowflake is a market leader for what they're doing. Right. So that they want to change their platform. I mean, kudos to them. They don't need to change the platform. They will be the last to change their platform to a ne to anything on premises. Right. But I think the trend already shows that it's going that way. >>Well, if you look at outpost is an signal, Dave, the success of outpost launched what four years ago, they announced it. >>What >>EKS is beating, what outpost is doing. Outpost is there. There's not a lot of buzz and talk to the insiders and the open source community, uh, EKS and containers. To your point mm-hmm <affirmative> is moving faster on, I won't say commodity hardware, but like could be white box or HP, Dell, whatever it's gonna be that scale differentiation and the edge story is, is a good one. And I think with what we're seeing in the market now it's the industrial edge. The back office was gen one cloud back office data center. Now it's hybrid. The focus will be industrial edge machine learning and AI, and they have it here. And there's some, some early conversations with, uh, I heard it from, uh, this morning, you guys interviewed, uh, uh, John Schultz, right? With the world economic 4k birth Butterfield. She was amazing. And then you had Justin bring up a Hoar, bring up quantum. Yes. That is a differentiator. >>HP. >>Yes. Yeah. You, they have the computing shops. They had the R and D can they bring it to the table >>As, as HPC, right. To what they Schultz for of uh, the frontier system. Right. So very impressed. >>So the ecosystem is the key for them is because that's how they're gonna fill the gaps. They can't, they can't only, >>They could, they could high HPC edge piece. I wouldn't count 'em out of that game yet. If you co-locate a box, I'll use the word box, particularly at a telco tower. That's a data center. Yep. Right. If done properly. Yep. So, you know, what outpost was supposed to do actually is a hybrid opportunity. Aruba >>Gives them a unique, >>But the key thing is right. It's a yin and yang, right? It's the ecosystem it's partners to bring those software workload. Absolutely. Right. But HPE has to keep the platform attractive enough. Right. And the key thing there is that you have this workload capability thing that you can bring things, which you've built yourself. I mean, look at the telcos right. Network function, visualization, thousands of man, years into these projects. Right. So if I can't bring it to your edge box, no, I'm not trying to get to your Xbox. Right. >>Hold I gotta ask you since in the Dave too, since you guys both here and Lisa, you know, I said on the opening, they have serious customers and those customers have serious problems, cyber security, ransomware. So yeah. I teach transformation now. Industrial transformation machine learning, check, check, check. Oh, sounds good. But at the end of the day, their customers have some serious problems. Right? Cyber, this is, this is high stakes poker. Yeah. What do you think HP's position for in the security? You mentioned containers, you got all this stuff, you got open source, supply chain, you have to left supply chain issues. What is their position with security? Cuz that's the big one. >>I, I think they have to have a mature attitude that customers expect from HPE. Right? I don't have to educate HP on security. So they have to have the partner offerings again. We're back at the ecosystem to have what probably you have. So bring your own security apart from what they have to have out of the box to do business with them. This is why the shocker this morning was back up in recovery coming. <laugh> it's kind like important for that. Right? Well >>That's, that's, that's more ransomware and the >>More skeleton skeletons in the closet there, which customers should check of course. But I think the expectations HP understands that and brings it along either from partner or natively. >>I, I think it's, I think it's services. I think point next is the point of integration for their security. That's why two thirds is software and services. A lot of that is services, right? You know, you need security, we'll help you get there. We people trust HP >>Here, but we have nothing against point next or any professional service. They're all hardworking. But if I will have to rely on humans for my cyber security strategy on a daily level, I'm getting gray hair and I little gray hair >>Red. Okay. I that's, >>But >>I think, but I do think that's the camera strategy. I mean, I'm sure there's a lot of that stuff that's beginning to be designed in, but I, my guess is a lot of it is services. >>Well, you got the Aruba. Part of the booth was packed. Aruba's there. You mentioned that earlier. Is that good enough? Because the word zero trust is kicked around a lot. On one hand, on the other hand, other conversations, it's all about trust. So supply chain and software is trusting trust, trust and verified. So you got this whole mentality of perimeter gone mentality. It's zero trust. And if you've got software trust, interesting thoughts there, how do you reconcile zero trust? And then I need trust. What's what's you? What are you seeing older on that? Because I ask people all the time, they're like, uh, I'm zero trust or is it trust? >>Yeah. The middle ground. Right? Trusted. The meantime people are man manipulating what's happening in your runtime containers. Right? So, uh, drift control is a new password there that you check what's in your runtime containers, which supposedly impenetrable, but people finding ways to hack them. So we'll see this cat and mouse game going on all the time. Yeah. Yeah. There's always gonna be the need for being in a secure, good environment from that perspective. Absolutely. But the key is edge has to be more than Aruba, right? If yeah. HV goes away and says, oh yeah, we can manage your edge with our Aruba devices. That's not enough. It's the virtual probability. And you said the important thing before it's about the data, right? Because the dirty secret of containers is yeah, I move the code, but what enterprise code works without data, right? You can't say as enterprise, okay, we're done for the day check tomorrow. We didn't persist your data, auditor customer. We don't have your data anymore. So filling a way to transport the data. And there just one last thought, right? They have a super interesting asset. They want break lands for the venerable map R right. Which wrote their own storage drivers and gives you the chance to potentially do something in that area, which I'm personally excited about. But we'll see what happens. >>I mean, I think the holy grail is can I, can I put my data into a cloud who's ever, you know, call it a super cloud and can I, is it secure? Is it governed? Can I share it and be confident that it's discoverable and that the, the person I give it to has the right to use it. Yeah. And, and it's the correct data. There's not like a zillion copies running. That's the holy grail. And I, I think the answer today is no, you can, you can do that maybe inside of AWS or maybe inside of Azure, look maybe certainly inside of snowflake, can you do that inside a GreenLake? Well, you probably can inside a GreenLake, but then when you put it into the cloud, is it cross cloud? Is it really out to the edge? And that's where it starts to break down, but that's where the work is to be done. That's >>The one Exide is in there already. Right. So men being men. Yeah. >>But okay. But it it's in there. Yeah. Okay. What do you do with it? Can you share that data? What can you actually automate governance? Right? Uh, is that data discoverable? Are there multiple copies of that data? What's the, you know, master copy. Here's >>A question. You guys, here's a question for you guys analyst, what do you think the psychology is of the CIO or CSO when HP comes into town with GreenLake, uh, and they say, what's your relationship with the hyperscalers? Cause I'm a CIO. I got my environment. I might be CapEx centric or Hey, I'm open model. Open-minded to an operating model. Every one of these enterprises has a cloud relationship. Yeah. Yeah. What's the dynamic. What do you think the psychology is of the CIO when they're rationalizing their, their trajectory, their architecture, cloud, native scale integration with HPE GreenLake or >>HP service. I think she or he hears defensiveness from HPE. I think she hears HPE or he hears HPE coming in and saying, you don't need to go to the cloud. You know, you could keep it right here. I, I don't think that's the right posture. I think it should be. We are your cloud. And we can manage whether it's OnPrem hybrid in AWS, Azure, Google, across those clouds. And we have an edge story that should be the vision that they put forth. That's the super cloud vision, but I don't hear it >>From these guys. What do you think psycho, do you agree with that? >>I'm totally to make, sorry to be boring, but I totally agree with, uh, Dave on that. Right? So the, the, the multi-cloud capability from a trusted large company has worked for anybody up and down the stack. Right? You can look historically for, uh, past layers with cloud Foundry, right? It's history vulnerable. You can look for DevOps of Hashi coop. You can look for database with MongoDB right now. So if HPE provides that data access, right, with all the problems of data gravity and egres cost and the workability, they will be doing really, really well, but we need to hear it more, right. We didn't hear much software today in the keynote. Right. >>Do they have a competitive offering vis-a-vis or Azure? >>The question is, will it be an HPE offering or will, or the software platform, one of the offerings and you as customer can plug and play, right. Will software be a differentiator for HP, right. And will be close, proprietary to the point to again, be open enough for it, or will they get that R and D format that, or will they just say, okay, ES MES here on the side, your choice, and you can use OpenShift or whatever, we don't matter. That's >>The, that's the key question. That's the key question. Is it because it is a competitive strategy? Is it highly differentiated? Oracle is a highly differentiated strategy, right? Is Dell highly differentiated? Eh, Dell differentiates based on its breadth. What? >>Right. Well, let's try for the control plane too. Dell wants to be an, >>Their, their vision is differentiated. Okay. But their execution today is not >>High. All right. Let me throw, let me throw this out at you then. I'm I'm, I'm sorry. I'm I'm HPE. I wanna be the glue layer. Is that, does that fly? >>What >>Do you mean? The group glue layer? I'll I wanna be, you can do Amazon, but I wanna be the glue layer between the clouds and our GreenLake will. >>What's the, what's the incremental value that, that glue provides, >>Provides comfort and reliability and control for the single pane of glass for AWS >>And comes back to the data. In my opinion. Yeah. >>There, there there's glue levels on the data level. Yeah. And there's glue levels on API level. Right. And there's different vendors in the different spaces. Right. Um, I think HPE will want to play on the data side. We heard lots of data stuff. We >>Hear that, >>But we have to see it. Exactly. >>Yeah. But it's, it's lacking today. And so, Hey, you know, you guys know better than I APIs can be fragile and they can be, there's a lot of diversity in terms of the quality of APIs and the documentation, how they work, how mature they are, what, how, what kind of performance they can provide and recoverability. And so just saying, oh wow. We are living the API economy. You know, the it's gonna take time to brew, chime in here. Hi. >><laugh> oh, so guys, you've all been covering HPE for a long time. You know, when Antonio stood up on stage three years ago and said by 2022, and here we are, we're gonna be delivering everything as a service. He's saying we've, we've done it, but, and we're a new company. Do you guys agree with that? >>Definitely. >>I, yes. Yes. With the caveat, I think, yes. The COVID pandemic slowed them down a lot because, um, that gave a tailwind to the hyperscalers, um, because of the, the force of massive O under forecasting working at home. I mean, everyone I talked to was like, no one forecasted a hundred percent work at home, the, um, the CapEx investments. So I think that was an opportunity that they'd be much farther along if there's no COVID people >>Thought it wasn't impossible. Yeah. But so we had the old work from home thing right. Where people trying to get people fired at IBM and Yahoo. Right. So I would've this question covering the HR side and my other hat on. Right. And I would ask CHS let's assume, because I didn't know about COVID shame on me. Right. I said, big California, earthquake breaks. Right. Nobody gets hurt, but all the buildings have to be retrofitted and checked for seism logic down. So everybody's working from home, ask CHS, what kind of productivity gap hit would you get by forcing everybody working from home with the office unsafe? So one, one gentleman, I won't know him, his name, he said 20% and the other one's going ha you're smoking. It's 40 50%. We need to be in the office. We need to meet it first night. And now we went for this exercise. Luckily not with the California. Right. Well, through the price of COVID and we've seen what it can do to, to productivity well, >>The productivity, but also the impact. So like with all the, um, stories we've done over two years, the people that want came out ahead were the ones that had good cloud action. They were already in the cloud. So I, I think they're definitely in different company in the sense of they, I give 'em a pass. I think they're definitely a new company and I'm not gonna judge 'em on. I think they're doing great. But I think pandemic definitely slowed 'em down that about >>It. So I have a different take on this. I think. So we've go back a little history. I mean, you' said this, I steal your line. Meg Whitman took one for the Silicon valley team. Right. She came in. I don't think she ever was excited that I, that you said, you said that, and I think you wrote >>Up, get tape on that one. She >>Had to figure out how do I deal with this mess? I have EDS. I got PC. >>She never should have spun off the PC, but >>Okay. But >>Me, >>Yeah, you can, you certainly could listen. Maybe, maybe Gerstner never should have gone all in on services and IBM would dominate something other than mainframes. They had think pads even for a while, but, but, but so she had that mess to deal with. She dealt with it and however, they dealt with it, Antonio came in, he, he, and he said, all right, we're gonna focus the company. And we're gonna focus the mission on not the machine. Remember those yeah. Presentations, but you just make your eyes glaze over. We're going all in on Azure service >>And edge. He was all on. >>We're gonna build our own cloud. We acquired Aruba. He made some acquisitions in HPC to help differentiate. Yep. And they are definitely a much more focused company now. And unfortunately I wish Antonio would CEO in 2015, cuz that's really when this should have started. >>Yeah. And then, and if you remember back then, Dave, we were interviewing Docker with DevOps teams. They had composability, they were on hybrid really early. I think they might have even coined the term hybrid before VMware tri-state credit for it. But they were first on hybrid. They had DevOps, they had infrastructure risk code. >>HPE had an HP had an awesome cloud team. Yeah. But, and then, and then they tried to go public cloud. Yeah. You know, and then, you know, just made them, I mean, it was just a mess. The focus >>Is there. I give them huge props. And I think, I think the GreenLake to me is exciting here because it's much better than it was two years ago. When, when we talked to, when we started, it's >>Starting to get real. >>It's, it's a real thing. And I think the, the tell will be partners. If they make that right, can pull their different >>Ecosystem, >>Their scale and their customers and fill the software gas with partners mm-hmm <affirmative> and then create that integration opportunity. It's gonna be a home run if they don't do that, they're gonna miss the operating, >>But they have to have their own to your point. They have to have their own software innovation. >>They have to good infrastructure ways to build applications. I don't wanna build with somebody else. I don't wanna take a Microsoft stack on open source stack. I'm not sure if it's gonna work with HP. So they have to have an app dev answer. I absolutely agree with that. And the, the big thing for the partners is, which is a good thing, right? Yep. HPE will not move into applications. Right? You don't have to have the fear of where Microsoft is with their vocal large. Right. If AWS kind of like comes up with APIs and manufacturing, right. Google the same thing with their vertical push. Right. So HPE will not have the CapEx, but >>Application, >>As I SV making them, the partner, the bonus of being able to on premise is an attractive >>Part. That's a great point. >>Hold. So that's an inflection point for next 12 months to watch what we see absolutely running on GreenLake. >>Yeah. And I think one of the things that came out of the, the last couple events this past year, and I'll bring this up, we'll table it and we'll watch it. And it's early in this, I think this is like even, not even the first inning, the machine learning AI impact to the industrial piece. I think we're gonna see a, a brand new era of accelerated digital transformation on the industrial physical world, back office, cloud data center, accounting, all the stuff. That's applications, the app, the real world from space to like robotics. I think that HP edge opportunity is gonna be visible and different. >>So guys, Antonio Neri is on tomorrow. This is only day one. If you can imagine this power panel on day one, can you imagine tomorrow? What is your last question for each of you? What is your, what, what question would you want to ask him tomorrow? Hold start with you. >>How is HPE winning in the long run? Because we know their on premise market will shrink, right? And they can out execute Dell. They can out execute Lenovo. They can out Cisco and get a bigger share of the shrinking market. But that's the long term strategy, right? So why should I buy HPE stock now and have a good return put in the, in the safe and forget about it and have a great return 20 years from now? What's the really long term strategy might be unfair because they, they ran in survival mode to a certain point out of the mass post equipment situation. But what is really the long term strategy? Is it more on the hardware side? Is it gonna go on the HPE, the frontier side? It's gonna be a DNA question, which I would ask Antonio. >>John, >>I would ask him what relative to the macro conditions relative to their customer base, I'd say, cuz the customers are the scoreboard. Can they create a value proposition with their, I use the Microsoft 365 example how they kind of went to the cloud. So my question would be Antonio, what is your core value proposition to CIOs out there who want to transform and take a step function, increase for value with HPE? Tell me that story. I wanna hear. And I don't want to hear, oh, we got a portfolio and no, what value are you enabling your customers to do? >>What and what should that value be? >>I think it's gonna be what we were kind of riffing on, which is you have to provide either what their product market fit needs are, which is, are you solving a problem? Is it a pain point is a growth driver. Uh, and what's the, what's that tailwind. And it's obviously we know at cloud we know edge. The story is great, but what's the value proposition. But by going with HPE, you get X, Y, and Z. If they can explain that clearly with real, so qualitative and quantitative data it's home >>Run. He had a great line of the analyst summit today where somebody asking questions, I'm just listening to the customer. So be ready for this Steve jobs photo, listening to the customer. You can't build something great listening to the customer. You'll be good for the next quarter. The next exponential >>Say, what are the customers saying? <laugh> >>So I would make an observation. And my question would, so my observation would be cloud is growing collectively at 35%. It's, you know, it's approaching 200 billion with a big, big four. If you include Alibaba, IBM has actually said, Hey, we're gonna gr they've promised 6% growth. Uh, Cisco I think is at eight or 9% growth. Dow's growing in double digits. Antonio and HPE have promised three to 4% growth. So what do you have to do to actually accelerate growth? Because three to 4%, my view, not enough to answer Holger's question is why should I buy HPE stock? Well, >>If they have product, if they have customer and there's demand and traction to me, that's going to drive the growth numbers. And I think the weak side of the forecast means that they don't have that fit yet. >>Yeah. So what has to happen for them to get above five, 6% growth? >>That's what we're gonna analyze. I mean, I, I mean, I don't have an answer for that. I wish I had a better answer. I'd tell them <laugh> but I feel, it feels, it feels like, you know, HP has an opportunity to say here's the new HPE. Yeah. Okay. And this is what we stand for. And here's the one thing that we're going to do that consistently drives value for you, the customer. And that's gonna have to come into some, either architectural cloud shift or a data thing, or we are your store for blank. >>All of the above. >>I guess the other question is, would, would you know, he won't answer a rude question, would suspending things like dividends and stock buybacks and putting it into R and D. I would definitely, if you have confidence in the market and you know what to do, why wouldn't you just accelerate R and D and put the money there? IBM, since 2007, IBM spent is the last stat. And I'm looking go in 2007, IBM way, outspent, Google, and Amazon and R and D and, and CapEx two, by the way. Yep. Subsequent to that, they've spent, I believe it's the numbers close to 200 billion on stock buyback and dividends. They could have owned cloud. And so look at this business, the technology business by and large is driven by innovation. Yeah. And so how do you innovate if >>You have I'm buying, I'm buying HP because they're reliable high quality and they have the outcomes that I want. Oh, >>Buy their products and services. I'm not sure I'd buy the stock. Yeah. >>Yeah. But she has to answer ultimately, because a public company. Right. So >>Right. It's this job. Yeah. >>Never a dull moment with the three of you around <laugh> guys. Thank you so much for sharing your insights, your, an analysis from day one. I can't imagine what day two is gonna bring tomorrow. Debut and I are gonna be anchoring here. We've got a jam packed day, lots going on, hearing from the ecosystem from leadership. As we mentioned, Antonio is gonna be Tony >>Alma Russo. I'm dying. Dr. >>EDMA as well as on the CTO gonna be another action pack day. I'm excited for it, guys. Thanks so much for sharing your insights and for letting me join this power panel. >>Great. Great to be here. >>Power panel plus me. All right. For Holger, John and Dave, I'm Lisa, you're watching the cube our day one coverage of HPE discover wraps right now. Don't go anywhere, cuz we'll see you tomorrow for day two, live from Vegas, have a good night.
