(soft electronic music) >> Hey everyone, welcome to this CUBE conversation as part of the AWS Startup Showcase, season three, episode one, featuring Astronomer. I'm your host, Lisa Martin. I'm in the CUBE's Palo Alto Studios, and today excited to be joined by a couple of guests, a couple of co-founders from Astronomer. Viraj Parekh is with us, as is Paola Peraza-Calderon. Thanks guys so much for joining us. Excited to dig into Astronomer. >> Thank you so much for having us. >> Yeah, thanks for having us. >> Yeah, and we're going to be talking about the role of data orchestration. Paola, let's go ahead and start with you. Give the audience that understanding, that context about Astronomer and what it is that you guys do. >> Mm-hmm. Yeah, absolutely. So, Astronomer is a, you know, we're a technology and software company for modern data orchestration, as you said, and we're the driving force behind Apache Airflow. The Open Source Workflow Management tool that's since been adopted by thousands and thousands of users, and we'll dig into this a little bit more. But, by data orchestration, we mean data pipeline, so generally speaking, getting data from one place to another, transforming it, running it on a schedule, and overall just building a central system that tangibly connects your entire ecosystem of data services, right. So what, that's Redshift, Snowflake, DVT, et cetera. And so tangibly, we build, we at Astronomer here build products powered by Apache Airflow for data teams and for data practitioners, so that they don't have to. So, we sell to data engineers, data scientists, data admins, and we really spend our time doing three things. So, the first is that we build Astro, our flagship cloud service that we'll talk more on. But here, we're really building experiences that make it easier for data practitioners to author, run, and scale their data pipeline footprint on the cloud. And then, we also contribute to Apache Airflow as an open source project and community. So, we cultivate the community of humans, and we also put out open source developer tools that actually make it easier for individual data practitioners to be productive in their day-to-day jobs, whether or not they actually use our product and and pay us money or not. And then of course, we also have professional services and education and all of these things around our commercial products that enable folks to use our products and use Airflow as effectively as possible. So yeah, super, super happy with everything we've done and hopefully that gives you an idea of where we're starting. >> Awesome, so when you're talking with those, Paola, those data engineers, those data scientists, how do you define data orchestration and what does it mean to them? >> Yeah, yeah, it's a good question. So, you know, if you Google data orchestration you're going to get something about an automated process for organizing silo data and making it accessible for processing and analysis. But, to your question, what does that actually mean, you know? So, if you look at it from a customer's perspective, we can share a little bit about how we at Astronomer actually do data orchestration ourselves and the problems that it solves for us. So, as many other companies out in the world do, we at Astronomer need to monitor how our own customers use our products, right? And so, we have a weekly meeting, for example, that goes through a dashboard and a dashboarding tool called Sigma where we see the number of monthly customers and how they're engaging with our product. But, to actually do that, you know, we have to use data from our application database, for example, that has behavioral data on what they're actually doing in our product. We also have data from third party API tools, like Salesforce and HubSpot, and other ways in which our customer, we actually engage with our customers and their behavior. And so, our data team internally at Astronomer uses a bunch of tools to transform and use that data, right? So, we use FiveTran, for example, to ingest. We use Snowflake as our data warehouse. We use other tools for data transformations. And even, if we at Astronomer don't do this, you can imagine a data team also using tools like, Monte Carlo for data quality, or Hightouch for Reverse ETL, or things like that. And, I think the point here is that data teams, you know, that are building data-driven organizations have a plethora of tooling to both ingest the right data and come up with the right interfaces to transform and actually, interact with that data. And so, that movement and sort of synchronization of data across your ecosystem is exactly what data orchestration is responsible for. Historically, I think, and Raj will talk more about this, historically, schedulers like KRON and Oozie or Control-M have taken a role here, but we think that Apache Airflow has sort of risen over the past few years as the defacto industry standard for writing data pipelines that do tasks, that do data jobs that interact with that ecosystem of tools in your organization. And so, beyond that sort of data pipeline unit, I think where we see it is that data acquisition is not only writing those data pipelines that move your data, but it's also all the things around it, right, so, CI/CD tool and Secrets Management, et cetera. So, a long-winded answer here, but I think that's how we talk about it here at Astronomer and how we're building our products. >> Excellent. Great context, Paola. Thank you. Viraj, let's bring you into the conversation. Every company these days has to be a data company, right? They've got to be a software company- >> Mm-hmm. >> whether it's my bank or my grocery store. So, how are companies actually doing data orchestration today, Viraj? >> Yeah, it's a great question. So, I think one thing to think about is like, on one hand, you know, data orchestration is kind of a new category that we're helping define, but on the other hand, it's something that companies have been doing forever, right? You need to get data moving to use it, you know. You've got it all in place, aggregate it, cleaning it, et cetera. So, when you look at what companies out there are doing, right. Sometimes, if you're a more kind of born in the cloud company, as we say, you'll adopt all these cloud native tooling things your cloud provider gives you. If you're a bank or another sort of institution like that, you know, you're probably juggling an even wider variety of tools. You're thinking about a cloud migration. You might have things like Kron running in one place, Uzi running somewhere else, Informatics running somewhere else, while you're also trying to move all your workloads to the cloud. So, there's quite a large spectrum of what the current state is for companies. And then, kind of like Paola was saying, Apache Airflow started in 2014, and it was actually started by Airbnb, and they put out this blog post that was like, "Hey here's how we use Apache Airflow to orchestrate our data across all their sources." And really since then, right, it's almost been a decade since then, Airflow emerged as the open source standard, and there's companies of all sorts using it. And, it's really used to tie all these tools together, especially as that number of tools increases, companies move to hybrid cloud, hybrid multi-cloud strategies, and so on and so forth. But you know, what we found is that if you go to any company, especially a larger one and you say like, "Hey, how are you doing data orchestration?" They'll probably say something like, "Well, I have five data teams, so I have eight different ways I do data orchestration." Right. This idea of data orchestration's been there but the right way to do it, kind of all the abstractions you need, the way your teams need to work together, and so on and so forth, hasn't really emerged just yet, right? It's such a quick moving space that companies have to combine what they were doing before with what their new business initiatives are today. So, you know, what we really believe here at Astronomer is Airflow is the core of how you solve data orchestration for any sort of use case, but it's not everything. You know, it needs a little more. And, that's really where our commercial product, Astro comes in, where we've built, not only the most tried and tested airflow experience out there. We do employ a majority of the Airflow Core Committers, right? So, we're kind of really deep in the project. We've also built the right things around developer tooling, observability, and reliability for customers to really rely on Astro as the heart of the way they do data orchestration, and kind of think of it as the foundational layer that helps tie together all the different tools, practices and teams large companies have to do today. >> That foundational layer is absolutely critical. You've both mentioned open source software. Paola, I want to go back to you, and just give the audience an understanding of how open source really plays into Astronomer's mission as a company, and into the technologies like Astro. >> Mm-hmm. Yeah, absolutely. I mean, we, so we at Astronomers started using Airflow and actually building our products because Airflow is open source and we were our own customers at the beginning of our company journey. And, I think the open source community is at the core of everything we do. You know, without that open source community and culture, I think, you know, we have less of a business, and so, we're super invested in continuing to cultivate and grow that. And, I think there's a couple sort of concrete ways in which we do this that personally make me really excited to do my own job. You know, for one, we do things like we organize meetups and we sponsor the Airflow Summit and there's these sort of baseline community efforts that I think are really important and that reminds you, hey, there just humans trying to do their jobs and learn and use both our technology and things that are out there and contribute to it. So, making it easier to contribute to Airflow, for example, is another one of our efforts. As Viraj mentioned, we also employ, you know, engineers internally who are on our team whose full-time job is to make the open source project better. Again, regardless of whether or not you're a customer of ours or not, we want to make sure that we continue to cultivate the Airflow project in and of itself. And, we're also building developer tooling that might not be a part of the Apache Open Source project, but is still open source. So, we have repositories in our own sort of GitHub organization, for example, with tools that individual data practitioners, again customers are not, can use to make them be more productive in their day-to-day jobs with Airflow writing Dags for the most common use cases out there. The last thing I'll say is how important I think we've found it to build sort of educational resources and documentation and best practices. Airflow can be complex. It's been around for a long time. There's a lot of really, really rich feature sets. And so, how do we enable folks to actually use those? And that comes in, you know, things like webinars, and best practices, and courses and curriculum that are free and accessible and open to the community are just some of the ways in which I think we're continuing to invest in that open source community over the next year and beyond. >> That's awesome. It sounds like open source is really core, not only to the mission, but really to the heart of the organization. Viraj, I want to go back to you and really try to understand how does Astronomer fit into the wider modern data stack and ecosystem? Like what does that look like for customers? >> Yeah, yeah. So, both in the open source and with our commercial customers, right? Folks everywhere are trying to tie together a huge variety of tools in order to start making sense of their data. And you know, I kind of think of it almost like as like a pyramid, right? At the base level, you need things like data reliability, data, sorry, data freshness, data availability, and so on and so forth, right? You just need your data to be there. (coughs) I'm sorry. You just need your data to be there, and you need to make it predictable when it's going to be there. You need to make sure it's kind of correct at the highest level, some quality checks, and so on and so forth. And oftentimes, that kind of takes the case of ELT or ETL use cases, right? Taking data from somewhere and moving it somewhere else, usually into some sort of analytics destination. And, that's really what businesses can do to just power the core parts of getting insights into how their business is going, right? How much revenue did I had? What's in my pipeline, salesforce, and so on and so forth. Once that kind of base foundation is there and people can get the data they need, how they need it, it really opens up a lot for what customers can do. You know, I think one of the trendier things out there right now is MLOps, and how do companies actually put machine learning into production? Well, when you think about it you kind of have to squint at it, right? Like, machine learning pipelines are really just any other data pipeline. They just have a certain set of needs that might not not be applicable to ELT pipelines. And, when you kind of have a common layer to tie together all the ways data can move through your organization, that's really what we're trying to make it so companies can do. And, that happens in financial services where, you know, we have some customers who take app data coming from their mobile apps, and actually run it through their fraud detection services to make sure that all the activity is not fraudulent. We have customers that will run sports betting models on our platform where they'll take data from a bunch of public APIs around different sporting events that are happening, transform all of that in a way their data scientist can build models with it, and then actually bet on sports based on that output. You know, one of my favorite use cases I like to talk about that we saw in the open source is we had there was one company whose their business was to deliver blood transfusions via drone into remote parts of the world. And, it was really cool because they took all this data from all sorts of places, right? Kind of orchestrated all the aggregation and cleaning and analysis that happened had to happen via airflow and the end product would be a drone being shot out into a real remote part of the world to actually give somebody blood who needed it there. Because it turns out for certain parts of the world, the easiest way to deliver blood to them is via drone and not via some other, some other thing. So, these kind of, all the things people do with the modern data stack is absolutely incredible, right? Like you were saying, every company's trying to be a data-driven company. What really energizes me is knowing that like, for all those best, super great tools out there that power a business, we get to be the connective tissue, or the, almost like the electricity that kind of ropes them all together and makes so people can actually do what they need to do. >> Right. Phenomenal use cases that you just described, Raj. I mean, just the variety alone of what you guys are able to do and impact is so cool. So Paola, when you're with those data engineers, those data scientists, and customer conversations, what's your pitch? Why use Astro? >> Mm-hmm. Yeah, yeah, it's a good question. And honestly, to piggyback off of Viraj, there's so many. I think what keeps me so energized is how mission critical both our product and data orchestration is, and those use cases really are incredible and we work with customers of all shapes and sizes. But, to answer your question, right, so why use Astra? Why use our commercial products? There's so many people using open source, why pay for something more than that? So, you know, the baseline for our business really is that Airflow has grown exponentially over the last five years, and like we said has become an industry standard that we're confident there's a huge opportunity for us as a company and as a team. But, we also strongly believe that being great at running Airflow, you know, doesn't make you a successful company at what you do. What makes you a successful company at what you do is building great products and solving problems and solving pin points of your own customers, right? And, that differentiating value isn't being amazing at running Airflow. That should be our job. And so, we want to abstract those customers from meaning to do things like manage Kubernetes infrastructure that you need to run Airflow, and then hiring someone full-time to go do that. Which can be hard, but again doesn't add differentiating value to your team, or to your product, or to your customers. So, folks to get away from managing that infrastructure sort of a base, a base layer. Folks who are looking for differentiating features that make their team more productive and allows them to spend less time tweaking Airflow configurations and more time working with the data that they're getting from their business. For help, getting, staying up with Airflow releases. There's a ton of, we've actually been pretty quick to come out with new Airflow features and releases, and actually just keeping up with that feature set and working strategically with a partner to help you make the most out of those feature sets is a key part of it. And, really it's, especially if you're an organization who currently is committed to using Airflow, you likely have a lot of Airflow environments across your organization. And, being able to see those Airflow environments in a single place and being able to enable your data practitioners to create Airflow environments with a click of a button, and then use, for example, our command line to develop your Airflow Dags locally and push them up to our product, and use all of the sort of testing and monitoring and observability that we have on top of our product is such a key. It sounds so simple, especially if you use Airflow, but really those things are, you know, baseline value props that we have for the customers that continue to be excited to work with us. And of course, I think we can go beyond that and there's, we have ambitions to add whole, a whole bunch of features and expand into different types of personas. >> Right? >> But really our main value prop is for companies who are committed to Airflow and want to abstract themselves and make use of some of the differentiating features that we now have at Astronomer. >> Got it. Awesome. >> Thank you. One thing, one thing I'll add to that, Paola, and I think you did a good job of saying is because every company's trying to be a data company, companies are at different parts of their journey along that, right? And we want to meet customers where they are, and take them through it to where they want to go. So, on one end you have folks who are like, "Hey, we're just building a data team here. We have a new initiative. We heard about Airflow. How do you help us out?" On the farther end, you know, we have some customers that have been using Airflow for five plus years and they're like, "Hey, this is awesome. We have 10 more teams we want to bring on. How can you help with this? How can we do more stuff in the open source with you? How can we tell our story together?" And, it's all about kind of taking this vast community of data users everywhere, seeing where they're at, and saying like, "Hey, Astro and Airflow can take you to the next place that you want to go." >> Which is incredibly- >> Mm-hmm. >> and you bring up a great point, Viraj, that every company is somewhere in a different place on that journey. And it's, and it's complex. But it sounds to me like a lot of what you're doing is really stripping away a lot of the complexity, really enabling folks to use their data as quickly as possible, so that it's relevant and they can serve up, you know, the right products and services to whoever wants what. Really incredibly important. We're almost out of time, but I'd love to get both of your perspectives on what's next for Astronomer. You give us a a great overview of what the company's doing, the value in it for customers. Paola, from your lens as one of the co-founders, what's next? >> Yeah, I mean, I think we'll continue to, I think cultivate in that open source community. I think we'll continue to build products that are open sourced as part of our ecosystem. I also think that we'll continue to build products that actually make Airflow, and getting started with Airflow, more accessible. So, sort of lowering that barrier to entry to our products, whether that's price wise or infrastructure requirement wise. I think making it easier for folks to get started and get their hands on our product is super important for us this year. And really it's about, I think, you know, for us, it's really about focused execution this year and all of the sort of core principles that we've been talking about. And continuing to invest in all of the things around our product that again, enable teams to use Airflow more effectively and efficiently. >> And that efficiency piece is, everybody needs that. Last question, Viraj, for you. What do you see in terms of the next year for Astronomer and for your role? >> Yeah, you know, I think Paola did a really good job of laying it out. So it's, it's really hard to disagree with her on anything, right? I think executing is definitely the most important thing. My own personal bias on that is I think more than ever it's important to really galvanize the community around airflow. So, we're going to be focusing on that a lot. We want to make it easier for our users to get get our product into their hands, be that open source users or commercial users. And last, but certainly not least, is we're also really excited about Data Lineage and this other open source project in our umbrella called Open Lineage to make it so that there's a standard way for users to get lineage out of different systems that they use. When we think about what's in store for data lineage and needing to audit the way automated decisions are being made. You know, I think that's just such an important thing that companies are really just starting with, and I don't think there's a solution that's emerged that kind of ties it all together. So, we think that as we kind of grow the role of Airflow, right, we can also make it so that we're helping solve, we're helping customers solve their lineage problems all in Astro, which is our kind of the best of both worlds for us. >> Awesome. I can definitely feel and hear the enthusiasm and the passion that you both bring to Astronomer, to your customers, to your team. I love it. We could keep talking more and more, so you're going to have to come back. (laughing) Viraj, Paola, thank you so much for joining me today on this showcase conversation. We really appreciate your insights and all the context that you provided about Astronomer. >> Thank you so much for having us. >> My pleasure. For my guests, I'm Lisa Martin. You're watching this Cube conversation. (soft electronic music)

(upbeat electronic music) >> Hello everyone, welcome to this CUBE conversation here from the studios in the CUBE in Palo Alto, California. I'm John Furrier, your host. We're featuring a startup, Astronomer. Astronomer.io is the URL, check it out. And we're going to have a great conversation around one of the most important topics hitting the industry, and that is the future of machine learning and AI, and the data that powers it underneath it. There's a lot of things that need to get done, and we're excited to have some of the co-founders of Astronomer here. Viraj Parekh, who is co-founder of Astronomer, and Paola Peraza Calderon, another co-founder, both with Astronomer. Thanks for coming on. First of all, how many co-founders do you guys have? >> You know, I think the answer's around six or seven. I forget the exact, but there's really been a lot of people around the table who've worked very hard to get this company to the point that it's at. We have long ways to go, right? But there's been a lot of people involved that have been absolutely necessary for the path we've been on so far. >> Thanks for that, Viraj, appreciate that. The first question I want to get out on the table, and then we'll get into some of the details, is take a minute to explain what you guys are doing. How did you guys get here? Obviously, multiple co-founders, sounds like a great project. The timing couldn't have been better. ChatGPT has essentially done so much public relations for the AI industry to kind of highlight this shift that's happening. It's real, we've been chronicalizing, take a minute to explain what you guys do. >> Yeah, sure, we can get started. So, yeah, when Viraj and I joined Astronomer in 2017, we really wanted to build a business around data, and we were using an open source project called Apache Airflow that we were just using sort of as customers ourselves. And over time, we realized that there was actually a market for companies who use Apache Airflow, which is a data pipeline management tool, which we'll get into, and that running Airflow is actually quite challenging, and that there's a big opportunity for us to create a set of commercial products and an opportunity to grow that open source community and actually build a company around that. So the crux of what we do is help companies run data pipelines with Apache Airflow. And certainly we've grown in our ambitions beyond that, but that's sort of the crux of what we do for folks. >> You know, data orchestration, data management has always been a big item in the old classic data infrastructure. But with AI, you're seeing a lot more emphasis on scale, tuning, training. Data orchestration is the center of the value proposition, when you're looking at coordinating resources, it's one of the most important things. Can you guys explain what data orchestration entails? What does it mean? Take us through the definition of what data orchestration entails. >> Yeah, for sure. I can take this one, and Viraj, feel free to jump in. So if you google data orchestration, here's what you're going to get. You're going to get something that says, "Data orchestration is the automated process" "for organizing silo data from numerous" "data storage points, standardizing it," "and making it accessible and prepared for data analysis." And you say, "Okay, but what does that actually mean," right, and so let's give sort of an an example. So let's say you're a business and you have sort of the following basic asks of your data team, right? Okay, give me a dashboard in Sigma, for example, for the number of customers or monthly active users, and then make sure that that gets updated on an hourly basis. And then number two, a consistent list of active customers that I have in HubSpot so that I can send them a monthly product newsletter, right? Two very basic asks for all sorts of companies and organizations. And when that data team, which has data engineers, data scientists, ML engineers, data analysts get that request, they're looking at an ecosystem of data sources that can help them get there, right? And that includes application databases, for example, that actually have in product user behavior and third party APIs from tools that the company uses that also has different attributes and qualities of those customers or users. And that data team needs to use tools like Fivetran to ingest data, a data warehouse, like Snowflake or Databricks to actually store that data and do analysis on top of it, a tool like DBT to do transformations and make sure that data is standardized in the way that it needs to be, a tool like Hightouch for reverse ETL. I mean, we could go on and on. There's so many partners of ours in this industry that are doing really, really exciting and critical things for those data movements. And the whole point here is that data teams have this plethora of tooling that they use to both ingest the right data and come up with the