Screaming in the Cloud - How MongoDB is Paving The Way for Frictionless Innovation with Peder Ulander

Episode Date: November 30, 2023

Peder Ulander, Chief Marketing & Strategy Officer at MongoDB, joins Corey on Screaming in the Cloud to discuss how MongoDB is paving the way for innovation. Corey and Peder discuss how Peder made the decision to go from working at Amazon to MongoDB, and Peder explains how MongoDB is seeking to differentiate itself by making it easier for developers to innovate without friction. Peder also describes why he feels databases are more ubiquitous than people realize, and what it truly takes to win the hearts and minds of developers. About Peder Peder Ulander, the maestro of marketing mayhem at MongoDB, juggles strategies like a tech wizard on caffeine. As the Chief Marketing & Strategy Officer, he battles buzzwords, slays jargon dragons, and tends to developers with a wink. From pioneering Amazon's cloud heyday as Director of Enterprise and Developer Solutions Marketing to leading the brand behind cloud.com's insurgency, Peder's built a legacy as the swashbuckler of software, leaving a trail of market disruptions one vibrant outfit at a time. Peder is the Scarlett Johansson of tech marketing — always looking forward, always picking the edgy roles that drive what's next in technology.Links Referenced:MongoDB: https://mongodb.com

Hello, and welcome to Screaming in the Cloud, with your host, Chief Cloud Economist at the Duckbill Group, Corey Quinn. This weekly show features conversations with people doing interesting work in the world of cloud, thoughtful commentary on the state of the technical world, and ridiculous titles for which Corey refuses to apologize. This is Screaming in the Cloud. Welcome to Screaming in the Cloud. I'm Corey Quinn.

This promoted guest episode of Screaming in the Cloud is brought to us by my friends and yours at MongoDB. And into my veritable verbal gristmill, they have sent Peter Uhlender, their chief marketing officer. Peter, an absolute pleasure to talk to you again. Always good to see you, Corey. Thanks for having me. So once upon a time, you worked in marketing over at AWS, and then you transitioned off to Mongo to, again, work in marketing. Imagine that, almost like there's a narrative arc to your

career. A lot of things change when you change companies. But before we dive into things, I just want to call out that you are a bit of an aberration in that every single person that I have spoken to who has worked within your org has nothing but good things to say about you, which means you are incredibly effective at silencing dissent. Good work. Or it just shows that I'm a good marketer and make sure that we paint the right picture that the world needs to see. Exactly. Do we have any proof of you being a great person to work for? No, just word of mouth and everyone, ah, that's how marketing works. Exactly. See, I'm glad you picked up somewhere. So let's dive into that a little bit. Why would you leave AWS to go work at Mongo?

And again, my usual snark and sarcasm would come up with a half dozen different answers, each more offensive than the last. Let's be serious for a second. At AWS, there's an incredibly powerful engine that drives so much stuff and the breadth is enormous, MongoDB, despite an increasingly broad catalog of offerings, is nowhere near that level of just universal applicability. Your product strategy is not a post-it note with the word yes written on it. There are things that you do across the board, but they all revolve around databases. Yeah. So going back prior to MongoDB, I think, you know, at AWS, I was across a number of different things from the developer ecosystem to the enterprise transformation to the open source work, et cetera, et cetera. And being privy to how customers were adopting technology to change their business or change the experiences that they were delivering to their customers or increase the value of the applications that they built, there was a common thread of something that fundamentally needed to change. And I like to go back to just the evolution of tech in that sense.

We could talk about going from physical on-prem systems to now we're distributed into the cloud. You could talk about application constructs that started as big, fat, monolithic apps that moved to virtual, then microservices, and now functions. Or you think about networking. We've gone from fixed wireline to network edge and cellular and what have you. All of the tech stack has changed

with the exception of one layer, and that's the data layer. And I think for the last 20 years, what's been in place has worked okay, but we're now meeting this new level of scale, this new level of reach where the old systems are not what's going to be what the new systems are built on or the new experiences are built on. And as I was approached by MongoDB, I kind of sat back and said, you know, I'm super happy at AWS. I love the learning. I