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What are some of the things that you heard I mean, So, oh, wow. but it's in the Florida swarm. I know Dave always for the stats, right. Well it's the 70 plus cloud services, right. Keep recycling storage and you back. But the company who knows the enterprise, right. We had that conversation, the, uh, kickoff or on who's their target, I get the cloud broad to me then the general markets, of course, people who still need to run stuff on premises. with kind of the GreenLake, you know, model with their existing stuff. So I don't see that happening so much, but GreenLake as a platform itself course interesting because enterprise I think you guys are right on say, this is how we're doing business now. As I changed it, now <laugh> two know And I don't wanna rent because rental's more expensive and blah, And if you go to a board in Germany and say, Hey, we can pay our usual hardware, refresh, HP's, HP's made the statement that anything you can do in the cloud you I think they're talking about the, their If you had to sort of take your best guess as to where Yeah. So they quite that's the I mean similar. And then the rest of those services But in terms of just the basic platform, I, I would agree. I think HP story is wonderful Aruba, you know, hybrid cloud, Between filling the gaps on the software? I know from my own history, The original exit data was HP. But I think the key thing is we know that all modern I, I think it's, I think that's an opportunity because that changes the game and agility and There that's the big benefit to the ISVs, if our HPE I'd be saying, Hey, because the way the snowflake deal worked, you probably know this is I think they did that deal because the customer came to them and said, you don't exactly that deal. Customers think crazy things happen, right? So if they can get that right with you have to be in snowflake in order to get the governance and the scalability, But you can't do it data clean room unless you are in snowflake. But I think the trend already shows that it's going that way. Well, if you look at outpost is an signal, Dave, the success of outpost launched what four years ago, And I think with what we're seeing in the market now it's They had the R and D can they bring it to the table So very impressed. So the ecosystem is the key for them is because that's how they're gonna fill the gaps. So, you know, I mean, look at the telcos right. I said on the opening, they have serious customers and those customers have serious problems, We're back at the ecosystem to have what probably But I think the expectations I think point next is the point of integration for their security. But if I will have to rely on humans for I mean, I'm sure there's a lot of that stuff that's beginning Because I ask people all the time, they're like, uh, I'm zero trust or is it trust? I move the code, but what enterprise code works without data, I mean, I think the holy grail is can I, can I put my data into a cloud who's ever, So men being men. What do you do with it? You guys, here's a question for you guys analyst, what do you think the psychology is of the CIO or I think she hears HPE or he hears HPE coming in and saying, you don't need to go to the What do you think psycho, do you agree with that? So if HPE provides that data access, right, with all the problems of data gravity and egres one of the offerings and you as customer can plug and play, right. That's the key question. Right. But their execution today is not I wanna be the glue layer. I'll I wanna be, you can do Amazon, but I wanna be the glue layer between the clouds and And comes back to the data. And there's glue levels on API level. But we have to see it. And so, Hey, you know, you guys know better than I APIs can be fragile and Do you guys agree with that? I mean, everyone I talked to was like, no one forecasted a hundred percent work but all the buildings have to be retrofitted and checked for seism logic down. But I think pandemic definitely slowed I don't think she ever was excited that I, that you said, you said that, Up, get tape on that one. I have EDS. Presentations, but you just make your eyes glaze over. And edge. I wish Antonio would CEO in 2015, cuz that's really when this should have started. I think they might have even coined the term You know, and then, you know, just made them, I mean, And I think, I think the GreenLake to me is And I think the, the tell will be partners. It's gonna be a home run if they don't do that, they're gonna miss the operating, But they have to have their own to your point. You don't have to have the fear of where Microsoft is with their vocal large. the machine learning AI impact to the industrial piece. If you can imagine this power panel But that's the long term strategy, And I don't want to hear, oh, we got a portfolio and no, what value are you enabling I think it's gonna be what we were kind of riffing on, which is you have to provide either what their product So be ready for this Steve jobs photo, listening to the customer. So what do you have to do to actually accelerate growth? And I think the weak side of the forecast means that they don't I feel, it feels, it feels like, you know, HP has an opportunity to say here's I guess the other question is, would, would you know, he won't answer a rude question, You have I'm buying, I'm buying HP because they're reliable high quality and they have the outcomes that I want. I'm not sure I'd buy the stock. So Yeah. Never a dull moment with the three of you around <laugh> guys. Thanks so much for sharing your insights and for letting me join this power panel. Great to be here. Don't go anywhere, cuz we'll see you tomorrow for day two, live from Vegas,
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Day One Kickoff | HPE Discover 2022
>>The cube presents HPE discover 2022 brought to you by HPE. >>Hey everyone. Welcome to Las Vegas. It's the cube live on the show floor at HPE discover 2022, the first in person discover in three years, there are about 8,000 people here. The keynote was standing room only Lisa Martin here. I got a powerhouse group joining me for this keynote analysis. Dave ante joins us, Keith Townsend, John farrier, guys. Lot of news. It's all about HPE GreenLake. What were some of the things Dave, that stuck out to you? >>Well, I'll tell you right now, I gotta just quote, Antonio OIR said, Neri said four years ago, I declared that the enterprise of the future would be edge centric, cloud enabled and data driven. As a result, we launched HPE GreenLake. It kind of declared victory. Now I would say that what they're talking about and what they announced, I would consider table stakes. You know, I wish it started in 2014. I wish Antonio took over in 2015 instead of 2018, but I have to give credit, he's brought a focus and uh, and a, he think he's amped it up, John. I mean, if he's really prioritizing, uh, the, as a service they're going on in all in they're burning the boats, uh, and it's good. They got a lot of work to do. They >>Got a lot of work to do three years ago, John Antonio stood on this very stage saying we, and by 2022, we're gonna be delivering our entire portfolio as a service here we are with GreenLake. What I wanna get your thoughts on Keith's as well. >>Yeah. Well, first of all, I think that the crowded house was, uh, and a sign of people wanna come back together. So it's, to me, that was the first good news I saw, which was the HP community, their customer base. They're all here. They're glad to be back and forth. So it shows that they, their customer base it's resonating their value proposition of annual recurring revenue as a service plus the contract values with GreenLake are up. So this resonance with the customers, Dave, on the new operating model, that's a great check the box there. Um, I would say that I don't think HP's, as far along as Antonio had hopes, he'd be the pandemic was a setback. Um, but GreenLake is a real shining star. It's, uh, it's producing some green if you will money for them in terms of contracts, but they still got a lot more work to do because they're in a really interesting zone, Dave, because edge the cloud, although relevant and accurate where the, the shift is going, are they really there with, with the goods? And to me, I'm looking forward to seeing this discover if they have it or not. Certainly the messaging's good, but we're gonna UN UN unpeel that onion back and look at it. But >>Keith they're on the curve, right? At least they're on the cloud curve. >>They're absolutely on the curve. They have APIs, they have consistent developer experience. They announced the developer portal. They're developer centric. You can now consume your three par storage array services via a Terraform, uh, provider. They speak the language of cloud practitioners. You might struggle a little bit if I'm a small startup, you know, why would I look towards HPE? They kind of answered that a little bit. They had evil genius as a customer on stage, not a huge organization. A lot of the pushback they've been given is that if I may startup, I can simply go to a AWS portal, launch, a free trial service and run it. HPE kind of buried the lead. They now have, at least they announced preannounced the capability to, to trial GreenLake. So they're moving in the right direction. But you know, it's, it's it's table states. Well, >>Here's the thing. Here's the dynamic day that's going on. This is something that we've got got we're first of we've been covering HPE HP for now 11 years with the cube and look at Amazon's success and look at where Amazon's struggling. If you can say that they're having crossed overs to the enterprise, uh, cuz the enterprises are now just getting up to speed. You're seeing the rise of lack of talent. It certainly changing, uh, cyber security. You can't find talent. Kubernetes, good luck with that. Try to find someone. So you're seeing the enterprise aren't really geared up or staffed up for doing what I call, you know, high end cloud. So the rise of managed services is, is what we're seeing out there right now. You want Kubernetes clusters is a great set of managed services. You want other services? So that's the tell sign that the enterprises H HP's customers are now walking before they can run. They're crawling, they're now they're walking. So it's they have time to get in the Amazon lane in my opinion. Well, you >>Think about the hallmarks of cloud, obviously there's as a service, there's consumption based pricing. There's a developer, you know, friendliness, uh, there's ecosystem, which is really, really important. I think today, a lot of the ecosystem is partners, resellers and managed service providers. And to your point, Keith table stakes are things like single sign on being able to have, you know, a console being able to do it from a, from a URL to your point about startups is really interesting because that's one of the other hallmarks of cloud is you attract startups. And Lisa, we were at the snowflake summit and I asked the same question, can snowflake attract startups with their own super cloud. And what you saw was ecosystem partners developing in the snowflake cloud and monetizing. And that's something that we're waiting to see here. And I, I think they know >>You're suggesting way you suggesting that HP's gonna attract startups. >>Well, >>I, I think that's a sign if they can do that. That's a sign. And, and right now, I mean, you heard the example that Keith Keith gave. Uh, but, but not, not many. >>Yeah. I'm hoping that H I don't think HP is gonna ever attract startups, but I think the opportunity GreenLake affords the ecosystem is build clouds or purpose driven clouds around GreenLake. Mm-hmm <affirmative> whether it's the agreement with Equinix or all the cos and semi clouds, I think GreenLake gets most small CSPs, a leg up or 80% of the way there, where they can add that 20% of the IP and build services around GreenLake. And then that can attract the, the startup >>Or entrepreneurs. So the, the big question is, okay, where are these developers gonna come from? They could come from incumbents inside of companies. You know, the, the, the DevOps crowd from the enterprise, the really ops dev crowd. Right? I mean, yeah, don't you see that as a sort of a form of innovation startup, even though it's not a true startup. >>Yeah. Even though it's not, >>So Todd's making faces over there, we <laugh> >>Look, it, look it, they have >>Listen, if they don't, if they can't >>Do that, no, this is their focus is not startups. I agree with Keith on this one, they have to take care of business, home Depot. They have big customers and they have a lot of SMBs as well. They've got a great channel. H HP's got amazing infrastructure and, and client action going on. They gotta get the operating model, right job one as a service ARR, and then contract value and, and nail that with GreenLake. >>Who's their ideal customer profile. >>Their ideal is their install base. Look what Microsoft did with 365, they were going down. Their stock price was 26. At one point go to the, they went to the cloud 365, moved everything to the cloud and look at the success they're having. HP has the same kind of installed base. They gotta bring them along. They gotta get the operating model, right. And the developers that they're targeting are the ones inside the company and, or manage services that they're gonna go to the ecosystem for. That's where the cloud native comes in. That's where thing kind of comes together. So to me, I'm bullish on the operating model, but I'm skeptical that HP can get that cloud native developer. I haven't seen it yet. I'm looking for it. We're gonna look for it here. >>A key to that is going to be consistently. I, the, one of the things I'm looking for on the tech side, I, I hate to compare what HPE is doing to what VMware did with vCloud error years ago, but vCloud error on the outside looked >>Wonderful. Yes, >>It did. Once you tried to use it, it was just flaky underneath. And that's the part I'm looking to see customers pounding on it and saying, you know what API call after API I call, can I, uh, provision 10,000 pods a day? Does it scale down? Does it scale? And is it consistent? Is it >>Fragile Al roo she's co seasoned veteran? Uh, she was at V VMware cloud. She saw that movie. She gets a Mulligan, Dave. So I think her leadership is impressive. And I think she could bring a lot to the table to your point about don't make that same mistake and they gotta get this architecture, right. If they get the operating model right with GreenLake, they can double down on that and enable the developers that are driving the digital transformation. That to me is the, the key positions that they have to nail. And they do that. The rest is just fringe work. In my opinion, >>The reason why Alma was brought in, sorry, Lisa, it was, and then you gotta chime in here was to really build out that platform so that internal people at HPE can actually build value on top of it and the ecosystem that's her priority. >>We're gonna hear a lot from the ecosystem in the next couple of days, but I wanna get your perspective on, you've been following HPE a long time, all three of you. What are some of the things that you're hearing right now that are differentiators? We were just at Dell technologies. We talking about apex. We saw the big announcement they had with snowflake. We were at snowflake two weeks ago. I wanna get all three of your opinions on what are you seeing? Where is HP leading? >>I mean, HPE and Dell will, both with Dell, with apex are go, they're both gonna differentiate with their strengths. And, you know, for Dell, that's their breadth and their, their portfolio. And for, for HPE, that's their sort of open posture. I mean, John, you, you know this well, uh, that's their, their ecosystem, which I know has to evolve. And to me, their focus, you know, Antonio laid out some of the key differentiators. I, I, I think some of them were kind of, you know, pushing the envelope a little bit. Uh, but, but I think they're focus on as a service burning the, the, the boats telling wall street, this is our business. I think that's their differentiator. Is that they're, they're all in. >>Yeah. I, I think they, they try to highlight it by re announcing their private cloud service. I don't even know why they needed to announce that they have a private cloud. GreenLake is a cloud it's is a private cloud >>With block storage, hit disaster recovery. It's like good >>With like everything you get. But I think the, the key is, is that all of that is available today and you can get it in all kinds of frame of, of formats and, and frames specifically, if I'm a customer and I wanna get outta the data center and you, you know, Dave, we go back and forth about this all the time, and I wanna repatriate some workloads to Kubernetes on prem. I don't need to spend up another data center. I can go to Equinix, get GreenLake min IO, object storage on the back end, HPE lighthouse, all those services that I need for Kubernetes and repatriate my workloads without buying a new data center. And I get it as a service. I can get that Dave from HPE GreenLake, Dell apex is on the way. The >>Other thing they're differentiating with Aruba, that's something that Dell doesn't have. Yeah. And, and that is their edge play, I think is stronger than >>Of the others. Mean the, to me, the differentiator for HP is their, their history. Their channel's amazing. They got great Salesforce and they have serious customers and they have serious customers that have serious problems, uh, cyber security, uh, infrastructure, the security paradigm's changed. Uh, the deployment is changed how they deploy applications in their customer base. So they gotta step up to that challenge. And I think their differentiator is gonna be their size, their field and their ability to bring that operating model. And the hybrid model is a steady state. That's clear multi-cloud is just hybrids stitched together, but hybrid cloud, which is basically on premises and cloud to edge operating model is the number one thing that they need to nail. And if they nail that right, they will have a poll position that they could accelerate on. And again, I'm really gonna be watching how well they could enable cloud native developers, okay. To build modern agile applications while solving those serious problems with those serious customers. So again, I think hybrids spun in their direction. I'm not gonna say they got lucky, cuz they've always been on the hybrid bandwagon since we've been covering them. But I thought they'd be for a long day, but they're lucky to have hybrid. That's good for them. And I think do what Microsoft did convert their customers over and they do that, right? >>I think the key to that is gonna be ecosystem. Again, the developers need to see, especially the data piece, they talk about the cloud operating model. I think they're really moving that direction. The data piece to me is the weakest. Like they'll, they'll make claims that we can do anything that the cloud can do. You can't run snowflake, can't run data bricks, can't run Mongo Atlas. So they gotta figure out that data layer and that's optionality of, of data stores. And they don't have that today. >>Yeah. They, they, they have an announcement coming and I can't pre-announce it, but they're, they've, I've deemed them against it. They have the vision, Emeral data services, their data fabric multi-protocol access is a great start. They need the data network behind it. They need the ability to build a super cloud, a across multiple cloud providers, bringing some Google infos love inside of, uh, right next to your data. They have the hardware, they have the infrastructure, but they don't have the services. >>That's a key thing. I think one, you just brought up great point, Keith, and that is, is that at the end of the day, Dave, we're in a market now where agility and speed can be accomplished by startups or any company and HP's customers. Okay. Can move fast too. Okay. And so whoever can extend that value. If HPE can enable value creation for their customers, that's gonna be truly their, their task at hand, they got the channel, they got some leverage, but at the end of the day, the customers have alternatives now and they can move faster to get the value that they need to solve their serious problems. Uh, like cyber, like scalable infrastructure, like infrastructures code, like data ops, like AI ops, it's all here. And it's all coming really fast. Can GreenLake carry the day. And >>By the way, everything we just said about GreenLake in terms of table stakes and everything else, it applies for Dell. >>Yeah, absolutely. >>No question. It does guys. We have, and jam packed three days. We're gonna be talking with the ecosystem. We're gonna be talking with HPE leaders with customers. You're gonna hear all of these, uh, all this information unpacked over the next three days. We will be right back with our first guest for Dave ante, Keith Townson and John furrier. I'm Lisa Martin. Our first guest joins us momentarily.
SUMMARY :
It's the cube live on the show floor at I declared that the enterprise of the future would be edge centric, cloud enabled and data driven. Got a lot of work to do three years ago, John Antonio stood on this very stage saying we, And to me, I'm looking forward to seeing this discover if they have it or At least they're on the cloud curve. I can simply go to a AWS portal, launch, a free trial service and run it. So that's the tell sign that the enterprises H HP's customers the other hallmarks of cloud is you attract startups. I, I think that's a sign if they can do that. the startup I mean, yeah, don't you see that as a sort of a form of innovation startup, They gotta get the operating model, right job one as a service ARR, the company and, or manage services that they're gonna go to the ecosystem for. I, I hate to compare what HPE is doing to what VMware did with vCloud error years ago, And that's the part I'm looking to see customers pounding on it and saying, And I think she could bring a lot to the table to your point about don't make that same mistake and they and the ecosystem that's her priority. We saw the big announcement they had with snowflake. And to me, their focus, you know, Antonio laid out some of the key differentiators. I don't even know why they needed to announce that they have a private cloud. It's like good I don't need to spend up another data center. And, and that is their edge play, I think is stronger than And I think their differentiator is gonna be their size, their field and their ability to bring that operating Again, the developers need to see, especially the data piece, They have the hardware, they have the infrastructure, now and they can move faster to get the value that they need to solve their serious problems. We're gonna be talking with the ecosystem.
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Sahir Azam & Guillermo Rauch | MongoDB World 2022
>> We're back at the Big Apple, theCUBE's coverage of MongoDB World 2022. Sahir Azam is here, he's the Chief Product Officer of MongoDB, and Guillermo Rauch who's the CEO of Vercel. Hot off the keynotes from this morning guys, good job. >> Thank you. >> Thank you. >> Thank you for joining us here. Thanks for having us. Guillermo when it comes to modern web development, you know the back-end, the cloud guys got to it kind of sewn up, >> you know- >> Guillermo: Forget about it. >> But all the action's in the front end, and that's where you are. Explain Vercel. >> Yeah so Vercel is the company that pioneers front-end development as serverless infrastructure. So we built Next.js which is the most popular React framework in the world. This is what front-end engineers choose to build innovative UI's, beautiful websites. Companies like Dior and GitHub and TikTok and Twitch, which we mentioned in the keynote, are powering their entire dot-coms or all of their new parts of their dot-coms with Next.js. And Vercel is the serverless platform where you can deploy frameworks like in Next.js and others like Svelte and Vue to create really fast experiences on the web. >> So I hear, so serverless, I hear that's the hot trend. You guys made some announcements today. I mean when you look at the, we have spending data with our friends at ETR right down the street. I mean it's just off the charts, whether it's Amazon, Google, Azure Functions, I mean it's just exploding. >> Sahir: Yeah, it's I think in many ways, it's a natural trend. You know, we talk a lot about, whether it be today's keynote or another industry talks you see around our industry that developers are constantly looking for ways to focus on innovation and the business logic that defines their application and as opposed to managing the plumbing, and management of infrastructure. And we've seen this happen over and over again across every layer of the stack. And so for us, you know MongoDB, we have a bit of, you know sort of a lens of a broad spectrum of the market. We certainly have you know, large enterprises that are modernizing existing kind of core systems, then we have developers all over the world who are building the next big best thing. And that's what led us to partner with Vercel is just the bleeding edge of developers building in a new way, in a much more efficient way. And we wanted to make sure we provide a data platform that fits naturally in the way they want to work. >> So explain to our audience the trade-offs of serverless, and I want to get into sort of how you've resolved that. And then I want to hear from Guillermo, what that means for developers. >> Sahir: Yeah in our case, we don't view it as an either or, there are certain workloads and definitely certain companies that will gravitate towards a more traditional database infrastructure where they're choosing the configuration of their cluster. They want full control over it. And that provides, you know, certain benefits around cost predictability or isolation or perceived benefits at least of those things. And customers will gravitate towards that. Now on the flip side, if you're building a new application or you want the ability to scale seamlessly and not have to worry about any of the plumbing, serverless is clearly the easier model. So over the long term, we certainly expect to see as a mix of things, more and more serverless workloads being built on our platform and just generally in the industry, which is why we leaned in so heavily on investing in Atlas serverless. But the flexibility to not be forced into a particular model, but to get the same database experience across your application and even switch between them is an important characteristic for us as we build going forward. >> And you stressed the cost efficiency, and not having to worry about, you know, starting cold. You've architected around that, and what does that mean for a developer? >> Guillermo: For a developer it means that you kind of get the best of both worlds, right? Like you get the best possible performance. Front-end developers are extremely sensitive to this. That's why us pioneering this concept, serverless front-end, has put us in a very privileged position because we have to deliver that really quick time to first buy, that really quick paint. So any of the old trade-offs of serverless are not accepted by the market. You have to be extremely fast. You have to be instant to deliver that front-end content. So what we talked about today for example, with the Vercel Edge network, we're removing all of the cost of that like first hit. That cold start doesn't really exist. And now we're seeing it all across the board, going into the back-end where Mongo has also gotten rid of it. >> Dave: How do you guys collaborate? What's the focus of integration specifically from, you know, an engineering resource standpoint? >> Yeah the main idea is, idea to global app in seconds, right? You have your idea. We give you the framework. We don't give you infrastructure primitives. We give you all the necessary tools to start your application. In practice this means you host it in a Git repo. You import it onto Vercel. You install the Mongo integration. Now your front-end and your data back-end are connected. And then your application just goes global in seconds. >> So, okay. So you've abstracted away the complexity of those primitives, is that correct? >> Guillermo: Absolutely. >> Do do developers ever say, "That's awesome but I'd like to get to them every now and then." Or do you not allow that? >> Definitely. We expose all the underlying APIs, and the key thing we hear is that, especially with the push for usage-based billing models, observability is of the essence. So at any time you have to be able to query, in real time, every data point that the platform is observing. We give you performance analytics in real time to see how your front-end is performing. We give you statistics about how often you're querying your back-end and so on, and your cache hit ratios. So what I talked about today in the keynote is, it's not just about throwing more compute at the problem, but the ability to use the edge to your advantage to memoize computation and reuse it across different visits. >> When we think of mission critical historically, you know, you think about going to the ATM, right? I mean a financial transaction. But Mongo is positioning for mission critical applications across a variety of industries. Do we need to rethink what mission critical means? >> I think it's all in the eye of the beholder so to speak. If you're a new business starting up, your software and your application is your entire business. So if you have a cold start latency or God forbid something actually goes down, you don't have a business. So it's just as mission critical to that founder of a new business and new technology as it is, you know, an established enterprise that's running sort of a more, you know, day-to-day application that we may all interact with. So we treat all of those scenarios with equal fervor and importance right? And many times, it's a lot of those new experiences that the become the day-to-day experiences for us globally, and are super important. And we power all of those, whether it be an established enterprise all the way to the next big startup. >> I often talk about COVID as the forced march to digital. >> Sahir: Mm-Hmm. >> Which was obviously a little bit rushed, but if you weren't in digital business, you were out of business. And so now you're seeing people step back and say, "All right, let's be more thoughtful about our digital transformation. We've got some time, we've obviously learned some things made some mistakes." It's all about the customer experience though. And that becomes mission critical right? What are you seeing Guillermo, in terms of the patterns in digital transformation now that we're sort of exiting the isolation economy? >> One thing that comes to mind is, we're seeing that it's not always predictable how fast you're going to grow in this digital economy. So we have customers in the ecommerce space, they do a drop and they're piggybacking on serverless to give them that ability to instantly scale. And they couldn't even prepare for some of these events. We see that a lot with the Web3 space and NFT drops, where they're building in such a way that they're not sensitive to this massive fluctuations in traffic. They're taking it for granted. We've put in so much work together behind the scenes to support it. But the digital native creator just, "Oh things are scaling from one second to the next like I'm hitting like 20,000 requests per second, no problem Vercel is handling it." But the amount of infrastructural work that's gone behind the scenes in support has been incredible. >> We see that in gaming all the time, you know it's really hard for a gaming company to necessarily predict where in the globe a game's going to be particularly hot. Games get super popular super fast if they're successful, it's really hard to predict. It's another vertical that's got a similar dynamic. >> So gaming, crypto, so you're saying that you're able to assist your customers in architecting so that the website doesn't crash. >> Guillermo: Absolutely. >> But at the same time, if the the business dynamic changes, they can dial down. >> Yeah. >> Right and in many ways, slow is the new down, right? And if somebody has a slow experience they're going to leave your site just as much as if it's- >> I'm out of here- >> You were down. So you know, it's really maintaining that really fast performance, that amazing customer experience. Because this is all measured, it's scientific. Like anytime there's friction in the process, you're going to lose customers. >> So obviously people are excited about your keynote, but what have they been saying? Any specific comments you can share, or questions that you got that were really interesting or? >> I'm already getting links to the apps that people are deploying. So the whole idea- >> Come on! >> All over the world. Yeah so it's already working I'm excited. >> So they were show they were showing off, "Look what I did" Really? >> Yeah on Twitter. >> That's amazing. >> I think from my standpoint, I got a question earlier, we were with a bunch of financial analysts and investors, and they said they've been talking to a lot of the customers in the halls. And just to see, you know, from the last time we were all in person, the number of our customers that are using multiple capabilities across this idea of a developer data platform, you know, certainly MongoDB's been a popular core database open source for a long time. But the new capabilities around search, analytics, mobile being adopted much more broadly to power these experiences is the most exciting thing from our side. >> So from 2019 to now, you're saying substantial uptick in adoption for these features? >> Yeah. And many of them are new. >> Time series as well, that's pretty new, so yeah. >> Yeah and you know, our philosophy of development at MongoDB is to get capabilities in the hands of customers early. Get that feedback to enrich and drive that product-market fit. And over the last three years especially, we've been transitioning from a single product kind of core, you know, non relational modern database to a data platform, a developer data platform that adds more and more capabilities to power these modern applications. And a lot of those were released during the pandemic. Certainly we talked about them in our virtual conferences and all the zoom meetings we had over the years. But to actually go talk to all these customers, this is the largest conference we've ever put on, and to get a sense of, wow all the amazing things they're doing with them, it's definitely a different feeling when we're all together. >> So that's interesting, when you have such a hot product, product-led growth which is what Mongo has been in, and you add these new features. They're coming from the developers who are saying, "Hey, we need this." >> Yip. >> Okay so you have a pretty high degree of confidence, but how do you know when you have product-market fit? I mean, is it adoption, usage, renewals? What's your metric? >> Yeah I think it's a mix of quantitative measures that you know, around conversion rates, the size of your funnel, the retention rate, NPS which obviously can be measured, but also just qualitative. You know when you're talking to a developer or a technology executive around what their needs are, and then you see how they actually apply it to solve a problem, it's that balance between the qualitative and the quantitative measurement of things. And you can just sort of, frankly you can feel it. You can see it in the numbers sure, but you can kind of feel that excitement, you can see that adoption and what it empowers people to do. And so to me, as a product leader, it's always a blend of those things. If you get too obsessed with purely the metrics, you can always over optimize something for the wrong reason. So you have to bring in that qualitative feedback to balance yourself out. >> Right. >> Guillermo, what's next? What do you not have that you want from Sahir and Mongo? >> So the natural next step for serverless computing is, is the Edge. So we have to auto-scale, we have to tolerate fares. We have to be avail. We have to be easy, but we have to be global. And right now we've been doing this by using a lot of techniques like caching and replication and things like this. But the future's about personalizing even more to each visitor depending on where they are. So if I'm in New York, I want to get the latest offers for New York on demand, just for me, and using AI to continue to personalize that experience. So giving the developer these tools in a way where it feels natural to build an application like this. It doesn't feel like, "Oh I'm going to do this year 10 if I make it, I'm going to do it since the very beginning." >> Dave: Okay interesting. So that says to me that I'm not going to make a round trip to the cloud necessarily for that experience. So I'm going to have some kind, Apple today, at the Worldwide Developer Conference announced the M2, right. I've been looking at the M1 Ultra, and I'm going wow look at that! And so- >> Sahir: You were talking about that new one backstage. >> I mean it's this amazing pace of Silicon development and they're focusing on the NPU and you look at what Tesla's doing. I mean it's just incredible. So you're going to have some new hardware architecture that emerges. Most of the AI that's done today is modeling in the cloud. You're going to have a real time inferencing at the Edge. So that's not going to do the round trip. There's going to be a data store there, I think it has to be. You're going to persist some of the data, maybe not all of it. So it's a whole new architecture- >> Sahir: Absolutely. >> That's developing. That sounds very disruptive. >> Sahir: Yeah. >> How do you think about that, and how does Mongo play there? Guillermo first. >> What I spent a lot of time thinking about is obviously the developer experience, giving the programmer a programming model that is natural, intuitive, and produces its great results. So if they have to think about data that's local because of regulatory reasons for example, how can we let the framework guide them to success? I'm just writing an application I deployed to the cloud and then everything else is figured out. >> Yeah or speed of light is another challenge. (Sahir and Guillermo laugh) >> How can we overcome the speed of light is our next task for sure. >> Well you're working on that aren't you? You've got the best engineers on that one. (Sahir and Guillermo laugh) >> We can solve a lot of problems, I'm not sure of that one. >> So Mongo plays in that scenario or? >> Yeah so I think, absolutely you know, we've been focused heavily on becoming the globally distributed cloud data layer. The back-end data layer that allows you to persist data to align with performance and move data where it needs to be globally or deal with data sovereignty, data nationalism that's starting to rise, but absolutely there is more data being pushed out to the Edge, to your point around processing or inference happening at the Edge. And there's going to be a globally distributed front-end layer as well, whether data and processing takes apart. And so we're focused on one, making sure the data connectivity and the layer is all connected into one unified architecture. We do that in combination with technologies that we have that do with mobility or edge distribution and synchronization of data with realm. And we do it with partnerships. We have edge partnerships with AWS and Verizon. We have partnerships with a lot of CVM players who are building out that Edge platform and making sure that MongoDB is either connected to it or just driving that synchronization back and forth. >> I call that unified experience super cloud, Robbie Belson from Verizon the cloud continuum, but that consistent experience for developers whether you're on Prim, whether you're in you know, Azure, Google, AWS, and ultimately the Edge. That's the big- >> That's where it's going. >> White space right now I'm hearing, Guillermo, right? >> I think it'll define the next generation of how software is built. And we're seeing this almost like a coalition course between some of the ideas that the Web3 developers are excited about, which is like decentralization almost to the extreme. But the Web2 also needs more decentralization, because we're seeing it with like, the data needs to be local to me, I need more privacy. I was looking at the latest encryption features in Mongo, like I think both Web2 need to incorporate more of the ideas of Web3 and vice versa to create the best possible consumer experience. Privacy matters more than ever before. Latency for conversion matters more than ever before. And regulations are changing. >> Sahir: Yeah. >> And you talked about Web3 earlier, talked about new protocols, a new distributed you know, decentralized system emerging, new hardware architectures. I really believe we really think that new economics are going to bleed back into the data center, and yeah every 15 years or so this industry gets disrupted. >> Sahir: Yeah. >> Guillermo: Absolutely. >> You know you ain't see nothing yet guys. >> We all talked about hardware becoming commoditized 10, 15 years ago- >> Yeah of course. >> We get the virtualization, and it's like nope not at all. It's actually a lot of invention happening. >> The lower the price the more the consumption. So guys thanks so much. Great conversation. >> Thank you. >> Really appreciate your time. >> Really appreciate it I enjoyed the conversation. >> All right and thanks for watching. Keep it right there. We'll be back with our next segment right after this short break. Dave Vellante for theCUBE's coverage of MongoDB World 2022. >> Man Offscreen: Clear. (clapping) >> All right wow. Don't get up. >> Sahir: Okay. >> Is that a Moonwatch? >> Sahir: It is a Speedmaster but it's that the-
SUMMARY :
he's the Chief Product Officer of MongoDB, the cloud guys got to it kind of sewn up, and that's where you are. And Vercel is the I mean it's just off the charts, and the business logic that So explain to our audience But the flexibility to not be forced and not having to worry about, So any of the old trade-offs You install the Mongo integration. is that correct? "That's awesome but I'd like to get the edge to your advantage you know, that the become the day-to-day experiences the forced march to digital. in terms of the patterns behind the scenes to support it. We see that in gaming all the time, the website doesn't crash. But at the same time, friction in the process, So the whole idea- All over the world. from the last time we were all in person, And many of them are new. so yeah. and all the zoom meetings They're coming from the it's that balance between the qualitative So giving the developer So that says to me that I'm about that new one backstage. So that's not going to do the round trip. That's developing. How do you think about that, So if they have to think (Sahir and Guillermo laugh) How can we overcome the speed of light You've got the best engineers on that one. I'm not sure of that one. and the layer is all connected That's the big- the data needs to be local to me, that new economics are going to bleed back You know you ain't We get the virtualization, the more the consumption. enjoyed the conversation. of MongoDB World 2022. All right wow.