right interfaces to transform and interact with that data. And data orchestration, in our view, is really the heartbeat of all of those processes, right? And tangibly the unit of data orchestration is a data pipeline, a set of tasks or jobs that each do something with data over time and eventually run that on a schedule to make sure that those things are happening continuously as time moves on and the company advances. And so, for us, we're building a business around Apache Airflow, which is a workflow management tool that allows you to author, run, and monitor data pipelines. And so when we talk about data orchestration, we talk about sort of two things. One is that crux of data pipelines that, like I said, connect that large ecosystem of data tooling in your company. But number two, it's not just that data pipeline that needs to run every day, right? And Viraj will probably touch on this as we talk more about Astronomer and our value prop on top of Airflow. But then it's all the things that you need to actually run data and production and make sure that it's trustworthy, right? So it's actually not just that you're running things on a schedule, but it's also things like CICD tooling, secure secrets management, user permissions, monitoring, data lineage, documentation, things that enable other personas in your data team to actually use those tools. So long-winded way of saying that it's the heartbeat, we think, of of the data ecosystem, and certainly goes beyond scheduling, but again, data pipelines are really at the center of it. >> One of the things that jumped out, Viraj, if you can get into this, I'd like to hear more about how you guys look at all those little tools that are out. You mentioned a variety of things. You look at the data infrastructure, it's not just one stack. You've got an analytic stack, you've got a realtime stack, you've got a data lake stack, you got an AI stack potentially. I mean you have these stacks now emerging in the data world that are fundamental, that were once served by either a full package, old school software, and then a bunch of point solution. You mentioned Fivetran there, I would say in the analytics stack. Then you got S3, they're on the data lake stack. So all these things are kind of munged together. >> Yeah. >> How do you guys fit into that world? You make it easier, or like, what's the deal? >> Great question, right? And you know, I think that one of the biggest things we've found in working with customers over the last however many years is that if a data team is using a bunch of tools to get what they need done, and the number of tools they're using is growing exponentially and they're kind of roping things together here and there, that's actually a sign of a productive team, not a bad thing, right? It's because that team is moving fast. They have needs that are very specific to them, and they're trying to make something that's exactly tailored to their business. So a lot of times what we find is that customers have some sort of base layer, right? That's kind of like, it might be they're running most of the things in AWS, right? And then on top of that, they'll be using some of the things AWS offers, things like SageMaker, Redshift, whatever, but they also might need things that their cloud can't provide. Something like Fivetran, or Hightouch, those are other tools. And where data orchestration really shines, and something that we've had the pleasure of helping our customers build, is how do you take all those requirements, all those different tools and whip them together into something that fulfills a business need? So that somebody can read a dashboard and trust the number that it says, or somebody can make sure that the right emails go out to their customers. And Airflow serves as this amazing kind of glue between that data stack, right? It's to make it so that for any use case, be it ELT pipelines, or machine learning, or whatever, you need different things to do them, and Airflow helps tie them together in a way that's really specific for a individual business' needs. >> Take a step back and share the journey of what you guys went through as a company startup. So you mentioned Apache, open source. I was just having an interview with a VC, we were talking about foundational models. You got a lot of proprietary and open source development going on. It's almost the iPhone/Android moment in this whole generative space and foundational side. This is kind of important, the open source piece of it. Can you share how you guys started? And I can imagine your customers probably have their hair on fire and are probably building stuff on their own. Are you guys helping them? Take us through, 'cause you guys are on the front end of a big, big wave, and that is to make sense of the chaos, rain it in. Take us through your journey and why this is important. >> Yeah, Paola, I can take a crack at this, then I'll kind of hand it over to you to fill in whatever I miss in details. But you know, like Paola is saying, the heart of our company is open source, because we started using Airflow as an end user and started to say like, "Hey wait a second," "more and more people need this." Airflow, for background, started at Airbnb, and they were actually using that as a foundation for their whole data stack. Kind of how they made it so that they could give you recommendations, and predictions, and all of the processes that needed orchestrated. Airbnb created Airflow, gave it away to the public, and then fast forward a couple years and we're building a company around it, and we're really excited about that. >> That's a beautiful thing. That's exactly why open source is so great. >> Yeah, yeah. And for us, it's really been about watching the community and our customers take these problems, find a solution to those problems, standardize those solutions, and then building on top of that, right? So we're reaching to a point where a lot of our earlier customers who started to just using Airflow to get the base of their BI stack down and their reporting in their ELP infrastructure, they've solved that problem and now they're moving on to things like doing machine learning with their data, because now that they've built that foundation, all the connective tissue for their data arriving on time and being orchestrated correctly is happening, they can build a layer on top of that. And it's just been really, really exciting kind of watching what customers do once they're empowered to pick all the tools that they need, tie them together in the way they need to, and really deliver real value to their business. >> Can you share some of the use cases of these customers? Because I think that's where you're starting to see the innovation. What are some of the companies that you're working with, what are they doing? >> Viraj, I'll let you take that one too. (group laughs) >> So you know, a lot of it is... It goes across the gamut, right? Because it doesn't matter what you are, what you're doing with data, it needs to be orchestrated. So there's a lot of customers using us for their ETL and ELT reporting, right? Just getting data from other disparate sources into one place and then building on top of that. Be it building dashboards, answering questions for the business, building other data products and so on and so forth. From there, these use cases evolve a lot. You do see folks doing things like fraud detection, because Airflow's orchestrating how transactions go, transactions get analyzed. They do things like analyzing marketing spend to see where your highest ROI is. And then you kind of can't not talk about all of the machine learning that goes on, right? Where customers are taking data about their own customers, kind of analyze and aggregating that at scale, and trying to automate decision making processes. So it goes from your most basic, what we call data plumbing, right? Just to make sure data's moving as needed, all the ways to your more exciting expansive use cases around automated decision making and machine learning. >> And I'd say, I mean, I'd say that's one of the things that I think gets me most excited about our future, is how critical Airflow is to all of those processes, and I think when you know a tool is valuable is when something goes wrong and one of those critical processes doesn't work. And we know that our system is so mission critical to answering basic questions about your business and the growth of your company for so many organizations that we work with. So it's, I think, one of the things that gets Viraj and I and the rest of our company up every single morning is knowing how important the work that we do for all of those use cases across industries, across company sizes, and it's really quite energizing. >> It was such a big focus this year at AWS re:Invent, the role of data. And I think one of the things that's exciting about the open AI and all the movement towards large language models is that you can integrate data into these models from outside. So you're starting to see the integration easier to deal with. Still a lot of plumbing issues. So a lot of things happening. So I have to ask you guys, what is the state of the data orchestration area? Is it ready for disruption? Has it already been disrupted? Would you categorize it as a new first inning kind of opportunity, or what's the state of the data orchestration area right now? Both technically and from a business model standpoint. How would you guys describe that state of the market? >> Yeah, I mean, I think in a lot of ways, in some ways I think we're category creating. Schedulers have been around for a long time. I released a data presentation sort of on the evolution of going from something like Kron, which I think was built in like the 1970s out of Carnegie Mellon. And that's a long time ago, that's 50 years ago. So sort of like the basic need to schedule and do something with your data on a schedule is not a new concept. But to our point earlier, I think everything that you need around your ecosystem, first of all, the number of data tools and developer tooling that has come out industry has 5X'd over the last 10 years. And so obviously as that ecosystem grows, and grows, and grows, and grows, the need for orchestration only increases. And I think, as Astronomer, I think we... And we work with so many different types of companies, companies that have been around for 50 years, and companies that got started not even 12 months ago. And so I think for us it's trying to, in a ways, category create and adjust sort of what we sell and the value that we can provide for companies all across that journey. There are folks who are just getting started with orchestration, and then there's folks who have such advanced use case, 'cause they're hitting sort of a ceiling and only want to go up from there. And so I think we, as a company, care about both ends of that spectrum, and certainly want to build and continue building products for companies of all sorts, regardless of where they are on the maturity curve of data orchestration. >> That's a really good point, Paola. And I think the other thing to really take into account is it's the companies themselves, but also individuals who have to do their jobs. If you rewind the clock like 5 or 10 years ago, data engineers would be the ones responsible for orchestrating data through their org. But when we look at our customers today, it's not just data engineers anymore. There's data analysts who sit a lot closer to the business, and the data scientists who want to automate things around their models. So this idea that orchestration is this new category is right on the money. And what we're finding is the need for it is spreading to all parts of the data team, naturally where Airflow's emerged as an open source standard and we're hoping to take things to the next level. >> That's awesome. We've been up saying that the data market's kind of like the SRE with servers, right? You're going to need one person to deal with a lot of data, and that's data engineering, and then you're got to have the practitioners, the democratization. Clearly that's coming in what you're seeing. So I have to ask, how do you guys fit in from a value proposition standpoint? What's the pitch that you have to customers, or is it more inbound coming into you guys? Are you guys doing a lot of outreach, customer engagements? I'm sure they're getting a lot of great requirements from customers. What's the current value proposition? How do you guys engage? >> Yeah, I mean, there's so many... Sorry, Viraj, you can jump in. So there's so many companies using Airflow, right? So the baseline is that the open source project that is Airflow that came out of Airbnb, over five years ago at this point, has grown exponentially in users and continues to grow. And so the folks that we sell to primarily are folks who are already committed to using Apache Airflow, need data orchestration in their organization, and just want to do it better, want to do it more efficiently, want to do it without managing that infrastructure. And so our baseline proposition is for those organizations. Now to Viraj's point, obviously I think our ambitions go beyond that, both in terms of the personas that we addressed and going beyond that data engineer, but really it's to start at the baseline, as we continue to grow our our company, it's really making sure that we're adding value to folks using Airflow and help them do so in a better way, in a larger way, in a more efficient way, and that's really the crux of who we sell to. And so to answer your question on, we get a lot of inbound because they're... >> You have a built in audience. (laughs) >> The world that use it. Those are the folks who we talk to and come to our website and chat with us and get value from our content. I mean, the power of the opensource community is really just so, so big, and I think that's also one of the things that makes this job fun. >> And you guys are in a great position. Viraj, you can comment a little, get your reaction. There's been a big successful business model to starting a company around these big projects for a lot of reasons. One is open source is continuing to be great, but there's also supply chain challenges in there. There's also we want to continue more innovation and more code and keeping it free and and flowing. And then there's the commercialization of productizing it, operationalizing it. This is a huge new dynamic, I mean, in the past 5 or so years, 10 years, it's been happening all on CNCF from other areas like Apache, Linux Foundation, they're all implementing this. This is a huge opportunity for entrepreneurs to do this. >> Yeah, yeah. Open source is always going to be core to what we do, because we wouldn't exist without the open source community around us. They are huge in numbers. Oftentimes they're nameless people who are working on making something better in a way that everybody benefits from it. But open source is really hard, especially if you're a company whose core competency is running a business, right? Maybe you're running an e-commerce business, or maybe you're running, I don't know, some sort of like, any sort of business, especially if you're a company running a business, you don't really want to spend your time figuring out how to run open source software. You just want to use it, you want to use the best of it, you want to use the community around it, you want to be able to google something and get answers for it, you want the benefits of open source. You don't have the time or the resources to invest in becoming an expert in open source, right? And I think that dynamic is really what's given companies like us an ability to kind of form businesses around that in the sense that we'll make it so people get the best of both worlds. You'll get this vast open ecosystem that you can build on top of, that you can benefit from, that you can learn from. But you won't have to spend your time doing undifferentiated heavy lifting. You can do things that are just specific to your business. >> It's always been great to see that business model evolve. We used a debate 10 years ago, can there be another Red Hat? And we said, not really the same, but there'll be a lot of little ones that'll grow up to be big soon. Great stuff. Final question, can you guys share the history of the company? The milestones of Astromer's journey in data orchestration? >> Yeah, we could. So yeah, I mean, I think, so Viraj and I have obviously been at Astronomer along with our other founding team and leadership folks for over five years now. And it's been such an incredible journey of learning, of hiring really amazing people, solving, again, mission critical problems for so many types of organizations. We've had some funding that has allowed us to invest in the team that we have and in the software that we have, and that's been really phenomenal. And so that investment, I think, keeps us confident, even despite these sort of macroeconomic conditions that we're finding ourselves in. And so honestly, the milestones for us are focusing on our product, focusing on our customers over the next year, focusing on that market for us that we know can get valuable out of what we do, and making developers' lives better, and growing the open source community and making sure that everything that we're doing makes it easier for folks to get started, to contribute to the project and to feel a part of the community that we're cultivating here. >> You guys raised a little bit of money. How much have you guys raised? >> Don't know what the total is, but it's in the ballpark over $200 million. It feels good to... >> A little bit of capital. Got a little bit of cap to work with there. Great success. I know as a Series C Financing, you guys have been down. So you're up and running, what's next? What are you guys looking to do? What's the big horizon look like for you from a vision standpoint, more hiring, more product, what is some of the key things you're looking at doing? >> Yeah, it's really a little of all of the above, right? Kind of one of the best and worst things about working at earlier stage startups is there's always so much to do and you often have to just kind of figure out a way to get everything done. But really investing our product over the next, at least over the course of our company lifetime. And there's a lot of ways we want to make it more accessible to users, easier to get started with, easier to use, kind of on all areas there. And really, we really want to do more for the community, right, like I was saying, we wouldn't be anything without the large open source community around us. And we want to figure out ways to give back more in more creative ways, in more code driven ways, in more kind of events and everything else that we can keep those folks galvanized and just keep them happy using Airflow. >> Paola, any final words as we close out? >> No, I mean, I'm super excited. I think we'll keep growing the team this year. We've got a couple of offices in the the US, which we're excited about, and a fully global team that will only continue to grow. So Viraj and I are both here in New York, and we're excited to be engaging with our coworkers in person finally, after years of not doing so. We've got a bustling office in San Francisco as well. So growing those teams and continuing to hire all over the world, and really focusing on our product and the open source community is where our heads are at this year. So, excited. >> Congratulations. 200 million in funding, plus. Good runway, put that money in the bank, squirrel it away. It's a good time to kind of get some good interest on it, but still grow. Congratulations on all the work you guys do. We appreciate you and the open source community does, and good luck with the venture, continue to be successful, and we'll see you at the Startup Showcase. >> Thank you. >> Yeah, thanks so much, John. Appreciate it. >> Okay, that's the CUBE Conversation featuring astronomer.io, that's the website. Astronomer is doing well. Multiple rounds of funding, over 200 million in funding. Open source continues to lead the way in innovation. Great business model, good solution for the next gen cloud scale data operations, data stacks that are emerging. I'm John Furrier, your host, thanks for watching. (soft upbeat music)

(soft music) >> Hello everyone, welcome to this Cube conversation here from the studios of theCube in Palo Alto, California. John Furrier, your host. We're featuring a startup, Astronomer, astronomer.io is the url. Check it out. And we're going to have a great conversation around one of the most important topics hitting the industry, and that is the future of machine learning and AI and the data that powers it underneath it. There's a lot of things that need to get done, and we're excited to have some of the co-founders of Astronomer here. Viraj Parekh, who is co-founder and Paola Peraza Calderon, another co-founder, both with Astronomer. Thanks for coming on. First of all, how many co-founders do you guys have? >> You know, I think the answer's around six or seven. I forget the exact, but there's really been a lot of people around the table, who've worked very hard to get this company to the point that it's at. And we have long ways to go, right? But there's been a lot of people involved that are, have been absolutely necessary for the path we've been on so far. >> Thanks for that, Viraj, appreciate that. The first question I want to get out on the table, and then we'll get into some of the details, is take a minute to explain what you guys are doing. How did you guys get here? Obviously, multiple co-founders sounds like a great project. The timing couldn't have been better. ChatGPT has essentially done so much public relations for the AI industry. Kind of highlight this shift that's happening. It's real. We've been chronologicalizing, take a minute to explain what you guys do. >> Yeah, sure. We can get started. So yeah, when Astronomer, when Viraj and I joined Astronomer in 2017, we really wanted to build a business around data and we were using an open source project called Apache Airflow, that we were just using sort of as customers ourselves. And over time, we realized that there was actually a market for companies who use Apache Airflow, which is a data pipeline management tool, which we'll get into. And that running Airflow is actually quite challenging and that there's a lot of, a big opportunity for us to create a set of commercial products and opportunity to grow that open source community and actually build a company around that. So the crux of what we do is help companies run data pipelines with Apache Airflow. And certainly we've grown in our ambitions beyond that, but that's sort of the crux of what we do for folks. >> You know, data orchestration, data management has always been a big item, you know, in the old classic data infrastructure. But with AI you're seeing a lot more emphasis on scale, tuning, training. You know, data orchestration is the center of the value proposition when you're looking at coordinating resources, it's one of the most important things. Could you guys explain what data orchestration entails? What does it mean? Take us through the definition of what data orchestration entails. >> Yeah, for sure. I can take this one and Viraj feel free to jump in. So if you google data orchestration, you know, here's what you're going to get. You're going to get something that says, data orchestration is the automated process for organizing silo data from numerous data storage points to organizing it and making it accessible and prepared for data analysis. And you say, okay, but what does that actually mean, right? And so let's give sort of an example. So let's say you're a business and you have sort of the following basic asks of your data team, right? Hey, give me a dashboard in Sigma, for example, for the number of customers or monthly active users and then make sure that that gets updated on an hourly basis. And then number two, a consistent list of active customers that I have in HubSpot so that I can send them a monthly product newsletter, right? Two very basic asks for all sorts of companies and organizations. And when that data team, which has data engineers, data scientists, ML engineers, data analysts get that request, they're looking at an ecosystem of data sources that can help them get there, right? And that includes application databases, for example, that actually have end product user behavior and third party APIs from tools that the company uses that also has different attributes and qualities of those customers or users. And that data team needs to use tools like Fivetran, to ingest data, a data warehouse like Snowflake or Databricks to actually store that data and do analysis on top of it, a tool like DBT to do transformations and make sure that that data is standardized in the way that it needs to be, a tool like Hightouch for reverse ETL. I mean, we could go on and on. There's so many partners of ours in this industry that are doing really, really exciting and critical things for those data movements. And the whole point here is that, you know, data teams have this plethora of tooling that they use to both ingest the right data and come up with the right interfaces to transform and interact with that data. And data orchestration in our view is really the heartbeat of all of those processes, right? And tangibly the unit of data orchestration, you know, is a data pipeline, a set of tasks or jobs that each do something with data over time and eventually run that on a schedule to make sure that those things are happening continuously as time moves on. And, you know, the company advances. And so, you know, for us, we're building a business around Apache Airflow, which is a workflow management tool that allows you to author, run and monitor data pipelines. And so when we talk about data orchestration, we talk about sort of two things. One is that crux of data pipelines that, like I said, connect that large ecosystem of data tooling in your company. But number two, it's not just that data pipeline that needs to run every day, right? And Viraj will probably touch on this as we talk more about Astronomer and our value prop on top of Airflow. But then it's all the things that you need to actually run data and production and make sure that it's trustworthy, right? So it's actually not just that you're running things on a schedule, but it's also things like CI/CD tooling, right? Secure secrets management, user permissions, monitoring, data lineage, documentation, things that enable other personas in your data team to actually use those tools. So long-winded way of saying that, it's the heartbeat that we think of the data ecosystem and certainly goes beyond scheduling, but again, data pipelines are really at the center of it. >> You know, one of the things that jumped out Viraj, if you can get into this, I'd like to hear more about how you guys look at all those little tools that are out there. You mentioned a variety of things. You know, if you look at the data infrastructure, it's not just one stack. You've got an analytic stack, you've got a realtime stack, you've got a data lake stack, you got an AI stack potentially. I mean you have these stacks now emerging in the data world that are >> Yeah. - >> fundamental, but we're once served by either a full package, old school software, and then a bunch of point solution. You mentioned Fivetran there, I would say in the analytics stack. Then you got, you know, S3, they're on the data lake stack. So all these things are kind of munged together. >> Yeah. >> How do you guys fit into that world? You make it easier or like, what's the deal? >> Great question, right? And you know, I think that one of the biggest things we've found in working with customers over, you know, the last however many years, is that like if a data team is using a bunch of tools to get what they need done and the number of tools they're using is growing exponentially and they're kind of roping things together here and