love the people. I love the space I was in. But if I were to put my crystal ball together or use a Bezos statement of looking around corners, the data space is probably one of the biggest spaces ripe for disruption and opportunity. And I think Mongo is in an incredible position to go take advantage of that. I mean, there's an easy number of jokes to make about Amazon Basics MongoDB, which is my disparaging name for their DocumentDB first party offering. And for a time, it really felt like AWS's perspective toward its partners was one of outright hostility, if not antagonism. But that narrative no longer holds true in 2023. There's been a definite shift. And to be direct, part of the reason that I believe that is the things you have said, both personally and professionally, in your role as CMO of Mongo, that has caused me to reevaluate this. Because despite all of your faults, a counted list of

which I can provide you after the show, you do not say things that you do not believe to be true. So something has changed. What is it? So I think there's an element of co-opetition, right? So I would go as far as to say the media loved to sensationalize. Actually, even the venture community loved to sensationalize the screen scraping, stripping of open source communities that Amazon represented a number of years ago. The reality was their intent was pretty simple. They built an incredibly amazing IT stack and they wanted to run whatever applications and software were important to their customers.

And when you think about that, the majority of systems today, people want to run open source because it removes friction, it removes cost, it enables them to go do cool new things and be on the bleeding edge of technology. And Amazon did their best to work with the top open source projects in the world to make it available to their customers. Now, for the commercial vendors that are leaning into this space, that obviously does present itself threat, right? And we've seen that along a number of the cohorts of whether you want to call it single vendor open source or companies that have a heavy vested interest in seeing the success of their enterprise stack match the success of the open source stack. And that's, I think, where media analysts venture all kind of jumped on the bandwagon of

not really kind of painting that bigger picture for the future. I think today, when I look at Amazon, and candidly, it'll be any of the hyperscalers, they all have a clone of our database. It's an entry point. They're running just the raw open source operational database capabilities that we have in our community edition and making that available to customers. We believe there's a bigger value in going beyond just that database and introducing anything from the distributed zones to what we do around vector search to what we do around stream processing and encryption and all of these advanced features and capabilities that enable our customers to scale rapidly on our platform. And the dependency on delivering that is with the hyperscalers. So that's where that coopetition comes in. And that becomes really important for us when we're casting our web to

engage with some of the world's largest customers out there. But interestingly enough, we become a big drag of services for an AWS or any of the other hyperscalers out there, meaning that for every dollar that goes to a MongoDB, there's $3, $5, $10 that goes to these hyperscalers. And so they're very active in working with us to ensure that we have fair and competing offers in the marketplace, that they're promoting us through their own marketplace as well as their own channels, and that we're working together to further the success of our customers. When you take a look at the exciting things that are happening at the data layer, because you mentioned that we haven't really seen significant innovation in that space for a

while. One of the things that I see happening is with the rise of generative AI, which requires very special math that can only be handled by very special types of computers, I'm seeing at least a temporary inversion in what has traditionally been thought of as data gravity, whereas it's easier to move compute

close to the data. But in this case, since the compute only lives in the sparkling US East 1 regions of Virginia, otherwise it's just generic, sparkling, expensive computers. Great. You have to effectively move the mountain to Mohammed, so to speak. So in that context, what else is happening that is driving innovation in the data space right now?

Yeah, yeah. I love your analogy of move the mountain to Mohammed, because that's actually how we look at the opportunity in the whole generative AI movement. There are a lot of tools and capabilities out there, whether we're looking at co-generation tools, LLM modeling vendors, some of the other vector database companies that are out there, and they're all built on the premise of bring your data to my tool. And I actually think that's a flawed strategy. I think that these are things that are going to be features in core application databases or operational databases, and it's going to be dependent on the reach and breadth of that database and the integrations with all of these AI tools that will define the victor going forward. We look at Atlas, 111 availability zones across all three hyperscalers with a single unified interface.