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Dev Ittycheria, MongoDB | MongoDB World 2022
>> Welcome back to New York City everybody. This is The Cube's coverage of MongoDB World 2022, Dev Ittycheria, here is the president and CEO of MongoDB. Thanks for spending some time with us. >> It's Great to be here Dave, thanks for having me. >> You're very welcome. So your keynotes this morning, I was hearkening back to Steve Ballmer, running around the stage screaming, developers, developers, developers. You weren't jumping around like a madman, but the message was the same. And you've not deviated from that message. I remember when it was 10th Gen, so you've been consistent. >> Yes. >> Why is Mongo DB so alluring to developers? >> Yeah, because I would say the reason we're so popular Dave is that our whole business was founded on the ethos, so making developers incredibly productive. Just getting the infrastructure out of the way so that the developers is really focused on what's important and that's building great applications that transform their business. And the way you do that is you look at where they spend most of the time. and they spend most of the time working with data. How do you present data, the right data, the right time, at the right place, and the right way. And when you remove the friction of working with data, you unleash so much more productivity, which people just say, oh my goodness, I can move so much faster. Product leaders can get products out the door faster than the competitors. Senior level executives can seize new opportunities or respond to new threats. And that was so profound during COVID when everyone had to think about pivoting their business. >> When you came to MongoDB, why did you choose this company? What was it that excited you about it? >> I get that question a lot. I would say conventional wisdom would suggest that MongoDB was not a great choice. There weren't that many companies who were very successful in open source, Red Hat was the only one. No one had really built a deep technology company in New York city. They say, you got to do it in the valley. And database companies need a lot of capital. Now turns out that raising capital of this past decade was a lot easier, but it still takes a lot of time, and a lot of capitals, you have to have a lot of patience. When I did my diligence, I was actually a VC before I joined MongoDB. The whole next generation database segment was really taking off. And actually I looked at some competing investments to MongoDB, and when I did my diligence, it was clear even then. And this is circa 2012, that MongoDB is way ahead in terms of customer attraction, commercials, and even kind of developer mind share. And so I ended up passing those investments. and then lo and behold, I got a call from a very senior executive recruiter who said, Dev, you got to take a meeting with MongoDB, there's something really interesting going on. And they had raised a lot of capital and they had just not been able to kind of really execute in terms of the opportunity. And they realized they needed to make a change. And so one thing led to another. One of the things that really actually convinced me, is when I did my diligence, I realized the customers they had loved MongoDB. They just really weren't executing on all cylinders. And I always believe you never bet against a company whose customers love the product. And said, that's something here. The second thing I would say is open source. Yes, is true that open source was not very successful, but that was open source 1.0. Open source 2.0, the technology is much better than the commercial options. And so that convinced me. And then New York, I lived in New York a big part of my life. I think New York's a fabulous place to build a business. There's so much talent, your customers are right... You walk out the door, there's customers all over the place. And getting to Europe is very easy, Almost like flying to the west coast. So it's a very central place to build a business. >> And it's easier to fix execution, wouldn't you say? And maybe even go to market than it is to fix a product that customers really don't love. >> Correct, it's much easier to fix leadership issues, culture issues, execution issues. Nailing product market fit is very, very hard. And there were signs, there's still some issues, there's still some rough spots, but there a lot of signs that this company was very, very close, and that's why I took the bet. >> And this is before there was that huge influx of capital into the separating compute from storage and the whole cloud thing, which is interesting. Because you take a company like Cloudera, they got caught up in that and got kind of washed over. And I guess you could argue Hortonworks did too, and they could have dead ended both. And then that just didn't work. But it's interesting to see Mongo, the market kind of came to you. And that really does speak to the product. It wasn't a barrier for you. You guys have obviously a lot of work to get into the cloud with Atlas, but it seemed like a natural fit with the product. It wasn't like a complete fork. >> Well, I think the challenge that we had was we had a lot of adoption, but we had tough time commercializing the business. And at some point I had to tell the all employees, it's great that we have all these people who are using MongoDB, but if you don't start generating revenue, our investors are going to get tired of subsidizing this company. So I had to try and change the culture. And as you imagine, the engineers didn't really like the salespeople, the salespeople thought the engineers didn't really want to make any money. And what I said, like, let's all galvanize around customers and let's make them really excited and try and create a lot of value. And so we just put a lot more discipline in terms of how we prosecuted deals. We put a lot more discipline in terms of what are the problems we're trying to solve. And one thing led to another, we started building the business brick by brick. And one of the things that became clear for me was that the old open source model of trying to find that happy medium between what you give away and what you charge for, is always a tough game. Like because finding that where the paywall is, if you give away too much new features, you don't make any money. If you don't give away enough, you don't have any adoption. So you're caught in this catch-22. The best way to monetize open source, is open source as a service. And we saw Amazon do that frankly. We learned a lot from how Amazon did that. And one of the advantages that MongoDB had that I didn't fully appreciate when I joined the company, but I was very grateful. It is that they had a much more restrictive license. Which we ended up actually changing and made it even more restrictive, which allowed us to perfect ourselves from being cannibalized by the cloud providers, so that we could build our own business using our own IP that we had invested in and create a cloud service. >> That was a huge milestone. And of course you have great relationships with all the cloud providers, but it got contentious there for a while, but, you give the cloud providers an inch, they're going to take a mile. That's just the way, they're aggressive like that. But thank you for going through the history with me a little bit, because when you go back to the IPO, IPO was 2017, right? >> Correct. >> I always tell young investors, my kids especially, don't buy a stock at IPO, you're going to have a better chance, but the window from Mongo was very narrow. So, you didn't really get a much better chance a little bit. And then it's been a rocket ship since then. Sure, there's been some volatility, but you look at some of the big IPOs, like Facebook, or Snap, or even Snowflake, there was better opportunities. But you guys have executed really, really well. That's part of your ethos in your management team. And it came across on the earnings call recently. >> Yep. >> It was very optimistic, yet at the same time you set cautious tones and you got, I think high marks. >> Yes. >> For some of that caution but that execution. So talk about where you feel the business is today given the economic uncertainty? >> Well, what I'd say is we feel really good about the long term. We feel like the secular trends are really in our favor. Software's fundamentally transforming every industry. And people want to use modern software to either automate inefficient processes, enable new capabilities, drive better customer experiences. And the level of performance and scale you need for today's modern applications is profoundly different than applications yesterday. So we think we're well positioned for that. What we said on the earnings call was that we started seeing a moderation of growth, slight moderation of growth in our low end of the business in Europe. It was in our self-serve business and in the SMB space for the NQ1, towards the end of Q1. And we saw a little bit of that show up in the self-serve business in may in Q2. And that's why while we raised guidance, we basically quantified the impact, which is roughly about 30 to 35 million for the year, based on what we saw. And in that assumption, we assumed like... We just can't assume it's going to only be at the low in the market, probably some effect at the enterprise market. Maybe not as much, but there'll be some effect. So we need to factor that in. And we wanted to help kind of investors have some sort of framework to think about what the impact is. We don't want to be one of those companies that said absolutely nothing. And we don't want to be one of those companies that just waves the hand, but then it wasn't really that useful for investors. >> Yeah, I thought it was substantive. You talked about those market trends, you cited three things. The developers recognize that there are limits to legacy RDBMS. You talked about the, what I call point solutions creep. And then the document model is the best for developers. >> Great. >> And when the conversation turned to consumption, everybody's concerned about consumption obviously. You said... My take, somewhat insulated from that because you're running mission critical apps. It's not discretionary. My question to you is, should we rethink the definition of mission-critical? You think of Oracle mission critical running a bank. Mission -critical today in this digital world seems to be different, is that fair? >> Gosh, when's the last time you ever saw a website down? Like if you're running like any kind of digital channel, or engaging with the customers, or your partners, or your suppliers, you need to be up all the time. And so you need a very resilient, highly available data platform. It needs to be highly performance as you add more users, you need to be scale. And we saw a lot of that when COVID hit. Like companies had to completely repovit. And we talked about some examples where like a health and beauty retailer who was all kind of basically retail, had to suddenly pivot to e-commerce strategy. We've had streaming and gaming companies suddenly saw this massive influx of data that they scaled their operations very, very quickly. So I would say anytime you're engaging with customers, customers they're so used to the kind of the consumer facing applications. I almost joke like slow is the old down. If you're not performant, it doesn't matter. They're going to abandon you and go somewhere else. So if you're an e-commerce site and you're not performing well and not serving up the right skews, depending on what they're looking for, they're going to go somewhere else. >> So it's a click away. You talk about a hundred billion TAM, maybe that's even undercounted as you start to bring new capabilities in there. But there's no lack of market for you. >> Correct. >> How do you think about the market opportunity? >> Well, we believe... Again, software is transforming so many industries. IDC says that 715 million applications will be built over the next two to three years by 2025. To put that number of perspective, that's more apps that will be built the next three to four years than were built in the last 40. The rate and pace of innovation is as exploding. And people are building custom applications. Yes, Workday, Salesforce, other companies, commercial companies are great companies, but my competitors can use Workday or Salesforce, some of those commercial companies. That doesn't gimme a competitive advantage, what gives me a competitive advantage is building custom software that better engage my customers, that transforms my business in adding new capabilities or drives more efficiency. And the applications are only getting smarter. And so you're seeing that innovation explode and that plays to our strength. People need platforms like MongoDB to build the next generation of applications. >> So Atlas is now roughly 60% of your business, think is growing at 85%. So it's at least the midterm future. But my question to you is, is it the future? 'Cause when we start to think about the edge, it's not necessarily the cloud. You're not going to be able to go that round trip and the latency. And we had Verizon on earlier, talking about what they're doing with 5G, and the Mobile Edge. Is Mongo positioning for that edge? And is our definition of cloud changing? Where it's not just OnPrem and across clouds, but it's also out to the edge, this continuous experience. >> So I'll make two points. One, definitely we believe the applications of the future will be mobile first or purely mobile. Because one with the advent of 5G, the distinction between mobile and web is going to blur, with a hundred times faster networking speeds. But the second point I make is that how that shows up on our revenue on our income table will look like Atlas. Because we don't charge nothing for the end point, it's basically driving consumption of the back end. And so we've introduced a bunch of very, very sophisticated capabilities to synchronized data from the edge to the backend and vice versa with things like flexible sync. So we see so many customers now using that capability, whether you're field service technicians, whether you're a mobile first company, et cetera. So that will drive Atlas revenue. So on an income statement, it'll look like Atlas, but we're obviously addressing those broader set of mobile needs. >> You talk a lot about product market fit former VC, of course, Mark Andreen says, product market fit you kind of know when you see it, your hair's on fire, you can't buy a service. How do you know when you have product market fit? >> Well, one, we have the luxury of lots of customers. So they tell us pretty clearly when they're happy, and we can see that by usage behavior. Now the other benefit of a cloud service, is we can see the level of activity. We can see the level of engagement. We can see how much data they're consuming. We can see all the actions they're taking. So you get the fidelity of feedback you get from Atlas versus someone doing something behind their own firewall. And you kind of call 'em and check in on them is very, very different. So that level of insight gives us visibility in terms of what products and features have been used, gives us a sense how things going well, or is there something awry. Maybe they have misconfigured something or they don't know how to use some capabilities. So the level of engagement that we can have with a customer using a service is so much different. And so we've really invested in our customer success organization. So the byproduct of that is that our retention rates are also very, very strong. Because you have such better information about what's happening in terms of your customers. >> See retention in real time. You've been somewhat... Is just so hard to say this 'cause you're growing at 50% a year. But you're somewhat conservative about the pace of hiring for go to market. And I'm curious as to how you think about scaling, especially when you introduce new products. Atlas is several years ago. But as you extend your capabilities and add new products, how do you decide when to scale? >> So it's a constant process. We've been quite aggressive in scaling organization for a couple reasons. One, we have very low market share, so the market's vastly under penetrated. We still don't have reps in every NFL sitting in the United States, which just kind of crazy. There's other parts of the world that we are just still vastly under penetrated in. But we also look at how those organizations are doing. So if we see a team really killing it, we're going to deploy more resources. Because one, it tells us there's more opportunity there, and there's a strong team there. If we see a team that maybe is struggling a little bit, we'll try and uncover. Rather than just applying more resources in, we'll try and uncover what are the issues and make sure we stabilize the organization and then devote resources. It's all in the measure of like being very disciplined about where we deploy our resources, to get those kind of returns. And on the product side, we obviously go through a very iterative process and kind of do rank order all the projects and what we think the expected returns are. Obviously, we look at the customer feedback, we look at what our strategic priorities are. And that informs what projects we fund and what projects kind of are below the line. And we do that over and over again every quarter. So every quarter we revisit the business, we have a very QBR centric culture. So we're constantly checking in and seeing how the business is operating. And then we make those investment decisions. In general, we've been investing very aggressively in terms of expanding our reach around the world. >> It seems like, well, with Mongo, your product portfolios... From an outside observer standpoint, it seems like you've always had pretty good product market fit. But I was curious, in your VC days, would you ever encourage companies to scale go to market prior to having confidence in product market fit? Or did you always see those as sequential activities? >> Well, I think the challenge is this part it's analysis part is judgment. So you don't necessarily have to have perfect product market fit to start investing. But you also don't want to plow a bunch of resources and realize the product doesn't work and then how you're burning through a lot of cash. So there's a little bit of art to the process. When I joined MongoDB, I could tell that we had a strong engineering team. They knew how to build high quality products, but we just struggled with commercialization. The culture wasn't great across the company. And we had some leadership challenges. So that's when I joined, I kind of focused on those things and tried to bring the organization together. And slowly we started chipping away and making people feel like they were winners. And once you start winning, that becomes contagious. And then the nice thing is when you start winning, you get a lot more customer feedback. That feedback helps you refine your products even more, which then adds... It's like the flywheel effect that starts taking off. >> So it seems the culture's working now. Do you have a favorite product from the announcements today? >> Well, I really like our foray to analytics. And essentially what we're seeing is really two big trends. One you're seeing applications get smarter. What applications are doing is really automating a lot of processes and rather than someone having to press a button. Based on analytics, you can automate a lot of decision making. So that's one theme that we're seeing as applications get smarter. The second theme is that people want more and more insight in terms of what's happening. And the source of that is insights is your operational database. Because that's where you're having transactions, that's where you know what products are selling, that's where you know what customers are buying. So people want more and more real time data versus waiting to take that data, put it somewhere else and then run reports and then get some update at the end of the night or maybe at the week. So that's driving a lot of really interesting use cases. And especially when you marry in things like time series use cases where you're collecting a lot of data people want to see trend analysis what's happening. Which I think it's a very exciting area. We introduced a very cool feature called Queryable Encryption, which basically... The problem with encrypting data, is you can't really query it because my definition's encrypted. >> Yeah, you're right. >> But obviously data security is very important. What we announced, is we're using very sophisticated cryptography. People can query the data, but they don't have really access to the data. So it really protects you from like data breaches or malicious users accessing your data, but you still can kind of make that data usable. So that was a very interesting announcer that we made today. >> Sounds like magic without the performance hit. >> Yes. >> You can do that. Dev, thanks so much for coming in The Cube. Congratulations on all activity, bumper sticker on day one. >> Oh, it's super exciting. The energy was palpable, 3,300 people in the room, lots of customers, lots of users. We had lots of investors here as well for our investor day, have a dinner tonight with a bunch of senior execs, so it's been a busy day. >> Future is bright for MongoBD. Dev, thanks for so much for coming on The Cube. And thanks for watching, this is Dave Vellante and we'll see you next time. (upbeat music)
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7 Sahir Azam & Guillermo Rauch
>> Man Offscreen: Standby. Dave is coming you in 5, 4, 3, 2. >> We're back at the Big Apple, theCUBE's coverage of MongoDB World 2022. Sahir Azam is here, he's the Chief Product Officer of MongoDB, and Guillermo Rauch who's the CEO of Vercel. Hot off the keynotes from this morning guys, good job. >> Thank you. >> Thank you. >> Thank you for joining us here. Thanks for having us. Guillermo when it comes to modern web development, you know the back-end, the cloud guys got to it kind of sewn up, >> you know- >> Guillermo: Forget about it. >> But all the action's in the front end, and that's where you are. Explain Vercel. >> Yeah so Vercel is the company that pioneers front-end development as serverless infrastructure. So we built Next.js which is the most popular React framework in the world. This is what front-end engineers choose to build innovative UI's, beautiful websites. Companies like Dior and GitHub and TikTok and Twitch, which we mentioned in the keynote, are powering their entire dot-coms or all of their new parts of their dot-coms with Next.js. And Vercel is the serverless platform where you can deploy frameworks like in Next.js and others like Svelte and Vue to create really fast experiences on the web. >> So I hear, so serverless, I hear that's the hot trend. You guys made some announcements today. I mean when you look at the, we have spending data with our friends at ETR right down the street. I mean it's just off the charts, whether it's Amazon, Google, Azure Functions, I mean it's just exploding. >> Sahir: Yeah, it's I think in many ways, it's a natural trend. You know, we talk a lot about, whether it be today's keynote or another industry talks you see around our industry that developers are constantly looking for ways to focus on innovation and the business logic that defines their application and as opposed to managing the plumbing, and management of infrastructure. And we've seen this happen over and over again across every layer of the stack. And so for us, you know MongoDB, we have a bit of, you know sort of a lens of a broad spectrum of the market. We certainly have you know, large enterprises that are modernizing existing kind of core systems, then we have developers all over the world who are building the next big best thing. And that's what led us to partner with Vercel is just the bleeding edge of developers building in a new way, in a much more efficient way. And we wanted to make sure we provide a data platform that fits naturally in the way they want to work. >> So explain to our audience the trade-offs of serverless, and I want to get into sort of how you've resolved that. And then I want to hear from Guillermo, what that means for developers. >> Sahir: Yeah in our case, we don't view it as an either or, there are certain workloads and definitely certain companies that will gravitate towards a more traditional database infrastructure where they're choosing the configuration of their cluster. They want full control over it. And that provides, you know, certain benefits around cost predictability or isolation or perceived benefits at least of those things. And customers will gravitate towards that. Now on the flip side, if you're building a new application or you want the ability to scale seamlessly and not have to worry about any of the plumbing, serverless is clearly the easier model. So over the long term, we certainly expect to see as a mix of things, more and more serverless workloads being built on our platform and just generally in the industry, which is why we leaned in so heavily on investing in Atlas serverless. But the flexibility to not be forced into a particular model, but to get the same database experience across your application and even switch between them is an important characteristic for us as we build going forward. >> And you stressed the cost efficiency, and not having to worry about, you know, starting cold. You've architected around that, and what does that mean for a developer? >> Guillermo: For a developer it means that you kind of get the best of both worlds, right? Like you get the best possible performance. Front-end developers are extremely sensitive to this. That's why us pioneering this concept, serverless front-end, has put us in a very privileged position because we have to deliver that really quick time to first buy, that really quick paint. So any of the old trade-offs of serverless are not accepted by the market. You have to be extremely fast. You have to be instant to deliver that front-end content. So what we talked about today for example, with the Vercel Edge network, we're removing all of the cost of that like first hit. That cold start doesn't really exist. And now we're seeing it all across the board, going into the back-end where Mongo has also gotten rid of it. >> Dave: How do you guys collaborate? What's the focus of integration specifically from, you know, an engineering resource standpoint? >> Yeah the main idea is, idea to global app in seconds, right? You have your idea. We give you the framework. We don't give you infrastructure primitives. We give you all the necessary tools to start your application. In practice this means you host it in a Git repo. You import it onto Vercel. You install the Mongo integration. Now your front-end and your data back-end are connected. And then your application just goes global in seconds. >> So, okay. So you've abstracted away the complexity of those primitives, is that correct? >> Guillermo: Absolutely. >> Do do developers ever say, "That's awesome but I'd like to get to them every now and then." Or do you not allow that? >> Definitely. We expose all the underlying APIs, and the key thing we hear is that, especially with the push for usage-based billing models, observability is of the essence. So at any time you have to be able to query, in real time, every data point that the platform is observing. We give you performance analytics in real time to see how your front-end is performing. We give you statistics about how often you're querying your back-end and so on, and your cache hit ratios. So what I talked about today in the keynote is, it's not just about throwing more compute at the problem, but the ability to use the edge to your advantage to memoize computation and reuse it across different visits. >> When we think of mission critical historically, you know, you think about going to the ATM, right? I mean a financial transaction. But Mongo is positioning for mission critical applications across a variety of industries. Do we need to rethink what mission critical means? >> I think it's all in the eye of the beholder so to speak. If you're a new business starting up, your software and your application is your entire business. So if you have a cold start latency or God forbid something actually goes down, you don't have a business. So it's just as mission critical to that founder of a new business and new technology as it is, you know, an established enterprise that's running sort of a more, you know, day-to-day application that we may all interact with. So we treat all of those scenarios with equal fervor and importance right? And many times, it's a lot of those new experiences that the become the day-to-day experiences for us globally, and are super important. And we power all of those, whether it be an established enterprise all the way to the next big startup. >> I often talk about COVID as the forced march to digital. >> Sahir: Mm-Hmm. >> Which was obviously a little bit rushed, but if you weren't in digital business, you were out of business. And so now you're seeing people step back and say, "All right, let's be more thoughtful about our digital transformation. We've got some time, we've obviously learned some things made some mistakes." It's all about the customer experience though. And that becomes mission critical right? What are you seeing Guillermo, in terms of the patterns in digital transformation now that we're sort of exiting the isolation economy? >> One thing that comes to mind is, we're seeing that it's not always predictable how fast you're going to grow in this digital economy. So we have customers in the ecommerce space, they do a drop and they're piggybacking on serverless to give them that ability to instantly scale. And they couldn't even prepare for some of these events. We see that a lot with the Web3 space and NFT drops, where they're building in such a way that they're not sensitive to this massive fluctuations in traffic. They're taking it for granted. We've put in so much work together behind the scenes to support it. But the digital native creator just, "Oh things are scaling from one second to the next like I'm hitting like 20,000 requests per second, no problem Vercel is handling it." But the amount of infrastructural work that's gone behind the scenes in support has been incredible. >> We see that in gaming all the time, you know it's really hard for a gaming company to necessarily predict where in the globe a game's going to be particularly hot. Games get super popular super fast if they're successful, it's really hard to predict. It's another vertical that's got a similar dynamic. >> So gaming, crypto, so you're saying that you're able to assist your customers in architecting so that the website doesn't crash. >> Guillermo: Absolutely. >> But at the same time, if the the business dynamic changes, they can dial down. >> Yeah. >> Right and in many ways, slow is the new down, right? And if somebody has a slow experience they're going to leave your site just as much as if it's- >> I'm out of here- >> You were down. So you know, it's really maintaining that really fast performance, that amazing customer experience. Because this is all measured, it's scientific. Like anytime there's friction in the process, you're going to lose customers. >> So obviously people are excited about your keynote, but what have they been saying? Any specific comments you can share, or questions that you got that were really interesting or? >> I'm already getting links to the apps that people are deploying. So the whole idea- >> Come on! >> All over the world. Yeah so it's already working I'm excited. >> So they were show they were showing off, "Look what I did" Really? >> Yeah on Twitter. >> That's amazing. >> I think