 Welcome back everyone. Live Cube Coverage here in San Francisco for Google Next 2020 because theCUBE's coverage, two and a half days, wall-to-wall team coverage. I'm John Furrier, host with Rob Strecce. We've got Dustin Kirkland, Lisa Martin, Rob Ho, Mark Alvis, the whole team on the ground here, getting all the stories. The story here is about innovation, Ian Massingham, CMO, Avon, Ivan, and Deep Dups Wejeward, Hanna. CTO of Supermetrics, partner of Ivan. Guys, thanks for coming on. Thank you, thanks for having us back, John. AI in your name is very valuable now. You know that, right? Yeah, I do. AI, Ivan. So that wasn't by design either, the shirt. No, it wasn't by design. Ivan was founded back in 2016. So you could say that we predate the AI wave or the AI hype depending on how we want to look at it. And our founders, as you know, were working at F-Secure on malware ingestion, large-scale data pipelines and processing. They stumbled on the idea that what they were doing there was somewhat replicable and relevant to other organizations. And they created Ivan to try and make it simple for organizations to use open source data infrastructure tech. I mean, you're teed up for whatever AI coming because the data aspect of it. Of course, yeah. I mean, model building, inference. It's very, very tightly linked to the data ecosystem. And that's precisely where Ivan operates. And we have many, many customers today that are using Ivan to drive AI workloads that are very, very close to what Ivan does. I believe they call you Dups too as well. It's your nickname. Yeah, absolutely. And yeah, like I told you, only my mother calls me, my real name, so. Well, you guys are a customer together up here. Talk about Supermetric. What do you guys do? It's a very fascinating product. And you're on Google Cloud, big bet with Google. Yeah, yeah. So, Supermetrics, what we help companies do is consolidate their data into where they need to do an analysis. And specifically, we focus on marketing data. So, Facebook ads, Google ads, LinkedIn. You bring it all into BigQuery, Google Sheets, Look at Studio, where some of the most popular there. And yes, we're a big customer of Ivan and has been instrumental in our transformation from being a single cloud application to a multi-homed, multi-cloud, wherever the person wants their data processed. Ian, you too also saw before we came on camera that you're also a customer of theirs. Yeah, we're a Supermetrics customer. So we use Supermetrics to ingest our own performance marketing data, figure out which of our digital ad campaigns are working. And actually, in the future, we're going to be using machine learning models to try and optimize our ad spend as well, using this same data set that Supermetrics helps us collect and aggregate. So, quite the compliment that these guys are working with you guys is they love data. You guys are into data. I mean, this is a good match. That's actually how we heard about Ivan, was that who is this customer Ivan? And then we were looking for a database provider and we're like, ah, let's actually check them out. Yeah, awesome. Yeah, so I mean, so you play in the CDP market, is that when you say your customer data platform visualization or are you really, you're providing out, you said you connect into Looker, is it more a semantic layer? No, we actually grab data. So you can, let's say, Looker Studio, for example, you can use one of our connectors to go into Facebook ads, get the data, do the visualizations there. And yeah, we process that data for you. I mean, the weird thing for people that might not be super familiar with digital ad technology is believe it or not, there are very few standards. All of the different providers provide the data in a different format and provide different functionality. So the choice for a customer like us is, do you want to do that yourself and maintain all of those different connectors to Facebook, Instagram, LinkedIn, Google ads? Or do you want to put a simple solution like Supermetrics in the middle to make that a standardized process so that you don't have to worry about maintaining all of this different custom connector infrastructure? Actually, there's one use case that's happening right now that is dear and near to a lot of marketers is that Google, as you know, retires certain things and builds new things. One of them is Universal Analytics, which is going away, and GA4 is there. But they are not one-to-one. That's right, yeah. Yep, so you can use Supermetrics, for example, because we have already done the hard work of trying to translate that. So if you've already got your reporting for Universal Analytics, you can use Supermetrics. Hey, Bob's your uncle. Sorry. How does Ivan help you? You mentioned the multi-cloud, or almost super cloud, as we would call it, but how do you be cross-cloud for that and knowing that you're still, you know, big Google, but how has that helped you? So Ivan's been instrumental for us to be able to move into GCP. We were a single cloud, and our central databases were running in that single cloud. What we needed to have was a like-for-like database that we could move in an instant, like within a second could be moved from one cloud to another cloud. And this is the infrastructure that Ivan provides us. A very simple to use, automatically set up configurations with power usage for the databases, ready to go. It's remarkable. We literally can move a database now from AWS to Google in three seconds. Well, nobody even notices. And it's incredible. Well, we've been talking about our super cloud discussion on theCUBE and also in studio around this notion of this data layer between multiple clouds. And this is the number one thing people are talking about is I want to have data span clouds because the apps are going to be on different clouds. Why can't I share the data? This comes down to be a really hard problem. And you guys are tackling this. Take us through the secret sauce. And what makes it all work? Well, we offer 11 different open source data infrastructure products as cloud managed services. So we have what we would consider to be the essential tool kit for developers that are building data centric applications and want