there, that's actually a sign of a productive team, not a bad thing, right? It's because that team is moving fast. They have needs that are very specific to them and they're trying to make something that's exactly tailored to their business. So a lot of times what we find is that customers have like some sort of base layer, right? That's kind of like, you know, it might be they're running most of the things in AWS, right? And then on top of that, they'll be using some of the things AWS offers, you know, things like SageMaker, Redshift, whatever. But they also might need things that their Cloud can't provide, you know, something like Fivetran or Hightouch or anything of those other tools and where data orchestration really shines, right? And something that we've had the pleasure of helping our customers build, is how do you take all those requirements, all those different tools and whip them together into something that fulfills a business need, right? Something that makes it so that somebody can read a dashboard and trust the number that it says or somebody can make sure that the right emails go out to their customers. And Airflow serves as this amazing kind of glue between that data stack, right? It's to make it so that for any use case, be it ELT pipelines or machine learning or whatever, you need different things to do them and Airflow helps tie them together in a way that's really specific for a individual business's needs. >> Take a step back and share the journey of what your guys went through as a company startup. So you mentioned Apache open source, you know, we were just, I was just having an interview with the VC, we were talking about foundational models. You got a lot of proprietary and open source development going on. It's almost the iPhone, Android moment in this whole generative space and foundational side. This is kind of important, the open source piece of it. Can you share how you guys started? And I can imagine your customers probably have their hair on fire and are probably building stuff on their own. How do you guys, are you guys helping them? Take us through, 'cuz you guys are on the front end of a big, big wave and that is to make sense of the chaos, reigning it in. Take us through your journey and why this is important. >> Yeah Paola, I can take a crack at this and then I'll kind of hand it over to you to fill in whatever I miss in details. But you know, like Paola is saying, the heart of our company is open source because we started using Airflow as an end user and started to say like, "Hey wait a second". Like more and more people need this. Airflow, for background, started at Airbnb and they were actually using that as the foundation for their whole data stack. Kind of how they made it so that they could give you recommendations and predictions and all of the processes that need to be or needed to be orchestrated. Airbnb created Airflow, gave it away to the public and then, you know, fast forward a couple years and you know, we're building a company around it and we're really excited about that. >> That's a beautiful thing. That's exactly why open source is so great. >> Yeah, yeah. And for us it's really been about like watching the community and our customers take these problems, find solution to those problems, build standardized solutions, and then building on top of that, right? So we're reaching to a point where a lot of our earlier customers who started to just using Airflow to get the base of their BI stack down and their reporting and their ELP infrastructure, you know, they've solved that problem and now they're moving onto things like doing machine learning with their data, right? Because now that they've built that foundation, all the connective tissue for their data arriving on time and being orchestrated correctly is happening, they can build the layer on top of that. And it's just been really, really exciting kind of watching what customers do once they're empowered to pick all the tools that they need, tie them together in the way they need to, and really deliver real value to their business. >> Can you share some of the use cases of these customers? Because I think that's where you're starting to see the innovation. What are some of the companies that you're working with, what are they doing? >> Raj, I'll let you take that one too. (all laughing) >> Yeah. (all laughing) So you know, a lot of it is, it goes across the gamut, right? Because all doesn't matter what you are, what you're doing with data, it needs to be orchestrated. So there's a lot of customers using us for their ETL and ELT reporting, right? Just getting data from all the disparate sources into one place and then building on top of that, be it building dashboards, answering questions for the business, building other data products and so on and so forth. From there, these use cases evolve a lot. You do see folks doing things like fraud detection because Airflow's orchestrating how transactions go. Transactions get analyzed, they do things like analyzing marketing spend to see where your highest ROI is. And then, you know, you kind of can't not talk about all of the machine learning that goes on, right? Where customers are taking data about their own customers kind of analyze and aggregating that at scale and trying to automate decision making processes. So it goes from your most basic, what we call like data plumbing, right? Just to make sure data's moving as needed. All the ways to your more exciting and sexy use cases around like automated decision making and machine learning. >> And I'd say, I mean, I'd say that's one of the things that I think gets me most excited about our future is how critical Airflow is to all of those processes, you know? And I think when, you know, you know a tool is valuable is when something goes wrong and one of those critical processes doesn't work. And we know that our system is so mission critical to answering basic, you know, questions about your business and the growth of your company for so many organizations that we work with. So it's, I think one of the things that gets Viraj and I, and the rest of our company up every single morning, is knowing how important the work that we do for all of those use cases across industries, across company sizes. And it's really quite energizing. >> It was such a big focus this year at AWS re:Invent, the role of data. And I think one of the things that's exciting about the open AI and all the movement towards large language models, is that you can integrate data into these models, right? From outside, right? So you're starting to see the integration easier to deal with, still a lot of plumbing issues. So a lot of things happening. So I have to ask you guys, what is the state of the data orchestration area? Is it ready for disruption? Is it already been disrupted? Would you categorize it as a new first inning kind of opportunity or what's the state of the data orchestration area right now? Both, you know, technically and from a business model standpoint, how would you guys describe that state of the market? >> Yeah, I mean I think, I think in a lot of ways we're, in some ways I think we're categoric rating, you know, schedulers have been around for a long time. I recently did a presentation sort of on the evolution of going from, you know, something like KRON, which I think was built in like the 1970s out of Carnegie Mellon. And you know, that's a long time ago. That's 50 years ago. So it's sort of like the basic need to schedule and do something with your data on a schedule is not a new concept. But to our point earlier, I think everything that you need around your ecosystem, first of all, the number of data tools and developer tooling that has come out the industry has, you know, has some 5X over the last 10 years. And so obviously as that ecosystem grows and grows and grows and grows, the need for orchestration only increases. And I think, you know, as Astronomer, I think we, and there's, we work with so many different types of companies, companies that have been around for 50 years and companies that got started, you know, not even 12 months ago. And so I think for us, it's trying to always category create and adjust sort of what we sell and the value that we can provide for companies all across that journey. There are folks who are just getting started with orchestration and then there's folks who have such advanced use case 'cuz they're hitting sort of a ceiling and only want to go up from there. And so I think we as a company, care about both ends of that spectrum and certainly have want to build and continue building products for companies of all sorts, regardless of where they are on the maturity curve of data orchestration. >> That's a really good point Paola. And I think the other thing to really take into account is it's the companies themselves, but also individuals who have to do their jobs. You know, if you rewind the clock like five or 10 years ago, data engineers would be the ones responsible for orchestrating data through their org. But when we look at our customers today, it's not just data engineers anymore. There's data analysts who sit a lot closer to the business and the data scientists who want to automate things around their models. So this idea that orchestration is this new category is spot on, is right on the money. And what we're finding is it's spreading, the need for it, is spreading to all parts of the data team naturally where Airflows have emerged as an open source standard and we're hoping to take things to the next level. >> That's awesome. You know, we've been up saying that the data market's kind of like the SRE with servers, right? You're going to need one person to deal with a lot of data and that's data engineering and then you're going to have the practitioners, the democratization. Clearly that's coming in what you're seeing. So I got to ask, how do you guys fit in from a value proposition standpoint? What's the pitch that you have to customers or is it more inbound coming into you guys? Are you guys doing a lot of outreach, customer engagements? I'm sure they're getting a lot of great requirements from customers. What's the current value proposition? How do you guys engage? >> Yeah, I mean we've, there's so many, there's so many. Sorry Raj, you can jump in. - >> It's okay. So there's so many companies using Airflow, right? So our, the baseline is that the open source project that is Airflow that was, that came out of Airbnb, you know, over five years ago at this point, has grown exponentially in users and continues to grow. And so the folks that we sell to primarily are folks who are already committed to using Apache Airflow, need data orchestration in the organization and just want to do it better, want to do it more efficiently, want to do it without managing that infrastructure. And so our baseline proposition is for those organizations. Now to Raj's point, obviously I think our ambitions go beyond that, both in terms of the personas that we addressed and going beyond that data engineer, but really it's for, to start at the baseline. You know, as we continue to grow our company, it's really making sure that we're adding value to folks using Airflow and help them do so in a better way, in a larger way and a more efficient way. And that's really the crux of who we sell to. And so to answer your question on, we actually, we get a lot of inbound because they're are so many - >> A built-in audience. >> In the world that use it, that those are the folks who we talk to and come to our website and chat with us and get value from our content. I mean the power of the open source community is really just so, so big. And I think that's also one of the things that makes this job fun, so. >> And you guys are in a great position, Viraj, you can comment, to get your reaction. There's been a big successful business model to starting a company around these big projects for a lot of reasons. One is open source is continuing to be great, but there's also supply chain challenges in there. There's also, you know, we want to continue more innovation and more code and keeping it free and and flowing. And then there's the commercialization of product-izing it, operationalizing it. This is a huge new dynamic. I mean, in the past, you know, five or so years, 10 years, it's been happening all on CNCF from other areas like Apache, Linux Foundation, they're all implementing this. This is a huge opportunity for entrepreneurs to do this. >> Yeah, yeah. Open source is always going to be core to what we do because, you know, we wouldn't exist without the open source community around us. They are huge in numbers. Oftentimes they're nameless people who are working on making something better in a way that everybody benefits from it. But open source is really hard, especially if you're a company whose core competency is running a business, right? Maybe you're running e-commerce business or maybe you're running, I don't know, some sort of like any sort of business, especially if you're a company running a business, you don't really want to spend your time figuring out how to run open source software. You just want to use it, you want to use the best of it, you want to use the community around it. You want to take, you want to be able to google something and get answers for it. You want the benefits of open source. You don't want to have, you don't have the time or the resources to invest in becoming an expert in open source, right? And I think that dynamic is really what's given companies like us an ability to kind of form businesses around that, in the sense that we'll make it so people get the best of both worlds. You'll get this vast open ecosystem that you can build on top of, you can benefit from, that you can learn from, but you won't have to spend your time doing undifferentiated heavy lifting. You can do things that are just specific to your business. >> It's always been great to see that business model evolved. We used to debate 10 years ago, can there be another red hat? And we said, not really the same, but there'll be a lot of little ones that'll grow up to be big soon. Great stuff. Final question, can you guys share the history of the company, the milestones of the Astronomer's journey in data orchestration? >> Yeah, we could. So yeah, I mean, I think, so Raj and I have obviously been at astronomer along with our other founding team and leadership folks, for over five years now. And it's been such an incredible journey of learning, of hiring really amazing people. Solving again, mission critical problems for so many types of organizations. You know, we've had some funding that has allowed us to invest in the team that we have and in the software that we have. And that's been really phenomenal. And so that investment, I think, keeps us confident even despite these sort of macroeconomic conditions that we're finding ourselves in. And so honestly, the milestones for us are focusing on our product, focusing on our customers over the next year, focusing on that market for us, that we know can get value out of what we do. And making developers' lives better and growing the open source community, you know, and making sure that everything that we're doing makes it easier for folks to get started to contribute to the project and to feel a part of the community that we're cultivating here. >> You guys raised a little bit of money. How much have you guys raised? >> I forget what the total is, but it's in the ballpark of 200, over $200 million. So it feels good - >> A little bit of capital. Got a little bit of cash to work with there. Great success. I know it's a Series C financing, you guys been down, so you're up and running. What's next? What are you guys looking to do? What's the big horizon look like for you? And from a vision standpoint, more hiring, more product, what is some of the key things you're looking at doing? >> Yeah, it's really a little of all of the above, right? Like, kind of one of the best and worst things about working at earlier stage startups is there's always so much to do and you often have to just kind of figure out a way to get everything done, but really invest in our product over the next, at least the next, over the course of our company lifetime. And there's a lot of ways we wanting to just make it more accessible to users, easier to get started with, easier to use all kind of on all areas there. And really, we really want to do more for the community, right? Like I was saying, we wouldn't be anything without the large open source community around us. And we want to figure out ways to give back more in more creative ways, in more code driven ways and more kind of events and everything else that we can do to keep those folks galvanized and just keeping them happy using Airflow. >> Paola, any final words as we close out? >> No, I mean, I'm super excited. You know, I think we'll keep growing the team this year. We've got a couple of offices in the US which we're excited about, and a fully global team that will only continue to grow. So Viraj and I are both here in New York and we're excited to be engaging with our coworkers in person. Finally, after years of not doing so, we've got a bustling office in San Francisco as well. So growing those teams and continuing to hire all over the world and really focusing on our product and the open source community is where our heads are at this year, so. >> Congratulations. - >> Excited. 200 million in funding plus good runway. Put that money in the bank, squirrel it away. You know, it's good to kind of get some good interest on it, but still grow. Congratulations on all the work you guys do. We appreciate you and the open sourced community does and good luck with the venture. Continue to be successful and we'll see you at the Startup Showcase. >> Thank you. - >> Yeah, thanks so much, John. Appreciate it. - >> It's theCube conversation, featuring astronomer.io, that's the website. Astronomer is doing well. Multiple rounds of funding, over 200 million in funding. Open source continues to lead the way in innovation. Great business model. Good solution for the next gen, Cloud, scale, data operations, data stacks that are emerging. I'm John Furrier, your host. Thanks for watching. (soft music)

>>Hey everyone. Welcome to the cubes presentation of the AWS startup showcase. This is season two, episode four of our ongoing series. That's featuring exciting startups within the AWS ecosystem. This theme, cybersecurity protect and detect against threats. I'm your host. Lisa Martin. I've got two guests here with me. Please. Welcome back to the program. Sam Kam, a COO and co-founder of security scorecard and bar Roth. Charri team lead solutions marketing at confluent guys. It's great to have you on the program talking about cybersecurity. >>Thanks for having us, Lisa, >>Sam, let's go ahead and kick off with you. You've been on the queue before, but give the audience just a little bit of context about security scorecard or SSC as they're gonna hear it referred to. >>Yeah. AB absolutely. Thank you for that. Well, the easiest way to, to put it is when people wanna know about their credit risk, they consult one of the major credit scoring companies. And when companies wanna know about their cybersecurity risk, they turn to security scorecard to get that holistic view of, of, of the security posture. And the way it works is SSC is continuously 24 7 collecting signals from across the entire internet. I entire IPV four space and they're doing it to identify vulnerable and misconfigured digital assets. And we were just looking back over like a three year period. We looked from 2019 to 2022. We, we, we assessed through our techniques over a million and a half organizations and found that over half of them had at least one open critical vulnerability exposed to the internet. What was even more shocking was 20% of those organizations had amassed over a thousand vulnerabilities each. >>So SSC we're in the business of really building solutions for customers. We mine the data from dozens of digital sources and help discover the risks and the flaws that are inherent to their business. And that becomes increasingly important as companies grow and find new sources of risk and new threat vectors that emerge on the internet for themselves and for their vendor and business partner ecosystem. The last thing I'll mention is the platform that we provide. It relies on data collection and processing to be done in an extremely accurate and real time way. That's a key for that's allowed us to scale. And in order to comp, in order for us to accomplish this security scorecard engineering teams, they used a really novel combination of confluent cloud and confluent platform to build a really, really robust data for streaming pipelines and the data streaming pipelines enabled by confluent allow us at security scorecard to collect the data from a lot of various sources for risk analysis. Then they get feer further analyzed and provided to customers as a easy to understand summary of analytics. >>Rob, let's bring you into the conversation, talk about confluent, give the audience that overview and then talk about what you're doing together with SSC. >>Yeah, and I wanted to say Sam did a great job of setting up the context about what confluent is. So, so appreciate that, but a really simple way to think about it. Lisa is confident as a data streaming platform that is pioneering a fundamentally new category of data infrastructure that is at the core of what SSE does. Like Sam said, the key is really collect data accurately at scale and in real time. And that's where our cloud native offering really empowers organizations like SSE to build great customer experiences for their customers. And the other thing we do is we also help organizations build a sophisticated real time backend operations. And so at a high level, that's the best way to think about comfort. >>Got it. But I'll talk about data streaming, how it's being used in cyber security and what the data streaming pipelines enable enabled by confluent allow SSE to do for its customers. >>Yeah, I think Sam can definitely share his thoughts on this, but one of the things I know we are all sort of experiencing is the, is the rise of cyber threats, whether it's online from a business B2B perspective or as consumers just be our data and, and the data that they're generating and the companies that have access to it. So as the, the need to protect the data really grows companies and organizations really need to effectively detect, respond and protect their environments. And the best way to do this is through three ways, scale, speed, and cost. And so going back to the points I brought up earlier with conference, you can really gain real time data ingestion and enable those analytics that Sam talked about previously while optimizing for cost scale. So those are so doing all of this at the same time, as you can imagine, is, is not easy and that's where we Excel. >>And so the entire premise of data streaming is built on the concepts. That data is not static, but constantly moving across your organization. And that's why we call it data streams. And so at its core, we we've sort of built or leveraged that open source foundation of APA sheet Kafka, but we have rearchitected it for the cloud with a totally new cloud native experience. And ultimately for customers like SSE, we have taken a away the need to manage a lot of those operational tasks when it comes to Apache Kafka. The other thing we've done is we've added a ton of proprietary IP, including security features like role based access control. I mean, some prognosis talking about, and that really allows you to securely connect to any data no matter where it resides at scale at speed. And it, >>Can you talk about bar sticking with you, but some of the improvements, and maybe this is a actually question for Sam, some of the improvements that have been achieved on the SSC side as a result of the confluent partnership, things are much faster and you're able to do much more understand, >>Can I, can Sam take it away? I can maybe kick us off and then breath feel, feel free to chime in Lisa. The, the, the, the problem that we're talking about has been for us, it was a longstanding challenge. We're about a nine year old company. We're a high growth startup and data collection has always been in, in our DNA. It's at it's at the core of what we do and getting, getting the insights, the, and analytics that we synthesize from that data into customer's hands as quickly as possible is the, is the name of the game because they're trying to make decisions and we're empowering them to make those decisions faster. We always had challenges in, in the arena because we, well partners like confluent didn't didn't exist when we started scorecard when, when we we're a customer. But we, we, we think of it as a partnership when we found confluent technology and you can hear it from Barth's description. >>Like we, we shared a common vision and they understood some of the pain points that we were experiencing on a very like visceral and intimate level. And for us, that was really exciting, right? Just to have partners that are there saying, we understand your problem. This is exactly the problem that we're solving. We're, we're here to help what the technology has done for us since then is it's not only allowed us to process the data faster and get the analytics to the customer, but it's also allowed us to create more value for customers, which, which I'll talk about in a bit, including new products and new modules that we didn't have the capabilities to deliver before. >>And we'll talk about those new products in a second exciting stuff coming out there from SSC, bro. Talk about the partnership from, from confluence perspective, how has it enabled confluence to actually probably enhance its technology as a result of seeing and learning what SSC is able to do with the technology? >>Yeah, first of all, I, I completely agree with Sam it's, it's more of a partnership because like Sam said, we sort of shared the same vision and that is to really make sure that organizations have access to the data. Like I said earlier, no matter where it resides so that you can scan and identify the, the potential security security threads. I think from, from our perspective, what's really helped us from the perspective of partnering with SSE is just looking at the data volumes that they're working with. So I know a stat that we talked about recently was around scanning billions of records, thousands of ports on a daily basis. And so that's where, like I, like I mentioned earlier, our technology really excels because you can really ingest and amplify the volumes of data that you're processing so that you can scan and, and detect those threats in real time. >>Because I mean, especially the amount of volume, the data volume that's increasing on a year by basis, that aspect in order to be able to respond quickly, that is paramount. And so what's really helped us is just seeing what SSE is doing in terms of scanning the, the web ports or the data systems that are at are at potential risk. Being able to support their use cases, whether it's data sharing between their different teams internally are being able to empower customers, to be able to detect and scan their data systems. And so the learning for us is really seeing how those millions and billions of records get processed. >>Got it sounds like a really synergistic partnership that you guys have had there for the last year or so, Sam, let's go back over to you. You mentioned some new products. I see SSC just released a tax surface intelligence product. That's detecting thousands of vulnerabilities per minute. Talk to us about that, the importance of that, and another release that you're making. >>There are some really exciting products that we have released recently and are releasing at security scorecard. When we think about, when we think about ratings and risk, we think about it not just for our companies or our third parties, but we think