from my standpoint, I got a question earlier, we were with a bunch of financial analysts and investors, and they said they've been talking to a lot of the customers in the halls. And just to see, you know, from the last time we were all in person, the number of our customers that are using multiple capabilities across this idea of a developer data platform, you know, certainly MongoDB's been a popular core database open source for a long time. But the new capabilities around search, analytics, mobile being adopted much more broadly to power these experiences is the most exciting thing from our side. >> So from 2019 to now, you're saying substantial uptick in adoption for these features? >> Yeah. And many of them are new. >> Time series as well, that's pretty new, so yeah. >> Yeah and you know, our philosophy of development at MongoDB is to get capabilities in the hands of customers early. Get that feedback to enrich and drive that product-market fit. And over the last three years especially, we've been transitioning from a single product kind of core, you know, non relational modern database to a data platform, a developer data platform that adds more and more capabilities to power these modern applications. And a lot of those were released during the pandemic. Certainly we talked about them in our virtual conferences and all the zoom meetings we had over the years. But to actually go talk to all these customers, this is the largest conference we've ever put on, and to get a sense of, wow all the amazing things they're doing with them, it's definitely a different feeling when we're all together. >> So that's interesting, when you have such a hot product, product-led growth which is what Mongo has been in, and you add these new features. They're coming from the developers who are saying, "Hey, we need this." >> Yip. >> Okay so you have a pretty high degree of confidence, but how do you know when you have product-market fit? I mean, is it adoption, usage, renewals? What's your metric? >> Yeah I think it's a mix of quantitative measures that you know, around conversion rates, the size of your funnel, the retention rate, NPS which obviously can be measured, but also just qualitative. You know when you're talking to a developer or a technology executive around what their needs are, and then you see how they actually apply it to solve a problem, it's that balance between the qualitative and the quantitative measurement of things. And you can just sort of, frankly you can feel it. You can see it in the numbers sure, but you can kind of feel that excitement, you can see that adoption and what it empowers people to do. And so to me, as a product leader, it's always a blend of those things. If you get too obsessed with purely the metrics, you can always over optimize something for the wrong reason. So you have to bring in that qualitative feedback to balance yourself out. >> Right. >> Guillermo, what's next? What do you not have that you want from Sahir and Mongo? >> So the natural next step for serverless computing is, is the Edge. So we have to auto-scale, we have to tolerate fares. We have to be avail. We have to be easy, but we have to be global. And right now we've been doing this by using a lot of techniques like caching and replication and things like this. But the future's about personalizing even more to each visitor depending on where they are. So if I'm in New York, I want to get the latest offers for New York on demand, just for me, and using AI to continue to personalize that experience. So giving the developer these tools in a way where it feels natural to build an application like this. It doesn't feel like, "Oh I'm going to do this year 10 if I make it, I'm going to do it since the very beginning." >> Dave: Okay interesting. So that says to me that I'm not going to make a round trip to the cloud necessarily for that experience. So I'm going to have some kind, Apple today, at the Worldwide Developer Conference announced the M2, right. I've been looking at the M1 Ultra, and I'm going wow look at that! And so- >> Sahir: You were talking about that new one backstage. >> I mean it's this amazing pace of Silicon development and they're focusing on the NPU and you look at what Tesla's doing. I mean it's just incredible. So you're going to have some new hardware architecture that emerges. Most of the AI that's done today is modeling in the cloud. You're going to have a real time inferencing at the Edge. So that's not going to do the round trip. There's going to be a data store there, I think it has to be. You're going to persist some of the data, maybe not all of it. So it's a whole new architecture- >> Sahir: Absolutely. >> That's developing. That sounds very disruptive. >> Sahir: Yeah. >> How do you think about that, and how does Mongo play there? Guillermo first. >> What I spent a lot of time thinking about is obviously the developer experience, giving the programmer a programming model that is natural, intuitive, and produces its great results. So if they have to think about data that's local because of regulatory reasons for example, how can we let the framework guide them to success? I'm just writing an application I deployed to the cloud and then everything else is figured out. >> Yeah or speed of light is another challenge. (Sahir and Guillermo laugh) >> How can we overcome the speed of light is our next task for sure. >> Well you're working on that aren't you? You've got the best engineers on that one. (Sahir and Guillermo laugh) >> We can solve a lot of problems, I'm not sure of that one. >> So Mongo plays in that scenario or? >> Yeah so I think, absolutely you know, we've been focused heavily on becoming the globally distributed cloud data layer. The back-end data layer that allows you to persist data to align with performance and move data where it needs to be globally or deal with data sovereignty, data nationalism that's starting to rise, but absolutely there is more data being pushed out to the Edge, to your point around processing or inference happening at the Edge. And there's going to be a globally distributed front-end layer as well, whether data and processing takes apart. And so we're focused on one, making sure the data connectivity and the layer is all connected into one unified architecture. We do that in combination with technologies that we have that do with mobility or edge distribution and synchronization of data with realm. And we do it with partnerships. We have edge partnerships with AWS and Verizon. We have partnerships with a lot of CVM players who are building out that Edge platform and making sure that MongoDB is either connected to it or just driving that synchronization back and forth. >> I call that unified experience super cloud, Robbie Belson from Verizon the cloud continuum, but that consistent experience for developers whether you're on Prim, whether you're in you know, Azure, Google, AWS, and ultimately the Edge. That's the big- >> That's where it's going. >> White space right now I'm hearing, Guillermo, right? >> I think it'll define the next generation of how software is built. And we're seeing this almost like a coalition course between some of the ideas that the Web3 developers are excited about, which is like decentralization almost to the extreme. But the Web2 also needs more decentralization, because we're seeing it with like, the data needs to be local to me, I need more privacy. I was looking at the latest encryption features in Mongo, like I think both Web2 need to incorporate more of the ideas of Web3 and vice versa to create the best possible consumer experience. Privacy matters more than ever before. Latency for conversion matters more than ever before. And regulations are changing. >> Sahir: Yeah. >> And you talked about Web3 earlier, talked about new protocols, a new distributed you know, decentralized system emerging, new hardware architectures. I really believe we really think that new economics are going to bleed back into the data center, and yeah every 15 years or so this industry gets disrupted. >> Sahir: Yeah. >> Guillermo: Absolutely. >> You know you ain't see nothing yet guys. >> We all talked about hardware becoming commoditized 10, 15 years ago- >> Yeah of course. >> We get the virtualization, and it's like nope not at all. It's actually a lot of invention happening. >> The lower the price the more the consumption. So guys thanks so much. Great conversation. >> Thank you. >> Really appreciate your time. >> Really appreciate it I enjoyed the conversation. >> All right and thanks for watching. Keep it right there. We'll be back with our next segment right after this short break. Dave Vellante for theCUBE's coverage of MongoDB World 2022. >> Man Offscreen: Clear. (clapping) >> All right wow. Don't get up. >> Sahir: Okay. >> Is that a Moonwatch? >> Sahir: It is a Speedmaster but it's that the-
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Tony Baer, dbInsight | MongoDB World 2022
>>Welcome back to the big apple, everybody. The Cube's continuous coverage here of MongoDB world 2022. We're at the new Javet center. It's it's quite nice. It was built during the pandemic. I believe on top of a former bus terminal. I'm told by our next guest Tony bear, who's the principal at DB insight of data and database expert, longtime analyst, Tony. Good to see you. Thanks for coming >>On. Thanks >>For having us. You face to face >>And welcome to New York. >>Yeah. Right. >>New York is open for business. >>So, yeah. And actually, you know, it's interesting. We've been doing a lot of these events lately and, and especially the ones in Vegas, it's the first time everybody's been out, you know, face to face, not so much here, you know, people have been out and about a lot of masks >>In, >>In New York city, but, but it's good. And, and this new venue is fantastic >>Much nicer than the old Javits. >>Yeah. And I would say maybe 3000 people here. >>Yeah. Probably, but I think like most conferences right now are kind of, they're going through like a slow ramp up. And like for instance, you know, sapphires had maybe about one third, their normal turnout. So I think that you're saying like one third to one half seems to be the norm right now are still figuring out how we're, how and where we're gonna get back together. Yeah. >>I think that's about right. And, and I, but I do think that that in most of the cases that we've seen, it's exceeded people's expectations at tenants, but anyway sure. Let's talk about Mongo, very interesting company. You know, we've been kind of been watching their progression from just sort of document database and all the features and functions they're adding, you just published a piece this morning in venture beat is time for Mongo to get into analytics. Yes. You know? Yes. One of your favorite topics. Well, can they expand analytics? They seem to be doing that. Let's dig into it. Well, >>They're taking, they've been taking slow. They've been taking baby steps and there's good reason for that because first thing is an operational database. The last thing you wanna do is slow it down with very complex analytics. On the other hand, there's huge value to be had if you would, if you could, you know, turn, let's say a smart, if you can turn, let's say an operational database or a transaction database into a smart transaction database. In other words, for instance, you know, let's say if you're, you're, you're doing, you know, an eCommerce site and a customer has made an order, that's basically been out of the norm. Whether it be like, you know, good or bad, it would be nice. Basically, if at that point you could then have a next best action, which is where analytics comes in. But it's a very lightweight form of analytics. It's not gonna, it's actually, I think probably the best metaphor for this is real time credit scoring. It's not that they're doing your scoring you in real time. It's that the model has been computed offline so that when you come on in real time, it can make a smart decision. >>Got it. Okay. So, and I think it was your article where I, I wrote down some examples. Sure. Operational, you know, use cases, patient data. There's certainly retail. We had Forbes on earlier, right? Obviously, so very wide range of, of use cases for operational will, will Mongo, essentially, in your view, is it positioned to replace traditional R D BMS? >>Well, okay. That's a long that's, that's much, it's >>Sort of a loaded question, but >>That's, that's a very loaded question. I think that for certain cases, I think it will replace R D BMS, but I still, I mean, where I, where I depart from Mongo is I do not believe that they're going to replace all R D D BMSs. I think, for instance, like when you're doing financial transactions, you know, the world has been used to table, you know, you know, columns and rows and tables. That's, it's a natural form for something that's very structured like that. On the other hand, when you take a look, let's say OT data, or you're taking a look at home listings that tends to more naturally represent itself as documents. And so there's a, so it's kind of like documents are the way that let's say you normally see the world. Relational is the way that you would structure the world. >>Okay. Well, I like that. So, but I mean, in the early days, obviously, and even to this day, it's like the target for Mongo has been Oracle. Yeah. Right, right. And so, and then, you know, you talk to a lot of Oracle customers as do I sure. And they are running the most mission, critical applications in the world, and it's like banking and financial and so many. And, and, and, you know, they've kind of carved out that space, but are we, should we be rethinking the definition of, of mission critical? Is that changing? >>Well, number one, I think what we've traditionally associated mission critical systems with is our financial transaction systems and to a less, and also let's say systems that schedule operations. But the fact is there are many forms of operations where for instance, let's say you're in a social network, do you need to have that very latest update? Or, you know, basically, can you go off, let's say like, you know, a server that's eventually consistent. In other words, the, do you absolutely have, you know, it's just like when you go on Twitter, do you naturally see all the latest tweets? It's not the system's not gonna crash for that reason. Whereas let's say if you're doing it, you know, let's say an ATM banking ATM system, that system better be current. So I think there's a delineation. The fact is, is that in a social network, arguably that operational system is mission critical, but it's mission critical in a different way from a, you know, from, let's say a banking system. >>So coming back to this idea of, of this hybrid, I think, you know, I think Gartner calls it H tab hybrid, transactional analytics >>Is changed by >>The minute, right. I mean, you mentioned that in, in your article, but basically it's bringing analytics to transactions bringing those, those roles together. Right. Right. And you're saying with Mongo, it's, it's lightweight now take, you use two other examples in your article, my SQL heat wave. Right. I think you had a Google example as well, DB, those are, you're saying much, much heavier analytics, is that correct? Or >>I we'll put it this way. I think they're because they're coming from a relational background. And because they also are coming from companies that already have, you know, analytic database or data warehouses, if you will, that their analytic, you know, capabilities are gonna be much more fully rounded than what Mongo has at this point. It's not a criticism of a Mongo MongoDB per >>Per, is that by design though? Or ne not necessarily. Is that a function of maturity? >>I think it's function of maturity. Oh, okay. I mean, look, to a certain extent, it's also a function of design in terms of that the document model is a little, it's not impossible to basically model it for analytics, but it takes more, you know, transformation to, to decide which, you know, let's say field in that document is gonna be a column. >>Now, the big thing about some of these other, these hybrid systems is, is eliminating the need for two databases, right? Eliminating the need for, you know, complex ETL. Is, is that a value proposition that will emerge with, with Mongo in your view? >>You know, I, I mean, put it this way. I think that if you take a look at how they've, how Mongo is basically has added more function to its operations, someone talking about analytics here, for instance, adding streaming, you know, adding, adding, search, adding time series, that's a matter of like where they've eliminated the need to do, you know, transformation ETL, but that's not for analytics per se for analytics. I think through, you know, I mean through replication, there's still gonna be some transformation in terms of turning, let's say data, that's, that's formed in a document into something that's represented by columns. There is a form of transformation, you know, so that said, and Mongo is already, you know, it has some NA you know, nascent capability there, but it's all, but this is still like at a rev 1.0 level, you know, I expect a lot more >>Of so refin you, how Amazon says in the fullness of time, all workloads will be in the cloud. And we could certainly debate that. What do we mean by cloud? So, but there's a sort of analog for Mongo that I'll ask you in the fullness of time, will Mongo be in a position to replace data warehouses or data lakes? No. Or, or, or, and we know the answer is no. So that's of course, yeah. But are these two worlds on a quasi collision course? I think they >>More on a convergence course or the collision course, because number one is I said, the first principle and operational database is the last thing you wanna do is slow it down. And to do all this complex modeling that let's say that you would do in a data bricks, or very complex analytics that you would do in a snowflake that is going to get, you know, you know, no matter how much you partition the load, you know, in Atlas, and yes, you can have separate nodes. The fact is you really do not wanna burden the operational database with that. And that's not what it's meant for, but what it is meant for is, you know, can I make a smart decision on the spot? In other words, kinda like close the loop on that. And so therefore there's a, a form of lightweight analytic that you can perform in there. And actually that's also the same principle, you know, on which let's say for instance, you know, my SQL heat wave and Allo DBR based on, they're not, they're predicated on, they're not meant to replace, you know, whether it be exit data or big query, the idea there is to do more of the lightweight stuff, you know, and keep the database, you know, keep the operations, you know, >>Operating. And, but from a practitioner's standpoint, I, I, I can and should isolate you're saying that node, right. That's what they'll do. Sure. How does that affect cuz my understanding is that that the Mon Mongo specifically, but I think document databases generally will have a primary node. Right? And then you can set up secondary nodes, which then you have to think about availability, but, but would that analytic node be sort of fenced off? Is that part of the >>Well, that's actually what they're, they've already, I mean, they already laid the groundwork for it last year, by saying that you can set up separate nodes and dedicate them to analytics and what they've >>As, as a primary, >>Right? Yes, yes. For analytics and what they've added, what they're a, what they are adding this year is the fact to say like that separate node does not have to be the same instance class, you know, as, as, as, as the, >>What, what does that mean? Explain >>That in other words, it's a, you know, you could have BA you know, for instance, you could have a node for operations, that's basically very eye ops intensive, whereas you could have a node let's say for analytics that might be more compute intensive or, or more he, or, or more heavily, you know, configured with, with memory per se. And so the idea here is you can tailor in a node to the workload. So that's, you know what they're saying with, you know, and I forget what they're calling it, but the idea that you can have a different type, you can specify a different type of node, a different type of instance for the analytic node, I think is, you know, is a major step forward >>And that, and that that's enabled by the cloud and architecture. >>Of course. Yes. I mean, we're separating, compute from data is, is, is the starter. And so yeah. Then at that point you can then start to, you know, you know, to go less vanilla. I think, you know, the re you know, the, you know, the, I guess the fruition of this is going to be when they say, okay, you can run your, let's say your operational nodes, you know, dedicated, but we'll let you run your analytic nodes serverless. Can't do it yet, but I've gotta believe that's on the roadmap. >>Yeah. So seq brings a lot of overhead. So you get MQL, but now square this circle for me, cuz now you got Mago talking sequel. >>They had to start doing that some time. I mean, and I it's been a court take I've had from them from the, from the get go, which I said, I understand that you're looking at this as an alternative to SQL and that's perfectly valid, but don't deny the validity of SQL or the reason why we, you know, we need it. The fact is that you have, okay, the number, you know, according to Ty index, JavaScript is the seventh, most popular language. Most SQL follows closely behind at the ninth, most popular language you don't want to cl. And the fact is those people exist in the enterprise and they're, and they're disproportionately concentrated in analytics. I mean, you know, it's getting a little less, so now we're seeing like, you know, basically, you know, Python, the programmatic, but still, you know, a lot of sequel expertise there. It does not make, it makes no sense for Mongo to, to, to ignore or to overlook that audience. I think now they're, you know, you know, they're taking baby steps to start, you know, reaching out to them. >>It's interesting. You see it going both ways. See Oracle announces a Mongo, DB, Mongo. I mean, it's just convergence. You called it not, I love collisions, you know, >>I know it's like, because you thrive on drama and I thrive on can't. We all love each other, but you know, act. But the thing is actually, I've been, I wrote about this. I forget when I think it was like 2014 or 2016. It's when we, I was noticed I was noting basically the, you know, the rise of all these specialized databases and probably Amazon, you know, AWS is probably the best exemplar of that. I've got 15 or 16 or however, number of databases and they're all dedicated purpose. Right. But I also was, you know, basically saw that inevitably there was gonna be some overlap. It's not that all databases were gonna become one and the same we're gonna be, we're gonna become back into like the, you know, into a pan G continent or something like that. But that you're gonna have a relational database that can do JSON and, and a, and a document database that can do relational. I mean, you know, it's, to me, that's a no brainer. >>So I asked Andy Ja one time, I'd love to get your take on this, about those, you know, multiple data stores at the time. They probably had a thousand. I think they're probably up to 15 now, right? Different APIs, different S et cetera. And his response. I said, why don't you make it easier for, for customers and maybe build an abstraction or converge these? And he said, well, it's by design. What if you buy this? And, and what your thoughts are, cuz I, you know, he's a pretty straight shooter. Yeah. It's by design because it allows us as the market moves, we can move with it. And if we, if we give developers access to those low level primitives and APIs, then they can move with, with at market speed. Right. And so that again, by design, now we heard certainly Mongo poo pooing that today they didn't mention, they didn't call out Amazon. Yeah. Oracle has no compunction about specifically calling out Amazon. They do it all the time. What do you make of that? Can't Amazon have its cake and eat it too. In other words, extend some of the functionality of those specific databases without going to the Swiss army. >>I I'll put it this way. You, you kind of tapped in you're, you're sort of like, you know, killing me softly with your song there, which is that, you know, I was actually kind of went on a rant about this, actually know in, you know, come, you know, you know, my year ahead sort of out predictions. And I said, look, cloud folks, it's great that you're making individual SAS, you know, products easy to use. But now that I have to mix and match SAS products, you know, the burden of integration is on my shoulders. Start making my life easier. I think a good, you know, a good example of this would be, you know, for instance, you could take something like, you know, let's say like a Google big query. There's no reason why I can't have a piece of that that might, you know, might be paired, say, you know, say with span or something like that. >>The idea being is that if we're all working off a common, you know, common storage, we, you know, it's in cloud native, we can separate the computer engines. It means that we can use the right engine for the right part of the task. And the thing is that maybe, you know, myself as a consumer, I should not have to be choosing between big query and span. But the thing is, I should be able to say, look, I want to, you know, globally distribute database, but I also wanna do some analytics and therefore behind the scenes, you know, new microservices, it could connect the two wouldn't >>Microsoft synapse be an example of doing that. >>It should be an example. I wish I, I would love to hear more from Microsoft about this. They've been radio silent for about the past two or three years in data. You hardly hear about it, but synapse is actually those actually one of the ideas I had in mind now keep in mind that with synapse, you're not talking about, let's say, you know, I mean, it's, it's obviously a sequel data warehouse. It's not pure spark. It's basically their, it was their curated version of spark, but that's fine. But again, I would love to hear Microsoft talk more about that. They've been very quiet. >>Yeah. You, you, the intent is there to >>Simplify >>It exactly. And create an abstraction. Exactly. Yeah. They have been quiet about it. Yeah. Yeah. You would expect that, that maybe they're still trying to figure it out. So what's your prognosis from Mongo? I mean, since this company IP, you know, usually I, I tell and I tell everybody this, especially my kids, like don't buy a stock at IPO. You'll always get a better chance at a cheaper price to buy it. Yeah. And even though that was true with Mongo, you didn't have a big window. No. Like you did, for instance, with, with Facebook, certainly that's been the case with snowflake and sure. Alibaba, I mean, I name a zillion style was almost universal. Yeah. But, but since that, that, that first, you know, few months, period, this, this company has been on a roll. Right. And it, it obviously has been some volatility, but the execution has been outstanding. >>No question about that. I mean, the thing is, look what I, what I, and I'm just gonna talk on the product side on the sales side. Yeah. But on the product side, from the get go, they made a product that was easy for developers. Whereas let's say someone's giving an example, for instance, Cosmo CB, where to do certain operations. They had to go through multiple services in, you know, including Azure portal with Atlas, it's all within Atlas. So they've really, it's been kinda like design thinking from the start initially with, with the core Mongo DB, you know, you, the on premise, both this predates Atlas, I mean, part of it was that they were coming with a language that developers knew was just Javas script. The construct that they knew, which was JS on. So they started with that home core advantage, but they weren't the only ones doing that. But they did it with tooling that was very intuitive to developers that met developers, where they lived and what I give them, you know, then additional credit for is that when they went to the cloud and it wasn't an immediate thing, Atlas was not an overnight success, but they employed that same design thinking to Atlas, they made Atlas a good cloud experience. They didn't just do a lift and shift the cloud. And so that's why today basically like five or six years later, Atlas's most of their business. >>Yeah. It's what, 60% of the business now. Yeah. And then Dave, on the, on the earning scholar, maybe it wasn't Dave and somebody else in response to question said, yeah, ultimately this is the future will be be 90% of the business. I'm not gonna predict when. So my, my question is, okay, so let's call that the midterm midterm ATLA is gonna be 90% of the business with some exceptions that people just won't move to the cloud. What's next is the edge. A new opportunity is Mongo architecturally suited for the, I mean, it's certainly suited for the right, the home Depot store. Sure. You know, at the edge. Yeah. If you, if you consider that edge, which I guess it is form of edge, but how about the far edge EVs cell towers, you know, far side, real time, AI inferencing, what's the requirement there, can Mongo fit there? Any thoughts >>On that? I think the AI and the inferencing stuff is interesting. It's something which really Mongo has not tackled yet. I think we take the same principle, which is the lightweight stuff. In other words, you'll say, do let's say a classification or a prediction or some sort of prescriptive action in other words, where you're not doing some convolution, neural networking and trying to do like, you know, text, text to voice or, or, or vice versa. Well, you're not trying to do all that really fancy stuff. I think that's, you know, if you're keeping it SIM you know, kinda like the kiss principle, I think that's very much within Mongo's future. I think with the realm they have, they basically have the infrastructure to go out to the edge. I think with the fact that they've embraced GraphQL has also made them a lot more extensible. So I think they certainly do have, you know, I, I do see the edge as being, you know, you know, in, in, you know, in their, in their pathway. I do see basically lightweight analytics and lightweight, let's say machine learning definitely in their >>Future. And, but, and they would, would you agree that they're in a better position to tap that opportunity than say a snowflake or an Oracle now maybe M and a can change that. R D can maybe change that, but fundamentally from an architectural standpoint yeah. Are they in a better position? >>Good question. I think that that Mongo snowflake by virtual fact, I mean that they've been all, you know, all cloud start off with, I think makes it more difficult, not impossible to move out to the edge, but it means that, and I, and know, and I, and I said, they're really starting to making some tentative moves in that direction. I'm looking forward to next week to, you know, seeing what, you know, hearing what we're gonna, what they're gonna be saying about that. But I do think, right. You know, you know, to answer your question directly, I'd say like right now, I'd say Mongo probably has a, you know, has a head start there. >>I'm losing track of time. I could go forever with you. Tony bear DB insight with tons of insights. Thanks so much for coming back with. >>It's only one insight insight, Dave. Good to see you again. All >>Right. Good to see you. Thank you. Okay. Keep it right there. Right back at the Java center, Mongo DB world 2022, you're watching the cube.