to benefit from the innovation, speed and security benefits that come with open source. We have a control plane that we've built. We have an adapter layer that allows us to communicate with the different cloud providers APIs. And then we provide a mechanism for customers to both deploy control and scale the instances of this open source data infrastructure technology, either in a single hyperscaler across multiple or to do some of the advanced things that Doug's is talking about, like moving databases between providers or establishing data streaming infrastructure that spans multiple different hyperscalers. And yeah, you're right. The flexibility and power of migration is one big benefit here, but the other big area that customers get a lot of benefit from is the introduction of a simple abstraction layer that means that they only have to tool their developers once, regardless of which provider they're building their apps on, their experience in accessing this data infrastructure technology is consistent and familiar, and they can reuse those skills across the different providers. And we found many, many ISVs who clearly have a need to be in all of the different hyperscalers get a huge amount of value out of that consistency and simplification benefit that we offer. I smile internally, I'm kind of cheering because this is something we've been talking about on theCUBE for almost eight years, maybe 10 years around how the role of data, but before that DevOps was dominating infrastructure as code and then security shift left. So everything's kind of going through the develop, it feels like we're at a time now and all the AI discusses kind of point to this is that the developer pipeline and managing data is not IT, it's DevOps. And so all this is DevOps like feeling to it where when I say DevOps, I mean like things are built for the developer to perform better with the data. Yeah, and there's a huge amount happening in the ecosystem. I mean, Ivan's a great example of a company that's building tooling to simplify this, but if you look adjacent to us, you can find huge, huge advances have been made in things like data documentation, providing tooling that enables data engineers and developers to self serve, build applications in a way which is simpler and more robust and actually solve some problems that I think five or 10 years ago would have been really, really difficult to sort of get your hands around and solve for. Talk us through the use case of a customer that needs your solution. What's going through their mind? If they have a pain, is it like a frustration? Is it the developer? Who's engaging with you out of the game? What's the core person? I mean, there's many different pathways, I would say, for customers to discover Ivan and users, but I think there are three primary drivers that result in developers and organizations using our platform. The first is a very simple one, which is I want to use this open source technology because I feel like it's highly valuable, but I don't want to engage in the heavy lifting that's required to deploy an operator. It's complicated and actually it distracts from building your core product, right? From the things that are really unique and differentiated about your organization. So to steal an Andy Jassy phrase, it's like offload that undifferentiated heavy lifting to an expert provider. That's one big driver. The second is this idea of standardization where you get the same tooling, the same developer experience, regardless of which underlying platform you're using, and that fundamentally is about cost and risk reduction, right? I don't have to train teams in five different platforms, and once I've learned to do something well, I can repeat it across different providers with predictability, helps with security, helps with compliance. But the third is relatively new for us and that is something called bringing your own cloud. And this is a deployment construct that allows customers to put Ivan services inside their own hyperscaler account. So you can run Ivan inside your own GCP account, inside your own Google Cloud account. You can run it inside your other hyperscaler accounts. You can exploit your discounting frameworks, the committed cost structures that you have with the providers. And this is where Ivan can play a big role in cost reduction for organizations, just raw cost reduction. Like I want to drive down my aggregate cloud spend in the face of challenging economic conditions or other investment priorities. Basically you're checking the productivity box with developers. The ease of use gives you efficiency access on costs, savings, relative to operations. Yep, yep. And I can say that all of that is true. When we looked at what our customers wanted to do was to process their data, let's say in the United States. In the United States and GCP very specifically, that's where they want their data sovereignty to be. That requires a database to be there and that database needs to perform at exactly the same level as the database in GCP Europe as well as in CloudX. Like you just have to get that. You need that consistency as a developer. It's not just compliance. Yeah, yeah, it's definitely needed. Is there cases where people are just so not yet ready for this or is it more advanced environments have that as a multi-cloud? I think you have to look pretty hard around the world today to find an organization that's not using some of the open source technology that we support. I mean, there are a few companies out there that are essentially proprietary software shops but they're pretty few and far between in my opinion. So I think we've got really high applicability of the solution and of course to use Ivan you have to be using a hyperscaler because our platform is only deployed inside the three major clouds and a number of smaller cloud providers as well. So as long as you fit those criteria, I'd say most organizations that want to move forward and survive probably fit them. I would say that pretty much every customer, every organization has a use case for Ivan. Yeah, it would seem like to your point about the bring your own cloud and riding the cost curves and being able to have your EDPs and all those