about it in a, in a broader sense of an, of an ecosystem, because it's important to have data on third parties, but we also want to have the data on their third parties as well. No, nobody's operating in a vacuum. Everybody's operating in this hyper connected ecosystem and the risk can live not just in the third parties, but they might be storing processing data in a myriad of other technological solutions, which we want to understand, but it's really hard to get that visibility because today the way it's done is companies ask their third parties. Hey, send me a list of your third parties, where my data is stored. >>It's very manual, it's very labor intensive, and it's a trust based exercise that makes it really difficult to validate. What we've done is we've developed a technology called a V D automatic vendor detection. And what a V D does is it goes out and for any company, your own company or another business partner that you work with, it will go detect all of the third party connections that we see that have a live network connection or data connection to an organization. So that's like an awareness and discovery tool because now we can see and pull the veil back and see what the bigger ecosystem and connectivity looks like. Thus allowing the customers to go hold accountable, not just the third parties, but their fourth parties, fifth parties really end parties. And they, and they can only do that by using scorecard. The attack surface intelligence tool is really exciting for us because well, be before security scorecard people thought what we were doing was fairly, I impossible. >>It was really hard to get instant visibility on any company and any business partner. And at the same time, it was of critical importance to have that instant visibility into the risk because companies are trying to make faster decisions and they need the risk data to steer those decisions. So when I think about, when I think about that problem in, in managing sort of this evolving landscape, what it requires is it requires insightful and actionable, real time security data. And that relies on a couple things, talent and tech on the talent side, it starts with people. We have an amazing R and D team. We invest heavily. It's the heartbeat of what we do. That team really excels in areas of data collection analysis and scaling large data sets. And then we know on the tech side, well, we figured out some breakthrough techniques and it also requires partners like confluent to help with the real time streaming. >>What we realized was those capabilities are very desired in the market. And we created a new product from it called the tech surface intelligence. A tech surface intelligence focuses less on the rating. There's, there's a persona on users that really value the rating. It's easy to understand. It's a bridge language between technical and non-technical stakeholders. That's on one end of the spectrum on the other end of the spectrum. There's customers and users, very technical customers and users that may not have as much interest in a layman's rating, but really want a deep dive into the strong threat Intel data and capabilities and insights that we're producing. So we produced ASI, which stands for attack surface intelligence that allows customers to look at the surface area of attack all of the digital assets for any organization and see all of the threats, vulnerabilities, bad actors, including sometimes discoveries of zero day vulnerabilities that are, that are out in the wild and being exploited by bad guys. So we have a really strong pulse on what's happening on the internet, good and bad. And we created that product to help service a market that was interested in, in going deep into the data. >>So it's >>So critical. Go >>Ahead to jump in there real quick, because I think the points that Sam brought up, we had a great, great discussion recently while we were building on the case study that I think brings this to life, going back to the AVD product that Sam talked about and, and Sam can probably do a better job of walking through the story, but the way I understand it, one of security scorecards customers approached them and told them that they had an issue to resolve and what they ended up. So this customer was using an AVD product at the time. And so they said that, Hey, the car SSE, they said, Hey, your product shows that we used, you were using HubSpot, but we stopped using that age server. And so I think when SSE investigated, they did find a very recent HubSpot ping being used by the marketing team in this instance. And as someone who comes from that marketing background, I can raise my hand and said, I've been there, done that. So, so yeah, I mean, Sam can probably share his thoughts on this, but that's, I think the great story that sort of brings this all to life in terms of how actually customers go about using SSCs products. >>And Sam, go ahead on that. It sounds like, and one of the things I'm hearing that is a benefit is reduction in shadow. It, I'm sure that happens so frequently with your customers about Mar like a great example that you gave of, of the, the it folks saying we don't use HubSpot, have it in years marketing initiates an instance. Talk about that as some of the benefits in it for customers reducing shadow it, there's gotta be many more benefits from a security perspective. >>Yeah, the, there's a, there's a big challenge today because the market moved to the cloud and that makes it really easy for anybody in an organization to go sign, sign up, put in a credit card, or get a free trial to, to any product. And that product can very easily connect into the corporate system and access the data. And because of the nature of how cloud products work and how easy they are to sign up a byproduct of that is they sort of circumvent a traditional risk assessment process that, that organizations go through and organizations invest a, a lot of money, right? So there's a lot of time and money and energy that are invested in having good procurement risk management life cycles, and making sure that contracts are buttoned up. So on one side you have companies investing loads of energy. And then on the other side, any employee can circumvent that process by just going and with a few clicks, signing up and purchasing a product. >>And that's, and, and, and then that causes a, a disparity and Delta between what the technology and security team's understanding is of the landscape and, and what reality is. And we're trying to close that gap, right? We wanna close and reduce any windows of time or opportunity where a hacker can go discover some misconfigured cloud asset that somebody signed up for and maybe forgot to turn off. I mean, it's a lot of it is just human error and it, and it happens the example that Barra gave, and this is why understanding the third parties are so important. A customer contacted us and said, Hey, you're a V D detection product has an error. It's showing we're using a product. I think it was HubSpot, but we stopped using that. Right. And we don't understand why you're still showing it. It has to be a false positive. >>So we investigated and found that there was a very recent live HubSpot connection, ping being made. Sure enough. When we went back to the customer said, we're very confident the data's accurate. They looked into it. They found that the marketing team had started experimenting with another instance of HubSpot on the side. They were putting in real customer data in that instance. And it, it, you know, it triggered a security assessment. So we, we see all sorts of permutations of it, large multinational companies spin up a satellite office and a contractor setting up the network equipment. They misconfigure it. And inadvertently leave an administrator portal to the Cisco router exposed on the public internet. And they forget to turn off the administrative default credentials. So if a hacker stumbles on that, they can ha they have direct access to the network. We're trying to catch those things and surface them to the client before the hackers find it. >>So we're giving 'em this, this hacker's eye view. And without the continuous data analysis, without the stream processing, the customer wouldn't have known about those risks. But if you can automatically know about the risks as they happen, what that does is that prevents a million shoulder taps because the customer doesn't have to go tap on the marketing team's shoulder and go tap on employees and manually interview them. They have the data already, and that can be for their company. That can be for any company they're doing business with where they're storing and processing data. That's a huge time savings and a huge risk reduction, >>Huge risk reduction. Like you're taking blinders off that they didn't even know were there. And I can imagine Sam tune in the last couple of years, as SAS skyrocketed the use of collaboration tools, just to keep the lights on for organizations to be able to communicate. There's probably a lot of opportunity in your customer base and perspective customer base to engage with you and get that really full 360 degree view of their entire organization. Third parties, fourth parties, et cetera. >>Absolutely. Absolutely. CU customers are more engaged than they've ever been because that challenge of the market moving to the cloud, it hasn't stopped. We've been talking about it for a long time, but there's still a lot of big organizations that are starting to dip their toe in the pool and starting to cut over from what was traditionally an in-house data center in the basement of the headquarters. They're, they're moving over to the cloud. And then on, on top of that cloud providers like Azure, AWS, especially make it so easy for any company to go sign up, get access, build a product, and launch that product to the market. We see more and more organizations sitting on AWS, launching products and software. The, the barrier to entry is very, very low. And the value in those products is very, very high. So that's drawing the attention of organizations to go sign up and engage. >>The challenge then becomes, we don't know who has control over this data, right? We don't have know who has control and visibility of our data. We're, we're bringing that to surface and for vendors themselves like, especially companies that sit in AWS, what we see them doing. And I think Lisa, this is what you're alluding to. When companies engage in their own scorecard, there's a bit of a social aspect to it. When they look good in our platform, other companies are following them, right? So now all of the sudden they can make one motion to go look good, make their scorecard buttoned up. And everybody who's looking at them now sees that they're doing the right things. We actually have a lot of vendors who are customers, they're winning more competitive bakeoffs and deals because they're proving to their clients faster that they can trust them to store the data. >>So it's a bit of, you know, we're in a, two-sided kind of market. You have folks that are assessing other folks. That's fun to look at others and see how they're doing and hold them accountable. But if you're on the receiving end, that can be stressful. So what we've done is we've taken the, that situation and we've turned it into a really positive and productive environment where companies, whether they're looking at someone else or they're looking at themselves to prove to their clients, to prove to the board, it turns into a very productive experience for them >>One. Oh >>Yeah. That validation. Go ahead, bro. >>Really. I was gonna ask Sam his thoughts on one particular aspect. So in terms of the industry, Sam, that you're seeing sort of really moving to the cloud and like this need for secure data, making sure that the data can be trusted. Are there specific like verticals that are doing that better than the others? Or do you see that across the board? >>I think some industries have it easier and some industries have it harder, definitely in industries that are, I think, health, healthcare, financial services, a absolutely. We see heavier activity there on, on both sides, right? They they're, they're certainly becoming more and more proactive in their investments, but the attacks are not stopping against those, especially healthcare because the data is so valuable and historically healthcare was under, was an underinvested space, right. Hospitals. And we're always strapped for it folks. Now, now they're starting to wake up and pay very close attention and make heavier investments. >>That's pretty interesting. >>Tremendous opportunity there guys. I'm sorry. We are out of time, but this is such an interesting conversation. You see, we keep going, wanna ask you both where can, can prospective interested customers go to learn more on the SSC side, on the confluence side, through the AWS marketplace? >>I let some go first. >>Sure. Oh, thank thank, thank you. Thank you for on the security scorecard side. Well look, security scorecard is with the help of Colu is, has made it possible to instantly rate the security posture of any company in the world. We have 12 million organizations rated today and, and that, and that's going up every day. We invite any company in the world to try security scorecard for free and experience how, how easy it is to get your rating and see the security rating of, of any company and any, any company can claim their score. There's no, there's no charge. They can go to security, scorecard.com and we have a special, actually a special URL security scorecard.com/free-account/aws marketplace. And even better if someone's already on AWS, you know, you can view our security posture with the AWS marketplace, vendor insights, plugin to quickly and securely procure your products. >>Awesome. Guys, this has been fantastic information. I'm sorry, bro. Did you wanna add one more thing? Yeah. >>I just wanted to give quick call out leads. So anyone who wants to learn more about data streaming can go to www confluent IO. There's also an upcoming event, which has a separate URL. That's coming up in October where you can learn all about data streaming and that URL is current event.io. So those are the two URLs I just wanted to quickly call out. >>Awesome guys. Thanks again so much for partnering with the cube on season two, episode four of our AWS startup showcase. We appreciate your insights and your time. And for those of you watching, thank you so much. Keep it right here for more action on the, for my guests. I am Lisa Martin. We'll see you next time.

(upbeat music) >> Welcome, everyone, to theCUBE's presentation of the AWS Startup Showcase. And this episode two of season two is called "Data as Code," the ongoing series covering exciting new startups in the AWS ecosystem. I'm John Furrier, your host of theCUBE. Today, we're excited to be joined by Jon Dahl, who is the co-founder and CEO of MUX, a hot new startup building cloud video for developers, video with data. John, great to see you. We did an interview on theCube Conversation. Went into big detail of the awesomeness of your company and the trend that you're on. Welcome back. >> Thank you, glad to be here. >> So, video is everywhere, and video for pivot to video, you hear all these kind of terms in the industry, but now more than ever, video is everywhere and people are building with it, and it's becoming part of the developer experience in applications. So people have to stand up video into their code fast, and data is code, video is data. So you guys are specializing this. Take us through that dynamic. >> Yeah, so video clearly is a growing part of how people are building applications. We see a lot of trends of categories that did not involve video in the past making a major move towards video. I think what Peloton did five years ago to the world of fitness, that was not really a big category. Now video fitness is a huge thing. Video in education, video in business settings, video in a lot of places. I think Marc Andreessen famously said, "Software is eating the world" as a pretty, pretty good indicator of what the internet is actually doing to the economy. I think there's a lot of ways in which video right now is eating software. So categories that we're not video first are becoming video first. And that's what we help with. >> It's not obvious to like most software developers when they think about video, video industries, it's industry shows around video, NAB, others. People know, the video folks know what's going on in video, but when you start to bring it mainstream, it becomes an expectation in the apps. And it's not that easy, it's almost a provision video is hard for a developer 'cause you got to know the full, I guess, stack of video. That's like low level and then kind of just basic high level, just play something. So, in between, this is a media stack kind of dynamic. Can you talk about how hard it is to build video for developers? How is it going to become easier? >> Yeah, I mean, I've lived this story for too long, maybe 13 years now, when I first build my first video stack. And, you know, I'll sometimes say, I think it's kind of a miracle every time a video plays on the internet because the internet is not a medium designed for video. It's been hijacked by video, video is 70% of internet traffic today in an unreliable, sort of untrusted network space, which is totally different than how television used to work or cable or things like that. So yeah, so video is hard because there's so many problems from top to bottom that need to be solved to make video work. So you have to worry about video compression encoding, which is a complicated topic in itself. You have to worry about delivering video around the world at scale, delivering it at low cost, at low latency, with good performance, you have to worry about devices and how every device, Android, iOS, web, TVs, every device handles video differently and so there's a lot of work there. And at the end of the day, these are kind of unofficial standards that everyone's using. So one of the miracles is like, if you want to watch a video, somehow you have to get like Apple and Google to agree on things, which is not always easy. And so there's just so many layers of complexity that are behind it. I think one way to think about it is, if you want to put an image online, you just put an image online. And if you want to put video online, you build complex software, and that's the exact problem that MUX was started to help solve. >> It's interesting you guys have almost creating a whole new category around video infrastructure. And as you look at, you mentioned stack, video stack. I'm looking at a market where the notion of a media stack is developing, and you're seeing these verticals having similar dynamics with cloud. And if you go back to the early days of cloud computing, what was the developer experience or entrepreneurial experience, you had to actually do a lot of stuff before you even do anything, provision a server. And this has all kind of been covered in great detail in the glory of Agile and whatnot. It was expensive, and you had that actually engineer before you could even stand up any code. Now you got video that same thing's happening. So the developers have two choices, go do a bunch of stuff complex, building their own infrastructure, which is like building a data center, or lean in on MUX and say, "Hey, thank you for doing all that years of experience building out the stacks to take that hard part away," but using APIs that they have. This is a developer focused problem that you guys are solving. >> Yeah, that's right. my last company was a company called Zencoder, that was an API to video encoding. So it was kind of an API to a small part of what MUX does today, just one of those problems. And I think the thing that we got right at Zencoder, that we're doing again here at MUX, was building four developers first. So our number one persona is a software developer. Not necessarily a video expert, just we think any developer should be able to build with video. It shouldn't be like, yeah, got to go be a specialist to use this technology, because it should become just of the internet. Video should just be something that any developer can work with. So yeah, so we build for developers first, which means we spend a lot of time thinking about API design, we spend a lot of time thinking about documentation, transparent pricing, the right features, great support and all those kind of things that tend to be characteristics of good developer companies. >> Tell me about the pipe lining of the products. I'm a developer, I work for a company, my boss is putting pressure on me. We need video, we have all this library, it's all stacking up. We hired some people, they left. Where's the video, we've stored it somewhere. I mean, it's a nightmare, right? So I'm like, okay, I'm cloud native, I got an API. I need to get my product to market fast, 'cause that is what Agile developers want. So how do you describe that acceleration for time to market? You mentioned you guys are API first, video first. How do these customers get their product into the market as fast as possible? >> Yeah, well, I mean the first thing we do is we put what we think is probably on average, three to four months of hard engineering work behind a single API call. So if you want to build a video platform, we tell our customers like, "Hey, you can do that." You probably need a team, you probably need video experts on your team so hire them or train them. And then it takes several months just to kind of to get video flowing. One API call at MUX gives you on-demand video or live video that works at scale, works around the world with good performance, good reliability, a rich feature set. So maybe just a couple specific examples, we worked with Robin Hood a few years ago to bring video into their newsfeed, which was hugely successful for them. And they went from talking to us for the first time to a big launch in, I think it was three months, but the actual code time there was like really short. I want to say they had like a proof of concept up and running in a couple days, and then the full launch in three months. Another customer of ours, Bandcamp, I think switched from a legacy provider to MUX in two weeks in band. So one of the big advantages of going a little bit higher in the abstraction layer than just building it yourself is that time to market. >> Talk about this notion of video pipeline 'cause I know I've heard people I talk about, "Hey, I just want to get my product out there. I don't want to get stuck in the weeds on video pipeline." What does that mean for folks that aren't understanding the nuances of video? >> Yeah, I mean, it's all the steps that it takes to publish video. So from ingesting the video, if it's live video from making sure that you have secure, reliable ingest of that live feed potentially around the world to the transcoding, which is we talked a little bit about, but it is a, you know, on its own is a massively complicated problem. And doing that, well, doing that well is hard. Part of the reason it's hard is you really have to know where you're publishing too. And you might want to transcode video differently for different devices, for different types of content. You know, the pipeline typically would also include all of the workflow items you want to do with the video. You want to thumbnail a video, you want clip, create clips of the video, maybe you want to restream the video to Facebook or Twitter or a social platform. You want to archive the video, you want it to be available for downloads after an event. If it's just a, if it's a VOD upload, if it's not live in the first place. You have all those things and you might want to do simulated live with the video. You might want to actually record something and then play it back as a live stream. So, the pipeline Ty typically refers to everything from the ingest of the video to the time that the bits are delivered to a device. >> You know, I hear a lot of people talking about video these days, whether it's events, training, just want peer to peer experience, video is powerful, but customers want to own their own platform, right? They want to have the infrastructure as a service. They kind of want platform as a service, this is cloud talk now, but they want to have their own capability to build it out. This allows them to get what they want. And so you see this, like, is it SaaS? Is it platform? People want customization? So kind of the general purpose video solution does it really exist or doesn't? I mean, 'cause this is the question. Can I just buy software and work or is it going to be customized always? How do you see that? Because this becomes a huge discussion point. Is it a SaaS product or someone's going to make a SaaS product? >> Yeah, so I think one of the most important elements of designing any software, but especially when you get into infrastructure is choosing an abstraction level. So if you think of computing, you can go all the way down to building a data center, you can go all the way down to getting a colo and racking a server like maybe some of us used to do, who are older than others. And that's one way to run a server. On the other extreme, you have just think of the early days of cloud competing, you had app engine, which was a really fantastic, really incredible product. It was one push deploy of, I think Python code, if I remember correctly, and everything just worked. But right in the middle of those, you had EC2, which was, EC2 is basically an API to a server. And it turns out that that abstraction level, not Colo, not the full app engine kind of platform, but the API to virtual server was the right abstraction level for maybe the last 15 years. Maybe now some of the higher level application platforms are doing really well, maybe the needs will shift. But I think that's a little bit of how we think about video. What developers want is an API to video. They don't want an API to the building blocks of video, an API to transcoding, to video storage, to edge caching. They want an API to video. On the other extreme, they don't want a big application that's a drop in white label video in a box like a Shopify kind of thing. Shopify is great, but developers don't want to build on top of Shopify. In the payments world developers want Stripe. And that abstraction level of the API to the actual thing you're getting tends to be the abstraction level that developers want to build on. And the reason for that is, it's the most productive layer to build on. You get maximum flexibility and also maximum velocity when you have that API directly to a function like video. So, we like to tell our customers like you, you own your video when you build on top of MUX, you have full control over everything, how it's stored, when it's stored, where it goes, how it's published, we handle all of the hard technology and we give our customers all of the flexibility in terms of designing their products. >> I want to get back some use case, but you brought that up I might as well just jump to my next point. I'd like you to come back and circle back on some references 'cause I know you have some. You said building on infrastructure that you own, this is a fundamental cloud concept. You mentioned API to a server for the nerds out there that know that that's cool, but the people who aren't super nerdy, that means you're basically got an interface into a server behind the scenes. You're doing the same for video. So, that is a big thing around building services. So what wide range of services can we expect beyond MUX? If I'm going to have an API to video, what could I do possibly? >> What sort of experience could you build? >> Yes, I got a team of developers saying I'm all in API to video, I don't want to do all that transit got straight there, I want to build experiences, video experiences on my app. >> Yeah, I mean, I think, one way to think about it is that, what's the range of key use cases that people do with video? We tend to think about six at MUX, one is kind