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We're at the new Javet center. You face to face and especially the ones in Vegas, it's the first time everybody's been out, you know, And, and this new venue is fantastic And like for instance, you know, sapphires had maybe about one third, their normal turnout. you just published a piece this morning in venture beat is time for Mongo It's that the model has been computed offline so that when you come on in Operational, you know, use cases, patient data. That's a long that's, that's much, it's transactions, you know, the world has been used to table, you know, you know, columns and rows and and then, you know, you talk to a lot of Oracle customers as do I sure. you know, it's just like when you go on Twitter, do you naturally see all the latest tweets? I mean, you mentioned that in, in your article, but basically it's bringing analytics to transactions bringing are coming from companies that already have, you know, analytic database or data warehouses, Per, is that by design though? but it takes more, you know, transformation to, to decide which, you know, Eliminating the need for, you know, complex ETL. I think through, you know, I mean through replication, there's still gonna be some transformation in terms of turning, but there's a sort of analog for Mongo that I'll ask you in the fullness of time, And actually that's also the same principle, you know, on which let's say for instance, And then you can set up secondary nodes, which then you have to think about availability, the fact to say like that separate node does not have to be the same instance class, you know, for the analytic node, I think is, you know, is a major step forward you know, the re you know, the, you know, the, I guess the fruition of this is going to be when they but now square this circle for me, cuz now you got Mago talking sequel. I think now they're, you know, you know, they're taking baby steps to start, you know, reaching out to them. You called it not, I love collisions, you know, I mean, you know, it's, to me, that's a no brainer. I said, why don't you make it easier for, for customers and maybe build an abstraction or converge these? I think a good, you know, a good example of this would be, you know, for instance, you could take something But the thing is, I should be able to say, look, I want to, you know, globally distribute database, let's say, you know, I mean, it's, it's obviously a sequel data warehouse. I mean, since this company IP, you know, usually I, I tell and I tell everybody this, to developers that met developers, where they lived and what I give them, you know, but how about the far edge EVs cell towers, you know, you know, you know, in, in, you know, in their, in their pathway. And, but, and they would, would you agree that they're in a better position to tap that opportunity I mean that they've been all, you know, all cloud start off with, I could go forever with you. Good to see you again. Right back at the Java center, Mongo DB
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Tony Coleman, Temenos and Boris Bialek, MongoDB | MongoDB World 2022
>>Yeah, yeah, yeah. We're back at the center of the coverage of the world 20 twenty-two, the first live event in three years. Pretty amazing. And I'm really excited to have Tony Coleman. Here is the c e o of those who changing the finance and banking industry. And this is the global head of industry solutions. That would be welcome. Back to the cube. Welcome. First time. Um, so thanks for coming on. Thank you. >>Thanks for having us, >>Tony. Tell us about what are you guys up to? Disrupting the finance world. >>So tomorrow is everyone's banking platform. So we are a software company. We have over 3000 financial institutions around the world. Marketing tell me that that works out is over 1.2 billion people rely on terminal software for their banking and financial needs. 41 of the top 50 banks in the world run software and we are very proud to be powering all of those entities on their innovation journeys and bringing you know, that digital transformation that we've seen so much all over the past few years and enabling a lot of the world's unbanked through digital banking become, you know, members of the >>community. So basically you're bringing the software platform to enable that to somebody you don't have to build it themselves because they never get there. Absolutely. And and so that's why I don't know if you consider that disruptive. I guess I do to the industry to a certain extent. But when you think of disruption in the business, you think of Blockchain and crypto, and 50 is that is completely separate world and you guys participate in that as well. Well, I >>would say it's related right? I mean, I was doing a podcast recently and they had this idea of, um, buzzword jail where you could choose words to go into jail and I said 50 not because I think they're intrinsically bad, but I think just at the moment they are a rife for scam area. I think it's one of those one of these technologies and investment area that people don't understand it, and there's a lot of a lot of mistakes that can be made in that, >>Yeah, >>I mean, it's a fascinating piece that it could be truly transformative if we get it right, but it's very emerging, so we'll see so don't play a huge part in the Blockchain industry directly. We work with partners in that space, but in terms of digital assets and that sort of thing. Yeah, absolutely. >>So, Boris, you have industry solutions in your title. What does that entail? So >>basically, I'm responsible for all the verticals, and that includes great partners like Tony. And we're doing a lot of verticals by now. When you listen. Today in all these various talks, we have so much stuff ranging from banking, go retail, healthcare, insurance, you name it, we have it by now. And that's obviously the clients moving from the edge solution. Like touching a little toe in the water, but longer to going all in building biggest solutions you saw on stage the lady from this morning. These are not second Great. Yeah, we do something small now. We're part of the transformation journey. And this is where Tony and I can regularly together how we transform things and how we built a new way of banking is done with Michael services and technology surrounding it. Yeah, >>but what about performance in this world? Can you tell me about that? >>Yeah. This is an interesting thing because people always challenging what is performance and document databases. And Tony challenged us actually, six weeks before his own show several weeks ago in London and says, Boris, let's do a benchmark And maybe you bring your story because if I get too excited, I follow. >>Yeah, sure, that performance and efficiency topics close close to my heart. I have been for for years. And so, yeah, we every two or three years, we run a high water. We've got a high water benchmark, and this year we sort of double down literally double down on everything we did previously. So this was 200 million accounts, 100 million customers, and we were thrashing through 102,800 seventy-five transactions a second, which is a phenomenal number. And, uh, >>can I do that on the Blockchain? >>Wow. Yeah, exactly. Right. So this is you know, I get asked why we do such high numbers and the reason is very straightforward. If somebody wants 10,000 transactions a second, we're seeing banks now that need that sort of thing. If I can give them a benchmark report, this is 100,000. I don't need to keep doing benchmarks. 10. >>Yeah. Tell me more about the Anytime you get into benchmarks, you want to understand the configuration. The workload. Tell me more about that. So we have >>a pretty well path of a standard transaction mix. We call it a retail transaction mix. And so it's the tries to the workload. Is that because it's a simulation right around what you would do in your daily basis? So you're going to make payments you're going to check? Your balance is you're going to see what he's moved on your account. So we do all of that and we run it through a proper production, good environment. And this is really important. This is something we do in the lab you couldn't go live on. This is all all of the horrible, non functional requirements around high availability, >>security, security passes, private wings, all these things. And one thing is, they're doing this for a long time. So this is not like let's define something new for the world. Now, this is something Tony's doing for literally 10, 15 years now, right? >>It was only 15 years, but this >>is your benchmark >>top >>developed Okay, >>so we run it through and, um yeah, some fantastic numbers. And not just on the share sort of top-level numbers 100,000 transactions. A second response time out of it was fantastic. One-millisecond, which is just brilliant. So it means you get these really efficient numbers what that helped us do with, you know, some of the other partners that are involved in the benchmark as well. It meant that our throughput court, which is a really good measure of efficiency, is up to four times better than we ran it three years ago. So in terms of a sustainability piece, which is so important that that's really a huge improvement, that's down to application changes, architect changes as well as using appropriate technology in the right place. >>How important? With things like the number, of course, the memory size is the block sizes. All that stuff. >>We are very tiny. So this is the part. When I talk to people, we have what we call a system in the back of people. Look at me. Um, how many transactions on that one? So, to be fair, three-quarters, we're going to be one quarter or something else because we're still putting some components of and start procedures for disclosure. But when I think Seventy-five 1000 transactions on a single single 80 system, which is thirty-two cause you're saying correctly, something like that. This is a tiny machine in the world of banking. So before this was the main friends and now it's wonderful instance on a W s. And this is really amazing. Costed and environmental footprint is so, so important >>and there's a heavy right heavy environment. >>So the the way we the way we architect the solution is it follows something called a command query responsibility, segregated segregation. So what we do, we do all the commands inappropriate database for that piece, and that was running at about Twenty-five 1000 transactions a second and then we're streaming the data out of that directly into So actually I was doing more than the Seventy-five 1000 queries. A second, which is the part of it was also investing Twenty-five 1000 transactions the second at the same time >>and okay, and the workload had a high locality medium locality. It was just give us a picture of what that's like. Sorry. So, >>yeah, >>we don't have that. Yeah, >>so explain that That's not That's not the mindset for a document. Exactly. >>Exactly. In the document database, you don't have the hot spotting the one single field off the table, which is suddenly hot spotting. And now you have literally and recovery comes up and we say, What goes, goes together, get together belongs together, comes out together. So the number of, for example, it's much, much smaller and the document system, then historically, relationship. >>So it is not a good good indicator, necessarily >>anymore. That's what this is so much reduced. The number of access patterns are smaller, and I mean it is highly optimized, for example, internally as well. The internal structures, so that was very close to a >>traditional benchmark, would have a cash in front of a high cash rate. So 100 and 99% right, That's a high locality reference. But that's that's irrelevant. >>It's gone. There's no cashing in the middle anymore. It goes straight against the database. All these things are out, and that's what makes it so exciting and all the things in a real environment. I think we really need to stress it. It's not a test that at home. It's a real life environment out into the wild with the benchmark driving and driving. >>How did your customers respond? You did this for your recent event? >>Yeah, we did it for our use. A conference, our community for, um, which was a few weeks ago in London. Um, and the You know, the reaction was Certainly it was a great reception, of course, but the main thing that people are fascinated about, how much more efficient the whole platform it's explaining. So you know when we can run and it's a great number that we've got the team pulled out, which is so having doubled throughput on the platform from what we did three years ago, we're actually using 20% less infrastructure to give double the performance. Uh, macro-level, that's a phenomenal achievement. And that means that these changes that we make everything that we're doing benefits all of our customers. So all of the banks, when they take the latest release, is they get these benefits. Everything is that much more efficient. So everybody benefits from every investment, >>and this was running in the cloud. Is that correct? You're running out of this. >>So this was list, Um, 80 on a W s with a W s cases and processes. And so it was a really reality driven environment, >>pure pure cloud-native or using mana services on a W s. And then at least for the peace. It's >>awesome. I mean, uh, So now how convenient for the timing from, uh, the world. How are you socializing with your community? >>We're having this afternoon session as well, where we talk a little bit more detail about that, and he has a session as well tomorrow. So we see a lot of good feedback as well when we bring it up with clients. Obviously some clients get very specific because this reduction footprint is so huge when you think a client has 89 environments from early development systems to production to emergency standby, maybe a different cloud. All these things what day talks about the different Atlas features multi cloud environmentally. All this stuff comes to play. And this is why I'm so excited to work with them. We should bring up as well the other things which are available to ready already with your front and solutions with Infinity services because that's the other part of the modernization, the Michael Services, which Tony so politely not mentioning. So there's a lot of cool technology into that one, which fits to how it works in micros services. Happy I first all these what they called factors. Micro service a p. I cloud-native headless. I think that was the right order now. So all these things are reflected as well. But with their leadership chief now, I think a lot of companies have to play Catch-up now to what Tony and his team are delivering on the bank. This >>gets the modernization. We really haven't explicitly talks about that. Everything you've just said talks to modernization. So you typically in financial services find a lot of relation. Database twenty-year-old, hardened, etcetera, high availability. Give them credit for that. But a lot of times you'll see them just shift that into the cloud. You guys chose not to do that. What was the modernization journey look like? >>So it's a bit of, um yeah, a firm believer in pragmatism and using. I think you touched on earlier the appropriate technology. So >>horses for courses >>exactly right out of my mouth. And I was talking to one of the uh, the investor analysts earlier. And you know, the exact same question comes up, right? So if you've got a relation database or you've got a big legacy system and you're not gonna mainframe or whatever it is and you wanna pull that over when you it's not just a case of moving the data model from one paradigm to another. You need to look at it holistically, and you need to be ambitious. I think the industry has got, you know, quite nervous about some of these transformation projects, but in some ways it might be counter intuitive. I think being ambitious and being in bold is a better way. Better way through, you know, take take of you, look at it holistically. Layout of plan. It is hard. It is hard to do these sorts of transformations, but that's what makes it the challenge. That's what makes it fun. Take take those bold steps. Look at it holistically. Look at the end state and then work out a practical way. You can deliver value to the business and your customers as you deliver on the road. So >>did you migrate from a traditional R D B. M s to go. >>So So, Yeah, this is a conversation. So, uh, in the late nineties, the kind of the phrase document model hasn't really been coined yet. And for some of our work at the time, we refer to as a hierarchical model. Um, And at that point in time, really, if you wanted to sell to a bank, you needed to be running Oracle. So we took this data model and we got it running an article and then other relational databases as well, but actually under the colors there it is, sort of as well. So there is a project that we're looking at to say Well, okay, taking that model, which is in a relational database. And of course, you build over time, you do rely on some of the features of relations databases moving that over to something like, isn't it? You know, it's not quite as simple as just changing the data model. Um, so there's a few bits and pieces that we need to work through, but there is a concept that we are running, which is looking really promising and spurred on by the amazing results from the benchmark. That could be something That's really >>yeah, I think you know, 20 years ago you probably wouldn't even thought about it. It's just too risky. But today, with the modern tools and the cloud and you're talking about micro services and containers, it becomes potentially more feasible. >>But the other side of it is, you know, it's only relatively recently the Mongo who's had transaction support across multiple document multi collection transactions and in banking. As we all know, you know, it's highly regulated. That is, all of your worst possible non functional requirement. Security transaction reality. Thomas City You know, the whole the whole shebang. Your worst possible nightmare is Monday morning for >>us. So and I think one part which is exciting about this Tony is a very good practical example about this large scale modernization and cutting out by cutting off that layer and going back to the hierarchical internal structures. We're simply find a lot of the backing components of our because obviously translation which was done before, it's not need it anymore. And that is as well for me, an exciting example to see how long it takes what it is. So Tony space in my life experiments so to speak >>well, you're right because it used to be those migrations. Where how many line of code? How long do I have to freeze it? And that a lot of times lead people to say, Well, forget it, because the business is going to shut down. >>But now we do that. We do that. So I'm working, obviously, besides the work with a lot of financial clients, and but now it's my job is normally shift and left a pain in the game because the result of the work is when they move everything to the cloud and it was bad before. It will not be better in the cloud only because it's in somebody else's data center. So these modernization and innovation factor is absolutely critical. And it's only said that people get it by now. This shift and left over it is how can I innovate? How can accelerate innovation, and that leads very quickly to the document model discussion. >>Yeah, I think the world practitioners will tell you, if you really want to affect the operational model, have a meaningful impact on your business. You have to really modernized. You can't just lift shift that they're absolutely. You know, what's the difference between hundreds of millions or billions in some cases, versus, you know, some nice little hits here or there. >>So we see as well a lot of clients asking for solutions like the terminal solutions. And like others where there is not anymore discussion about how to move to the The question is how fast how can accelerate. We see the services request the first one. It's amazing. After the event, what we had in London, 100 clients calling us. So it's not our sales people calling upon the clients, the clients coming in. I saw it. How do we get started? And that is for me, from the vendor perspective, so to speak. Amazing moment >>yourself. You go, guys, we're gonna go. Thanks so much for that. You have to have you back and see how that goes. That. Yeah, that's a big story of if you're a great All right, keep it right there. Everybody will be right back. This is David for the Cube. You're watching our live coverage of mongo D B World 20 twenty-two from New York City. >>Yeah, >>Yeah, yeah, yeah, yeah
SUMMARY :
Here is the c e o of those Disrupting the finance world. So we are a software And and so that's why I don't know if you consider that disruptive. of, um, buzzword jail where you could choose words to go into I mean, it's a fascinating piece that it could be truly transformative if we get it right, So, Boris, you have industry solutions in your title. And that's obviously the clients moving show several weeks ago in London and says, Boris, let's do a benchmark And maybe you bring your story So this was 200 million accounts, 100 million customers, So this is you know, So we have This is something we do in the lab you couldn't go live on. So this is not like let's define something new for the world. So it means you get these really efficient numbers what that helped us do with, All that stuff. When I talk to people, we have what we call a system So the the way we the way we architect the solution is it follows something and okay, and the workload had a high locality medium locality. we don't have that. so explain that That's not That's not the mindset for a document. In the document database, you don't have the hot spotting the one single field so that was very close to a So 100 and It's a real life environment out into the wild with the benchmark driving and driving. So all of the banks, when they take the latest release, is they get these benefits. and this was running in the cloud. So this was list, Um, 80 on a W s with a W s cases And then at least for the peace. the timing from, uh, the world. So we see a lot of good feedback as well when we bring it So you typically in financial I think you touched on earlier the appropriate technology. And you know, the exact same question comes up, So So, Yeah, this is a conversation. yeah, I think you know, 20 years ago you probably wouldn't even thought about it. But the other side of it is, you know, it's only relatively recently the the backing components of our because obviously translation which was done before, it's not need it anymore. And that a lot of times lead people to say, of financial clients, and but now it's my job is normally shift and left a pain in the what's the difference between hundreds of millions or billions in some cases, versus, you know, So we see as well a lot of clients asking for solutions like You have to have you back and see how that goes.
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Ian Massingham, MongoDB and Robbie Belson, Verizon | MongoDB World 2022
>>Welcome back to NYC the Cube's coverage of Mongo DB 2022, a few thousand people here at least bigger than many people, perhaps expected, and a lot of buzz going on and we're gonna talk devs. I'm really excited to welcome back. Robbie Bellson who's the developer relations lead at Verizon and Ian Massingham. Who's the vice president of developer relations at Mongo DB Jens. Good to see you. Great >>To be here. >>Thanks having you. So Robbie, we just met a few weeks ago at the, the red hat summit in Boston and was blown away by what Verizon is doing in, in developer land. And of course, Ian, you know, Mongo it's rayon Detra is, is developers start there? Why is Mongo so developer friendly from your perspective? >>Well, it's been the ethos of MongoDB since day one. You know, back when we launched the first version of MongoDB back in 2009, we've always been about making developers lives easier. And then in 2016, we announced and released MongoDB Atlas, which is our cloud managed service for MongoDB, you know, starting with a small number of regions built on top of AWS and about 2,500 adoption events per week for MongoDB Atlas. After the first year today, MongoDB Atlas provides a managed service for MongoDB developers around the world. We're present in almost a hundred cloud regions across S DCP and Azure. And that adoption number is now running at about 25,000 developers a week. So, you know, the proof are in proof is really in the metrics. MongoDB is an incredibly popular platform for developers that wanna build data-centric applications. You just can't argue with the metrics really, >>You know, Ravi, sometimes there's an analyst who come up with these theories and one of the theories I've been spouting for a long time is that developers are gonna win the edge. And now to, to see you at Verizon building out this developer community was really exciting to me. So explain how you got this started with this journey. >>Absolutely. As you think about Verizon 5g edge or mobile edge computing portfolio, we knew from the start that developers would play a central role and not only consuming the service, but shaping the roadmap for what it means to build a 5g future. And so we started this journey back in late 20, 19 and fast forward to about a year ago with Mongo, we realized, well, wait a minute, you look at the core service offerings available at the edge. We didn't know really what to do with data. We wanted to figure it out. We wanted the vote of confidence from developers. So there I was in an apartment in Colorado racing, your open source Mongo against that in the region edge versus region, what would you see? And we saw tremendous performance improvements. It was so much faster. It's more than 40% faster for thousands and thousands of rights. And we said, well, wait a minute. There's something here. So what often starts is an organic developer, led intuition or hypothesis can really expand to a much broader go to market motion that really brings in the enterprise. And that's been our strategy from day one. Well, >>It's interesting. You talk about the performance. I, I just got off of a session talking about benchmarks in the financial services industry, you know, amazing numbers. And that's one of the hallmarks of, of Mongo is it can play in a lot of different places. So you guys both have developer relations in your title. Is that how you met some formal developer relations? >>We were a >>Program. >>Yeah, I would say that Verizon is one of the few customers that we also collaborate with on a developer relations effort. You know, it's in our mutual best interest to try to drive MongoDB consumption amongst developers using Verizon's 5g edge network and their platform. So of course we work together to help, to increase awareness of MongoDB amongst mobile developers that want to use that kind of technology. >>But so what's your story on this? >>I mean, as I, as I mentioned, everything starts with an organic developer discovery. It all started. I just cold messaged a developer advocate on Twitter and here we are at MongoDB world. It's amazing how things turn out. But one of the things that's really resonated with me as I was speaking with one of, one of your leads within your organization, they were mentioning that as Mongo DVIA developed over the years, the mantra really became, we wanna make software development easy. Yep. And that really stuck with me because from a network perspective, we wanna make networking easy. Developers are not gonna care about the internals of 5g network. In fact, they want us to abstract away those complexities so that they can focus on building their apps. So what better co-innovation opportunity than taking MongoDB, making software easy, and we make the network easy. >>So how do you think about the edge? How does you know variety? I mean, to me, you know, there's a lot of edge use cases, you know, think about the home Depot or lows. Okay, great. I can put like a little mini data center in there. That's cool. That's that's edge. Like, but when I think of Verizon, I mean, you got cell towers, you've got the far edge. How do you think about edge Robbie? >>Well, the edge is a, I believe a very ambiguous term by design. The edge is the device, the mobile device, an IOT device, right? It could be the radio towers that you mentioned. It could be in the Metro edge. The CDN, no one edge is better than the other. They're all just serving different use cases. So when we talk about the edge, we're focused on the mobile edge, which we believe is most conducive to B2B applications, a fleet of IOT devices that you can control a manufacturing plant, a fleet of ground and aerial robotics. And in doing so you can create a powerful compute mesh where you could have a private network and private mobile edge computing by way of say an AWS outpost and then public mobile edge computing by way of AWS wavelength. And why keep them separate. You could have a single compute mesh even with MongoDB. And this is something that we've been exploring. You can extend Atlas, take a cluster, leave it in the region and then use realm the mobile portfolio and spread it all across the edge. So you're creating that unified compute and data mesh together. >>So you're describing what we've been expecting is a new architecture emerging, and that's gonna probably bring new economics of new use cases, right? Where are we today in that first of all, is that a reasonable premise that this is a sort of a new architecture that's being built out and where are we in that build out? How, how do you think about the, the future of >>That? Absolutely. It's definitely early days. I think we're still trying to figure it out, but the architecture is definitely changing the idea to rip out a mobile device that was initially built and envisioned for the device and only for the device and say, well, wait a minute. Why can't it live at the edge? And ultimately become multi-tenant if that's the data volume that may be produced to each of those edge zones with hypothesis that was validated by developers that we continue to build out, but we recognize that we can't, we can't get that static. We gotta keep evolving. So one of our newest ideas as we think about, well, wait a minute, how can Mongo play in the 5g future? We started to get really clever with our 5g network APIs. And I, I think we talked about this briefly last time, 5g, programmability and network APIs have been talked about for a while, but developers haven't had a chance to really use them and our edge discovery service answering the question in this case of which database is the closest database, doesn't have to be invoked by the device anymore. You can take a thin client model and invoke it from the cloud using Atlas functions. So we're constantly permuting across the entire portfolio edge or otherwise for what it means to build at the edge. We've seen such tremendous results. >>So how does Mongo think about the edge and, and, and playing, you know, we've been wondering, okay, which database is actually gonna be positioned best for the edge? >>Well, I think if you've got an ultra low latency access network using data technology, that adds latency is probably not a great idea. So MongoDB since the very formative years of the company and product has been built with performance and scalability in mind, including things like in memory storage for the storage engine that we run as well. So really trying to match the performance characteristics of the data infrastructure with the evolution in the mobile network, I think is really fundamentally important. And that first principles build of MongoDB with performance and scalability in mind is actually really important here. >>So was that a lighter weight instance of, of Mongo or not >>Necessarily? No, not necessarily. No, no, not necessarily. We do have edge cashing with realm, the mobile databases Robbie's already mentioned, but the core database is designed from day one with those performance and scalability characteristics in mind, >>I've been playing around with this. This is kind of a, I get a lot of heat for this term, but super cloud. So super cloud, you might have data on Preem. You might have data in various clouds. You're gonna have data out at the edge. And, and you've got an abstraction that allows a developer to, to, to tap services without necessarily if, if he or she wants to go deep into the S great, but then there's a higher level of services that they can actually build for their customers. So is that a technical reality from a developer standpoint, in your view, >>We support that with the Mongo DB multi-cloud deployment model. So you can place Mongo DB, Atlas nodes in any one of the three hyperscalers that we mentioned, AWS, GCP or Azure, and you can distribute your data across nodes within a cluster that is spread across different cloud providers. So that kinds of an kind of answers the question about how you do data placement inside the MongoDB clustered environment that you run across the different providers. And then for the abstraction layer. When you say that I hear, you know, drivers ODMs the other intermediary software components that we provide to make developers more productive in manipulating data in MongoDB. This is one of the most interesting things about the technology. We're not forcing developers to learn a different dialect or language in order to interact with MongoDB. We meet them where they are by providing idiomatic interfaces to MongoDB in JavaScript in C sharp, in Python, in rust, in that in fact in 12 different pro programming languages that we support as a first party plus additional community contributed programming languages that the community have created drivers for ODMs for. So there's really that model that you've described in hypothesis exist in reality, using >>Those different Compli. It's not just a series of siloed instances in, >>In different it's the, it's the fabric essentially. Yeah. >>What, what does the Verizon developer look like? Where does that individual come from? We talked about this a little bit a few weeks ago, but I wonder if you could describe it. >>Absolutely. My view is that the Verizon or just mobile edge ecosystem in general for developers are present at this very conference. They're everywhere. They're building apps. And as Ian mentioned, those idiomatic interfaces, we need to take our network APIs, take the infrastructure that's being exposed and make sure that it's leveraging languages, frameworks, automation, tools, the likes of Terraform and beyond. We wanna meet developers where they are and build tools that are easy for them to use. And so you had talked about the super cloud. I often call it the cloud continuum. So we, we took it P abstraction by abstraction. We started with, will it work in one edge? Will it work in multiple edges, public and private? Will it work in all of the edges for a given region, public or private, will it work in multiple regions? Could it work in multi clouds? We've taken it piece by piece by piece and in doing so abstracting way, the complexity of the network, meaning developers, where they are providing those idiomatic interfaces to interact with our API. So think the edge discovery, but not in a silo within Atlas functions. So the way that we're able to converge portfolios, using tools that dev developers already use know and love just makes it that much easier. Do, >>Do you feel like I like the cloud continuum cause that's really what it is. The super cloud does the security model, how does the security model evolve with that? >>At least in the context of the mobile edge, the attack surface is a lot smaller because it's only for mobile traffic not to say that there couldn't be various configuration and human error that could be entertained by a given application experience, but it is a much more secure and also reliable environment from a failure domain perspective, there's more edge zones. So it's less conducive to a regionwide failure because there's so many more availability zones. And that goes hand in hand with security. Mm. >>Thoughts on security from your perspective, I mean, you added, you've made some announcements this week, the, the, the encryption component that you guys announced. >>Yeah. We, we issued a press release this morning about a capability called queryable encryption, which actually as we record this Mark Porter, our CTO is talking about in his keynote, and this is really the next generation of security for data stored within databases. So the trade off within field level encryption within databases has always been very hard, very, very rigid. Either you have keys stored within your database, which means that your memory, so your data is decrypted while it's resident in memory on your database engine. This allow, of course, allows you to perform query operations on that data. Or you have keys that are managed and stored in the client, which means the data is permanently OBS from the engine. And therefore you can't offload query capabilities to your data platform. You've gotta do everything in the client. So if you want 10 records, but you've got a million encrypted records, you have to pull a million encrypted records to the client, decrypt them all and see performance hit in there. Big performance hit what we've got with queryable encryption, which we announced today is the ability to keep data encrypted in memory in the engine, in the database, in the data platform, issue queries from the client, but use a technology called structural encryption to allow the database engine, to make decisions, operate queries, and find data without ever being able to see it without it ever being decrypted in the memory of the engine. So it's groundbreaking technology based on research in the field of structured encryption with a first commercial database provided to bring this to market. >>So how does the mobile edge developer think about that? I mean, you hear a lot about shifting left and not bolting on security. I mean, is this, is this an example of that? >>It certainly could be, but I think the mobile edge developer still stuck with how does this stuff even work? And I think we need to, we need to be mindful of that as we build out learning journeys. So one of my favorite moments with Mongo was an immersion day. We had hosted earlier last year where we, our, from an enterprise perspective, we're focused on BW BS, but there's nothing stopping us. You're building a B2C app based on the theme of the winner Olympics. At the time, you could take a picture of Sean White or of Nathan Chen and see that it was in fact that athlete and then overlaid on that web app was the number of medals they accrued with the little trumpeteer congratulating you for selecting that athlete. So I think it's important to build trust and drive education with developers with a more simple experience and then rapidly evolve overlaying the features that Ian just mentioned over time. >>I think one of the keys with cryptography is back to the familiar messaging for the cloud offloading heavy lifting. You actually need to make it difficult to impossible for developers to get this wrong, and you wanna make it as easy as possible for developers to deal with cryptography. And that of course is what we're trying to do with our driver technology combined with structure encryption, with query encryption. >>But Robbie, your point is lots of opportunity for education. I mean, I have to say the developers that I work with, it's, I'm, I'm in awe of how they solve problems and I, and the way they solve problems, if they don't know the answer, they figure out how to go get it. So how, how are your two communities and other communities, you know, how are they coming together to, to solve such problems and share whether it's best practices or how do I do this? >>Well, I'm not gonna lie in person. Events are a bunch of fun. And one of the easiest domain knowledge exchange opportunities, when you're all in person, you can ideate, you can whiteboard, you can brainstorm. And often those conversations are what leads to that infrastructure module that an immersion day features. And it's just amazing what in person events can do, but community groups of interest, whether it's a Twitch stream, whether it's a particular code sample, we rely heavily on digital means today to upscale the developer community, but also build on by, by means of a simple port request, introduce new features that maybe you weren't even thinking of before. >>Yeah. You know, that's a really important point because when you meet people face to face, you build a connection. And so if you ask a question, you're more likely perhaps to get an answer, or if one doesn't exist in a, in a search, you know, you, oh, Hey, we met at the, at the conference and let's collaborate on this guys. Congratulations on, on this brave new world. You're in a really interesting spot. You know, developers, developers, developers, as Steve bomber says screamed. And I was glad to see Dave was not screaming and jumping up and down on the stage like that, but, but the message still resonates. So thank you, definitely appreciate. All right, keep it right there. This is Dave ante for the cubes coverage of Mago DB world 2022 from New York city. We'll be right back.