different pricing structures that they have out there makes a lot of sense. Does that complicate the manageability access to it or how you actually run the service for them? Not at all, not at all. So we use the same control plane and then in our adapter layer that I described to you that allows us to talk to different cloud providers instead of talking to our service account where our resources would live under the kind of default configuration option. We're talking with a set of credentials that are provided to us by a customer and they obviously scope those credentials accordingly with the right set of permissions that we need in order to control and deploy resources within the specific network segments that the customer determines. So it's a very high control environment for a customer and actually they have the keys. So they gave us the keys to operate. If they decide they don't want us to do anything anymore they can remove those keys. It's quite simple for them to do that. You guys are both growing really fast. Companies, congratulations. You guys just rebooted your startup program, 2.0. Yeah, we announced close to 2.0 on Monday this week. This is our own program to support early stage organizations with access to Ivan's services. We're offering between $12,000 and $100,000 of credits to startups at series A or series B stages. And we have some really, really fun organizations in the cohort, including surprisingly enough, an awful lot of companies that are doing GEN AI. Ha ha ha, great. How, talk about your guys success with the ecosystem partners. Obviously connecting things together. You're used to that. You're connecting up environments with APIs, with super metrics, your growth in the ecosystem, open source based. How has your journeys been? Take us through some of the highlights. Well, five years ago we were 10 people in Helsinki, Finland. And now we're 400 globally. So that's an exponential growth in and of itself, along with the customers that we've grown. And we've seen, we now process what 200 billion result rows of data coming out of our system. It's insane. And this is all being fed into databases that have to be now be used. Before it was boring ML, now it is exciting GEN AI. Tomorrow it will be. Which is really ML, we'd be purposed to be generative. Well, yes. Generate more AI. Well, as long as we don't go to degenerative AI, we're good. Well, there's some out there. There's some degenerate AI out there. I mean, the hallucination's been decided. It's a double-edged sword. AI is, you know, there's two sides of that coin. You know, there's a spectrum. So all exciting. And I would assume that also the five countries that have outlawed GA basically in Europe has that helped your business as well? I know you do integrations with Google Analytics, and I'm sure you can also augment that as well for those. We have 150 connectors, and we even have a program where you can actually build or you can work with us to build your own connector to your own data. So it's quite, for us, we're there. And also, Ivan has a lot of third-party integrations as well, it looks like. So for data teams that are really looking, maybe they have a data breaks or a snowflake and... Yeah, I mean, that's one of the most elegant aspects of the open-source ecosystem upon which we depend, right? You have a really, really broad cohort of developers that are contributing to that ecosystem. We ourselves have an open-source program office and focus extensively on contributing open-source code, open-source solutions that help our customers solve problems. Just this week, we announced a connector that allows you to connect Apache Flink for stream processing, stateful applications to Google BigQuery, and our entry into the Google BigQuery partner program comes as a result of that innovation. But yeah, there are many, many integrations between Ivan and other services, Datadog, AWS and GCP native services as well as third-party services, and of course the border open-source ecosystem as well. Data is, it has to come from somewhere, right? And it has to go somewhere, and that ability to connect and interchange data with different systems is obviously really, really important for our customers. And you guys got an award from Google, I hear? We did, we recognized this week as their breakthrough partner of the year for the Amir region. And it's no small part due to the work that we've been doing with customers like Supermetrics, Ovo Energy in the UK, Adeo. These are really large joint Google and Ivan customers that we've collaborated on to bring really, really significant success to those orgs. So we're obviously delighted to get that, but it's more about what we've managed to help customers achieve in the Amir region than it is about Ivan's own success, I think anyway. Well, congratulations to both of you guys. Great success. Love to see the growing business with the scale and cloud, and congratulations on the growth in both of you guys. Final words, closing thoughts on the partnership, Google Cloud, what's in front of you in the industry? What's your closing thoughts for this discussion? You know what, we're big supporters of open source and Google Cloud, and I genuinely feel like I get the transparency, and I'm so happy to see the progress. And no matter what I just said about AI, I know it's going to be big for us, and we definitely are there to give the data. We're there with it, I don't know. Ivan, we use, well, I don't know, six or seven different types of databases from Ivan. So for us, you've been absolutely wonderful for us to grow on, so thank you. Thank you, thank you. You should check out Supermetrics at supermetrics.com. And you should check out Ivan at Ivan.com. Check out silkenangle.com, that's where all the action is. It's the queue bringing you all the data. Super analytics, super metrics, super cloud is here, super applications, super chips. I even heard Jensen say super chips at one of his conferences. Thanks guys for coming on. Appreciate it. Thank you very much. Google Cloud coverage, day two of three days of coverage. I'm John Furrier, Rob Stretcher, for Lisa, Martin, Dustin, Kirkland. We'll be back with more live coverage after this short break.