of the places where the content is, the prop. So one of the things that use video is you can create great video. Think of online courses or fitness or entertainment or news or things like that. That's kind of the first thing everyone thinks of, when you think video, you think Netflix, and that's great. But we see a lot of really interesting uses of video in the world of social media. So customers of ours like Visco, which is an incredible photo sharing application, really for photographers who really care about the craft. And they were able to bring video in and bring that same kind of Visco experience to video using MUX. We think about B2B tools, videos. When you think about it, all video is, is a high bandwidth way of communicating. And so customers are as like HubSpot use video for the marketing platform, for business collaboration, you'll see a lot of growth of video in terms of helping businesses engage their customers or engage with their employees. We see live events obviously have been a massive category over the last few years. You know, we were all forced into a world where we had to do live events two years ago, but I think now we're reemerging into a world where the online part of a conference will be just as important as the in-person component of a conference. So that's another big use case we see. >> Well, full disclosure, if you're watching this live right now, it's being powered by MUX. So shout out, we use MUX on theCUBE platform that you're experiencing in this. Actually in real time, 'cause this is one application, there's many more. So video as code, is data as code is the theme, that's going to bring up the data ops. Video also is code because (laughs) it's just like you said, it's just communicating, but it gets converted to data. So data ops, video ops could be its own new category. What's your reaction to that? >> Yeah, I mean, I think, I have a couple thoughts on that. The first thought is, video is a way that, because the way that companies interact with customers or users, it's really important to have good monitoring and analytics of your video. And so the first product we ever built was actually a product called MUX video, sorry, MUX data, which is the best way to monitor a video platform at scale. So we work with a lot of the big broadcasters, we work with like CBS and Fox Sports and Discovery. We work with big tech companies like Reddit and Vimeo to help them monitor their video. And you just get a huge amount of insight when you look at robust analytics about video delivery that you can use to optimize performance, to make sure that streaming works well globally, especially in hard to reach places or on every device. That's we actually build a MUX data platform first because when we started MUX, we spent time with some of our friends at companies like YouTube and Netflix, and got to know how they use data to power their video platforms. And they do really sophisticated things with data to ensure that their streams well, and we wanted to build the product that would help everyone else do that. So, that's one use. I think the other obvious use is just really understanding what people are doing with their video, who's watching what, what's engaging, those kind of things. >> Yeah, data is definitely there. You guys mentioned some great brands that are working with you guys, and they're doing it because of the developer experience. And I'd like you to explain, if you don't mind, in your words, why is the MUX developer experience so good? What are some of the results you're seeing from your customers? What are they saying to you? Obviously when you win, you get good feedback. What are some of the things that they're saying and what specific develop experiences do they like the best? >> Yeah, I mean, I think that the most gratifying thing about being a startup founder is when your customers like what you're doing. And so we get a lot of this, but it's always, we always pay attention to what customers say. But yeah, people, the number one thing developers say when they think about MUX is that the developer experience is great. I think when they say that, what they mean is two things, first is it's easy to work with, which helps them move faster, software velocity is so important. Every company in the world is investing and wants to move quickly and to build quickly. And so if you can help a team speed up, that's massively valuable. The second thing I think when people like our developer experience is, you know, in a lot of ways that think that we get out of the way and we let them do what they want to do. So well, designed APIs are a key part of that, coming back to abstraction, making sure that you're not forcing customers into decisions that they actually want to make themselves. Like, if our video player only had one design, that that would not be, that would not work for most developers, 'cause developers want to bring their own design and style and workflow and feel to their video. And so, yeah, so I think the way we do that is just think comprehensively about how APIs are designed, think about the workflows that users are trying to accomplish with video, and make sure that we have the right APIs, make sure they're the right information, we have the right webhooks, we have the right SDKs, all of those things in place so that they can build what they want. >> We were just having a conversation on theCUBE, Dave Vellante and I, and our team, and I'd love to get you a reaction to this. And it's more and more, a riff real quick. We're seeing a trend where video as code, data as code, media stack, where you're starting to see the emergence of the media developer, where the application of media looks a lot like kind of software developer, where the app, media as an app. It could be a chat, it could be a peer to peer video, it could be part of an event platform, but with all the recent advances, in UX designers, coders, the front end looks like an emergence of these creators that are essentially media developers for all intent and purpose, they're coding media. What's your reaction to that? How do you see that evolving? >> I think the. >> Or do you agree with it? >> It's okay. >> Yeah, yeah. >> Well, I think a couple things. I think one thing, I think this goes along through saying, but maybe it's disagreement, is that we don't think you should have to be an expert at video or at media to create and produce or create and publish good video, good audio, good images, those kind of things. And so, you know, I think if you look at software overall, I think of 10 years ago, the kind of DevOps movement, where there was kind of a movement away from specialization in software where the same software developer could build and deploy the same software developer maybe could do front end and back end. And we want to bring that to video as well. So you don't have to be a specialist to do it. On the other hand, I do think that investments and tooling, all the way from video creation, which is not our world, but there's a lot of amazing companies out there that are making it easier to produce video, to shoot video, to edit, a lot of interesting innovations there all the way to what we do, which is helping people stream and publish video and video experiences. You know, I think another way about it is, that tool set and companies doing that let anyone be a media developer, which I think is important. >> It's like DevOps turning into low-code, no-code, eventually it's just composability almost like just, you know, "Hey Siri, give me some video." That kind of thing. Final question for you why I got you here, at the end of the day, the decision between a lot of people's build versus buy, "I got to get a developer. Why not just roll my own?" You mentioned data center, "I want to build a data center." So why MUX versus do it yourself? >> Yeah, I mean, part of the reason we started this company is we have a pretty, pretty strong opinion on this. When you think about it, when we started MUX five years ago, six years ago, if you were a developer and you wanted to accept credit cards, if you wanted to bring payment processing into your application, you didn't go build a payment gateway. You just probably used Stripe. And if you wanted to send text messages, you didn't build your own SMS gateway, you probably used Twilio. But if you were a developer and you wanted to stream video, you built your own video gateway, you built your own video application, which was really complex. Like we talked about, you know, probably three, four months of work to get something basic up and running, probably not live video that's probably only on demand video at that point. And you get no benefit by doing it yourself. You're no better than anyone else because you rolled your own video stack. What you get is risk that you might not do a good job, maybe you do worse than your competitors, and you also get distraction where you've just taken, you take 10 engineers and 10 sprints and you apply it to a problem that doesn't actually really give you differentiated value to your users. So we started MUX so that people would not have to do that. It's fine if you want to build your own video platform, once you get to a certain scale, if you can afford a dozen engineers for a VOD platform and you have some really massively differentiated use case, you know, maybe, live is, I don't know, I don't have the rule of thumb, live videos maybe five times harder than on demand video to work with. But you know, in general, like there's such a shortage of software engineers today and software engineers have, frankly, are in such high demand. Like you see what happens in the marketplace and the hiring markets, how competitive it is. You need to use your software team where they're maximally effective, and where they're maximally effective is building differentiation into your products for your customers. And video is just not that, like very few companies actually differentiate on their video technology. So we want to be that team for everyone else. We're 200 people building the absolute best video infrastructure as APIs for developers and making that available to everyone else. >> John, great to have you on with the showcase, love the company, love what you guys do. Video as code, data as code, great stuff. Final plug for the company, for the developers out there and prospects watching for MUX, why should they go to MUX? What are you guys up to? What's the big benefit? >> I mean, first, just check us out. Try try our APIs, read our docs, talk to our support team. We put a lot of work into making our platform the best, you know, as you dig deeper, I think you'd be looking at the performance around, the global performance of what we do, looking at our analytics stack and the insight you get into video streaming. We have an emerging open source video player that's really exciting, and I think is going to be the direction that open source players go for the next decade. And then, you know, we're a quickly growing team. We're 60 people at the beginning of last year. You know, we're one 50 at the beginning of this year, and we're going to a add, we're going to grow really quickly again this year. And this whole team is dedicated to building the best video structure for developers. >> Great job, Jon. Thank you so much for spending the time sharing the story of MUX here on the show, Amazon Startup Showcase season two, episode two, thanks so much. >> Thank you, John. >> Okay, I'm John Furrier, your host of theCUBE. This is season two, episode two, the ongoing series cover the most exciting startups from the AWS Cloud Ecosystem. Talking data analytics here, video cloud, video as a service, video infrastructure, video APIs, hottest thing going on right now, and you're watching it live here on theCUBE. Thanks for watching. (upbeat music)

(upbeat music) >> Every company needs great salespeople, it's one of the most lucrative professions out there. And there's plenty of wisdom and knowledge that's been gathered over the years about selling. We've heard it all, famous quotes from the greatest salespeople of our time, like Zig Ziglar and Jeffrey Gitomer, and Dale Carnegie and Jack Welch, and many others. Things like, "Each of us has only 24 hours in a day, "it's all about how we use our time." And, "You don't have to be great to start, "but you have to start to be great." And then I love this one, "People hate to be sold, but they love to buy." "There are no traffic jams on the extra mile, "make change before you have to." And the all time classic, "Put that coffee down. "Coffee is for closers." Thousands of pieces of sales advice are readily available in books, videos, on blogs and in podcasts, and many of these are free of charge. So why would entrepreneurs start a company to train salespeople? And how is it that sharp investors are pouring millions of dollars into this space? Hello everyone, and welcome to this Cube Video Exclusive, my name is Dave Vellante, and today we welcome Paul Fifield who's the co-founder and CEO of Sales Impact Academy who's going to answer these questions and share some exciting news on the startups. Paul, welcome to "The Cube" good to see you again. >> Yeah, good to see you again, Dave, great to be here. >> Hey, so before we get into the hard news, tell us a little bit about the Sales Impact Academy, why'd you start the company, maybe some of the fundamentals of this market, your total available market, who you're targeting, you know, what's the premise behind the company? >> Yeah sure. So I mean, I started the company, it was actually pretty organic in the way it began. I had a 10 year career as a CRO and it was, you know, had a couple of great hits with two companies, but it was a real struggle to basically, you know, operate as a CRO and learn your craft at the same time. And so when I left my last company, I kind of got out there, I wanted to kind of give back a little bit and I started doing some voluntary teaching in and around London, and I actually, one of the companies I started was in New York so I got schooled very much on a sort of US approach to how you build a modern you know, go to market and sales operation. Started going out there, doing some teaching, realized that so many people just didn't have a clue about how to build a scalable and predictable revenue function, and I kind of felt sorry for them. So I literally started doing some, you know, online classes myself, got my co-founder Alex to put curriculum together as well and we literally started just doing online classes, very live, very organic, just a Google Drive and some decks, and it really just blew up from there. >> That's amazing. I mean, so you've my, you know, tongue and cheek up front, but people might wonder, why do you need a platform 'cause there's so much free information out there? Is it to organize, is it a discipline thing? Explain that. >> Well, I think the way I sort of see this is that is that the lack of structured learning and education is actually one of the greatest educational travesties, I think, of the last 50 years, okay. Now sales and go to market is a huge global profession, right? Half the world's companies are B2B, so roughly that's a proxy for half the world's GDP, right? Which is $40 trillion of GDP. Now that 40 trillion rests on kind of the success of the growth and the sales functions of all those companies. Yet in its infinite wisdom, the global education system literally just ignored sales and go to market as a profession. Some universities are kind of catching up, but it's really too little too late. So what I sort of say to people, you imagine this Dave, right. You imagine if the way that law worked as a profession let's say, is that there's no law school, there's no law training, there's no even in work professional continuous professional development in law. The way that it works is you leave university, join a company, start practicing law and just use like YouTube just to maybe like, you know, where you're struggling, just use YouTube to like work out what's going on. The legal profession would be in absolute chaos. And that's what's happened in the sales and go to market profession, okay. What this profession desperately desperately needs is structured learning, good pedagogy, good well designed course and curriculum. And here's the other thing, right? Is the sort of paradox of infinite information is that just because all the information is out there, right, doesn't mean it's actually a good learning experience. Like, where do you find it? What's good? What's not good? And also the other thing I'd point out is that there is this kind of myth that all the information is out there on the internet. But actually what we do, and we'll come into it in a second is, the people teaching on our platform are the elite people from the industry. They haven't got time to do blog posts and just explain to people how they operate. They're going from company to company working at like, you know, working at these kind of elite companies. And they're the people that teach, and that information is not readily available and freely out there on the internet. >> Yeah, real opportunity, you made some great points there. I think business schools are finally starting to teach a little bit about public speaking and presenting, but nobody's teaching us how to sell. As Earl Nightingale says, "To some degree we're all salespeople, "selling our family on living the good life" or whatever. What movie we want to see tonight. But okay, let's get to the hard news. You got fresh funding of 22 million, tell us about that, congratulations. You know, the investors, what else can you share with us? >> Sure. Well, I mean, obviously, you know, immensely proud. We started from very sort of humble beginnings, as I said, we've now scaled very rapidly, we're a subscription business, we're a SaaS business. We'll come onto some of the growth metrics shortly, but just in a couple of years, you know, the last year which ended January, we grew 500% from year one, we're now well over 125 people, and I'm very, very, very honored, flattered, humbled that MIT, obviously one of those prestigious universities in the world, has taken a direct investment by their endowment fund, HubSpot Ventures. Another Boston great has also taken a direct investment as well. They actually began as a customer and loved what we were doing so much that they then decided to make an investment. Stage 2 Capital who invested in our seed round pretty much tripled down, played a huge role in helping us assemble MIT and HubSpot ventures as investors, and they continue to be an incredible VC giving us amazing, amazing support that their LP network of go to market leaders is second to none. And then Emerge Education, who is our pre-seed investor, they're actually based in London, also joined this round as well. >> Great, well actually, let's jump ahead. Let's talk about the metrics. I mean, if Stage Two is involved, they're hardcore. What can you share with us about, you know, everybody's chasing AR and NR and the like, what can you share with us? >> They are both pretty important. Well, I think from a headcount perspective, so as I mentioned our fiscal ends at the end of January, each year. We've gone from 25 to over 125 employees in that time. We've gone from 82 to 260 customers also in that time. And customers now include HubSpot, Gong, Klaviyo, GitHub, GT, Six Cents, so some really sort of major SaaS companies in the space. Our revenue's grown significantly with 5X. So 500% increase in revenue year over year, which is pretty fast, very proud of that. Our learning community has gone from over 3000 people to almost 15,000 professionals, and that makes us comfortably, the largest go to market learning community in the world. >> How did you decide when to scale? What were the sort of signals that said to you, "Okay, we're ready, "we have product market fit, "we can now scale the go to market." What were the signals there, Paul? >> Yeah. Well, I mean, I think for a very small team to achieve that level of growth in customers, to be kind of honest with you, like it's the pull that we're getting from the market. And I think the thing that has surprised me the most, perhaps in the last 12 months, is the pull we're getting from the enterprise. We're you know, I can't really announce, we've actually got a huge pilot with one of the largest companies actually in the world which is going fantastically well, our pipeline for enterprise customers is absolutely huge. But as you can imagine, if you've got distributed teams all over the world, we're living and working in this kind of hybrid world, how on earth do you kind of upscale all those people, right, that are, like I say, that are so distributed. It's impossible. Like in work, in the office delivery of training is pretty much dead, right? And so we sort of fill this really big pain, we solved this really, really big pain of how to effectively upskill people through this kind of live curriculum and this live teaching approach that we have. So I think for me, it's the pull that we're getting from the market really meant that you know, we have to double down. There is such a massive TAM, it is absolutely ridiculous. I mean, I think there are 20 million people just in sales and go to market in tech alone, right. And I mentioned to you earlier, half the world's companies effectively, you know, are B2B and therefore represent, you know, at its largest scope, our TAM. >> Excellent, thank you for that. Tell us more about the product and the platform. How's it work if I'm a customer, what type of investment do I have to make both financially? And what's my time commitment? How do you structure that? >> So the model is basically on a seat model. So roughly speaking, every seat's about a thousand dollars per year per rep. The lift is light. So we've got a very low onboarding, it's not a highly complex technical product, right? We've got a vast curriculum of learning that covers learning for, you know, SDRs, and the AEs, and CS reps, and leadership management training. We're developing curriculum for technical pre-sales, we're developing curriculum for revenue operations. And so it's very, very simple. We basically, it's a seat model, people literally just send us the seats and the details, we get people up and running in the platform, they start then enrolling and we have a customer success team that then plots out learning journeys and learning pathways for all of our customers. And actually what's starting to happen now, which is very, very exciting is that, you know, we're actually a key part of people's career development pathway. So to go from you know, SDR1 let's say to SDR2, you have to complete these three courses with Sales Impact Academy, and let's say, get 75% in your exam and it becomes a very powerful and simple way of developing career pathway. >> Yeah, so really detailed curriculum. So I was going to say, do I as a sales professional, do I pick and choose the things that are most relevant for me? Or are people actually going through a journey in career progression, or maybe both? >> Yeah, it's a mixture of both. We tend to see now, we're sort of starting to standardize, but really we're developing enough curriculum that over, let's say a 15 year period, you could start with us as an SDR and then end as a chief revenue officer, you know, running the entire function. This is the other thing about the crazy world of go to market. Very often, people are put into roles and it's sink or swim. There's no real learning that happens, there's no real development that happens before people take these big steps. And what this platform does so beautifully is is it equips people with the right skills and knowledge before they take that next step in their profession and in their career. And it just dramatically improves their chances of succeeding. >> Who are the trainers? Who's leading the classes, how do you find these guys, how do you structure? What are the content, you know, vectors, where's all that come from? >> Yeah. So the sort of secret source of what we do, beyond just the live instruction, beyond the significant amount of peer to peer learning that goes on, is that we go and source the absolute most elite people in go to market to teach, okay. Now I mentioned to you before, you've got these people that are going from like job to job at the very like the sort of peak of their careers, working for these incredible companies, it's that knowledge that we want to get access to, right. And so Stage 2 Capital is an incredible resource. The interesting thing about Stage 2 Capital as you know Dave, you know, run by Mark Roberge, who was on when we spoke last year and also Jay Po is all the LPs of Stage 2 Capital represent 3 to 400 of the most elite go to market professionals in the world. So, you know, about seven or eight of those are now on an advisory board. And so we have access to this incredible pool of talent. And so we know by consulting these amazing people who are the best people in certain aspects of go to market. We reach out to them and very often they're at a stage in their career where they're really kind of willing to give back, of course there are commercials around it as well, and there's lots of other benefits that we provide our teachers and our faculty, and what we call our coaches. But yeah, we source the very, very best people in the world to teach. >> Now, how does it work as a user of your service? Is it all on demand? Do you do live content or a combination? >> Yeah look, one of the big differentiators is this is a live delivery of learning, okay. Most learning online is typically done on demand, self-directed, and there's a ton of research. There's a great blog post on Andrew's recent site. A short time ago, which is talking about how the completion rates of on demand learning are somewhere between 3 and 6%. That is like, that's awful. >> Terrible. >> I was like why bother? However, we're seeing through that live instruction. So we teach two, one hour classes a week, that's it. We're upskilling very busy people, they're stressed, they've got targets. We have to be very, very cognizant of that. So we teach two, one hour classes a week. Typically, you know, Monday and a Wednesday, or a Tuesday and a Thursday. And that pace of learning is about right, it's kind of how humans learn as well. You know, short bursts of information, and then put that learning and those skills that you've acquired in class literally to work minutes after the class finishes. And so through that, and it sits in your calendar like a meeting, it doesn't feel overwhelming, you're learning together as a team as well. And all that combined, we see completion rates often in excess of 80% for our courses. >> Okay, so they block that time out- >> In the calendar, yeah. >> And they make an investment. Go ahead, please. >> Yeah yeah, exactly, sorry Dave. Yeah, yeah, exactly. So like, you know, we have course lengths. So one of our shorter courses are like four hours long over two weeks. And again, it's just literally in the calendar. We also teach what we call The Magic Learning Hour. And the magic learning hour is this one specific hour in the day that enables teams all over the western hemisphere to join the same class. And that magic learning hour is eight o'clock Pacific 11 o'clock Eastern, >> 4: 00 PM over in the UK, and 5:00 PM in the rest of Europe. And that one time in the day means that these enterprises have got teams all over the western hemisphere joining that class, learning together as a team, plus it's in the calendar and it's that approach is why we're seeing such high engagement and completion. >> That's very cool, the time zone thing. Now who's the target buyer? Are you selling only to sales teams? Can I as an individual purchase your service? >> Yeah, that's a good question. Currently it's a very much like a B2B motion. As I mentioned earlier on, we're getting an enormous pull from the enterprise, which is very exciting. You know, we have an enterprise segment, we have sort of more of a startup earlier stage segment, and then we have a mid-market segment that we call our sort of strategic, and that's typically and most of like venture backed, fast growth tech companies. So very much at the moment a B2B motion. We're launching our own technology platform in the early summer, and then later on this year we're going to be adding what's called PLG or a product led growth, so individuals can actually sign up to SIA. >> Yeah, I mean, I think you said $1,000 per year per rep, is that right? I mean, that's- >> Yeah. >> That's a small investment for an individual that wants to be part of, you know, this community and grow his or her career. So that's the growth plan? You go down market I would imagine, you talked about the western hemisphere, there's international opportunities maybe, local language. What's the growth plan? >> Yeah, I mean look, we've identified the magic learning hour for the middle east and APAC, which is eight o'clock in the morning in Istanbul, right. Is 5:00 PM in Auckland, it's quite fun trying to work out like what this optimum magic learning hour is. What's incredible is we teach in that time and that opens up the whole of the middle east and the whole of APAC, right, right down to Australia. And so once we're teaching the curriculum in those two slots, that means literally you can have teams in any country in the world, I think apart from Hawaii, you can actually access our live learning products in work time and that's incredibly powerful. So we have so many like axis of growth, we've got single users as I mentioned, but really Dave that's single users we'll be winning from the enterprise and that will represent pipeline that we could then potentially convert as well. And look, you make a very good point. You know, we've seen students are now leaving university with over $100,000 dollars in debt. We've got a massive, massive debt problem here in the US with student debt. You could absolutely sign up to our platform at let's say a hundred bucks a month, right. And probably within six months, gain enough knowledge and skill to walk into a $60,000 a year based salary job as an SDR, that's a huge entry level salary. And you could do that without even going to university. So there could be a time here where we become a really viable alternative to actually even going to university. >> I love it. The cost education going through the roof, it's out of reach for so many people. Paul, congratulations on the progress, the fresh funding. Great to have you back in "The Cube." We'd love to have you back and follow your ascendancy. I think great things ahead for you guys. >> Thank you very much, Dave. >> All right, and thank you for watching. This is Dave Vellante for "The Cube, we'll see you next time. (upbeat music)

