 Welcome back to New York City. Everybody watching theCUBE's coverage of MongoDB World 2022. My name is Dave Vellante. Pretty good attendance here. I'd say over 3,000 people, great buzz. A lot of really technical sessions. There's an executive session going on. There's a financial analyst. There's a lot of diversity in this attendee base. Vadim Supitski is here. He's the CTO of Forbes and Abdul Razak is the Vice President of Solution Engineering at Google. Jens, 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, well, we all in the business world read for it. 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 are the scale 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 at that point. So Abdul, the solution you provided obviously worked. How did you guys end up getting together? What was that like? Yeah, I mean, like Vladimir said, right? I mean, maybe there's a little bit of a 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 Nadim said, primarily folks 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 this 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 website and off the main. 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're able to provide them with what they want. So the first party data platform is what a self-serve for advertisers 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, innovating products and offering our journalism and everything there to our readers and we're able to connect them to the right audiences at the right time. As well as personalization, you come into the website, you want to read what you want to read. So we're able to create that as well, using machine learning and AI. So a product might be a data product or might be a content product? It could be a data product. It could be just personalization or something like that. It could be newsletter, right? It could be a standalone 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, it'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 first party data platform gives the ability to create a seamless profile. 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 fullest and we embrace cloud, right? So we're using all the cloud-native technologies, right? We didn't want to just lift and shift. We wanted to make sure that we do it right and we focused on animation, even if we had to take a step back, we knew that that amazing 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 the time. Ten gen. Yeah, yes. It was... We remember. Many years ago it was MongoDB, MongoDB One, right? Yeah. And at that time, 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, all right, so what do we do? We compared a couple of NoSQL databases and Mongo was a winner because they checked all the boxes and the 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 NoSQL. And we scaled and we never looked back. And then obviously Atlas came. So there are kind of two inflection points here. One, switching to NoSQL 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 provisioning our environments and the kind of wasteful. So being in Atlas, that was the 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, but you know, this is the nature of the world we live in, isn't it? No, and then fundamentally, like that's, we always believe that customer choice is the primary notion, right? I mean, and Google Cloud Platform is more of a platform and ecosystem is critical to that, right? It's imperative. So, you know, 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 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 you know, sometimes it's competition, right? And you're still selling a lot of compute and storage and machine intelligence, 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, you know, half a decade or more, really. And you mentioned the developers loved it, right? As Mongo evolves its platform, is there a 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 a fly. When they need to test something, also things available to them right away. So, it actually, in general, as 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, you know, 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 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 failover. 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're asleep. Right, exactly, exactly, exactly. Yeah, plus the other part is you don't size for peak, right? You size as you grow and then you have that elasticity built in, right? That it is native and then, you know, Mongo is available on multiple Google Cloud regions. So, as you expand, you know, you don't worry about, you know, all the plumbing that you need to do and things of that nature. They asked a serverless this morning. How does that affect what you guys are doing together and what are your thoughts from Google's perspective and then, of course, Yeah, and that's the trend that we see constantly, right? Serverless really decouples, you know, 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 we'd love to hear how you're leveraging that. Yeah, we fully embrace serverless. We use all the tools you provide, I think. If you look at our architectural diagrams, there's like all these Pub-Sub, Cloud Functions, Composer, App Engine. So, we use the full suite and we love it. Yeah, yeah, okay, and talk this morning about 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 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? The, you know, if you're building an intelligent app, it has multiple components within it, right? There is Pub-Sub for messaging, there is Cloud Functions and things of that nature. So, you don't worry about, you know, 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, you know, removing friction. And that's the primary source of productivity loss, right? Which is the friction. You know, we used to come from a world where developers were more worried. 80% of the time, they would spend on, you know, plumbing this thing and then only 20% writing code, right? And then now, the 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? Full in the cloud. How long did that take? What is that like? It actually was really fast. We had a really aggressive timeline. It took us six months. Really? Yeah, yeah. 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% increased 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% decrease in hard 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 know. Do you golf? No, I watch golf. I used to watch. Okay, do you know what a mulligan is? Yeah. Okay, a mulligan is like a do-over, right? If you had a mulligan, would you do anything differently? You know, like we learned a lot. And one of the keys for me was, they 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 they were able to use. 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, because sometimes automation brings unintended consequences and, you know, 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, you know, we see a lot of, 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 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 protect it in many areas. So square this circle, because especially with COVID, so many unknowns, right? 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 things, you can change things much more easily. So when you talk about standardization, you're talking about standardizing, what, at the infrastructure layer? Where is that standardization occur? Where should it occur? I said, I mean, you could have it at the business process level. 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 use case, right? There are content curation, for example, right? 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, you know, 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? Yeah, we built our own custom CMS. It's AI-powered. We want to make our journalist's life easier. So we're constantly trying to figure out, like, what can we give them to make that 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 recommendation. And then you can automate the insertion of those words pressed every time that you were doing it. They're writing about the same topic. It's a recommendation process, obviously, but yeah. 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. So yeah, wow, amazing story, guys. Thanks so much for sharing it. Absolutely, thank you. All right, keep it right there. We're live from MongoDB World 2022 in New York City. We'll be right back.