We're actually able to have the customers keep their operational data where it's most important to them and then apply the tools of the hyperscalers or the partners where it makes most sense without moving the data, right? So you don't actually have to move the mountain to Mohammed. We're literally building an experience where those that are running on MongoDB and have been running on MongoDB can gain advantage of these new tools and capabilities instantly

without having to change anything in their architectures or how they're building their applications. There was a somewhat overexcited, I guess, over-focus in the space of vector databases, because whatever those are, which involves math, and I am in no way, shape, or form smart enough to grasp the nuances thereof, but everyone assures me that it's necessary for generative AI and machine learning and yada, yada, yada. So when in doubt, when I'm confronted by things I don't fully understand, I turn to people who do. And the almost universal consensus that I have picked up

from people who track databases for a living, as opposed to my own role of inappropriately using everything in the world except databases as a database, is that vector is very much a feature, not a core database type. Correct. The best way to think about it, I mean, databases in general, they're dealing with structured and unstructured data. And generally, especially when you're doing searches or relevance, you're limited to the fact that those things in the rows and the columns or in the documents is text, right? And the reality is there's a whole host of information that can be found in metadata,

in images, in sounds, in all of these other sources that were stored as individual files but unsearchable. Vector, vectorization and vector embeddings actually enable you to take things far beyond the text and numbers that you traditionally were searching against and actually apply more kind of intelligence to it or apply sounds or apply smell. You can vectorize smells to some extent. And what that does is it actually creates a more pleasing slash relevant experience for how you are actually building the engagements with your customers.

Now, I'll make it a little more simple because I was trying to define vectors, which as you know, is not the easiest thing. But imagine being able to vectorize, let's say I'm a car company, we're actually working with a car company on this. And you're able to store all of the audio files of cars that are showing certain diagnostic issues, the putters and the spurts and the pings and the pangs. And you can actually now isolate these sounds and apply them directly to the problem and resolution for the mechanics that are working on them. Using all of this stuff together, now you actually have a faster time to resolution. You don't want mechanics knowing the mechanics of vectors in that sense, right?

So you build an application that abstracts all of that complexity. You don't require them to go through PDFs of data and find all of the options for fixing this stuff. The relevance comes back and says, yes, we've seen that sound 20 times across this vehicle. Here's how you fix it, right? And that cuts significant amount of time, cost, efficiency, and complexity for those auto

mechanics. That is such a big push forward, I think, from a technology perspective and what the true promise of some of these new capabilities are and why I get excited about what we're doing with Vector and how we're enabling our customers to, you know, kind of recreate experiences in a way that are more human, more relevant. Now, I have to say that, of course, you're going to say nice things about your capabilities where Vector is concerned. You would be failing in your job if you did not. So I feel like I can safely discount every positive thing that you say about Mongo's positioning in the vector space and instead turn to, you know, third parties with no formalized relationship with you. Yesterday, Retool's state of AI report came across my desk.

I am a very happy Retool customer. They've been a periodic sponsor from time to time of my ridiculous nonsense, which is neither here nor there, but I want to disclaim the relationship. And they had a Gartner magic quadrant equivalent that on one axis had net promoter score, NPS, which is one of your people's kinds of things. And the other was popularity. And Mongo was so far up into the right that it was almost hilarious compared to every other entrant in the space. That is a positioning that I do not believe it is possible to market your way into directly. This is something that people who are actually doing these things have to use the product. It has to stand up. Mongo is clearly effective at doing this in a way that other entrants aren't.

Why? Yep. It's a good question. I think a big part of that goes back to the earlier statement I made that vector databases or vector technology, it's a feature, it's not a separate thing, right? And when I think about all of the new entrants, they're creating a new model where now you have to move your data out of your operational database and into their tool to get an answer and then push back in. The complexity, the integrations, the capabilities, it just slows everything down.