>> Narrator: From around the globe it's theCUBE, with digital coverage of AWS re:Invent 2020. Special coverage sponsored by AWS Global Partner Network. >> Hello and welcome to theCUBE Virtual and our coverage of AWS re:Invent 2020 with special coverage of APN partner experience. We are theCUBE Virtual and I'm your host, Justin Warren. And today I'm joined by Ed Walsh, CEO of ChaosSearch. Ed, welcome to theCUBE. >> Well thank you for having me, I really appreciate it. >> Now, this is not your first time here on theCUBE. You're a regular here and I've loved it to have you back. >> I love the platform you guys are great. >> So let's start off by just reminding people about what ChaosSearch is and what do you do there? >> Sure, the best way to say is so ChaosSearch helps our clients know better. We don't do that by a special wizard or a widget that you give to your, you know, SecOp teams. What we do is a hard work to give you a data platform to get insights at scale. And we do that also by achieving the promise of data lakes. So what we have is a Chaos data platform, connects and indexes data in a customer's S3 or glacier accounts. So inside your data lake, not our data lake but renders that data fully searchable and available for analysis using your existing tools today 'cause what we do is index it and publish open API, it's like API like Elasticsearch API, and soon SQL. So give you an example. So based upon those capabilities were an ideal replacement for a commonly deployed, either Elasticsearch or ELK Stack deployments, if you're hitting scale issues. So we talk about scalable log analytics, and more and more people are hitting these scale issues. So let's say if you're using Elasticsearch ELK or Amazon Elasticsearch, and you're hitting scale issues, what I mean by that is like, you can't keep enough retention. You want longer retention, or it's getting very expensive to keep that retention, or because the scale you hit where you have availability, where the cluster is hard to keep up running or is crashing. That's what we mean by the issues at scale. And what we do is simply we allow you, because we're publishing the open API of Elasticsearch use all your tools, but we save you about 80% off your monthly bill. We also give you an, and it's an and statement and give you unlimited retention. And as much as you want to keep on S3 or into Glacier but we also take care of all the hassles and management and the time to manage these clusters, which ends up being on a database server called leucine. And we take care of that as a managed service. And probably the biggest thing is all of this without changing anything your end users are using. So we include Kibana, but imagine it's an Elastic API. So if you're using API or Kibana, it's just easy to use the exact same tools used today, but you get the benefits of a true data lake. In fact, we're running now Elasticsearch on top of S3 natively. If that makes it sense. >> Right and natively is pretty cool. And look, 80% savings, is a dramatic number, particularly this year. I think there's a lot of people who are looking to save a few quid. So it'd be very nice to be able to save up to 80%. I am curious as to how you're able to achieve that kind of saving though. >> Yeah, you won't be the first person to ask me that. So listen, Elastic came around, it was, you know we had Splunk and we also have a lot of Splunk clients, but Elastic was a more cost effective solution open source to go after it. But what happens is, especially at scale, if it's fall it's actually very cost-effective. But underneath last six tech ELK Stack is a leucine database, it's a database technology. And that sits on our servers that are heavy memory count CPU count in and SSDs. So you can do on-prem or even in the clouds, so if you do an Amazon, basically you're spinning up a server and it stays up, it doesn't spin up, spin down. So those clusters are not one server, it's a cluster of those servers. And typically if you have any scale you're actually having multiple clusters because you don't dare put it on one, for different use cases. So our savings are actually you no longer need those servers to spin up and you don't need to pay for those seen underneath. You can still use Kibana under API but literally it's $80 off your bill that you're paying for your service now, and it's hard dollars. So it's not... And we typically see clients between 70 and 80%. It's up to 80, but it's literally right within a 10% margin that you're saving a lot of money, but more importantly, saving money is a great thing. But now you have one unified data lake that you can have. You used to go across some of the data or all the data through the role-based access. You can give different people. Like we've seen people who say, hey give that, help that person 40 days of this data. But the SecOp up team gets to see across all the different law. You know, all the machine generated data they have. And we can give you a couple of examples of that and walk you through how people deploy if you want. >> I'm always keen to hear specific examples of how customers are doing things. And it's nice that you've thought of drawn that comparison there around what what cloud is good for and what it isn't is. I'll often like to say that AWS is cheap to fail in, but expensive to succeed. So when people are actually succeeding with this and using this, this broad amount of data so what you're saying there with that savings I've actually got access to a lot more data that I can do things with. So yeah, if you could walk through a couple of examples of what people are doing with this increased amount of data that they have access to in EKL Search, what are some of the things that people are now able to unlock with that data? >> Well, literally it's always good for a customer size so we can go through and we go through it however it might want, Kleiner, Blackboard, Alert Logic, Armor Security, HubSpot. Maybe I'll start with HubSpot. One of our good clients, they were doing some Cloud Flare data that was one of their clusters they were using a lot to search for. But they were looking at to look at a denial service. And they were, we find everyone kind of at scale, they get limited. So they were down to five days retention. Why? Well, it's not that they meant to but basically they couldn't cost-effectively handle that in the scale. And also they're having scale issues with the environment, how they set the cluster and sharding. And when they also denial service tech, what happened that's when the influx of data that is one thing about scale is how fast it comes out, yet another one is how much data you have. But this is as the data was coming after them at denial service, that's when the cluster would actually go down believe it or not, you know right. When you need your log analysis tools. So what we did is because they're just using Kibana, it was easy swap. They ran in parallel because we published the open API but we took them from five days to nine days. They could keep as much as they want but nine days for denial services is what they wanted. And then we did save them in over $4 million a year in hard dollars, What they're paying in their environment from really is the savings on the server farm and a little bit on the Elasticsearch Stack. But more importantly, they had no outages since. Now here's the thing. Are you talking about the use case? They also had other clusters and you find everyone does it. They don't dare put it on one cluster, even though these are not one server, they're multiple servers. So the next use case for CloudFlare was one, the next QS and it was a 10 terabyte a day influx kept it for 90 days. So it's about a petabyte. They brought another use case on which was NetMon, again, Network Monitoring. And again, I'm having the same scale issue, retention area. And what they're able to do is easily roll that on. So that's one data platform. Now they're adding the next one. They have about four different use cases and it's just different clusters able to bring together. But now what they're able to do give you use cases either they getting more cost effective, more stability and freedom. We say saves you a lot of time, cost and complexity. Just the time they manage that get the data in the complexities around it. And then the cost is easy to kind of quantify but they've got better but more importantly now for particular teams they only need their access to one data but the SecOP team wants to see across all the data. And it's very easy for them to see across all the data where before it was impossible to do. So now they have multiple large use cases streaming at them. And what I love about that particular case is at one point they were just trying to test our scale. So they started tossing more things at it, right. To see if they could kind of break us. So they spiked us up to 30 terabytes a day which is for Elastic would even 10 terabytes a day makes things fall over. Now, if you think of what they just did, what were doing is literally three steps, put your data in S3 and as fast as you can, don't modify, just put it there. Once it's there three steps connect to us, you give us readability access to those buckets and a place to write the indexy. All of that stuff is in your S3, it never comes out. And then basically you set up, do you want to do live or do you want to do real time analysis? Or do you want to go after old data? We do the rest, we ingest, we normalize the schema. And basically we give you our back and the refinery to give the right people access. So what they did is they basically throw a whole bunch of stuff at it. They were trying to outrun S3. So, you know, we're on shoulders of giants. You know, if you think about our platform for clients what's a better dental like than S3. You're not going to get a better cross curve, right? You're not going to get a better parallelism. And so, or security it's in your, you know a virtual environment. But if you... And also you can keep data in the right location. So Blackboard's a good example. They need to keep that in all the different regions and because it's personal data, they, you know, GDPR they got to keep data in that location. It's easy, we just put compute in each one of the different areas they are. But the net net is if you think that architecture is shoulders of giants if you think you can outrun by just sheer volume or you can put in more cost-effective place to keep long-term or you think you can out store you have so much data that S3 and glacier can't possibly do it. Then you got me at your bigger scale at me but that's the scale we'r&e talking about. So if you think about the spiked our throughput what they really did is they try to outrun S3. And we didn't pick up. Now, the next thing is they tossed a bunch of users at us which were just spinning up in our data fabric different ways to do the indexing, to keep up with it. And new use cases in case they're going after everyone gets their own worker nodes which are all expected to fail in place. So again, they did some of that but really they're like you guys handled all the influx. And if you think about it, it's the shoulders of giants being on top of an Amazon platform, which is amazing. You're not going to get a more cost effective data lake in the world, and it's continuing to fall in price. And it's a cost curve, like no other, but also all that resiliency, all that security and the parallelism you can get, out of an S3 Glacier is just a bar none is the most scalable environment, you can build an environment. And what we do is a thin layer. It's a data platform that allows you to have your data now fully searchable and queryable using your tools >> Right and you, you mentioned there that, I mean you're running in AWS, which has broad experience in doing these sorts of things at scale but on that operational management side of things. As you mentioned, you actually take that off, off the hands of customers so that you run it on their behalf. What are some of the areas that you see people making in trying to do this themselves, when you've gone into customers, and brought it into the EKL Search platform? >> Yeah, so either people are just trying their best to build out clusters of Elasticsearch or they're going to services like Logz.io, Sumo Logic or Amazon Elasticsearch services. And those are all basically on the same ELK Stack. So they have the exact same limits as the same bits. Then we see people trying to say, well I really want to go to a data lake. I want to get away from these database servers and which have their limits. I want to use a data Lake. And then we see a lot of people putting data into environments before they, instead of using Elasticsearch, they want to use SQL type tools. And what they do is they put it into a Parquet or Presto form. It's a Presto dialect, but it into Parquet and structure it. And they go a lot of other way to, Hey it's in the data lake, but they end up building these little islands inside their data lake. And it's a lot of time to transform the data, to get it in a format that you can go after our tools. And then what we do is we don't make you do that. Just literally put the data there. And then what we do is we do the index and a polish API. So right now it's Elasticsearch in a very short time we'll publish Presto or the SQL dialect. You can use the same tool. So we do see people, either brute forcing and trying their best with a bunch of physical servers. We do see another group that says, you know, I want to go use an Athena use cases, or I want to use a there's a whole bunch of different startups saying, I do data lake or data lake houses. But they are, what they really do is force you to put things in the structure before you get insight. True data lake economics is literally just put it there, and use your tools natively to go after it. And that's where we're unique compared to what we see from our competition. >> Hmm, so with people who have moved into ChaosSearch, what's, let's say pick one, if you can, the most interesting example of what people have started to do with, with their data. What's new? >> That's good. Well, I'll give you another one. And so Armor Security is a good one. So Armor Security is a security service company. You know, thousands of clients doing great I mean a beautiful platform, beautiful business. And they won Rackspace as a partner. So now imagine thousand clients, but now, you know massive scale that to keep up with. So that would be an example but another example where we were able to come in and they were facing a major upgrade of their environment just to keep up, and they expose actually to their customers is how their customers do logging analytics. What we're able to do is literally simply because they didn't go below the API they use the exact same tools that are on top and in 30 days replaced that use case, save them tremendous amount of dollars. But now they're able to go back and have unlimited retention. They used to restrict their clients to 14 days. Now they have an opportunity to do a bunch of different things, and possible revenue opportunities and other. But allow them to look at their business differently and free up their team to do other things. And now they're, they're putting billing and other things into the same environment with us because one is easy it's scale but also freed up their team. No one has enough team to do things. And then the biggest thing is what people do interesting with our product is actually in their own tools. So, you know, we talk about Kibana when we do SQL again we talk about Looker and Tableau and Power BI, you know, the really interesting thing, and we think we did the hard work on the data layer which you can say is, you know I can about all the ways you consolidate the performance. Now, what becomes really interesting is what they're doing at the visibility level, either Kibana or the API or Tableau or Looker. And the key thing for us is we just say, just use the tools you're used to. Now that might be a boring statement, but to me, a great value proposition is not changing what your end users have to use. And they're doing amazing things. They're doing the exact same things they did before. They're just doing it with more data at bigger scale. And also they're able to see across their different machine learning data compared to being limited going at one thing at a time. And that getting the correlation from a unified data lake is really what we, you know we get very excited about. What's most exciting to our clients is they don't have to tell the users they have to use a different tool, which, you know, we'll decide if that's really interesting in this conversation. But again, I always say we didn't build a new algorithm that you going to give the SecOp team or a new pipeline cool widget that going to help the machine learning team which is another API we'll publish. But basically what we do is a hard work of making the data platform scalable, but more importantly give you the APIs that you're used to. So it's the platform that you don't have to change what your end users are doing, which is a... So we're kind of invisible behind the scenes. >> Well, that's certainly a pretty strong proposition there and I'm sure that there's plenty of scope for customers to come and and talk to you because no one's creating any less data. So Ed, thanks for coming out of theCUBE. It's always great to see you here. >> Know, thank you. >> You've been watching theCUBE Virtual and our coverage of AWS re:Invent 2020 with special coverage of APN partner experience. Make sure you check out all our coverage online, either on your desktop, mobile on your phone, wherever you are. I've been your host, Justin Warren. And I look forward to seeing you again soon. (soft music)

(upbeat music) >> From theCUBE studios in Palo Alto, in Boston, connecting with thought leaders all around the world. This is a Cube conversation. >> Hi everybody, this is Dave Vellante. And as you know, I've been running a CxO series in this COVID economy. And as we go into the post-isolation world, really want to focus and expand our scope and really look at startups. And of course, we're going to look at startups, let's follow the money. And I want to start with the investor. Mark Roberge is here. He's the managing director at Stage 2 capital. He's a professor at the Harvard Business School, former CRO over at HubSpot. Mark, great to see you. Thanks for coming on. >> Yeah, you bet, Dave. Thanks for having me. >> So I love that, you know... looking at your career a little bit, on your LinkedIn and following some of your videos, I love the fact that you did, and now you teach and you're also applying it with Stage 2 Capital. Tell us a little bit more about both of your career and Stage 2. >> Yeah, I mean, a lot of it's a bit serendipitous, especially last 10 years, but I've always had this learn, do, teach framework in my, in mind as I go through the decades of my career, you know, like you're probably like 80% learning in your twenties, early thirties and you know, 20% doing. Then, you know, I think my thirties was like leading the HubSpot sales team, a lot of doing, a little bit of teaching, you know, kind of hopping into different schools, et cetera, and also doing a lot of, some writing. And now like, I'm teaching it. I think investing kind of falls into that too, you know, where you've got this amazing opportunity to meet, the next generation of, of extraordinary entrepreneurs and engage with them. So yeah, that, that has been my career. You know, Dave, I've been a, passionate entrepreneur since 22 and then, the last one I did was HubSpot and that led to just an opportunity to build out one of the first sales teams in a complete inside environment, which opened up the doors for a data driven mindset and all this innovation that led to a book that led to recruitment on HBS's standpoint, to like come and teach that stuff, which was such a humbling honor to pursue. And that led to me a meeting my co-founder, Jay Po, of Stage 2 Capital, who was a customer to essentially start the first VC fund, running back by sales and marketing leaders, which was his vision. But when he proposed it to me, addressed a pretty sizeable void, that I saw, in the entrepreneur ecosystem that I thought could make a substantial impact to the success rate of startups. >> Great, I want to talk a little bit about how you guys compete and what's different there, but you know, I've read some of your work, looked at some of your videos, and we can bring that into the conversation. But I think you've got some real forward-thinking for example, on the, you know, the best path to the upper right. The upper right, being that, that xy-axis on growth and adoption, you know, do you go for hyper-growth or do you go for adoption? How you align sales and marketing, how you compensate salespeople. I think you've got some, some leading-edge thinking on that, that I'd love for you to bring into the conversation, but let's start with Stage 2. I mean, how do you compete with the big guys? What's different about Stage 2 Capital? >> Yeah, I mean, first and foremost, we're a bunch of sales and marketing and execs. I mean, our backing is, a hundred plus CROs, VPs of marketing, CMOs from, from the public companies. I mean, Dropbox, LinkedIn, Oracle, Salesforce, SurveyMonkey, Lyft, Asana, I mean, just pick a unicorn, we probably have some representation from it. So that's, a big part of how we compete, is most of the time, when a rocket ship startup is about to build a sales team, one of our LPs gets a call. And because of that, we get a call, right. And, and so there's, we're just deep in, in helping... So first off, assess the potential and risks of a startup in their current, go to market design, and then really, you know, stepping in, not just with capital, but a lot of know-how in terms of, you know, how to best develop this go-to-market for their particular context. So that's a big part of our differentiation. I don't think we've ever lost a deal that we tried to get into, you know, for that reason, just because we come in at the right stage, that's right for our value prop. I'd say Dave, the biggest, sort of difference, in our investing theme. And this really comes out of like, post HubSpot. In addition to teaching the HBS, I did parachute into a different startup every quarter, for one day, where you can kind of like assess their go-to-market, looking for, like, what is the underlying consistency of those series A businesses that become unicorns versus those that flatline. And if I, you know, I've now written like 50 pages on it, which I, you know, we can, we can highlight to the crew, but the underlying cliffnotes is really, the avoidance of a premature focus on top line revenue growth, and an acute focus early on, on customer attention. And, I think like, for those of you, who run in that early stage venture community these days, and especially in Silicon Valley, there's this like, triple, triple, double, double notion of, like year one, triple revenue, year two, triple revenue, year three, double revenue, year four, double revenue, it's kind of evolved to be like the holy grail of what your objectives should be. And I do think like there is a fraction of companies that are ready for that and a large amount of them that, should they pursue that path, will lead to failure. And, and so, we take a heavy lens toward world-class customer retention as a prerequisite, to any sort of triple, triple, double, double blitzscaling type model. >> So, let me ask you a couple of questions there. So it sounds like your LPs are heavily, not only heavily and financially invested, but also are very active. I mean, is that a, is that a fears thing? How active are the LPs in reality? I mean, they're busy people. They're they're software operators. >> Yeah. >> Do they really get involved in businesses? >> Absolutely. I mean, half of our deals that we did in fund one came from the LPs. So we get half of our funnel, comes from LPs. Okay. So it's always like source-pick-win-support. That's like, what basically a VC does. And our LPs are involved in every piece of that. Any deal that we do, we'll bring in four or five of our LPs to help us with diligence, where they have particular expertise in. So we did an insuretech company in Q4, one of our LPs runs insurance practice at Workday. And this particular play he's selling it to big insurance companies. He was extremely helpful, to understand that domain. Post investment, we always bring in four or five LPs to go deeper than I can on a particular topic. So one of our plays is about to stand up in account based marketing, you know, capability. So we brought in the CMO, a former CMO at Rapid7 and the CMO at Unisys, both of which have, stood in, stood up like, account based marketing practices, much more deeply, than I could. You know of course, we take the time to get to know our LPs and understand both their skills, and experiences as well as their willingness to help, We have Jay Simons, who's the President of Atlassian. He doesn't have like hours every quarter, he's running a $50 billion company, right? So we have Brian Halligan, the CEO of HubSpot, right? He's running a $10 billion company now. So, we just get deal flow from them and maybe like an event