SUMMARY :
Who's the vice president of developer relations at Mongo DB Jens. And of course, Ian, you know, Mongo it's rayon Detra is, is developers start Well, it's been the ethos of MongoDB since day one. So explain how you versus region, what would you see? So you guys both have developer relations in your So of course we But one of the things that's really resonated with me as I was speaking with one So how do you think about the edge? It could be the radio towers that you mentioned. the idea to rip out a mobile device that was initially built and envisioned for the of the company and product has been built with performance and scalability in mind, including things like the mobile databases Robbie's already mentioned, but the core database is designed from day one So super cloud, you might have data on Preem. So that kinds of an kind of answers the question about how It's not just a series of siloed instances in, In different it's the, it's the fabric essentially. but I wonder if you could describe it. So the way that we're able to model, how does the security model evolve with that? And that goes hand in hand with security. week, the, the, the encryption component that you guys announced. So it's groundbreaking technology based on research in the field of structured So how does the mobile edge developer think about that? At the time, you could take a picture of Sean White or of Nathan Chen And that of course is what we're trying to do with our driver technology combined with structure encryption, with query encryption. and other communities, you know, how are they coming together to, to solve such problems And one of the easiest domain knowledge exchange And so if you ask a question, you're more likely perhaps to get an answer, or if one doesn't exist
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Radhika Krishnan, Hitachi Vantara and Peder Ulander, MongoDB | MongoDB World 20222
(upbeat music) >> Welcome back to the Javits in the big apple, New York City. This is theCUBE's coverage of MongoDB World 2022. We're here for a full day of coverage. We're talking to customers, partners, executives and analysts as well. Peder Ulander is here. He's the Chief Marketing Officer of MongoDB and he's joined by Radhika Krishnan, who's the Chief Product Officer at Hitachi Ventara. Folks, welcome back to theCUBE. Great to see you both again. >> Good to see you. >> Thank you David, it's good to be back again. >> Peder, first time since 2019, we've been doing a lot of these conferences and many of them, it's the first time people have been out in a physical event in three years. Amazing. >> I mean, after three years to come back here in our hometown of New York and get together with a few thousand of our favorite customers, partners, analysts, and such, to have real good discussions around where we're taking the world with regards to our developer data platform. It's been great. >> I think a big part of that story of course, is ecosystem and partnerships and Radhika, I remember I was at an event when Hitachi announced its strategy and it's name change, and really tried to understand why and the what's behind that. And of course, Hitachi's a company that looks out over the long term, and of course it has to perform tactically, but it thinks about the future. So give us the update on what's new at Hitachi Ventara, especially as it relates to data. >> Sure thing, Dave. As many, many folks might be aware, there's a very strong heritage that Hitachi has had in the data space, right. By virtue of our products and our presence in the data storage market, which dates back to many decades, right? And then on the industrial side, the parent company Hitachi has been heavily focused on the OT sector. And as you know, there is a pretty significant digital transformation underway in the OT arena, which is all being led by data. So if you look at our mission statement, for instance, it's actually engineering the data driven because we do believe that data is the fundamental platform that's going to drive that digital transformation, irrespective of what industry you're in. >> So one of the themes that you guys both talk about is modernization. I mean, you can take a cloud, I remember Alan Nance, who was at the time, he was a CIO at Philips, he said, look, you could take a cloud workload, or on-prem workload, stick it into the cloud and lift it and shift it. And in your case, you could just put it on, run it on an RDBMS, but you're not going to affect the operational models. >> Peder Ulander: It's just your mess for less, man. >> If you do that. >> It's your mess, for less. >> And so, he goes, you'll get a few, you know, you'll get a couple of zeros out of that. But if you want to have, in his case, billion dollar impact to the business, you have to modernize. So what does modernize mean to each of you? >> Maybe Peder, you can start. >> Yeah, no, I'm happy to start. I think it comes down to what's going on in the industry. I mean, we are truly moving from a world of data centers to centers of data, and these centers of data are happening further and further out along the network, all the way down to the edges. And if you look at the transformation of infrastructure or software that has enabled us to get there, we've seen apps go from monoliths to microservices. We've seen compute go from physical to serverless. We've seen networking go from old wireline copper to high powered 5G networks. They've all transformed. What's the one layer that hasn't completely transformed yet, data, right? So if we do see this world where things are getting further and further out, you've got to rethink your data architecture and how you basically support this move to modernization. And we feel that MongoDB with our partners, especially with Hitachi, we're best suited to really kind of help with this transition for our customers as they move from data centers to centers of data. >> So architecture. And at the failure, I will say this and you tell me if you agree or not. A lot of the failures of sort of the big data architectures of today are there's, everything's in this monolithic database, you've got to go through a series of hyper-specialized professionals to get to the data. If you're a business individual, you're so frustrated because the market's changing faster than you can get answers. So you guys, I know, use this concept of data fabric, people talk about data mesh. So how do you think, Radhika, about modernization in the future of data, which by its very nature is distributed? >> Yeah. So Dave, everybody talks about the hybrid cloud, right? And so the reality is, every one of our customers is having to deal with data that's straddled across on-prem as well as the public cloud and many other places as well. And so it becomes incredibly important that you have a fairly seamless framework, that's relatively low friction, that allows you to go from the capture of the data, which could be happening at the edge, could be happening at the core, any number of places, all the way to publish, right. Which is ultimately what you want to do with data because data exists to deliver insights, right? And therefore you dramatically want to minimize the friction in the process. And that is exactly what we're attempting to do with our data fabric construct, right. We're essentially saying, customers don't have to worry about, like you mentioned, they may have federated data structures, architectures, data lakes, fitting in multiple locations. How do you ensure that you're not having to double up custom code in order to drive the pipelines, in order to drive the data movement from one location to the other and so forth. And so essentially what we're providing is a mechanism whereby they can be confident about the quality of the data at the end of the day. And this is so paramount. Every customer that I talk to is most worried about ensuring that they have data that is trustworthy. >> So this is a really important point because I've always felt like, from a data quality standpoint, you know you get the data engineers who might not have any business context, trying to figure out the quality problem. If you can put the data responsibility in the hands of the business owner, who, he or she, has context, that maybe starts to solve this problem. There's some buts though. So infrastructure becomes an operational detail. Let's hide that. Don't worry about it. Figure it out, okay, so the business can run, but you need self-service infrastructure and you have to figure out how to have federated governance so that the right people can have access. So how do you guys think about that problem in the future? 'Cause it's almost like this vision creates those two challenges. Oh, by the way, you got to get your organization behind it. Right, 'cause there's an organizational construct as well. But those are, to me, wonderful opportunities but they create technology challenges. So how are you guys thinking about that and how are you working on it? >> Yeah, no, that's exactly right, Dave. As we talk to data practitioners, the recurring theme that we keep hearing is, there is just a lot of use cases that require you to have deep understanding of data and require you to have that background in data sciences and so on, such as data governance and vary for their use cases. But ultimately, the reason that data exists is to be able to drive those insights for the end customer, for the domain expert, for the end user. And therefore it becomes incredibly important that we be able to bridge that chasm that exists today between the data universe and the end customer. And that is what we essentially are focused on by virtue of leaning into capabilities like publishing, right? Like self, ad hoc reporting and things that allow citizen data scientists to be able to take advantage of the plethora of data that exists. >> Peder, I'm interested in this notion of IT and OT. Of course, Hitachi is a partner, established in both. Talk about Mongo's position in thinking. 'Cause you've got on-prem customers, you're running now across all clouds. I call it super cloud connecting all these things. But part of that is the edge. Is Mongo running there? Can Mongo run there, sort of a lightweight version? How do you see that evolve? Give us some details there. >> So I think first and foremost, we were born on-prem, obviously with the origins of MongoDB, a little over five years ago, we introduced Atlas and today we run across a hundred different availability zones around the globe, so we're pretty well covered there. The third bit that I think people miss is we also picked up a product called Realm. Realm is an embedded database for mobile devices. So if you think about car companies, Toyota, for example, building connected cars, they'll have Realm in the car for the telemetry, connects back into an Atlas system for the bigger operational side of things. So there's this seamless kind of, or consistency that runs between data center to cloud to edge to device, that MongoDB plays across all the way through. And then taking that to the next level. We talked about this before we sat down, we're also building in the security elements of that because obviously you not only have that data in rest and data in motion, but what happens when you have that data in use? And announced, I think today? We purchased a little company, Aroki, experts in encryption, some of the smartest security minds on the planet. And today we introduce query-able encryption, which basically enables developers, without any security background, to be able to build searchable capabilities into their applications to access data and do it in a way where the security rules and the privacy all remain constant, regardless of whether that developer or the end user actually knows how that works. >> This is a great example of people talk about shift left, designing security in, for the developer, right from the start, not as a bolt-on. It's a great example. >> And I'm actually going to ground that with a real life customer example, if that's okay, Dave. We actually have a utility company in North Carolina that's responsible for energy and water. And so you can imagine, I mean, you alluded to the IO to use case, the industrial use case and this particular customer has to contend with millions of sensors that are constantly streaming data back, right. And now think about the challenge that they were encountering. They had all this data streaming in and in large quantities and they were actually resident on numerous databases, right. And so they had this very real challenge of getting to that quality data that I, data quality that I talked about earlier, as well, they had this challenge of being able to consolidate all of it and make sense of it. And so that's where our partnership with MongoDB really paid off where we were able to leverage Pentaho to integrate all of the data, have that be resident on MongoDB. And now they're leveraging some of the data capabilities, the data fabric capabilities that we bring to the table to actually deliver meaningful insights to their customers. Now their customers are actually able to save on their electricity and water bills. So great success story right there. >> So I love the business impact there, and also you mentioned Pentaho, I remember that acquisition was transformative for Hitachi because it was the beginning of sort of your new vector, which became Hitachi Ventara. What is Lumada? That's, I presume the evolution of Pentaho? You brought in organic, and added capabilities on top of that, bringing in your knowledge of IOT and OT? Explain what Lumada is. >> Yeah, no, that's a great question, Dave. And I'll say this, I mentioned this early on, we fundamentally believe that data is the backbone for all digital transformation. And so to that end, Hitachi has actually been making a series of acquisitions as well as investing organically to build up these data capabilities. And so Pentaho, as you know, gives us some of that front-end capability in terms of integrations and so forth. And the Lumada platform, the umbrella brand name is really connoting everything that we do in the data space that allow customers to go through that, to derive those meaningful insights. Lumada literally stands for illuminating data. And so that's exactly what we do. Irrespective of what vertical, what use case we're talking about. As you know very well, Hitachi is very prominent in just about every vertical. We're in like 90% of the Fortune 500 customers across banking and financial, retail, telecom. And as you know very well, very, very strong in the industrial space as well. >> You know, it's interesting, Peder, you and Radhika were both talking about this sort of edge model. And so if I understand it correctly, and maybe you could bring in sort of the IOT requirements as well. You think about AI, most of the AI that's done today is modeling in the cloud. But in the future and as we're seeing this, it's real-time inferencing at the edge and it's massive amounts of data. But you're probably not, you're going to persist some, I'm hearing, probably not going to persist all of it, some of it's going to be throwaway. And then you're going to send some back to the cloud. I think of EVs or, a deer runs in front of the vehicle and they capture that, okay, send that back. The amounts of data is just massive. Is that the right way to think about this new model? Is that going to require new architectures and hearing that Mongo fits in. >> Yeah. >> Beautifully with that. >> So this is a little bit what we talked about earlier, where historically there have been three silos of data. Whether it's classic system of record, system of engagement or system of intelligence and they've each operated independently. But as applications are pushing in further and further to the edge and real time becomes more and more important, you need to be able to take all three types of workloads or models, data models and actually incorporate it into a single platform. That's the vision we have behind our developer data platform. And it enables us to handle those transactional, operational and analytical workloads in real time, right. One of the things that we announced here this week was our columnar indexing, which enables some of that step into the analytics so that we can actually do in-app analytics for those things that are not going back into the data warehouse or not going back into the cloud, real time happening with the application itself. >> As you add, this is interesting, as basically Mongo's becoming this all-in-one database, as you add those capabilities, are you able to preserve, it sounds like you've still focused on simplicity, developer product productivity. Are there trade off, as you add, does it detract from those things or are you able to architecturally preserve those? >> I think it comes down to how we're thinking through the use case and what's going to be important for the developers. So if you look at the model today, the legacy model was, let's put it all in one big monolith. We recognize that that doesn't work for everyone but the counter to that was this explosion of niche databases, right? You go to certain cloud providers, you get to choose between 15 different databases for whatever workload you want. Time series here, graph here, in-memory here. It becomes a big mess that is pushed back on the company to glue back together and figure out how to work within those systems. We're focused on really kind of embracing the document model. We obviously believe that's a great general purpose model for all types of workloads. And then focusing in on not taking a full search platform that's doing everything from log management all the way through in-app, we're optimizing for in-app experiences. We're optimizing analytics for in-app experiences. We're optimizing all of the different things we're doing for what the developer is trying to go accomplish. That helps us maintain consistency on the architectural design. It helps us maintain consistency in the model by which we're engaging with our customers. And I think it helps us innovate as quickly as we've been been able to innovate. >> Great, thank you. Radhika, we'll give you the last word. We're seeing this convergence of function in the data based, data models, but at the same time, we're seeing the distribution of data. We're not, you're clearly not fighting that, you're embracing that. What does the future look like from Hitachi Ventara's standpoint over the next half decade or even further out? >> So, we're trying to lean into what customers are trying to solve for, Dave. And so that fundamentally comes down to use cases and the approaches just may look dramatically different with every customer and every use case, right? And that's perfectly fine. We're leaning into those models, whether that is data refining on the edge or the core or the cloud. We're leaning into it. And our intent really is to ensure that we're providing that frictionless experience from end to end, right. And I'll give a couple of examples. We had this very large bank, one of the top 10 banks here in the US, that essentially had multiple data catalogs that they were using to essentially sort through their metadata and make sense of all of this data that was coming into their systems. And we were able to essentially, dramatically simplify it. Cut down on the amount of time that it takes to deliver insights to them, right. And it was like, the metric shared was 600% improvement. And so this is the kind of thing that we're manically focused on is, how do we deliver that quantifiable end-customer improvement, right? Whether it's in terms of shortening the amount to drive the insights, whether it's in terms of the number of data practitioners that they have to throw at a problem, the level of manual intervention that is required, so we're automating everything. We're trying to build in a lot of security as Peder talked about, that is a common goal for both sides. We're trying to address it through a combination of security solutions at varying ends of the spectrum. And then finally, as well, delivering that resiliency and scale that is required. Because again, the one thing we know for sure that we can take for granted is data is exploding, right? And so you need that scale, you need that resiliency. You need for customers to feel like there is high quality, it's not dirty, it's not dark and it's something that they can rely upon. >> Yeah, if it's not trusted, they're not going to use it. The interesting thing about the partnership, especially with Hitachi, is you're in so many different examples and use cases. You've got IT. You've got OT. You've got industrial and so many different examples. And if Mongo can truly fit into all those, it's just, the rocket ship's going to continue. Peder, Radhika, thank you so much for coming back in theCUBE, it's great to see you both. >> Thank you, appreciate it. >> Thank you, my pleasure. >> All right. Keep it right there. This is Dave Vellante from the Javits Center in New York City at MongoDB World 2022. We'll be right back. (upbeat music)
SUMMARY :
Great to see you both again. good to be back again. and many of them, it's the and such, to have real good discussions that looks out over the long term, has had in the data space, right. So one of the themes that your mess for less, man. impact to the business, And if you look at the And at the failure, I will say this And so the reality is, so that the right people can have access. and the end customer. But part of that is the edge. and the privacy all remain constant, designing security in, for the developer, And I'm actually going to ground that So I love the business impact there, We're in like 90% of the Is that the right way to One of the things that we or are you able to but the counter to that was this explosion in the data based, data models, and the approaches just may it's great to see you both. from the Javits Center
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Abdul Razack, Google & Vadim Supitskiy, Forbes | MongoDB World 2022
(upbeat music) >> Welcome back to New York City everybody. You're watching theCUBE's coverage of MongoDB World 2022. My name is Dave Vellante. Pretty good attendance here. I'd say over 3000 people, great buzz, a lot of really technical sessions. There's an executive session going on. There's a financial analyst session. So a lot of diversity in this attendee base. Vadim Supitskiy is here. He's the CTO of Forbes and Abdul Razack is the vice president of Solution Engineering at Google. Gents, thanks for coming on theCUBE. >> Thanks Dave. >> Happy to be here. >> So, Forbes, very interesting business. I'm interested in what occurred during the pandemic for you guys. Right? Everybody went digital. Obviously you guys have a tremendous brand. We all, in the business world reaped from it, but what happened during the isolation era? What happened to your business? >> Yeah, so we've been innovating and going through digital transformation for years, since we launched our website probably 25 years ago. >> But during the pandemic, because of our coverage, our foresight to create a breaking news team, our audiences and readership really skyrocketed. >> Really? >> Yeah, and at that point, we were very happy and really lucky to be in Google Cloud and MongoDB Atlas. So when the audiences went up, we didn't feel any impact, right? Our environments auto-scaled and our users didn't experience any issues at all. So we were able to focus on innovation, our users loyalty and really building cool products. So we were very lucky and happy to be in Google Cloud and MongoDB Atlas. >> So Abdul, the solution and the title you provided, obviously worked. How did you guys end up getting together? What was that like? >> Yeah, I mean, like Vadim said, maybe there's a little bit of the right place at the right time in this case, but you can see the need for digital transformation and the pandemic really accelerated that. And like Vadim said, primarily Forbes wanted to focus on innovation and customer loyalty and the way that comes to bear, is that you have a technology platform that can serve those needs. Right? Whether it is through unique applications that can be delivered, the ability for developers to build those applications quickly and seamlessly and then remove the intangibles of scalability, performance, latency, and things of that nature. So, you can see this all coming together in this scenario. >> So as consumers, we see the website, we read online, maybe sometimes in the laptop, mostly on mobile. What is it that we don't see? I mean, the apps that Abdul talked about, community. What else is there? Paint a picture of that for us. >> Yeah. There is a lot going on behind the scene. Right? So focusing on audience, building communities, but also what it allowed us to do while everything was working well, we were scaling up. Right? We were able to focus on a lot of innovation. And one of those was first-party data platform that we built. We call it Forbes One. And that's in the center of everything that we do at Forbes right now. Right? So it allows us, one, to connect our partners, advertising partners with the audiences that they're looking to engage and to connect with. And then we are growing our consumer business as well and what that allows us to do is target the right products at the right time, to the right people, on the web website and our domain. So, that's just one of the examples that we've built our full first-party data platform on these technologies and we now know our customers so well that we are able to provide them with what they want. >> So the first-party data platform is what? A self-serve for advertiser, so they can identify? >> Not just advertisers. So it's in the center of everything. So advertiser comes in, we provide the segments and users that they want to reach. Now, we are creating products as well, building cool, innovative products and offering our journalism and everything there to our readers and we are able to connect them to the right audiences at the right time, as well as personalization. Right? You come onto the website, you want to read what you want to read. So we able to create that as well, using machine learning and AI. >> So a product, it might be a data product or it might be a content product? >> It could be a data product. It could be like just personalization or something like that. It could be newsletter. Right? It could be a stand-alone product, like investing product. So, there is a lot going on there, but we want to offer the right ones at the right time, to the right audiences and building that platform has allowed us to do that. >> Okay. Now Google's got great tech. What's the tech behind all this? >> Yeah. So when Vadim talked about segmenting to personalize something that is relevant to you and providing recommendations to you. Right? And all that is based on machine learning, AI technology. The fact that Vadim has all the data curated in a in a first-party data platform gives the ability to create a seamless profile. Right? You could be interested in a couple of products. Right? And then the underlying technology can tailor that to bring what is it that you're looking for at the right place at the right time. Right? So those are recommendations, things of that nature that's all powered by AI and machine learning technology. >> So it's running on Mongo, and then you're bringing in Google AI and machine intelligence tools? Can you double click on that? >> Yeah. It's basically a combination of both, using both platform to the deploy it and we embrace Cloud. Right? So we using all the Cloud native technologies. Right? We didn't want to just lift and shift. We wanted to make sure we do it right. And we focused on automation, even if we had to take a step back, we knew that automating things was a key for us. So yes, it's been really successful, but also really informative for us to use the right tools for the job. >> And you had prior experience with Mongo, or? >> We did. >> What's your journey been like there? >> Yeah, we actually were one of the first clients of Mongo. I think we were number 11 at that time. >> 10gen. >> Yes. It was. >> We remember. >> Many years ago it was MongoDB one, right? >> Yeah. >> And at that time we we introduced contributor network for us and our audiences were scaling as well. And we used Out-of-the-Box WordPress as our publishing platform, which couldn't scale. So we had to rethink and figure out, "Alright, so what do we do?" We compared couple of no SQL databases and Mongo was a winner because they checked all the boxes and developers loved it right away. Right? They're like, "All right, this is so much faster to develop on. It's just a great tool for the job going from SQL to, to no SQL". And we scaled and we never looked back. And then obviously Atlas came, so there are kind of two inflection points here. One switch into no SQL and two going away from managing databases. Like we don't want to be in that business. Right? Updates, patches, all of that, that we had to do manually, over-provision in our environments and kind of wasteful. So being on Atlas, that was a second kind of inflection point for us, which opened it up for us to do even more innovation and move faster. >> Okay. And you're happy about this partnership, despite, I mean, you partner with Mongo obviously, Google has its own databases, that's just the nature of the world we live in, isn't it? >> No and fundamentally like that, we always believe that customer choice is the primary notion. Right? I mean, and Google Cloud platform is more of a platform and the ecosystem is critical to that. Right? It's imperative. So, like Vadim said, the combination of Google and Mongo provides a truly Cloud native platform that can serve the needs for years to come, rather than from looking at it from a legacy perspective. And that's the way we look at it. Right? I mean, there is choices all the time and sometimes it's competition. >> Yeah. Yeah. And you're still selling a lot of compute and storage and machine intelligence, so machine learning. This morning in the keynotes, we heard a lot about a lot of different capabilities. We've certainly watched Mongo evolve its platform over the last half a decade or more really. But you've mentioned the developers loved it. Right? As Mongo evolves its platform, is there trade off from a developer simplicity standpoint? Are they able to preserve that from your perspective? >> I think with Atlas, it actually makes it easier now. So when they need to create an environment, they can do it on the fly. When they need to test something, also things available to them right away. So it actually, in general, as the platform becomes more mature and more stable, which is very important, but at the same time, the flexibility remains for development and for creation of environments and things like that. So we've been pretty happy with how it transitioned, to being a more mature platform. >> Did the move to Google Cloud and Atlas change the way that you're able to deliver high availability versus what you were doing when you were self-managing? Can you talk about that a little bit? >> Yeah, absolutely. We were in a data center, so kind of one location and moving to MongoDB Atlas and Google Cloud, now we're multi region. Right? So we have a full DR strategy and we feel a lot more secure and we feel very confident that anything that happens, we can scale, we can fail over. So absolutely, this helps us a lot. And the feature that was introduced probably a few years ago to auto scale MongoDB environments as well, that has been really key for us, so we can sleep well. >> Meaning you can scale while you sleep. >> Right, exactly. Exactly. >> Yeah. Plus the other part is you don't size for peak. right? You size as you grow, and then you, you have that elasticity built in. Right? That it is the nature. And then Mongo is available on multiple Google Cloud regions. So as you expand, you don't worry about all the plumbing that you need to do and things of that nature. >> They asked us serverless this morning. >> Yeah. >> How does that affect what you guys are doing together and what are your thoughts from Google's perspective and then of course, from Forbes? >> And that's the trend that we see constantly. Right? Serverless really decouples the tie to the VMs. Right? And so it makes it much more easier to provide the elasticity and have function calls across. Right? Function as a service and things of that nature. Right? So we see a lot of promise in that. Right? We do that even within our own products and we see that giving the ability to decompose and recompose applications and would love to hear how you're leveraging that. Right? >> Yeah. We fully embrace serverless. So we use all the tools you provide, I think. If you look at our architectural diagrams, it's like all these pops-up, cloud functions, composer, app engine. So we use the full suite and we love it. >> Yeah, Yeah. Okay. And then you talked this morning about the eliminating, the trade-offs with serverless of having to either when you dial it down You have to restart, but you've solved that problem, or I guess Mongo's helped you solve that problem. Can you explain that a little bit from a technical standpoint? >> Yeah. From a technical standpoint, if you look at, like as a developer, right? If you're building an intelligent app, it has multiple components within it. Right? There is pops-up for messaging, there is cloud functions and things of that nature. So you don't worry about, when it's encompassed in a serverless architecture, you don't worry about a lot of the complexities that go on behind it and so that makes the abstraction much more easier. And it eliminates the friction that a developer goes through. I think they've talked about removing friction and that's the primary source of productivity loss, which is the friction. We used to come from a world where developers were more worried. 80% of the time they would spend on plumbing this thing and then only 20% writing code. Right? And then now this whole paradigm should flip that. Right? That's where we see the promise of it. >> Do you still do stuff on Prem or are you pretty much all in the Cloud? >> Fully in the Cloud. >> How long did that take? What was that like? >> It actually was really fast. We had a real aggressive timeline. It took us six months. >> Really? >> Yeah. Yeah. And it was aggressive, but I was happy that we did it in a short period of time. >> And what was the business impact that you saw moving to the Google Cloud? >> Yeah, so obviously after we moved to the Cloud, we wanted to measure, especially the first year, how it affected us and what were the positives out of it. And yeah, we've seen tremendous results. 58% increase in speed to market. We were releasing four times more often than when we were on Prem. We saw 73% increase in initiatives delivered and while our velocity was scaling up, we also saw 30% decreased in hot fixes and rollbacks. So it became more stable while we scaled up the velocity and obviously very happy with those results. >> Wow. Do you golf? >> I don't actually. >> Do you golf? >> No. I watch golf. >> I used to watch. Okay. Do you know what a mulligan is? >> Yeah. >> Okay. mulligan is like a do-over right. If you had a mulligan, would you do anything differently? >> You know, we learned a lot and one of the keys for me was definitely automate everything, make sure that you automate as much as possible, even if it slows you down because in the future that will help you so much and use the platform and the tools that available to you. So, serverless. Right? Use Cloud the way it's supposed to be, as much as possible and I think that's the advice I would give. >> Are there any cautions with regard to automation, either of you that you see? I mean because sometimes automation brings unintended consequences and "Oops" happens really fast. >> Yeah. It's a little bit of a process. Right? If you take a step back, right, and typically what people tend to do is, there is a standardization process and once it's standardized, the next step is you gain efficiencies by automation. Right? In this whole thing, what is underestimated is change management. And we see a lot of room for improvement around educating on change management, getting ahead of that so that you can see what is coming. So that the organization moves across that. I don't know if you saw that in your case, but we see this predominantly in other other cases. >> Yeah. I mean, for us, we wanted to make sure that all the testing was in place and things like that. So not just automation of deploying or anything like that, but make sure that there is something there to catch if something goes wrong and roll back and things like that. So you want to make sure that you protected in many areas. >> So square this circle for me, because especially with COVID, so many unknowns and one of the benefits of document database is you're not tied into a schema. You got a flexible schema. Okay. So you're changing, you can change things much more easily. So when you talk about standardization, you're talking about standardizing, what at the infrastructure layer, or where does that standardization occur? Where should it occur. >> I mean, you could have it at the business process level. >> Okay. >> You could have it at the infrastructure level. You could also have it on the administration aspect of it. So there are three areas where you could apply automation to. >> So is there an analog to flexible schema at the business process level? Is that kind of how to think about it, whereas I'm not locked into a business process schema? I have to build flexibility into that as I change my? >> No, I mean, you can apply it any which way. I mean, I don't think the schema matters so much. Right? Like, for example, if you take the Forbes US case. Right? There is content curation, for example. Right? >> Yeah, okay. >> You could take content curation. Content curation in the previous world, like in the WordPress world, was not very flexible. Right? Like that it wouldn't scale. And now you are in a world where you have a very flexible schema, but the process of curating the content can be standardized. Right? And then the next step of that is to automate that. Right? And so you could apply it in any manner if you will. >> So have you built a custom CMS? Is that what you've done there? >> Yeah. We built our own custom CMS. It's AI powered. We want to make our journalist lives easier. So we're constantly trying to figure out what can we give them to make their day-to-day job much easier. >> So the machines can curate and find the best content. >> We do recommend things. Yes, absolutely. We curate, we tell them what would be the best headline, for example, what would >> Prior to them publishing? >> Yeah. Yeah. What would be the better keywords to include and things like that, what images. Just recommendations. >> And you can automate the insertion of those WordPress to go every time they do, even though they're writing about the same topic. >> It's a recommendation process obviously, but >> There is a human intelligence to that at the end. Right? I mean, but you can create a much more informed view by curating and recommending content rather than a myopic view. >> And you're eliminating that mundane keystroke task. Wow. Amazing story guys. Thanks so much for sharing. >> Absolutely. >> All right. Keep it right there. We're live from MongoDB World 2022 in New York city. Be right back. (upbeat music)
SUMMARY :
and Abdul Razack is the vice president during the pandemic for you guys. since we launched our website But during the pandemic, Yeah, and at that and the title you provided, and the way that comes to bear, What is it that we don't at the right time, to the right people, and we are able to connect at the right time, to the right audiences What's the tech behind all this? that is relevant to you and and we embrace Cloud. of the first clients of Mongo. And at that time we we of the world we live in, isn't it? And that's the way we look at it. This morning in the but at the same time, And the feature that all the plumbing that you need to do the tie to the VMs. So we use the full suite and we love it. And then you talked this and so that makes the It actually was really fast. that we did it in a short period of time. especially the first year, Do you know what a mulligan is? If you had a mulligan, would and one of the keys for me either of you that you see? So that the organization sure that you protected and one of the benefits I mean, you could have it You could also have it on the the Forbes US case. And so you could apply it to make their day-to-day job much easier. and find the best content. the best headline, for example, what would to include and things like And you can automate the insertion I mean, but you can create that mundane keystroke task. Keep it right there.