I think when you look at MongoDB's approach to take this developer data platform vision of getting all of the core tools that developers need to build compelling applications with from a data perspective, integrating it into one seamless experience, we're able to basically bring classic operational database capabilities, classic text search type capabilities, embed the vector search capabilities as well. It actually creates a richer platform and experience without

all of that complexity that's associated with a bolt-on sidecar GenAI tool or vector database. I would say that that's one of those things that, again, can only really be credibly proven by what the market actually does, as opposed to, you know, lip-sticking the heck out of a pig and hoping that people don't dig too deeply into what you're saying. It's definitely something we're seeing adoption of. Yeah, I mean, this kind of goes to some of the stuff, you know, you pointed out the retool thing. This is not something you can market your way into. This is something that, you know, users are going to dictate the winners in this place. The developers, they're going to dictate

the winners in this space. And so what do you have to do to win the hearts and minds of developers? You have to make the tech extremely approachable. It's got to be scalable to meet their needs. Not a lot of friction involved in learning these new capabilities and applying it to all of the stuff that has come before. All of these things put together, really focusing on that developer experience, I mean, that goes to the core of the MongoDB ethos. I mean, this is who we were when we started the company so long ago, and it's continued to drive the innovation that we do in the platform. And I think this is just yet again, another example of focusing on developer needs, making it super engaging and useful, removing the friction and enabling them to just go create new things.

That's what makes it so fun. And so when, you know, as a marketer and I get the retool chart across my desk, we haven't been pitching them. We haven't been marketing to them. We haven't tried to influence any of this stuff. So knowing that this is a true unbiased audience actually is pretty cool to see. It was, to your point, it was surprising how far up into the right that we sat given, you know, where we were and just, we launched this thing six months ago. We launched it in June. The amount of customers that have signed up, are using it and engaged with us on moving us forward has been absolutely amazing.

I think that there has been so much that gets lost in the noise of marketing. My approach has always been to cut through so much of it that I think AWS has always done very well with is almost to their detriment these days. But if you get on stage, you can say whatever you want about your company's product. And I will naturally and lovingly make fun of whatever it is that you say. that they have built to solve a very specific business problem that was causing us pain, then I shut up and I listen.

Because it's very hard to wind up dismissing that without being an outright jerk about things. I think the failure mode of that is taken too far. You lose the ability to tell your own story in a coherent way, and it becomes a crutch that becomes very hard to get rid of. But the proof is really in the pudding. For me, like the old jokes about in the early teens, where MongoDB would periodically lose data as configured by default.

Like MongoDB, it's Snapchat for databases. Hilarious joke at the time, but it really has worn thin. That's like being angry about what Microsoft did in 2005 and 2006. It's like, yeah, okay, you have a point, but it is also ancient history. And at some point you need to get with the modern era, get with the program. And I think that seeing the success and breadth of MongoDB that I do,

you are in virtually every customer that I talk to in some way, shape or form. And seeing what it is that they're doing with you folks, it is clear that you are not a passing fad, that you are not going away anytime soon. Right. And that even with building things in my spare time and following various tutorials of dubious credibility from various parts of the internet, as those things tend to go, MongoDB is very often a default go-to reference when someone needs a database for which a SQLite file won't do.

Right. It's fascinating to see the evolution of MongoDB. And today, we're lucky to track 45,000-plus customers on our platform doing absolutely incredible things. But I think, to your point, the biggest proof is in the pudding when you get these customers to stand up on stage and talk about it. And even just recently through our.local series, some of the customers that we've been highlighting are doing some amazing things using MongoDB in extremely business-critical situations. My favorite was I was out doing our.local in Hong Kong where Cathay Pacific got up on stage and they talked a little bit about their flight folder. Now, if you remember going through the airport, you'd always see the captains come through and they had those two big boxes of paperwork before they got onto the plane. Not

only was that killing the environment with all the trees that got cut down for it, it was cumbersome, complex, and added a lot of time and friction with regards to flight operations. Now take that from a single flight over all of the fleet that's happening across the world. We were able to work with Cathay Pacific to digitize their entire flight folder, all of their documentation, removing the need for cutting down trees and minimizing a carbon footprint form, but at the same time, actually delivering a solution where if it goes down, it grounds the entire fleet of the airline. So imagine that. That's so business critical, mission critical, has to be there, reliable, resilient, available for the pilots, or it shuts down the business. Seeing that growth and that transformation while also seeing the environmental benefit for what they've achieved. To me, that