once or twice a year, versus I would say like 10 to 20% of our LPs are like that. I would say 60% of them are active operators who are like, "You know what? I just miss the early days, and if I could be active with one or two companies a quarter, I would love that." And I would say like a quarter of them are like semi-retired and they're like, they're choosing between helping our company and being on the boat or the golf course. >> Is this just kind of a new model? Do you see having a different philosophy where you want to have a higher success rate? I mean, of course everybody wants to have a, you know, bat a thousand. >> Yeah. >> But I wonder if you could address that. >> Yeah. I don't think it, I'm not advocating slower growth, but just healthier growth. And it's just like an extra, it's really not different than sort of the blitzscaling oriented San Francisco VC, okay? So, you know, I would say when we were doing startups in the nineties, early 2000s before The Lean Startup, we would have this idea and build it in a room for a year and then sell it in parallel, basically sell it everywhere and Eric Ries and The Lean Startup changed all that. Like he introduced MVPs and pivots and agile development and we quickly moved to, a model of like, yeah, when you have this idea, it's not like... You're really learning, keep the team small, keep the burn low, pivot, pivot, pivot, stay agile and find product-market fit. And once you do that, scale. I would say even like, West Coast blitzscaling oriented VCs, I agree with that. My only take is... We're not being scientifically rigorous, on that transition point. Go ask like 10 VCs or 10 entrepreneurs, what's product-market fit, and you'll get 10 different answers. And you'll get answers like when you have lots of sales, I just, profoundly disagree with that. I think, revenue in sales has very little to do with product-market fit. That's like, that's like message-market fit. Like selling ice to Eskimos. If I can sell ice to Eskimos, it doesn't mean that product-market fit. The Eskimos didn't need the ice. It just means I was good at like pitching, right? You know, other folks talk about like, having a workable product in a big market. It's just too qualitative. Right? So, that's all I'm advocating is, that, I think almost all entrepreneurs and investors agree, there's this incubation, rapid learning stage. And then there's this thing called product-market fit, where we switch to rapid scale. And all I'm advocating is like more scientist science and rigor, to understanding some sequences that need to be checked off. And a little bit more science and rigor on what is the optimal pace of scale. Because when it comes to scale, like pretty much 50 out of 50 times, when I talk to a series A company, they have like 15 employees, two sales reps, they got to like 2 million in revenue. They raise an 8 million-dollar round in series A, and they hired 12 salespeople the next month. You know, and Dave, you and your brother, who runs a large sales team, can really understand how that's going to failure almost all the time. (Dave mumbles) >> Like it's just... >> Yeah it's a killer. >> To be able to like absorb 10 reps in a month, being a 50, it's just like... Who even does all those interviews? Who onboards them? Who manages them? How do we feed them with demand? Like these are some of the things I just think, warrant more data and science to drive the decisions on when and how fast to scale. >> Mark, what is the key indicator then, of product-market fit? Is it adoption? Is it renewal rates? >> Yeah. It's retention in my opinion. Right? So, so the, the very simple framework that I require is you're ready to scale when you have product-market and go to market-fit. And let's be, extremely precise, and rigorous on the definitions. So, product-market fit for me, the best metric is retention. You know, that essentially means someone not only purchased your offering, but experienced your offering. And, after that experience decided to repurchase. Whether they buy more from you or they renew or whatever it is. Now, the problem with it is, in many, like in the world we live inside's, it's like, the retention rate of the customers we acquire this quarter is not evident for a year. Right, and we don't have a year to learn. We don't have a year to wait and see. So what we have to do is come up with a leading indicator to customer retention. And that's something that I just hope we see more entrepreneurs talking about, in their product market fit journey. And more investors asking about, is what is your lead indicator to customer retention? Cause when that gets checked off, then I believe you have product-market fit, okay? So, there's some documentation on some unicorns that have flirted with this. I think Silicon Valley calls it the aha moment. That's great. Just like what. So like Slack, an example, like, the format I like to use for the lead indicator of customer retention is P percent of customers, do E event, in T time, okay? So, it basically boils it down to those three variables, P E T. So if we bring that to life and humanize it, 70% of the customers, we sign up, this is Slack, 70% of the customers who sign up, send 2000 team messages in 30 days, if that happens, we have product-market fit. I like that a lot more, than getting to a million in revenue or like having a workable product in a big market. Dropbox, 85% of customers, share one file in one hour. HubSpot, I know this was the case, 75% of customers, use five or more of the 25 features in the platform, within 60 days. Okay? P percent, do E event, in T time. So, if we can just format that, and look at that through customer cohorts, we often get visibility into, into true product market-fit within weeks, if not like a month or two. And it's scientifically, data-driven in terms of his foundation. >> Love it. And then of course, you can align sales compensation, you know, with that retention. You've talked a lot about that, in some of your work. I want to get into some of the things that stage two is doing. You invest in SaaS companies. If I understand it correctly, it's not necessarily early stage. You're looking for companies that have sort of achieved some degree of revenue and now need help. It needs some operational help and scaling. Is that correct? >> Yeah. Yeah. So it's a little bit broader in size, as any sort of like B2B software, any software company that's scaling through a sales team. I mean, look at our backers and look at my background. That's, that's what we have experience in. So not really any consumer plays. And yeah, I mean, we're not, we have a couple product LPs. We have a couple of CFO type LPs. We have a couple like talent HR LPs, but most of us are go-to-market. So we don't, you know, there's awesome seed funds out there that help people set up their product and engineering team and go from zero to one in terms of the MVP and find product-market fit. Right? We like to come in right after that. So it's usually like between the seed and the A, usually the revenue is between half a million and 1.5 million. And of course we put an extraordinary premium on customer retention, okay? Whereas I think most of our peers put an extraordinary premium on top line revenue growth. We put an extraordinary premium on retention. So if I find a $700,000 business that, you know, has whatever 50, 70 customers, you know, depending on their ticket size, it has like North of 90% local retention. That's super exciting. Even if they're only growing like 60%, it's super exciting. >> What's a typical size of investments. Do you typically take board seats or not? >> Yeah. We typically put in like between like seven hundred K, one and a half million, in the first check and then have, larger amounts for follow on. So on the A and the B. We try not to take board's seats to be honest with you, but instead the board observers. It's a little bit selfish in terms of our funds scale. Like the general counsel from other venture capitalists is of course, like, the board seat is there for proper governance in terms of like, having some control over expenditures and acquisition conversations, et cetera, or decisions. But a lot of people who have had experience with boards know that they're very like easy and time efficient when the company is going well. And there are a ton of work when the company is not going well. And it really hurts the scale, especially on a smaller fund like us. So we do like to have board observers seats, and we go to most of the board meetings so that our voice is heard. But as long as there's another fund in there that, has, world-class track record in terms of, holding proper governance at the board level, we prefer to defer to them on that. >> All right, so the COVID lock down, hit really in earnest in March, of course, we all saw the Sequoia memo, The Black Swan memo. You were, I think it HubSpot, when, you remember the Rest In Peace Good Times memo, came out very sort of negative, put up all over the industry, you know, stop spending. But there was some other good advice in there. I don't mean to sort of, go too hard on that, but, it was generally a negative sentiment. What was your advice to your portfolio companies, when COVID hit, what were you telling them? >> Yeah, I summarized this in our lead a blog article. We kicked off our blog, which is partially related to COVID in April, which has kind of summarize these tips. So yes, you are correct, Dave. I was running sales at HubSpot in '08 when we had last sort of major economic, destabilization. And I was freaking out, you know (laughs briefly) at the time we were still young, like 20, 30 reps and numbers to chase. And... I was, actually, after that year, looking back, we are very fortunate that we had a value prop that was very recession-proof. We were selling to the small business community, who at the time was cutting everything except new ways to generate sales. And we happen to have the answer to that and it happened to work, right? So it showed me that, there's different levels of being recession proof. And we accelerated the raise of our second fund for stage two with the anticipation that there would be a recession, which, you know, in the venture world, some of the best things you could do is close a fund and then go into a recession, because, there's more deals out there. The valuations are lower and it's much easier to understand, nice to have versus must have value props. So, the common theme I saw in talking to my peers who looked back in the '01 crisis, as well as the '08 crisis, a year later was not making a bolder decision to reorient their company in the current times. And usually on the go-to-market, that's two factors, the ICP who you're selling to, ideal customer profile and the CVP, what your message is, what's your customer value prop. And that was really, in addition to just stabilizing cash positions and putting some plans in there. That was the biggest thing we pushed our portfolio on was, almost like going through the exercise, like it's so hard as a human, to have put like nine months into a significant investment leading up to COVID and now the outcome of that investment is no longer relevant. And it's so hard to let that go. You know what I mean? >> Yeah. >> But you have to, you have to. And now it's everything from like, you spent two years learning how to sell to this one persona. And now that persona is like, gyms, retail and travel companies. Like you've got to let that go. (chuckle simultaneously) You know what I mean? Like, and, you know, it's just like... So that's really what we had to push folks on was just, you know, talking to founders and basically saying this weekend, get into a great headspace and like, pretend like you were parachuted into your company as a fresh CEO today. And look around and appreciate the world and what it is. What is this world? What are the buyers talking about? Which markets are hot, which markets are not, look at the assets that you have, look at your product, look at your staff, look at your partners, look at your customer base, and come up with a strategy from the ground up based on that. And forget about everything you've done in the last year. Right? And so, that's really what we pushed hard on. And in some cases, people just like jumped right on it. It was awesome. We had a residential real estate company that within two weeks, stood up a virtual open house module that sold like hotcakes. >> Yeah. >> That was fantastic execution. And we had other folks that we had to have like three meetings with to push them deep enough, to go more boldly. But that, was really the underlying pattern that I saw in past, recessions and something I pushed the portfolio on, is just being very bold on your pivots. >> Right? So I wanted to ask you how your portfolio companies are doing. I'm imagining you saw some looked at this opportunity as a tailwind. >> Yeah. >> You mentioned the virtual, open house, a saw that maybe were exposed, had, revenue exposure to hard-hit industries and others kind of in the middle. How are your portfolio companies doing? >> Yes, strong. I'm trying to figure out, like, of course I'm going to say that, but I'm trying to figure out like how to provide quant, to just demonstrate that. We were fortunate that we had no one, and this was just dumb luck. I mean, we had no one exclusively selling to like travel, or, restaurants or something. That's just bad luck if you were, and we're fortunate that we got a little lucky there, We put a big premium, obviously we had put a big premium on customer retention. And that, we always looked at that through our recession proof lens at all our investments. So I think that helped, but yeah, I mean, we've had, first off, we made one investment post COVID. That was the last investment on our first fund and that particular company, March, April, May, their results were 20% higher than any month in history. Those are the types of deals we're seeing now is like, you literally find some deals that are accelerating since COVID and you really just have to assess if it's permanent or temporary, but that one was exciting. We have a telemedicine company that's just like, really accelerating post COVID, again, luck, you know, in terms of just their alignment with the new world we're living in. And then, jeez! I mean, we've had, I think four term sheets, for markups in our portfolio since March. So I think that's a good sign. You know, we only made 11 investments and four of them, either have verbal or submitted term sheets on markups. So again, I feel like the portfolio is doing quite well, and I'm just trying to provide some quantitative measures. So it doesn't feel like a political answer. (Mark chuckles) >> Well, thank you for that, but now, how have you, or have you changed your sort of your thesis post COVID? Do you feel like your... >> Sure. >> Your approach was sort of geared towards, you know, this... >> Yeah. >> Post COVID environment? But what changes have you made. >> A little bit, like, I think in any bull market, generally speaking, there's just going to be a lot of like triple, triple, double, double blitzscaling, huge focus on top-line revenue growth. And in any down market, there's going to be a lot of focus on customer retention unit economics. Now we've always invested in the latter, so that doesn't change much. There's a couple of things that have changed. Number one, we do look for acceleration post COVID. Now, that obviously we were not, we weren't... That lens didn't exist pre-COVID, So in addition to like great retention, selling through a sales team, around the half million to a million revenue, we want to see acceleration since COVID and we'll do diligence to understand if that's a permanent, or a temporary advantage. I would say like... Markets like San Francisco, I think become more attractive in post COVID. There's just like, San Francisco has some magic happening there's some VC funds that avoid it, cause it's too expensive. There's some VC funds that only invest in San Francisco, because there's magic happening. We've always just been, you know... we have two portfolio companies there that have done well. Like we look at it and if it's too expensive, we have to avoid it. But we do agree that there's magic happening. I did look at a company last week. (chuckles inaudibly) So Dave, there are 300K in revenue, and their last valuation is 300 million. (both chuckle) >> Okay, so why is San Francisco more attractive, Mark? >> Well, I mean and those happened in Boston too. >> We looked at... (Mark speaks inaudibly) >> I thought you were going to tell me the valuations were down. (Dave speaks inaudibly) >> Here's the deal all right, sometimes they do, sometimes they don't and this is one, but in general, I think like they have come down. And honestly, the other thing that's happened is good entrepreneurs that weren't raising are now raising. Okay? So, a market like that I think becomes more attractive. The other thing that I think that happens is your sort of following strategies different. Okay so, there is some statistical evidence that, you know, obviously we're coming out of a bear market, a bullish market in, in both the public and the private equities. And there's been a lot of talk about valuations in the private sector is just outrageous. And so, you know, we're fortunate that we come in at this like post seed, pre-A, where it's not as impacted. It is, but not as or hasn't been, but because there's so many more multibillion-dollar funds that have to deploy 30 to 50 million per investment, there's a lot of heating up that's happened at that stage. Okay? And so pre COVID, we would have taken advantage of that by taking either all or some of our money off the table, in these following growth rounds. You know, as an example, we had a company that we made an investment with around 30 million evaluation and 18 months later, they had a term sheet for 500. So that's a pretty good return in 18 months. And you know, that's an expensive, you know, so that that's like, wow, you know, we probably, even though we're super bullish on the company, we may want to take off a 2X exposition... >> Yeah. >> And take advantage of the secondaries. And the other thing that happens here, as you pointed out, Dave is like, risk is not, it doesn't become de-risk with later rounds. Like these big billion dollar funds come in, they put pressure on very aggressive strategic moves that sometimes kills companies and completely outside of our control. So it's not that we're not bullish on the company, it's just that there's new sets of risks that are outside of the scope of our work. And so, so that that's probably like a less, a lesser opportunity post COVID and we have to think longer term and have more patient capital, as we navigate the next year or so of the economy. >> Yeah, so we've got to wrap, but I want to better understand the relationship between the public markets and you've seen the NASDAQ up, which is just unbelievable when you look at what's happening in main street, and the relationship between the public markets and the private markets, are you saying, they're sort of tracking, but not really identical. I mean, what's the relationship. >> Okay, there's a hundred, there's thousands of people that are better at that than me. Like the kind of like anecdotal thoughts that I, or the anecdotal narrative that I've heard in past recessions and actually saw too, was the private market, when the public market dropped, it took nine months roughly for the private market to correct. Okay, so there was a lag. And so there's, some arguments that, that would happen here, but this is just a weird situation, right? Of like the market, even though we're going through societal crazy uncertainty, turmoil and, and tremendous tragedy, the markets did drop, but they're pretty hot right now, specifically in tech. And so there's a number of schools of thoughts there that like some people claim that tech is like the utilities companies of the eighties, where it's just a necessity and it's always going to be there regardless of the economy. Some people argue that what's happened with COVID and the remote workplace have made, you know, accelerated the adoption of tech, the inevitable adoption, and others could argue that like, you know, the worst is still the come. >> Yeah. And of course, you've got The Fed injecting so much liquidity into the system, low interest rates, Mark, last question. Give me a pro tip for entrepreneurs. (Mark Sighs) >> I would say, like, we've talked a lot about, this methodology with, you know, customer retention, really focusing there, align everything there as opposed to top line revenue growth initially. I think that the extension I do at this point is, do your diligence on your investors, and what their thoughts are on your future growth plans to see if they're aligned. Cause that, that becomes like, I think a lot of entrepreneurs, when they dig into this work, they do want to operate around it. But that becomes that much harder when you have investors that think a different way. So I would just, you know, just always keep in mind that, you know, I know it's so hard to raise money, but you know, do the diligence on your investors to understand, what they'd like to see in the next two years and how it's aligned with your own vision. >> Mark is really great having you on. I'd love to have you back and as this thing progresses, and see how it all shakes out. It really a pleasure. Thanks for coming on. >> No, thanks, Dave. I appreciate you having me on. >> And thank you everybody for watching. This is Dave Vellante for The Cube. We'll see you next time. (music plays)

(upbeat music) >> From our studios in the heart of Silicon Valley, Palo Alto, California, this is a CUBE conversation. >> Hello everyone, welcome to Palo Altos Cube Studios for CUBE Conversation. I'm John Furrier, co-host of theCUBE. We're with Kevin Ackroyd, CEO of Cision, CUBE Alumni. He's been on before. Building one of the most compelling companies that's disrupting and changing the game in Comms, advertising, PR, with Cloud technologies. Kevin, great to see you again, thanks for coming in. >> Likewise John, It's really good to be back. >> So, we haven't chatted in two years. You've been busy. Our last conversation was the beginning of 2017. Cision's done a lot of interesting things. You've got a lot of M and A under your belt. You're putting this portfolio together with Cloud technologies. Really been interesting. I really got to say I think you cracked the code on I think a new reality, a new economic reality. Also new capabilities for comms folks. Congratulations. >> Thank you, it's been a fun ride. >> So give us the update. So two years since we talked, how many deals, companies have you bought? What's the headcount, what's the revenue? Give us an update. >> In the four years, 12 acquisitions, seven of which have happened since I've been here. Up to 4,500 employees in over 40 countries. Customer count has grown to over 50,000 customers globally. Revenue's kind of gone from 500s to just shy of 800 million. A lot of leadership changes, and as you just mentioned, pretty seismic change, finally. We've certainly been the catalyst and the cattle prod for that seismic change around tech, data, measurement and analytics finally becoming mature and adopted inside this line of business like the Chief Communication Officer, the earn media folks. To say that they were not tech savvy a few years ago would be an understatement. So, a lot's been going on. >> Yeah, and certainly the trend is your friend, in my opinion, for you. But I think the reality is not yet upon people's general mindset. It's coming quickly, so if you look at some of the big trends out there. Look at fake news, look at Facebook, look at the Google effect. Elizabeth Warren wants to break up Big Tech, Amazon. Cloud computing, in that time period that you were, prior to just going to Cision, you had Oracle Cloud, done a lot of great things on the Marketing Cloud side. But the timing of Cloud computing, the timing of how media has changed. There's not many journalists anymore. We had Andy Cunningham, a legendary industry veteran, formerly of Cunningham Communications. He did the PR for Steve Jobs. You said, there's no more journalists, a few left, but you got to tell your story direct to the consumer. >> You do. >> This is now a new marketing phenomenon. This is a tailwind for you at Cision because you guys, although put these cubbies together, have a unique vision around bringing brand value advertising at PR economics. >> Yeah, that's a good way to put it. >> Tell us the vision of Cision and specifically the shift that's happening. Why are you guys important? What wave are you riding? >> So, there's a couple shifts, John. You and I have talked about this in previous programs There's this shift of the line of business, having to work in a whole bunch of non-integrated point solutions. The CFO used to live in 17 different applications from 17 vendors. That's all squished together. Now I buy from one Cloud platform, right, from Oracle or SAP. Same thing happened in Human Capital Management. 