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Sanjeev Mohan, SanjMo | MongoDB World 2022
>>Mhm. Mhm. Yeah. Hello, everybody. Welcome to the Cubes. Coverage of Mongo db World 2022. This is the first Mongo live mongo DB World. Since 2019, the Cube has covered a number of of mongo shows actually going back to when the company was called Engine. Some of you may recall Margo since then has done an i p o p o in 2017, it's It's been a rocket ship company. It's up. It'll probably do 1.2 billion in revenue this year. It's got a billion dollars in cash on the balance sheet. Uh, despite the tech clash, it's still got a 19 or $20 million valuation growing above 50% a year. Uh, company just had a really strong quarter, and and there seems to be hitting on all cylinders. My name is Dave Volonte. And here to kick it off with me as Sanjeev Mohan, who was the principal at Sanremo. So great to see you. You become a wonderful cube contributor, Former Gartner analyst. Really sharp? No, the database space in the data space generally really well, so thanks for coming back on >>you. You know, it's just amazing how exciting. The entire data space is like they used to say. Companies are All companies are software companies. All companies are data >>companies, >>so data has become the the foundation. >>They say software is eating the world. Data is eating software and a little little quips here. But this is a good size show. Four or 5000 people? I don't really know exactly. You know the numbers, but it's exciting. And of course, a lot of financial services were here at the Javits Centre. Um, let's let's lay down the basics for people of Mongo, DB is a is a document database, but they've been advancing. That's a document database as an alternative to R D. B M s. Explain that, but explain also how Mongo has broadened its capabilities and serving a lot more use cases. >>So that's my forte is like databases technology. But before even I talk about that, I have to say I am blown away by this mongo db world because mongo db uh, in beckons to all of us during the pandemic has really come of age, and it's a billion dollar company. Now we are in this brand new Javits Centre That's been built during the pandemic. And and now the company is holding this event the high 1000 people last year. So I think this company has really grown. And why has it drawn is because its offerings have grown to more developers than just a document database document databases. Revolution revolutionised the whole DBM s space where no sequel came up. Because for a change, you don't need a structured schema. You could start bringing data in this document model scheme, uh, like varying schema. But since then, they've added, uh, things like such. So they have you seen such? They added a geospatial. They had a time series last year, and this year they keep adding more and more so like, for example, they are going to add some column store indexes. So from being a purely transactional, they are now starting to address analytical. And they're starting to address more use cases, like, you know, uh, like what? What was announced this morning at keynote was faceted search. So they're expanding the going deeper and deeper into these other data >>structures. Taking Lucy made a search of first class citizens, but I want to ask you some basic questions about document database. So it's no fixed schemes. You put anything in there? Actually, so more data friendly. They're trying to simplify the use of data. Okay, that's that's pretty clear. >>What are the >>trade offs of a document database? >>So it's not like, you know, one technology has solved every problem. Every technology comes with its own tradeoffs. So in a document, you basically get rid of joining tables with primary foreign keys because you can have a flexible schemer and so and wouldn't sing single document. So it's very easy to write and and search. But when you have a lot of repeated elements and you start getting more and more complex, your document size can start expanding quite a bit because you're trying to club everything into a single space. So So that is where the complexity goes >>up. So what does that mean for for practitioner, it means they have to think about what? How they how they are ultimately gonna structure, how they're going to query so they can get the best performances that right. So they're gonna put some time in up front in order to make it pay back at the tail end, but clearly it's it's working. But is that the correct way of thinking about >>100% in, uh, the sequel world? You didn't care about the sequel. Analytical queries You just cared about how your data model was structured and then sequel would would basically such any model. But in the new sequel world, you have to know your patterns before you. You invest into the database so it's changed that equation where you come in knowing what you are signing up. >>So a couple of questions, if I can kind of Colombo questions so to Margo talks about how it's really supporting mission critical applications and at the same time, my understanding is the architecture of mongo specifically, or a document database in general. But specifically, you've got a a primary, uh, database, and you and that is the sort of the master, if you will, right and then you can create secondaries. But so help me square the circle between mission critical and really maybe a more of a focus on, say, consistency versus availability. Do customers have to sort of think about and design in that availability? How do they do that? How a Mongol customers handling that. >>So I have to say, uh, my experience of mongo db was was that the whole company, the whole ethos was developed a friendly. So, to be honest, I don't think Mongo DB was as much focused on high availability, disaster, recovery, even security. To some extent, they were more focused on developer productivity. >>And you've experienced >>simplicity. Make it simple, make the developers productive as fast as you can. What has really, uh, was an inflexion point for Mongo DB was the launch of Atlas because the atlas they were able to introduce all of these management features and hide it abstracted from the end users. So now they've got, you know, like 2014 is when Atlas came out and it was in four regions. But today they're in 100 regions, so they keep expanding, then every hyper scale cloud provider, and they've abstracted that whole managed. >>So Atlas, of course, is the managed database as a service in the cloud. And so it's those clouds, cloud infrastructure and cloud tooling that has allowed them to go after those high available application. My other question is when you talk about adding search, geospatial time series There are a lot of specialised databases that take time series persons. You have time series specialists that go deep into time series can accompany like Mongo with an all in one strategy. Uh, how close can they get to that functionality? Do they have to be? You know, it's kind of a classic Microsoft, you know, maybe not perfect, but good enough. I mean, can they compete with those other areas? Uh, with those other specialists? And what happens to those specialists if the answer is yes. What's your take on that? If that question >>makes sense So David, this is not a mongo db only issue This is this is an issue with, you know, anytime serious database, any graph database Should I put a graph database or should I put a multifunctional database multidimensional database? And and I really think there is no right or wrong answer. It just really comes down to your use case. If you have an extremely let's, uh, complex graph, you know, then maybe you should go with best of breed purpose built database. But more and more, we're starting to see that organisations are looking to simplify their environment by going in for maybe a unified database that has multiple data structures. Yeah, well, >>it's certainly it's interesting when you hear Mongo speak. They don't They don't call out Oracle specifically, but when they talk about legacy r d m r d B m s that don't scale and are complex and are expensive, they're talking about Oracle first. And of course, there are others. Um, And then when they talk about, uh, bespoke databases the horses for courses, databases that they show a picture of that that's like the poster child for Amazon. Of course, they don't call out Amazon. They're a great partner of Amazon's. But those are really the sort of two areas that mangoes going after, Um, now Oracle. Of course, we'll talk about their converged strategy, and they're taking a similar approach. But so help us understand the difference. There is just because they're sort of or close traditional r d B M s, and they have all the drawbacks associated with that. But by the way, there are some benefits as well. So how do you see that all playing >>out? So you know it. Really, uh, it's coming down to the the origins of these databases. Uh, I think they're converging to a point where they are offering similar services. And if you look at some of the benchmark numbers or you talk to users, I from a business point of view, I I don't think there's too much of a difference. Uh, technology writes. The difference is that Mongo DB started in the document space. They were more interested in availability rather than consistency. Oracle started in the relation database with focus on financial services, so asset compliance is what they're based on. And since then they've been adding other pieces, so so they differ from where they started. Oracle has been in the industry for some since 19 seventies, so they have that maturity. But then they have that legacy, >>you know, I love. Recently, Oracle announced the mongo db uh, kpi. So basically saying why? Why leave Oracle when you can just, you know, do the market? So that, to me, is a sign that Mongo DB is doing well because the Oracle calls you out, whether your workday or snowflake or mongo. You know, whoever that's a sign to me that you've got momentum and you're stealing share in that marketplace, and clearly Mongo is they're growing at 50 plus percent per year. So thinking about the early I mentioned 10 gen Early on, I remember that one of the first conferences I went to mongo conferences. It was just It was all developers. A lot of developers here as well. But they have really, since 2014, expanded the capabilities you talk about, Atlas, you talked about all these other you know, types of databases that they've added. If it seems like Mongo is becoming a platform company, uh, what are your thoughts on that in terms of them sort of up levelling the message there now, a billion dollar plus company. What's the next? You know, wave for Mongo. >>So, uh, Oracle announced mongo db a p i s a W s has document d. B has cost most db so they all have a p. I compatible a p. I s not the source code because, you know, mongo DB has its own SPL licence, so they have written their own layer on top. But at the end of the day, you know, if you if you these companies have to keep innovating to catch up with Mongo DB because we can announce a brand new capability, then all these other players have to catch up. So other cloud providers have 80% or so of capabilities, but they'll never have 100% of what Mongo DB has. So people who are diehard Mongo DB fans they prefer to stay on mongo db. They are now able to write more applications like you know, mongo DB bought realm, which is their front end. Uh, like, you know, like, if you're on social media kind of thing, you can build your applications and sink it with Atlas. So So mongo DB is now at a point where they are adding more capabilities that more like developers like, You know, five G is coming. Autonomous cars are coming, so now they can address Iot kind of use cases. So that's why it's becoming such a juggle, not because it's becoming a platform rather than a single document database. >>So atlases, the near the midterm future. Today it's about 60% of revenues, but they have what we call self serve, which is really the traditional on premise stuff. They're connecting those worlds. You're bringing up the point that. Of course, they go across clouds. You also bring up the point that they've got edge plays. We're gonna talk to Verizon later on today. And they're they've got, uh, edge edge activity going on with developers. I I call it Super Cloud. Right, This layer that floats above. Now, of course, a lot of the super Cloud concert says we're gonna hide the underlying complexity. But for developers, they wanna they might want to tap those primitives, so presumably will let them do that. But But that hybrid that what we call Super Cloud that is a new wave of innovation, is it not? And do you? Do you agree with that? And do you see that as a real opportunity from Mongo in terms of penetrating a new tan? >>Yes. So I see this is a new opportunity. In fact, one of the reasons mongo DB has grown so quickly is because they are addressing more markets than they had three pandemic. Um, Also, there are all gradations of users. Some users want full control. They want an eye as kind of, uh, someone passed. And some businesses are like, you know, we don't care. We don't want to deal with the database. So today we heard, uh, mongo db. Several went gear. So now they have surveillance capability, their past. But if you if you're more into communities, they have communities. Operator. So they're addressing the full stack of different types of developers different workloads, different geographical regions. So that that's why the market is expected. >>We're seeing abstraction layers, you know, throughout the started a physical virtual containers surveillance and eventually SuperClubs Sanjeev. Great analysis. Thanks so much for taking your time to come with the cube. Alright, Keep it right there. But right back, right after this short break. This is Dave Volonte from the Javits Centre. Mongo db World 2022. Thank you. >>Mm.
SUMMARY :
So great to see you. like they used to say. You know the numbers, but it's exciting. So they have you seen such? Taking Lucy made a search of first class citizens, but I want to ask you So it's not like, you know, one technology has solved every problem. But is that the correct way of thinking about But in the new sequel world, you have to know your patterns before you. is the sort of the master, if you will, right and then you can create secondaries. So I have to say, uh, my experience of mongo db was was that the So now they've got, you know, like 2014 is when Atlas came out and So Atlas, of course, is the managed database as a service in the cloud. let's, uh, complex graph, you know, then maybe you should go So how do you see that all playing in the industry for some since 19 seventies, so they have that So that, to me, is a sign that Mongo DB is doing well because the Oracle calls you out, db. They are now able to write more applications like you know, mongo DB bought realm, So atlases, the near the midterm future. So now they have surveillance We're seeing abstraction layers, you know, throughout the started a physical virtual containers surveillance
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Breaking Analysis: How Lake Houses aim to be the Modern Data Analytics Platform
from the cube studios in palo alto in boston bringing you data driven insights from the cube and etr this is breaking analysis with dave vellante earnings season has shown a conflicting mix of signals for software companies well virtually all firms are expressing caution over so-called macro headwinds we're talking about ukraine inflation interest rates europe fx headwinds supply chain just overall i.t spend mongodb along with a few other names appeared more sanguine thanks to a beat in the recent quarter and a cautious but upbeat outlook for the near term hello and welcome to this week's wikibon cube insights powered by etr in this breaking analysis ahead of mongodb world 2022 we drill into mongo's business and what etr survey data tells us in the context of overall demand and the patterns that we're seeing from other software companies and we're seeing some distinctly different results from major firms these days we'll talk more about [Â __Â ] in this session which beat eps by 30 cents in revenue by more than 18 million dollars salesforce had a great quarter and its diversified portfolio is paying off as seen by the stocks noticeable uptick post earnings uipath which had been really beaten down prior to this quarter it's brought in a new co-ceo and it's business is showing a nice rebound with a small three cent eps beat and a nearly 20 million dollar top line beat crowdstrike is showing strength as well meanwhile managements at microsoft workday and snowflake expressed greater caution about the macroeconomic climate and especially on investors minds his concern about consumption pricing models snowflake in particular which had a small top-line beat cited softness and effects from reduced consumption especially from certain consumer-facing customers which has analysts digging more deeply into the predictability of their models in fact barclays analyst ramo lenchow published an especially thoughtful piece on this topic concluding that [Â __Â ] was less susceptible to consumption headwinds than for example snowflake essentially for a few reasons one because atlas mongo's cloud managed service which is the consumption model comprises only about 60 percent of mongo's revenue second is the premise that [Â __Â ] is supporting core operational applications that can't be easily dialed down or turned off and three that snowflake customers it sounds like has a more concentrated customer base and due to that fact there's a preponderance of its revenue is consumption driven and would be more sensitive to swings in these consumption patterns now i'll say this first consumption pricing models are here to stay and the much preferred model for customers is consumption the appeal of consumption is i can actually dial down turn off if i need to and stop spending for a while which happened or at least happened to a certain extent this quarter for certain companies but to the point about [Â __Â ] supporting core applications i do believe that over time you're going to see the increased emergence of data products that will become core monetization drivers in snowflake along with other data platforms is going to feed those data products and services and become over time maybe less susceptible and less sensitive to these consumption patterns it'll always be there but i think increasingly it's going to be tied to operational revenue last two points here in this slide software evaluations have reverted to their historical mean which is a good thing in our view we've taken some air out of the bubble and returned to more normalized valuations was really predicted and looked forward to look we're still in a lousy market for stocks it's really a bear market for tech the market tends to be at least six months ahead of the economy and often not always but often is a good predictor we've had some tough compares relative to the pandemic days in tech and we'll be watching next quarter very closely because the macro headwinds have now been firmly inserted into the guidance of software companies okay let's have a look at how certain names have performed relative to a software index benchmark so far this year here's a year-to-date chart comparing microsoft salesforce [Â __Â ] and snowflake to the igv software heavy etf which is shown in the darker blue line which by the way it does not own the ctf does not own snowflake or [Â __Â ] you can see that these big super caps have fared pretty well whereas [Â __Â ] and especially snowflake those higher growth companies have been much more negatively impacted year to date from a stock price standpoint now let's move on let's take a financial snapshot of [Â __Â ] and put it next to snowflake so we can compare these two higher growth names what we've done here in this chart has taken the most recent quarters revenue and multiplied it by 4x to get a revenue run rate and we've parenthetically added a projection for the full year revenue [Â __Â ] as you see will do north of a billion dollars in revenue while snowflake will begin to approach three billion dollars 2.7 and run right through that that four quarter run rate that they just had last quarter and you can see snowflake is growing faster than [Â __Â ] at 85 percent this past quarter and we took now these most of these profit of these next profitability ratios off the current quarter with one exception both companies have high gross margins of course you'd expect that but as we've discussed not as high as some traditional software companies in part because of their cloud costs but also you know their maturity or lack thereof both [Â __Â ] and snowflake because they are in high growth mode have thin operating margins they spend nearly half or more than half of their revenue on growth that's the sg a line mostly the s the sales and marketing is really where they're spending money uh and and they're specialists so they spend a fair amount of their revenue on r d but maybe not as high as you might think but a pretty hefty percentage the free cash flow as a percentage of revenue line we calculated off the full year projections because there was a kind of an anomaly this quarter in the in the snowflake numbers and you can see snowflakes free cash flow uh which again was abnormally high this quarter is going to settle in around 16 this year versus mongo's six percent so strong focus by snowflake on free cash flow and its management snowflake is about four billion dollars in cash and marketable securities on its balance sheet with little or no debt whereas [Â __Â ] has about two billion dollars on its balance sheet with a little bit of longer term debt and you can see snowflakes market cap is about double that of mongos so you're paying for higher growth with snowflake you're paying for the slootman scarpelli execution engine the expectation there a stronger balance sheet etc but snowflake is well off its roughly 100 billion evaluation which it touched during the peak days of tech during the pandemic and just that as an aside [Â __Â ] has around 33 000 customers about five times the number of customers snowflake has so a bit of a different customer mix and concentration but both companies in our view have no lack of market in terms of tam okay now let's dig a little deeper into mongo's business and bring in some etr data this colorful chart shows the breakdown of mongo's net score net score is etr's proprietary methodology that measures the percent of customers in the etr survey that are adding the platform new that's the lime green at nine percent existing customers that are spending six percent or more on the platform that's the forest green at 37 spending flat that's the gray at 46 percent decreasing spend that's the pinkish at around 5 and churning that's only 3 that's the bright red for [Â __Â ] subtract the red from the greens and you net out to a 38 which is a very solid net score figure note this is a survey of 1500 or so organizations and it includes 150 mongodb customers which includes by the way 68 global 2000 customers and they show a spending velocity or a net score of 44 so notably higher among the larger clients and while it's a smaller sample only 27 emea's net score for [Â __Â ] is 33 now that's down from 60 last quarter note that [Â __Â ] cited softness in its european business on its earning calls so that aligns to the gtr data okay now let's plot [Â __Â ] relative to some other data platforms these don't all necessarily compete head to head with [Â __Â ] but they are in data and database platforms in the etr data set and that's what this chart shows it's an xy graph with net score or as we say spending momentum on the vertical axis and overlap or presence or pervasiveness in the data set on the horizontal axis see that red dotted line there at 40 that indicates an elevated level of spending anything above that is highly elevated we've highlighted [Â __Â ] in that red box which is very close to that 40 percent line it has a pretty strong presence on the x-axis right there with gcp snowflake as we've reported has come down to earth but still well elevated again that aligns with the earnings releases uh aws and microsoft they have many data platforms especially aws so their plot position reflects their broad portfolio massive size on the x-axis um that's the presence and and very impressive on the vertical axis so despite that size they have strong spending momentum and you can see the pack of others including cockroach small on the verdict on the horizontal but elevated on the vertical couch base is creeping up since its ipo redis maria db which was launched the day that oracle bought sun and and got my sequel and some legacy platforms including the leader in database oracle as well as ibm and teradata's both cloud and on-prem platforms now one interesting side note here is on mongo's earning call it clearly cited the advantages of its increasingly all-in-one approach relative to others that offer a portfolio of bespoke or what we some sometimes call horses for courses databases [Â __Â ] cited the advantages of its simplicity and lower costs as it adds more and more functionality this is an argument often made by oracle and they often target aws as the company with too many databases and of course [Â __Â ] makes that argument uh as well but they also make the argument that oracle they don't necessarily call them out but they talk about traditional relational databases of course they're talking about oracle and others they say that's more complex less flexible and less appealing to developers than is [Â __Â ] now oracle of course would retur we retort saying hey we now support a mongodb api so why go anywhere else we're the most robust and the best for mission critical but this gives credence to the fact that if oracle is trying to capture business by offering a [Â __Â ] api for example that [Â __Â ] must be doing something right okay let's look at why they buy [Â __Â ] here's an etr chart that addresses that question it's it's mongo's feature breadth is the number one reason lower cost or better roi is number two integrations and stack alignment is third and mongo's technology lead is fourth those four kind of stand out with notice on the right hand side security and vision much lower there in the right that doesn't necessarily mean that [Â __Â ] doesn't have good security and and good vision although it has been cited uh security concerns um and and so we keep an eye on that but look [Â __Â ] has a document database it's become a viable alternative to traditional relational databases meaning you have much more flexibility over your schema um and in fact you know it's kind of schema-less you can pretty much put anything into a document database uh developers seem to love it generally it's fair to say mongo's architecture would favor consistency over availability because it uses a single master architecture as a primary and you can create secondary nodes in the event of a primary failure but you got to think about that and how to architect availability into the platform and got to consider recovery more carefully now now no schema means it's not a tables and rows structure and you can again shove anything you want into the database but you got to think about how to optimize performance um on queries now [Â __Â ] has been hard at work evolving the platform from the early days when you go back and look at its roadmap it's been you know started as a document database purely it added graph processing time series it's made search you know much much easier and more fundamental it's added atlas that fully managed cloud database uh service which we said now comprises 60 of its revenue it's you know kubernetes integrations and kind of the modern microservices stack and dozens and dozens and dozens of other features mongo's done a really fine job we think of creating a leading database platform today that is loved by customers loved by developers and is highly functional and next week the cube will be at mongodb world and we'll be looking for some of these items that we're showing here and this this chart this always going to be main focus on developers [Â __Â ] prides itself on being a developer friendly platform we're going to look for new features especially around security and governance and simplification of configurations and cluster management [Â __Â ] is likely going to continue to advance its all-in-one appeal and add more capabilities that reduce the need to to spin up bespoke platforms and we would expect enhance enhancements to atlas further enhancements there is atlas really is the future you know maybe adding you know more cloud native features and integrations and perhaps simplified ways to migrate to the cloud to atlas and improve access to data sources generally making the lives of developers and data analysts easier that's going to be we think a big theme at the event so these are the main things that we'll be scoping out at the event so please stop by if you're in new york city new york city at mongodb world or tune in to thecube.net okay that's it for today thanks to my colleagues stephanie chan who helps research breaking analysis from time to time alex meyerson is on production as today is as is andrew frick sarah kenney steve conte conte anderson hill and the entire team in palo alto thank you kristen martin and cheryl knight helped get the word out and rob hof is our editor-in-chief over there at siliconangle remember all these episodes are available as podcasts wherever you listen just search breaking analysis podcast we do publish each week on wikibon.com and siliconangle.com want to reach me email me david.velante siliconangle.com or dm me at divalante or a comment on my linkedin post and please do check out etr.ai for the best survey data in the enterprise tech business this is dave vellante for the cube insights powered by etr thanks for watching see you next time [Music] you
SUMMARY :
into the platform and got to consider
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Data Power Panel V3