makes me proud to work here. Similarly, we have companies like Ford, another big brand name company here in the States, where their entire connected car experience and how they're basically operationalizing the connection between the car and their home base, this is all being done using MongoDB as well. So as they think of these new ideas, recognizing that things are going to be either out at the edges or at a level of scale that you can't just bring it back into classic rows and columns, that's actually where we're so well suited to grow our footprint. And I remember back to when I was at Sun Microsystems. I don't know if anybody remembers that company. That was an old one. But at one point, it was Jonathan that said everything of value connects to the network,

right? Those things that are connecting to the network also need applications. They need data. They need all of these services. And the further out they go, the more you need a database that basically scales to meet them where they are versus trying to get them to come back to where your database happens to sit. And in order to do that, that's where you break the mold. That's where, I mean, that kind of goes

into the core ethos of why we built this company to begin with. The original founders were not here to build a database. They were building a consumer app that needed to scale to the edges of the earth. They recognized that databases didn't solve for that, so they built MongoDB. That's actually thinking ahead, everything connecting to the network, everything being distributed, everything basically scaling out to all the citizens of the planet fundamentally needs a new data layer. And that's where I think we've come in and succeeded exceptionally well. I would agree. Another example I like to come up with, and it's fun that the one that leaves the top of my mind is not one of the ones that you

mentioned, but HSBC, the massive bank, very publicly a few years ago, wound up consolidating, I think it was 46 relational databases onto MongoDB. And the jokes at the time wrote themselves, but let's be serious for a second. Despite the jokes that we all love to tell, they're a bank, a massive bank, and they don't play fast and loose or slap and tickle with transactional integrity or their data stores for these things, because there's a definite belief across the banking sector. And I know this having worked in it myself for years, that if at some point you have the ATM spitting out the wrong account balances, people will begin rioting in the streets. I don't know if that's strictly accurate or hyperbole, but it's going to cause massive amounts of chaos if it happens. So that is

something that absolutely cannot happen. The fact that they're willing to engage with you folks and your technology and be public about it at that scale, that's really all you need to know from a is this serious technology or clown shoes technology? Well, taking that comment, now let's exponentially increase that. You know, if I sit back and I look at my customer base, financial services is actually one of our biggest verticals as a business. And you mentioned HSBC. We had Wells Fargo on the stage last year at our world event. Nine out of the top 10 world's banks are using MongoDB in some of their applications, some at scale of HSBC, some are still just getting started. And it all comes down to the fact that we have proven ourselves. We are aligned to mission critical business environments.

And I think when it comes down to banks, especially that transactional side, building in the capabilities to be able to have high frequency transactions in the banking world is a hard thing to go do. And we've been able to prove it with some of the largest banks on the planet. I also want to give you credit, although it might be that I'm giving you credit for a slow release process. I hope not. But when I visit MongoDB.com, it still talks up front that you are, and I want to quote here, good lord, it changes every time I load the page. But it talks about build faster, build smarter on this particular version of the load.

It talks about the data platform. You have not effectively decided to pivot everything you say in public to tie directly into the generative AI hype bubble that we are currently experiencing. You have a bunch of different use cases, and you're not suddenly describing what you do in gen AI terms that make it impossible to understand just what the company slash product slash services actually do. Right. So I want to congratulate you on that. Appreciate that. Right. Look, it comes down to the core basics. We are a developer data platform. We bring together all of the capabilities, tools, and functions that developers need when building apps as it pertains to their data functions, their data layer, right? and building in search or stream processing or vector search. All of the things that we're bringing to the platform enable developers to move faster.

And what that says is we're great for all use cases out there, not just Gen AI use cases. We're great for all use cases where customers are building applications to change the way that they're engaging with the customers. And what I like about this is that you're clearly integrating this stuff under the hood. You are talking to people who are building fascinating stuff. You're building things yourself, but you're not wrapping yourself in the mantle of, this is exactly what we do because it's trendy right now.

And I appreciate that. It's still intelligible. And I wouldn't think that I had to congratulate someone on, wow, you built marketing that a human being can extract meaning from. That's amazing. But in 2023, the closing days thereof, it very much is. Yeah, yeah. And it speaks a lot to the technology that we've built

because, you know, on one side, it reminds me a lot of the early days of cloud where everything was kind of cloud washed for a bit. We're seeing a little bit of that in the hype cycle that we have right now. Sticking to our guns and making sure that we are building a technology platform that enables developers to move quickly, that removing the friction from the developer life cycle as it pertains to the data layer, that's where the success is, right? We have to stay on top of all of the trends.

We have to make sure that we're enabling Gen AI. We have to make sure that we're integrating with the Amazon bedrocks and the code whispers of the world, right, to go push this stuff forward. But to the point we made earlier, those are capabilities and features of a platform where the higher level order is to really empower our customers to develop innovative, disruptive, or market-leading technologies for how they engage with their customers. Yeah. And it's neat to be able to see that you are empowering companies to do that without feeling the need to basically claim their achievements as your own, which is an honest to God, hard thing to do, especially as you will become a platform company, because increasingly you are the plumbing that makes a lot of the flashy, interesting stuff possible. It's imperative. You can't have those

things without the underlying infrastructure, but it's hard to talk about that infrastructure too. You know, it's funny. I'm sure all of my colleagues would hate me for saying this, but the wheel doesn't turn without the ball bearing. Somebody still has to build the ball bearing in order for that sucker to move, right? And that's the thing. This is the infrastructure. This is the heart of everything that businesses need to build applications. And one of the, you know, another kind of snide comment I've made to some of my colleagues here is, if you think about every market leading app, in fact, let's go to the biggest experiences you and I use on our daily basis. I'm pretty sure you're booking travel online. You're searching for stuff on Google.

You're buying stuff through Amazon. You're renting a house through Airbnb. And you're listening to your music through Spotify. What are those? Those are databases with a search engine. The world is full of crud applications. These are effectively simply pretty front ends to a database. And as much as we like to pretend otherwise, that's very much the reality of it. And we want that to be the case. Different

modes of interaction, different requirements around them. But yeah, that is what so much of the world is. And I think to ignore that is to honestly blind yourself to a bunch of very key realities here. That kind of goes back to the original vision for when I came here. It's like, look, everything of value for us, everything that I engage with is, to your point, it's a database with a great experience on top of it. Now let's start to layer in this whole Gen AI push, right?

What's going on there? We're talking about increased relevance in search we're talking about new ways of thinking about sourcing information we've even seen that with some of the latest chat gpt stuff that developers are using that to get code snippets and figure out how to solve things within their platform the era of the classic search engine is in the middle of a complete change there and the opportunity I think that I see as this moves forward is that there is no incumbent. There isn't somebody who owns this space. So we're just at the beginning of what probably will be the next Google's, Airbnb's,

and Uber's of the world for the next generation. And that's really exciting to see. I'm right there with you. One of the interesting founding stories at Google is that they wound up calling typical storage vendors for what they needed, got basically, screw on out of here, kids, pricing. So they shrugged, and because they had no real choice to get enterprise-quality hardware,

they built a bunch of highly redundant systems on top of basically a bunch of decommissioned crap boxes from the university they were able to more or less get for free or damn near it. And that led to a whole innovation in technology. One of the glorious things about cloud that I think goes undersold is that I can build a ridiculous application tonight

for maybe, what, 27 cents in infrastructure spend? And if it doesn't work, I round up to a dollar. It'll probably get waived because it'll cost more to process the credit card transaction than take my 27 cents. Conversely, if it works, I'm already building with quote unquote enterprise grade components. I don't need to do a massive uplift. I can keep going. And that is no small thing. No, it's not. When you step back, every single one of those stories was about abstracting that complexity to the end user. In Google's case, they built their own systems. You or I probably

didn't know that they were screwing these things together and soldering them in the back room in the middle of the night. Similarly, when Amazon got started, that was about taking something that was only accessible to a few thousand and now making it accessible to a few million with the cost of 27 cents to build an app. There was, you remove the risk, you remove the friction from enabling a developer to be able to build. That next wave, and this is why I think the things we're doing around Gen AI and our vector search capabilities and literally how we're building our developer data platform is about removing that friction and limits and enabling developers to just come in and effectively