(upbeat music) >> The stampede to cloud and massive VC investments has led to the emergence of a new generation of object store based data lakes. And with them two important trends, actually three important trends. First, a new category that combines data lakes and data warehouses aka the lakehouse is emerged as a leading contender to be the data platform of the future. And this novelty touts the ability to address data engineering, data science, and data warehouse workloads on a single shared data platform. The other major trend we've seen is query engines and broader data fabric virtualization platforms have embraced NextGen data lakes as platforms for SQL centric business intelligence workloads, reducing, or somebody even claim eliminating the need for separate data warehouses. Pretty bold. However, cloud data warehouses have added complimentary technologies to bridge the gaps with lakehouses. And the third is many, if not most customers that are embracing the so-called data fabric or data mesh architectures. They're looking at data lakes as a fundamental component of their strategies, and they're trying to evolve them to be more capable, hence the interest in lakehouse, but at the same time, they don't want to, or can't abandon their data warehouse estate. As such we see a battle royale is brewing between cloud data warehouses and cloud lakehouses. Is it possible to do it all with one cloud center analytical data platform? Well, we're going to find out. My name is Dave Vellante and welcome to the data platform's power panel on theCUBE. Our next episode in a series where we gather some of the industry's top analysts to talk about one of our favorite topics, data. In today's session, we'll discuss trends, emerging options, and the trade offs of various approaches and we'll name names. Joining us today are Sanjeev Mohan, who's the principal at SanjMo, Tony Baers, principal at dbInsight. And Doug Henschen is the vice president and principal analyst at Constellation Research. Guys, welcome back to theCUBE. Great to see you again. >> Thank guys. Thank you. >> Thank you. >> So it's early June and we're gearing up with two major conferences, there's several database conferences, but two in particular that were very interested in, Snowflake Summit and Databricks Data and AI Summit. Doug let's start off with you and then Tony and Sanjeev, if you could kindly weigh in. Where did this all start, Doug? The notion of lakehouse. And let's talk about what exactly we mean by lakehouse. Go ahead. >> Yeah, well you nailed it in your intro. One platform to address BI data science, data engineering, fewer platforms, less cost, less complexity, very compelling. You can credit Databricks for coining the term lakehouse back in 2020, but it's really a much older idea. You can go back to Cloudera introducing their Impala database in 2012. That was a database on top of Hadoop. And indeed in that last decade, by the middle of that last decade, there were several SQL on Hadoop products, open standards like Apache Drill. And at the same time, the database vendors were trying to respond to this interest in machine learning and the data science. So they were adding SQL extensions, the likes Hudi and Vertical we're adding SQL extensions to support the data science. But then later in that decade with the shift to cloud and object storage, you saw the vendor shift to this whole cloud, and object storage idea. So you have in the database camp Snowflake introduce Snowpark to try to address the data science needs. They introduced that in 2020 and last year they announced support for Python. You also had Oracle, SAP jumped on this lakehouse idea last year, supporting both the lake and warehouse single vendor, not necessarily quite single platform. Google very recently also jumped on the bandwagon. And then you also mentioned, the SQL engine camp, the Dremios, the Ahanas, the Starbursts, really doing two things, a fabric for distributed access to many data sources, but also very firmly planning that idea that you can just have the lake and we'll help you do the BI workloads on that. And then of course, the data lake camp with the Databricks and Clouderas providing a warehouse style deployments on top of their lake platforms. >> Okay, thanks, Doug. I'd be remiss those of you who me know that I typically write my own intros. This time my colleagues fed me a lot of that material. So thank you. You guys make it easy. But Tony, give us your thoughts on this intro. >> Right. Well, I very much agree with both of you, which may not make for the most exciting television in terms of that it has been an evolution just like Doug said. I mean, for instance, just to give an example when Teradata bought AfterData was initially seen as a hardware platform play. In the end, it was basically, it was all those after functions that made a lot of sort of big data analytics accessible to SQL. (clears throat) And so what I really see just in a more simpler definition or functional definition, the data lakehouse is really an attempt by the data lake folks to make the data lake friendlier territory to the SQL folks, and also to get into friendly territory, to all the data stewards, who are basically concerned about the sprawl and the lack of control in governance in the data lake. So it's really kind of a continuing of an ongoing trend that being said, there's no action without counter action. And of course, at the other end of the spectrum, we also see a lot of the data warehouses starting to edit things like in database machine learning. So they're certainly not surrendering without a fight. Again, as Doug was mentioning, this has been part of a continual blending of platforms that we've seen over the years that we first saw in the Hadoop years with SQL on Hadoop and data warehouses starting to reach out to cloud storage or should say the HDFS and then with the cloud then going cloud native and therefore trying to break the silos down even further. >> Now, thank you. And Sanjeev, data lakes, when we first heard about them, there were such a compelling name, and then we realized all the problems associated with them. So pick it up from there. What would you add to Doug and Tony? >> I would say, these are excellent points that Doug and Tony have brought to light. The concept of lakehouse was going on to your point, Dave, a long time ago, long before the tone was invented. For example, in Uber, Uber was trying to do a mix of Hadoop and Vertical because what they really needed were transactional capabilities that Hadoop did not have. So they weren't calling it the lakehouse, they were using multiple technologies, but now they're able to collapse it into a single data store that we call lakehouse. Data lakes, excellent at batch processing large volumes of data, but they don't have the real time capabilities such as change data capture, doing inserts and updates. So this is why lakehouse has become so important because they give us these transactional capabilities. >> Great. So I'm interested, the name is great, lakehouse. The concept is powerful, but I get concerned that it's a lot of marketing hype behind it. So I want to examine that a bit deeper. How mature is the concept of lakehouse? Are there practical examples that really exist in the real world that are driving business results for practitioners? Tony, maybe you could kick that off. >> Well, put it this way. I think what's interesting is that both data lakes and data warehouse that each had to extend themselves. To believe the Databricks hype it's that this was just a natural extension of the data lake. In point of fact, Databricks had to go outside its core technology of Spark to make the lakehouse possible. And it's a very similar type of thing on the part with data warehouse folks, in terms of that they've had to go beyond SQL, In the case of Databricks. There have been a number of incremental improvements to Delta lake, to basically make the table format more performative, for instance. But the other thing, I think the most dramatic change in all that is in their SQL engine and they had to essentially pretty much abandon Spark SQL because it really, in off itself Spark SQL is essentially stop gap solution. And if they wanted to really address that crowd, they had to totally reinvent SQL or at least their SQL engine. And so Databricks SQL is not Spark SQL, it is not Spark, it's basically SQL that it's adapted to run in a Spark environment, but the underlying engine is C++, it's not scale or anything like that. So Databricks had to take a major detour outside of its core platform to do this. So to answer your question, this is not mature because these are all basically kind of, even though the idea of blending platforms has been going on for well over a decade, I would say that the current iteration is still fairly immature. And in the cloud, I could see a further evolution of this because if you think through cloud native architecture where you're essentially abstracting compute from data, there is no reason why, if let's say you are dealing with say, the same basically data targets say cloud storage, cloud object storage that you might not apportion the task to different compute engines. And so therefore you could have, for instance, let's say you're Google, you could have BigQuery, perform basically the types of the analytics, the SQL analytics that would be associated with the data warehouse and you could have BigQuery ML that does some in database machine learning, but at the same time for another part of the query, which might involve, let's say some deep learning, just for example, you might go out to let's say the serverless spark service or the data proc. And there's no reason why Google could not blend all those into a coherent offering that's basically all triggered through microservices. And I just gave Google as an example, if you could generalize that with all the other cloud or all the other third party vendors. So I think we're still very early in the game in terms of maturity of data lakehouses. >> Thanks, Tony. So Sanjeev, is this all hype? What are your thoughts? >> It's not hype, but completely agree. It's not mature yet. Lakehouses have still a lot of work to do, so what I'm now starting to see is that the world is dividing into two camps. On one hand, there are people who don't want to deal with the operational aspects of vast amounts of data. They are the ones who are going for BigQuery, Redshift, Snowflake, Synapse, and so on because they want the platform to handle all the data modeling, access control, performance enhancements, but these are trade off. If you go with these platforms, then you are giving up on vendor neutrality. On the other side are those who have engineering skills. They want the independence. In other words, they don't want vendor lock in. They want to transform their data into any number of use cases, especially data science, machine learning use case. What they want is agility via open file formats using any compute engine. So why do I say lakehouses are not mature? Well, cloud data warehouses they provide you an excellent user experience. That is the main reason why Snowflake took off. If you have thousands of cables, it takes minutes to get them started, uploaded into your warehouse and start experimentation. Table formats are far more resonating with the community than file formats. But once the cost goes up of cloud data warehouse, then the organization start exploring lakehouses. But the problem is lakehouses still need to do a lot of work on metadata. Apache Hive was a fantastic first attempt at it. Even today Apache Hive is still very strong, but it's all technical metadata and it has so many different restrictions. That's why we see Databricks is investing into something called Unity Catalog. Hopefully we'll hear more about Unity Catalog at the end of the month. But there's a second problem. I just want to mention, and that is lack of standards. All these open source vendors, they're running, what I call ego projects. You see on LinkedIn, they're constantly battling with each other, but end user doesn't care. End user wants a problem to be solved. They want to use Trino, Dremio, Spark from EMR, Databricks, Ahana, DaaS, Frink, Athena. But the problem is that we don't have common standards. >> Right. Thanks. So Doug, I worry sometimes. I mean, I look at the space, we've debated for years, best of breed versus the full suite. You see AWS with whatever, 12 different plus data stores and different APIs and primitives. You got Oracle putting everything into its database. It's actually done some interesting things with MySQL HeatWave, so maybe there's proof points there, but Snowflake really good at data warehouse, simplifying data warehouse. Databricks, really good at making lakehouses actually more functional. Can one platform do it all? >> Well in a word, I can't be best at breed at all things. I think the upshot of and cogen analysis from Sanjeev there, the database, the vendors coming out of the database tradition, they excel at the SQL. They're extending it into data science, but when it comes to unstructured data, data science, ML AI often a compromise, the data lake crowd, the Databricks and such. They've struggled to completely displace the data warehouse when it really gets to the tough SLAs, they acknowledge that there's still a role for the warehouse. Maybe you can size down the warehouse and offload some of the BI workloads and maybe and some of these SQL engines, good for ad hoc, minimize data movement. But really when you get to the deep service level, a requirement, the high concurrency, the high query workloads, you end up creating something that's warehouse like. >> Where do you guys think this market is headed? What's going to take hold? Which projects are going to fade away? You got some things in Apache projects like Hudi and Iceberg, where do they fit Sanjeev? Do you have any thoughts on that? >> So thank you, Dave. So I feel that table formats are starting to mature. There is a lot of work that's being done. We will not have a single product or single platform. We'll have a mixture. So I see a lot of Apache Iceberg in the news. Apache Iceberg is really innovating. Their focus is on a table format, but then Delta and Apache Hudi are doing a lot of deep engineering work. For example, how do you handle high concurrency when there are multiple rights going on? Do you version your Parquet files or how do you do your upcerts basically? So different focus, at the end of the day, the end user will decide what is the right platform, but we are going to have multiple formats living with us for a long time. >> Doug is Iceberg in your view, something that's going to address some of those gaps in standards that Sanjeev was talking about earlier? >> Yeah, Delta lake, Hudi, Iceberg, they all address this need for consistency and scalability, Delta lake open technically, but open for access. I don't hear about Delta lakes in any worlds, but Databricks, hearing a lot of buzz about Apache Iceberg. End users want an open performance standard. And most recently Google embraced Iceberg for its recent a big lake, their stab at having supporting both lakes and warehouses on one conjoined platform. >> And Tony, of course, you remember the early days of the sort of big data movement you had MapR was the most closed. You had Horton works the most open. You had Cloudera in between. There was always this kind of contest as to who's the most open. Does that matter? Are we going to see a repeat of that here? >> I think it's spheres of influence, I think, and Doug very much was kind of referring to this. I would call it kind of like the MongoDB syndrome, which is that you have... and I'm talking about MongoDB before they changed their license, open source project, but very much associated with MongoDB, which basically, pretty much controlled most of the contributions made decisions. And I think Databricks has the same iron cloud hold on Delta lake, but still the market is pretty much associated Delta lake as the Databricks, open source project. I mean, Iceberg is probably further advanced than Hudi in terms of mind share. And so what I see that's breaking down to is essentially, basically the Databricks open source versus the everything else open source, the community open source. So I see it's a very similar type of breakdown that I see repeating itself here. >> So by the way, Mongo has a conference next week, another data platform is kind of not really relevant to this discussion totally. But in the sense it is because there's a lot of discussion on earnings calls these last couple of weeks about consumption and who's exposed, obviously people are concerned about Snowflake's consumption model. Mongo is maybe less exposed because Atlas is prominent in the portfolio, blah, blah, blah. But I wanted to bring up the little bit of controversy that we saw come out of the Snowflake earnings call, where the ever core analyst asked Frank Klutman about discretionary spend. And Frank basically said, look, we're not discretionary. We are deeply operationalized. Whereas he kind of poo-pooed the lakehouse or the data lake, et cetera, saying, oh yeah, data scientists will pull files out and play with them. That's really not our business. Do any of you have comments on that? Help us swing through that controversy. Who wants to take that one? >> Let's put it this way. The SQL folks are from Venus and the data scientists are from Mars. So it means it really comes down to it, sort that type of perception. The fact is, is that, traditionally with analytics, it was very SQL oriented and that basically the quants were kind of off in their corner, where they're using SaaS or where they're using Teradata. It's really a great leveler today, which is that, I mean basic Python it's become arguably one of the most popular programming languages, depending on what month you're looking at, at the title index. And of course, obviously SQL is, as I tell the MongoDB folks, SQL is not going away. You have a large skills base out there. And so basically I see this breaking down to essentially, you're going to have each group that's going to have its own natural preferences for its home turf. And the fact that basically, let's say the Python and scale of folks are using Databricks does not make them any less operational or machine critical than the SQL folks. >> Anybody else want to chime in on that one? >> Yeah, I totally agree with that. Python support in Snowflake is very nascent with all of Snowpark, all of the things outside of SQL, they're very much relying on partners too and make things possible and make data science possible. And it's very early days. I think the bottom line, what we're going to see is each of these camps is going to keep working on doing better at the thing that they don't do today, or they're new to, but they're not going to nail it. They're not going to be best of breed on both sides. So the SQL centric companies and shops are going to do more data science on their database centric platform. That data science driven companies might be doing more BI on their leagues with those vendors and the companies that have highly distributed data, they're going to add fabrics, and maybe offload more of their BI onto those engines, like Dremio and Starburst. >> So I've asked you this before, but I'll ask you Sanjeev. 'Cause Snowflake and Databricks are such great examples 'cause you have the data engineering crowd trying to go into data warehousing and you have the data warehousing guys trying to go into the lake territory. Snowflake has $5 billion in the balance sheet and I've asked you before, I ask you again, doesn't there has to be a semantic layer between these two worlds? Does Snowflake go out and do M&A and maybe buy ad scale or a data mirror? Or is that just sort of a bandaid? What are your thoughts on that Sanjeev? >> I think semantic layer is the metadata. The business metadata is extremely important. At the end of the day, the business folks, they'd rather go to the business metadata than have to figure out, for example, like let's say, I want to update somebody's email address and we have a lot of overhead with data residency laws and all that. I want my platform to give me the business metadata so I can write my business logic without having to worry about which database, which location. So having that semantic layer is extremely important. In fact, now we are taking it to the next level. Now we are saying that it's not just a semantic layer, it's all my KPIs, all my calculations. So how can I make those calculations independent of the compute engine, independent of the BI tool and make them fungible. So more disaggregation of the stack, but it gives us more best of breed products that the customers have to worry about. >> So I want to ask you about the stack, the modern data stack, if you will. And we always talk about injecting machine intelligence, AI into applications, making them more data driven. But when you look at the application development stack, it's separate, the database is tends to be separate from the data and analytics stack. Do those two worlds have to come together in the modern data world? And what does that look like organizationally? >> So organizationally even technically I think it is starting to happen. Microservices architecture was a first attempt to bring the application and the data world together, but they are fundamentally different things. For example, if an application crashes, that's horrible, but Kubernetes will self heal and it'll bring the application back up. But if a database crashes and corrupts your data, we have a huge problem. So that's why they have traditionally been two different stacks. They are starting to come together, especially with data ops, for instance, versioning of the way we write business logic. It used to be, a business logic was highly embedded into our database of choice, but now we are disaggregating that using GitHub, CICD the whole DevOps tool chain. So data is catching up to the way applications are. >> We also have databases, that trans analytical databases that's a little bit of what the story is with MongoDB next week with adding more analytical capabilities. But I think companies that talk about that are always careful to couch it as operational analytics, not the warehouse level workloads. So we're making progress, but I think there's always going to be, or there will long be a separate analytical data platform. >> Until data mesh takes over. (all laughing) Not opening a can of worms. >> Well, but wait, I know it's out of scope here, but wouldn't data mesh say, hey, do take your best of breed to Doug's earlier point. You can't be best of breed at everything, wouldn't data mesh advocate, data lakes do your data lake thing, data warehouse, do your data lake, then you're just a node on the mesh. (Tony laughs) Now you need separate data stores and you need separate teams. >> To my point. >> I think, I mean, put it this way. (laughs) Data mesh itself is a logical view of the world. The data mesh is not necessarily on the lake or on the warehouse. I think for me, the fear there is more in terms of, the silos of governance that could happen and the silo views of the world, how we redefine. And that's why and I want to go back to something what Sanjeev said, which is that it's going to be raising the importance of the semantic layer. Now does Snowflake that opens a couple of Pandora's boxes here, which is one, does Snowflake dare go into that space or do they risk basically alienating basically their partner ecosystem, which is a key part of their whole appeal, which is best of breed. They're kind of the same situation that Informatica was where in the early 2000s, when Informatica briefly flirted with analytic applications and realized that was not a good idea, need to redouble down on their core, which was data integration. The other thing though, that raises the importance of and this is where the best of breed comes in, is the data fabric. My contention is that and whether you use employee data mesh practice or not, if you do employee data mesh, you need data fabric. If you deploy data fabric, you don't necessarily need to practice data mesh. But data fabric at its core and admittedly it's a category that's still very poorly defined and evolving, but at its core, we're talking about a common meta data back plane, something that we used to talk about with master data management, this would be something that would be more what I would say basically, mutable, that would be more evolving, basically using, let's say, machine learning to kind of, so that we don't have to predefine rules or predefine what the world looks like. But so I think in the long run, what this really means is that whichever way we implement on whichever physical platform we implement, we need to all be speaking the same metadata language. And I think at the end of the day, regardless of whether it's a lake, warehouse or a lakehouse, we need common metadata. >> Doug, can I come back to something you pointed out? That those talking about bringing analytic and transaction databases together, you had talked about operationalizing those and the caution there. Educate me on MySQL HeatWave. I was surprised when Oracle put so much effort in that, and you may or may not be familiar with it, but a lot of folks have talked about that. Now it's got nowhere in the market, that no market share, but a lot of we've seen these benchmarks from Oracle. How real is that bringing together those two worlds and eliminating ETL? >> Yeah, I have to defer on that one. That's my colleague, Holger Mueller. He wrote the report on that. He's way deep on it and I'm not going to mock him. >> I wonder if that is something, how real that is or if it's just Oracle marketing, anybody have any thoughts on that? >> I'm pretty familiar with HeatWave. It's essentially Oracle doing what, I mean, there's kind of a parallel with what Google's doing with AlloyDB. It's an operational database that will have some embedded analytics. And it's also something which I expect to start seeing with MongoDB. And I think basically, Doug and Sanjeev were kind of referring to this before about basically kind of like the operational analytics, that are basically embedded within an operational database. The idea here is that the last thing you want to do with an operational database is slow it down. So you're not going to be doing very complex deep learning or anything like that, but you might be doing things like classification, you might be doing some predictives. In other words, we've just concluded a transaction with this customer, but was it less than what we were expecting? What does that mean in terms of, is this customer likely to turn? I think we're going to be seeing a lot of that. And I think that's what a lot of what MySQL HeatWave is all about. Whether Oracle has any presence in the market now it's still a pretty new announcement, but the other thing that kind of goes against Oracle, (laughs) that they had to battle against is that even though they own MySQL and run the open source project, everybody else, in terms of the actual commercial implementation it's associated with everybody else. And the popular perception has been that MySQL has been basically kind of like a sidelight for Oracle. And so it's on Oracles shoulders to prove that they're damn serious about it. >> There's no coincidence that MariaDB was launched the day that Oracle acquired Sun. Sanjeev, I wonder if we could come back to a topic that we discussed earlier, which is this notion of consumption, obviously Wall Street's very concerned about it. Snowflake dropped prices last week. I've always felt like, hey, the consumption model is the right model. I can dial it down in when I need to, of course, the street freaks out. What are your thoughts on just pricing, the consumption model? What's the right model for companies, for customers? >> Consumption model is here to stay. What I would like to see, and I think is an ideal situation and actually plays into the lakehouse concept is that, I have my data in some open format, maybe it's Parquet or CSV or JSON, Avro, and I can bring whatever engine is the best engine for my workloads, bring it on, pay for consumption, and then shut it down. And by the way, that could be Cloudera. We don't talk about Cloudera very much, but it could be one business unit wants to use Athena. Another business unit wants to use some other Trino let's say or Dremio. So every business unit is working on the same data set, see that's critical, but that data set is maybe in their VPC and they bring any compute engine, you pay for the use, shut it down. That then you're getting value and you're only paying for consumption. It's not like, I left a cluster running by mistake, so there have to be guardrails. The reason FinOps is so big is because it's very easy for me to run a Cartesian joint in the cloud and get a $10,000 bill. >> This looks like it's been a sort of a victim of its own success in some ways, they made it so easy to spin up single note instances, multi note instances. And back in the day when compute was scarce and costly, those database engines optimized every last bit so they could get as much workload as possible out of every instance. Today, it's really easy to spin up a new node, a new multi node cluster. So that freedom has meant many more nodes that aren't necessarily getting that utilization. So Snowflake has been doing a lot to add reporting, monitoring, dashboards around the utilization of all the nodes and multi node instances that have spun up. And meanwhile, we're seeing some of the traditional on-prem databases that are moving into the cloud, trying to offer that freedom. And I think they're going to have that same discovery that the cost surprises are going to follow as they make it easy to spin up new instances. >> Yeah, a lot of money went into this market over the last decade, separating compute from storage, moving to the cloud. I'm glad you mentioned Cloudera Sanjeev, 'cause they got it all started, the kind of big data movement. We don't talk about them that much. Sometimes I wonder if it's because when they merged Hortonworks and Cloudera, they dead ended both platforms, but then they did invest in a more modern platform. But what's the future of Cloudera? What are you seeing out there? >> Cloudera has a good product. I have to say the problem in our space is that there're way too many companies, there's way too much noise. We are expecting the end users to parse it out or we expecting analyst firms to boil it down. So I think marketing becomes a big problem. As far as technology is concerned, I think Cloudera did turn their selves around and Tony, I know you, you talked to them quite frequently. I think they have quite a comprehensive offering for a long time actually. They've created Kudu, so they got operational, they have Hadoop, they have an operational data warehouse, they're migrated to the cloud. They are in hybrid multi-cloud environment. Lot of cloud data warehouses are not hybrid. They're only in the cloud. >> Right. I think what Cloudera has done the most successful has been in the transition to the cloud and the fact that they're giving their customers more OnRamps to it, more hybrid OnRamps. So I give them a lot of credit there. They're also have been trying to position themselves as being the most price friendly in terms of that we will put more guardrails and governors on it. I mean, part of that could be spin. But on the other hand, they don't have the same vested interest in compute cycles as say, AWS would have with EMR. That being said, yes, Cloudera does it, I think its most powerful appeal so of that, it almost sounds in a way, I don't want to cast them as a legacy system. But the fact is they do have a huge landed legacy on-prem and still significant potential to land and expand that to the cloud. That being said, even though Cloudera is multifunction, I think it certainly has its strengths and weaknesses. And the fact this is that yes, Cloudera has an operational database or an operational data store with a kind of like the outgrowth of age base, but Cloudera is still based, primarily known for the deep analytics, the operational database nobody's going to buy Cloudera or Cloudera data platform strictly for the operational database. They may use it as an add-on, just in the same way that a lot of customers have used let's say Teradata basically to do some machine learning or let's say, Snowflake to parse through JSON. Again, it's not an indictment or anything like that, but the fact is obviously they do have their strengths and their weaknesses. I think their greatest opportunity is with their existing base because that base has a lot invested and vested. And the fact is they do have a hybrid path that a lot of the others lack. >> And of course being on the quarterly shock clock was not a good place to be under the microscope for Cloudera and now they at least can refactor the business accordingly. I'm glad you mentioned hybrid too. We saw Snowflake last month, did a deal with Dell whereby non-native Snowflake data could access on-prem object store from Dell. They announced a similar thing with pure storage. What do you guys make of that? Is that just... How significant will that be? Will customers actually do that? I think they're using either materialized views or extended tables. >> There are data rated and residency requirements. There are desires to have these platforms in your own data center. And finally they capitulated, I mean, Frank Klutman is famous for saying to be very focused and earlier, not many months ago, they called the going on-prem as a distraction, but clearly there's enough demand and certainly government contracts any company that has data residency requirements, it's a real need. So they finally addressed it. >> Yeah, I'll bet dollars to donuts, there was an EBC session and some big customer said, if you don't do this, we ain't doing business with you. And that was like, okay, we'll do it. >> So Dave, I have to say, earlier on you had brought this point, how Frank Klutman was poo-pooing data science workloads. On your show, about a year or so ago, he said, we are never going to on-prem. He burnt that bridge. (Tony laughs) That was on your show. >> I remember exactly the statement because it was interesting. He said, we're never going to do the halfway house. And I think what he meant is we're not going to bring the Snowflake architecture to run on-prem because it defeats the elasticity of the cloud. So this was kind of a capitulation in a way. But I think it still preserves his original intent sort of, I don't know. >> The point here is that every vendor will poo-poo whatever they don't have until they do have it. >> Yes. >> And then it'd be like, oh, we are all in, we've always been doing this. We have always supported this and now we are doing it better than others. >> Look, it was the same type of shock wave that we felt basically when AWS at the last moment at one of their reinvents, oh, by the way, we're going to introduce outposts. And the analyst group is typically pre briefed about a week or two ahead under NDA and that was not part of it. And when they dropped, they just casually dropped that in the analyst session. It's like, you could have heard the sound of lots of analysts changing their diapers at that point. >> (laughs) I remember that. And a props to Andy Jassy who once, many times actually told us, never say never when it comes to AWS. So guys, I know we got to run. We got some hard stops. Maybe you could each give us your final thoughts, Doug start us off and then-- >> Sure. Well, we've got the Snowflake Summit coming up. I'll be looking for customers that are really doing data science, that are really employing Python through Snowflake, through Snowpark. And then a couple weeks later, we've got Databricks with their Data and AI Summit in San Francisco. I'll be looking for customers that are really doing considerable BI workloads. Last year I did a market overview of this analytical data platform space, 14 vendors, eight of them claim to support lakehouse, both sides of the camp, Databricks customer had 32, their top customer that they could site was unnamed. It had 32 concurrent users doing 15,000 queries per hour. That's good but it's not up to the most demanding BI SQL workloads. And they acknowledged that and said, they need to keep working that. Snowflake asked for their biggest data science customer, they cited Kabura, 400 terabytes, 8,500 users, 400,000 data engineering jobs per day. I took the data engineering job to be probably SQL centric, ETL style transformation work. So I want to see the real use of the Python, how much Snowpark has grown as a way to support data science. >> Great. Tony. >> Actually of all things. And certainly, I'll also be looking for similar things in what Doug is saying, but I think sort of like, kind of out of left field, I'm interested to see what MongoDB is going to start to say about operational analytics, 'cause I mean, they're into this conquer the world strategy. We can be all things to all people. Okay, if that's the case, what's going to be a case with basically, putting in some inline analytics, what are you going to be doing with your query engine? So that's actually kind of an interesting thing we're looking for next week. >> Great. Sanjeev. >> So I'll be at MongoDB world, Snowflake and Databricks and very interested in seeing, but since Tony brought up MongoDB, I see that even the databases are shifting tremendously. They are addressing both the hashtag use case online, transactional and analytical. I'm also seeing that these databases started in, let's say in case of MySQL HeatWave, as relational or in MongoDB as document, but now they've added graph, they've added time series, they've added geospatial and they just keep adding more and more data structures and really making these databases multifunctional. So very interesting. >> It gets back to our discussion of best of breed, versus all in one. And it's likely Mongo's path or part of their strategy of course, is through developers. They're very developer focused. So we'll be looking for that. And guys, I'll be there as well. I'm hoping that we maybe have some extra time on theCUBE, so please stop by and we can maybe chat a little bit. Guys as always, fantastic. Thank you so much, Doug, Tony, Sanjeev, and let's do this again. >> It's been a pleasure. >> All right and thank you for watching. This is Dave Vellante for theCUBE and the excellent analyst. We'll see you next time. (upbeat music)
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And Doug Henschen is the vice president Thank you. Doug let's start off with you And at the same time, me a lot of that material. And of course, at the and then we realized all the and Tony have brought to light. So I'm interested, the And in the cloud, So Sanjeev, is this all hype? But the problem is that we I mean, I look at the space, and offload some of the So different focus, at the end of the day, and warehouses on one conjoined platform. of the sort of big data movement most of the contributions made decisions. Whereas he kind of poo-pooed the lakehouse and the data scientists are from Mars. and the companies that have in the balance sheet that the customers have to worry about. the modern data stack, if you will. and the data world together, the story is with MongoDB Until data mesh takes over. and you need separate teams. that raises the importance of and the caution there. Yeah, I have to defer on that one. The idea here is that the of course, the street freaks out. and actually plays into the And back in the day when the kind of big data movement. We are expecting the end And the fact is they do have a hybrid path refactor the business accordingly. saying to be very focused And that was like, okay, we'll do it. So Dave, I have to say, the Snowflake architecture to run on-prem The point here is that and now we are doing that in the analyst session. And a props to Andy Jassy and said, they need to keep working that. Great. Okay, if that's the case, Great. I see that even the databases I'm hoping that we maybe have and the excellent analyst.
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