do what they do best, which is innovate versus all of the other things. In the Google world, it's no longer racking and stacking. In the cloud world, it's no longer managing and integrating all the systems. Well, in the data world, it's about making sure that all of those integrations are ready to go and at your fingertips, and you just focus on what you do well, which is creating those new experiences for customers. So we're recording this a little bit beforehand, but not by much. You are going to be at reInvent this year, as am I, for eight nights, because for me, at least, it is crappy cloud Hanukkah, and I've got to deal with that. What have you got coming up? What do you plan to announce? Anything fun, exciting, or are you just there basically to see how many badges you can actually scan in one day? Well, you know what? It's shaping up to be quite

an incredible week. There's no question. We'll see what brings to town. As you know, reInvent is a huge event for us. We do a lot within that ecosystem. A lot of the customers that are up on stage talking about the cool things they're doing with AWS. They're also MongoDB customers. So we go all out. I think you and I spoke before about our position there with Sugarcane right on the show floor. I think we've managed to secure you a Friends of Peter all access pass to Sugarcane. So I look forward to seeing you there, Corey.

Proving my old thesis of it really is who you know. And thank you for your generosity. Please continue. So we will be there in full force. We have a number of different innovation talks. We have a bunch of community-related events, working with developers, helping them understand how we play in the space. We're also doing a bunch of hands-on labs and design reviews that help customers basically build better, build faster, build smarter, to your point earlier on some of the marketing you're getting off of our website. But we're

also doing a number of announcements. I think, first off, it was actually this last week, we made the announcement of our integrations with Amazon CodeWhisperer. So their code generation tool for developers has now been fully trained on MongoDB so that you can take advantage of some of these code generation tools with MongoDB Atlas on AWS. Similarly, there's been a lot of noise around what Amazon is doing with Bedrock and the ability to automate certain tasks and things for developers. We are going to be announcing our integrations with agents for Amazon Bedrock

being supported inside of MongoDB Atlas. So we're excited to see that kind of move forward. And then ultimately, we're really there to celebrate our customers and connect them so that they can share what they're doing with many peers and others in the space to give them that inspiration that you so eloquently talked about, which is don't market your stuff. Let your customers tell what they're able to do with your stuff. And that'll set you up for success in the future. I'm looking forward to seeing what you announce in conjunction with what AWS announces and the interplay between those two. As always, I'm going to basically ignore 90% of what both

companies say and talk instead to customers. And what are you doing with it? Because that's the only way to get truth out of it. And frankly, I've been paying increasing amounts of attention to MongoDB over the past few years, just because of what people I trust who are actually good at databases have to say about you folks. Like my friends at RedMonk always like to say, I've stolen the line from them. You can buy my attention, but not my opinion. You've earned the opinion that you have at this point. Thank you for your sponsorship. It doesn't hurt, but again, you don't get to buy endorsements. I like what you're doing. Please keep going. No, I appreciate that, Corey.

You've always been supportive and definitely appreciate the opportunity to come on Screaming in the Cloud again. And I'll just push back to that Friends of Peter. There's also a little bit of ulterior motive there. It's not just who you know, but it's getting- It's also validating that you have friends. I get it. I get it.

Yeah, I know, right? And I don't have many, but I have a few. But the interesting thing there is we're going to be able to connect you with a number of It also validates that you have friends. I get it. I get it. Yeah, I know, right? And I don't have many, but I have a few. But the interesting thing there is we're going to be able to connect you with a number of the customers doing some of these cool things on top of MongoDB Atlas. I look forward to it. Thank you so much for your time. Peter Uhlender, Chief Marketing Officer at MongoDB. I'm cloud economist Corey Quinn, and this has been a Prom a promoted guest episode of Screaming in the Cloud brought to us

by our friends at Mongo. If you've enjoyed this podcast, please leave a five-star review on your podcast platform of choice. Whereas if you've hated this podcast, please leave a five-star review in your podcast platform of choice, along with an angry, insulting comment

that I will ignore because you basically wrapped it so tightly in generative AI messaging that I don't know what the hell your point is supposed to be. If your AWS bill keeps rising and your blood pressure is doing the same, then you need the Duck Bill Group. We help companies fix their AWS bill by making it smaller and less horrifying. The Duck Bill Group works for you, not AWS. We tailor recommendations to your business and we get to the point.

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