22 things squished into the Cloud, one from Workday, right. Same thing happened, you had 25 different things for sales and service. That all squished together, into one CRM in the Cloud, I buy from Salesforce, right. And our last rodeo, the early part of this stack, it was me and Adobe battling it out for the right to go squish the entire the LUMAscape into a marketing cloud, right, so there could be one ring to rule them all for the CMO. So, it happens in every single category. It just hasn't had over here, happened on the earned media side and the Chief Communications Officer. So, bringing the tech stack so that now we are for the CCO what Adobe is for the CMO what Salesforce is for the CRO, Workday is for the CHRO. That has to happen. You can't do, you can't manage it this way without sophisticated tech, without automation, without integration, you can't do it. The second thing that had to happen, especially in marketing and advertising, they all figured out how to get revenue credit. Advertising was a slow single-digit CAGR industry for 50 years. And then something happened. After 5% CAGR for 50 years, and then something happened over the next 10 years. Digital paid went from like 15 billion to 150 billion. And what happened is that old, I know half my advertising is wasted on this one half. That went bye-bye. Now I know immediately, down to the page, down the ad unit, down to this, exactly what worked, right. When I was able to put Pixels on ads, John, you'd go to that page, Pixel would go on you, It would follow you around If you ended up putting something in the e-commerce shop that ad got credit. I'm not saying that's right, I'm just saying that's how the entire-- >> But that's how the infrastructure would let you, allowed you, it enabled you to do that. Then again, paid advertising, paid search, paid advertising, that thing has created massive value in here. >> Massive value. But my buyer, right, so the person that does the little ad on the most regional tech page got credit. My buyer that got Bob Evans, the Cloud King, to write an article about why Microsoft is going to beat AWS, he's a credible third party influencer, writing objectively. That article's worth triple platinum and has more credibility than 20,000 Microsoft sales reps. We've never, until Cision, well let's Pixel that, let's go figure out how many of those are the target audience. Let's ride that all the way down to the lead form that's right. Basically it's super simple. Nobody's ever tracked the press releases, the articles or any of the earned media content, the way people have tracked banner ads or e-commerce emails. Therefore this line of business never get revenue credit. It stayed over here in the OpEx pile where things like commerce and advertising got dumped onto the revenue pile. Well, you saw the crazy investment shift. So, that's really the more important one, is Comms is finally getting quantified ROI and business's attribution like their commerce and advertising peers for the first time ever in 2018 via what Cision's rolled out. That's the exciting piece. >> I think, I mean, I guess what I hear you saying is that for the first time, the PR actually can be measured, similar to how advertising >> You got it. >> Couldn't be measured then be measured. Now PR or communications can be measured. >> They get measured the same way. And then one other thing. That ad, that press release, down to the business event. This one had $2 million dollars of ad spend, this one had no ad spend. When it goes to convert, in CRM or it goes to convert on a website, this one came from banner ad, this one came from credible third party content. Guess which one, not only had zero ad spend instead of $2 million in ad spend. Guess which one from which source actually converts better. It's the guy that chose to read credible third-party article. He's going to convert in the marketing system way better that somebody who just clicked on the ad. >> Well certainly, I'm biased-- >> So all the way down the funnel, we're talking about real financial impact based on capturing earned media ID, which is pretty exciting. >> Well, I think the more exciting thing is that you're basically taking a value that is unfunded quote by the advertising firm, has no budget basically, or thin budgets, trying to hit an organic, credible outlet which is converting in progression to a buyer, an outcome. That progression is now tracked. But let's just talk about the economics because you're talking about $2 million in spend, it could be $20 million. The ratio between ad spend and conversion to this new element you mentioned is different. You're essentially talking about the big mega trend, which is organic content. Meaning connecting to sources. >> That's right. >> That flow. Of course, we believe and we, at the Cube, everyone's been seeing that with our business. Let's talk about that dynamic because this is not a funded operationalized piece yet, so we've been seeing, in the industry, PR and comms becoming more powerful. So, the Chief Communication Officer isn't just rolling out press releases, although they have to do that to communicate. You've got medium posts now, you've got multiple channels. A lot of places to put the story. So the Chief Communication Officer really is the Chief Storyteller Officer, Not necessarily the CMO. >> Emphatically. >> The Martech Stack kind of tracking. So talk about that dynamic. How is the Chief Communication Officer role change or changing? Why is that important and what should people be thinking about, if they are a Chief Communication Officer? >> You know, it's interesting. There's a, I'm just going to call it an actual contradiction on this front. When you and I were getting out of our undergrad, 7 out of 10 times that CCO, the Chief Communication Officer, worked for the CEO and 30% of time other. Yet the role was materially narrow. The role has exploded. You just said it pretty eloquently. This role has really exploded and widened its aperture. Right now though 7 out of 10 of them actually do work for the CMO, which is a pretty interesting contradiction. And only 30% of them work for the CEO. Despite the fact that from an organizational stand point, that kind of counter intuitive org move has been made. It doesn't really matter because, so much of what you just said too, you was in marketing's purview or around brand or around reputation or around telling the story or around even owning the key assets. Key assets isn't that beautiful Budweiser frog commercial they played on Super Bowl anymore. The key assets are what's getting done over in the communications, in part. So, from a storytelling standpoint, from an ownership of the narrative, from a, not just a product or a service or promotion, but the whole company, the whole brand reputation, the goodwill, all of that is comms. Therefore you're seeing comms take the widest amount of real estate around the boardroom table than they've ever had. Despite the fact that they don't sit in the chair as much. I mentioned that just because I find it very interesting. Comms has never been more empowered, never had a wider aperture. >> But budget wise, they're not really that loaded up with funding. >> And to my earlier point, it's because they couldn't show. Super strategic. Showing ROI. >> So, showing ROI is critical. >> Not the quality of clippings. >> It was the Maslow of Hierarchy of Needs if you can just show me that I put a quarter in and I got a dollar out. Like the ads and the e-commerce folks do. It simply drives the drives me. >> So take us through some of those analytics because people who know about comms, the old school comms people who are doing this, they should really be thinking about what their operation is because, can I get an article in the Wall Street Journal? Can Silicon Angle write about us? I've got to get more clippings. That tend to be the thing. Did we get the press release out on time? They're not really tied into some of the key marketing mix pieces. They tend to be kind of a narrow scope. Those metrics were pretty clear. What are the new metrics? What's the new operational playbook.? >> Yeah, we call those Vanity Metrics. I cared about theoretical reach. Hey, Yahoo tells me I reached 222 billion people, so I plug in 222 billion people. I reached more people than there are on the planet with this PR campaign. I needed to get to the basic stuff like how many people did I actually reach, number one. But they don't, they do theoretical reach. They work in things like sentiment. Well, I'm going to come up with, 100 reporters wrote about me. I'm going to come up with, how many of them I thought were positive, negative, neutral. Sentiment analysis, they measure number of reporters or hits versus their competitors and say, Proctor and Gamble rolled out this diaper product, how did I do this five days? How much did Proctor and Gamble diapers get written about versus Craft diapers versus Unilever's. Share a voice. Not irrelevant metrics. But not metrics the CEO and the CFO are going to invest in. >> Conversion to brand or sales, those kind of things? >> They never just never existed. Those never existed. Now when we can introduce the same exact metrics that the commerce and the ad folks do and say, I can tell you exactly how many people. I can tell you exactly who they were, demographic, firmographic, lifestyle, you name it. I can tell you who the audience is you're reaching. I can tell you exactly what they do. When those kind of people read those kind of articles or those kind of people read those kind of press releases, they go to these destinations, they take these behaviors. And because I can track that all the way down to whatever that success metric is, which could be a lead form if I'm B2B for pipe. It could be a e-commerce store from B2C. It could be a rating or review or a user generation content gourd. It could be a sign up and register, if I'm trying to get database names. Whatever the business metric is. That's what the commerce and the ad people do all day every day. That's why they are more funded than ever. The fact that press releases, articles, tweets, blogs, the fact that the earned media stuff has never been able to do those things is why they just continue to suffer and have had a real lack of investment prices going on for the last 20 year. >> Talk about the trend around-- >> It's simple stuff. >> I know, if you improve the ROI, you get more budget. >> It really is that simple. >> That's been the challenge. I think PR is certainly becoming, comms is becoming more powerful. People know I talk about it all the time. I think comms is the new CMO I think command and control and organic content work together in the organic. We've seen it first hand in our business. But, it's an issue of tech savviness and also vision. A lot of people just are uncomfortable shifting to the new realities. >> That's for sure. >> What are some of the people tech savvy look at when they look at say revamping comms platform or strategy versus say old school? >> I'll give you two answers on that, John. Here is one thing that is good for us, that 7 out of 10 to the CCOs work for the CMO. Because when I was in this seat starting to light that fire under the CMO for the first time, which was not that long ago, and they were not tech savvy, and they were not sophisticated. They didn't know how to do this stuff either. That was a good 10 year journey to get the CMO from not sophisticated to very sophisticated. Now they're one of the more sophisticated lines of business in the world. But that was a slog. >> So are we going to see a Comms Stack? Like Martech, ComTech. >> ComTech is the decision communication Cloud, is ComTech. So we did it. We've built the Cloud stack. Again like I said, just like Adobe has the tech stack for marketing, Cision has the tech stack for comms, and we've replicated that. But because the CCO works for the CMO and the CMO's already been through this. Been through this with Ad Techs, been through this with MarTech, been through this with eCommerce, been through this with Web. You know, I've got a three or four year sophistication path this time just because >> The learnings are there >> The company's already done it everywhere else. The boss has already done it everywhere else. >> So the learnings are there from the MarTech so it's a pretty easy leap to take? >> That's exactly right. >> It's just-- >> How CommTech works is shocking. Incredibly similar to how MarTech and AdTech work. A lot of it is the same technology, just being applied different. >> That's good news >> So, the adoption curve for us is a fantastic thing. It's a really good thing for us that 70% of them work for CMOs because the CMO is the most impatient person on the planet, to get this over because the CMO is sick of doing customer journeys or omni channel across just paid and owned. They recognize that the most influential thing to influence you, it's not their emails, it's not their push notifications, It's not their ads. It's recognizing which credible third-party content you read, getting them into that, so that they're influencing you. >> It's kind of like Google PageRank in the old days. This source is more relevant than that one, give it more weight. >> And now all of a sudden if I have my Cision ID, I can plug in the more weight stuff under your profile. I want to let him go across paid and owned too, I materially improve the performance of the paid and owned because I'm putting in the really important signal versus what's sitting over there in the DMP or the CDP, which is kind of garbage. That's really important. >> I really think. >> I thinks you've got a home run here. I think you've really cracked the code on this. I think you are absolutely right on the money with comms and CommsTech. I see it all the time. In my years of experiences, it's so obvious. Then again, the tailwind is that they've been through the MarTech. The question I have for you is cultural shift. That's a big one. So, I'm out evangelizing all the time about the CUBE Cloud and some of the things we're doing. I run into the deer in the headlights on one side, what do you mean? And then people like, I believe, I totally understand. The believers and the non believers. What's the cultural shift? Because some chief comms op, they're very savvy, progressive, we've got to make the shift. How do they get the ship to turn? What are some of the cultural challenges? >> And boy is that right. I felt the same thing, getting more doing it with the CMO. A lot of people kept their head in the sand until they got obsoleted. They didn't know. Could they not see the train coming? They didn't want to see the train coming. Now you go look at the top 100 CMOs in the world today. Pretty different bunch than who those top 100 CMOs were 10 years ago. Really different bunch. History's repeating itself over here too. You've got the extremely innovative CCOs that are driving that change and transformation. You've got the deer in the headlight, okay, I know I need to do this, but I'm not sure how, and you do have your typical, you know, nope, I've got my do not disturb sign and police tape over my office. I won't even let you in my door. I don't want to hear about it. You've got all flavors. The good news is we are well past the half point where the innovators are starting actually to deploy and show results, the deer in the headlights are starting to innovate, and these folks are at least opening up the door and taking down some tape. >> Is there pressure on the agency side now? A lot of agencies charge a lot of monthly billings for these clients, the old school thing. Some are trying to be progressive and do more services. Have you seen, with the Cision Cloud and things that you're doing, that you're enabling, those agencies seem to be more productive? >> Yes. >> Are the client's putting pressure on those agencies so they see more value? Talk about the agency dynamic. >> That's also a virtuous cycle too, right? That cycle goes from, it's a Bell Curve. At the beginning of the bell curve, customers have no clue about the communications. They go to their agencies for advice. So, you have to educate the agencies on how to say nice things about you. By the time you're at the Bell Curve, the client's know about the tech or they've adopted the tech, and the agencies realize, oh, I can monetize the hell out of this. They need strategy and services and content and creative and campaign. This is yet another good old fashioned >> High gross profit. >> A buck for the tech means six bucks for me as the service agency. At the bottom, over here, I'll never forget this when we did our modern marketing experiences, Erik, the CMO of Clorox said, hey, to all you agencies out there, now that we're mature, you know, we choose our our agency based on their fluency around our tech stack. So it goes that violently and therefore, the agencies really do need to try to get fluent. The ones that do, really reap rewards because there is a blatant amount of need as the line of business customer tries to get from here to here. And the agency is the is the very first place that that customer is going to go to. >> So, basically the agency-- >> The customer has first right of refusal to go provide these services and monetize them. >> So, the agency has to keep up. >> They certainly do. >> Because, if the game gets changed by speed, it's accelerated >> If they keep up, yup. >> Value is created. If they don't have their running shoes on, they're out. >> If they keep up and they stay fluent, then they're going to be great. The last thing back in the things. We've kind of hit this. This is one of those magic points I've been talking about for 20 years. When the CFO or the CEO or the CMO walk down to the CCOs office and say, where are we on this, 'cause it's out in the wild now, there are over 1200 big brands doing this measurement, Cision ID, CommsTech stuff. It's getting written about by good old fashioned media. Customer says, wow, I couldn't do this for 50 years, now I am, and look what I just did to my Comms program. That gets read. The world's the same place as it always has been. You and I read that. We go down to our comms department and say, wow, I didn't know that was possible, where are we on this? So the Where Are We On This wave is coming to communications, which is an accelerant. >> It's an accountability-- >> Now it's accountability, and therefore, the urgency to get fluent and changed. So now they're hiring up quantums and operations and statisticians and database people just like the marketers did. The anatomy of a communications department is starting to like half science half art, just like happened in marketing. Whereas before that, it was 95% art and 5% science. But it's getting to be 50/50. >> Do you have any competition? >> We have, just like always. >> You guys pretty much have PR Newswire, a lot of big elements there. >> We do. >> You've got a good foothold. >> This is just an example. Even though Marketo is part of Adobe, giant. And Eloqua is part of Oracle, giant and Pardot is part of Salesforce. You've got three goliaths in marketing automation. Hubspot's still sticking around. PeerPlay, marketing Automation. You can just picture it. CRM giants, Microsoft and Salesforce have eaten the world Zendesk's still kicking around. It's a little PeerPlay. That equivalent exists. I have nobody that's even one fifth as big as I am, or as global or complete. But I do have some small, point specific solution providers. They're still hanging out there. >> The thing is, one, first you're a great leader. You've seen the moving on the marking tech side. You've got waves of experience under your belt. But I think what's interesting is that like the Web 1.0, having websites and webpages, Web 2.0 and social networks. That was about the first generation. Serve information, create Affiliate programs, all kind of coded tracking. You mentioned all that. I over-simplified it, but you get the idea. Now, every company needs a new capability. They need to stand up media infra structure. What does that mean? They're going to throw a podcast, they're going to take their content, put them into multiple channels. That's a comms function. Now comms is becoming the new CMO-like capability in this earned channel. So, your Cloud becomes that provisioning entity for companies to stand up capabilities without waiting. Is that the vision? >> You've nailed it. And that is one of the key reasons why you have to have a tech stack. That's a spot on one, another one. Early in my career, the 20 influences that mattered, they were all newspaper reporters or TV folks. There was only 20 of them. I had a Rolodex. so I could take each one of them out for a three Martini lunch, they'd write something good about me. >> Wish is was that easy now. >> Now, you have thousands of influencers across 52 channels, and they change in real time, and they're global in nature. It's another example of where, well, if you don't automate that with tech and by the way. >> You're left behind. >> If you send out digital content they talk back to you in real time. You have to actually not only do influencer identification, outreach and curation, you've got to do real time engagement. >> There's no agility. >> There's none. >> Zero agility. >> None, exactly. >> There's no like Dev Ops mindset in there at all. >> Then the speed with which, it's no longer okay for comms to call the agency and say, give me a ClipBook, I've got to get it to my CEO by Friday. That whole start the ClipBook on Tuesday, I've got to have the ClipBook, the physical ClipBook on the CEO as an example. Nope, if I'm not basically streaming my senior executives in real time, curated and analyzed as to what's important and what it means, I can't do that without a tech stack. >> Well, Andy Cunningham was on the Cube. >> This whole thing has been forced to get modernized by cloud technology and transformation >> Andy Cunningham, a legend in the comms business who did all Steve Jobs comms, legend. She basically said on The Cube, it's not about waiting for the clips to create the ClipBook, create your own ClipBook and get it out there. Then evaluate and engage. This is the new command and control with digital assets. >> Now, it's become the real-time, curated feed that never stops. It sure as hell better not. Because comms is in trouble if it does. >> Well this is a great topic. But let's have you in this, I can go deep on this. I think this is a really important shift, and you guys are the only ones that are on it at this level. I don't think the Salesforce and the Adobe yet, I don't think they're nimble enough to go after this wave. I think they're stuck on their wave and they're making a lot of money. >> You know John, paid media and owned media. The Google Marketing Cloud, that SAP Marketing Cloud, Adobe, Oracle, Salesforce Marketing Clouds. They don't do anything in earned. Nothing. This is one of the reasons I jumped because I knew this needed to happen. But, you know, they're also chasing much bigger pots of money. Marketing and Advertising is still a lot more money. We're working on it to grow the pie for comms. But, bottom line is, they're chasing the big markets as I was at Oracle. And they're still pretty much in a violent arms race against each other. Salesforce is still way more focused on what Adobe's doing. >> You're just on a different wave. >> So, we're just over here doing this, building a billion dollar cloud leader, that is mission critical to everyone of their customers. They're going to end up being some pretty import partners to us, because they've been too focused on the big arms race against each other, in paid and owned and have not had the luxury to even go here. >> Well I think this wave that you're on is going to be really big. I think they don't see it, in my opinion, or can't get there. With the right surfboard, to use a surfing analogy, there's going to be a big wave. Thanks for sharing your insights. >> Absolutely. >> While you're here, get the plug in for Cision. What's going on, what's next? What's the big momentum? Get the plug in for the company. What are you guys still going to do? >> Plugin for the company. The company has acquired a couple of companies in January. You might see, one of which is Falcon. Basically Falcon is one of the big four in the land of Hootsuite, Sprinklr, Spredfast. Cloud companies do this. Adobe has Creative Cloud, Document Cloud, Parking Cloud. Salesforce has Sales Cloud, Service Cloud, Marketing Cloud. Cision has just become a multi cloud company. We now have the Cision Social Cloud and the Cision Communications Cloud. And we're going to go grab a couple hundred million dollars of stuff away from Sprinklr, Hootsuite and collapse social into this. Most of social is earned as well. So, look for a wing spread, into another adjacent market. I think that's number one. Then look for publishing of the data. That's probably going to be the most exciting thing because we just talked about, again our metrics and capabilities you can buy But, little teaser. If we can say, in two months here's the average click through on a Google ad, YouTube ad, a banner ad, I'll show it to you on a Blog, a press release, an article. Apples to apples. Here is the conversion rate. If I can start becoming almost like an eMarketer or publisher on what happens when people read earned, there's going to be some unbelievable stats and they're going to be incredibly telling, and it's going to drive where are we on that. So this is going to be the year. >> It's a new digital advertising format. It's a new format. >> That's exactly right. >> It's a new digital advertising format. >> And its one when the CEO understands that he or she can have it for earned now, the way he's had it for marketing and advertising, that little conversation walking down the hall. In thousands of companies where the CCO or the VP of PR looks up and the CEO is going where are we on that? That's the year that that can flip switches, which I'm excited about. >> Every silo function is now horizontally connected with data, now measured, fully instrumented. The value will be there and whoever can bring the value gets the budget. That's the new model. Kevin Ackroyd, CEO of Cision, changing the game in the shift around the Chief Communications Officer and how that is becoming more tech savvy. Really disrupting the business by measuring earned media. A big wave that's coming. Of course, it's early, but it's going to be a big one. Kevin, thanks for coming on. >> My pleasure, John, thank you. >> So, CUBE conversation here in Palo Alto Thanks for watching. >> Thanks John. (upbeat music)

(intense orchestral music) >> Hi I'm Peter Burris, and welcome to another CUBE Conversation. Got a great conversation with a CMO today, we're going to spend some time talking about some of the changes affecting the tech industry, and specifically affecting marketing in the tech industry, and we're gonna be having that conversation with Meagen Eisenberg who's the CMO of MongoDB, Meagen welcome to theCUBE. >> Thank you, thank you for having me. >> Well so, we're gonna spend some time talking about a number of different things but MongoDB is an especially interesting company in the context of this conversation, why don't we start by tell us a little bit about MongoDB. >> Sure, MongoDB is a leading modern general database platform, downloaded by 35 million developers, and is used by the hottest private companies like Coinbase to storied brands like HSBC. >> So if we think about it, the reason why I think this is especially interesting is because MongoDB is an opensource company and so that means that that has some specific marketing challenges it recently went through an IPO, and the marketing role in IPO is especially interesting, but very importantly here's where I wanna start, that in many respects the tech industry has always been set up to sell products, and the proposition was I know about my product as a seller, you don't know that much about it, user, so I'm gonna spend an enormous amount of time bashing you about why my product is better, that's changed a bit, as we move to this digital transformation and the role that data plays in helping companies transform it's less about what the vendor's doing and more how the company utilized the technology it's kinda this underlying from a product orientation to a services orientation it has a continuous relationship. >> Yes, that's right. >> Especially in the opensource world where you have a continuous relationship with your developers. Tell us a little bit about how, at least in your experience at MongoDB, that relationship, that from a product orientation to a service, ongoing service orientation, affects marketing. >> Sure, I mean we think a lot about how are user are using the product. You know, we wanna win the hearts and minds of developers, they're out there building new ideas, they're using it, when we enter a company through one developer we have the opportunity to spread to many others you know, if we think of all size businesses there's thousands if not 10s of thousands of databases and applications, so we wanna make sure they have a great experience that we're collecting data that's useful to help them, and that it spreads to others. >> Now lemme amplify wat you just said, because again, we could go back and think about other technology companies where the role was to explain what a relational database was and why it was better than something else, and what you just described is no, we wanna create a community of users that are constantly developing their own visibility their own insight and our job is to call the best of that and use that as part of the marketing experience, do I got that right? >> Yeah, that's right. Developers are actually quite social, and when they're out there building or they find something new, they're creating apps, they're creating new tools, they're sharing that knowledge and so, from a marketing standpoint, we do a lot of work with developer relations building apps, out there speaking to language communities, we're out there at conferences really showing what the technology can do. >> So the, many years ago I had a conversation with a CEO who's now worth billions of dollars, and I asked specifically, I thought that marketing had been essential to his success, and he said something very interesting, he said ah, marketing, that's what I put between my engineers and my sales people so they don't kill each other. (Meagen laughs) That can't be the role of marketing in a community-oriented company. Tell us about how marketing stands in a collaborative relationship between, with product and sales at MongoDB. >> Sure, so, I mean for myself personally as a CMO, I think the success of marketing is it's relationships not only with sales but with engineering, and that they're really, sales I see as a internal customer, understanding what they need to be successful, making sure that we're talking to the right persona that we're helping them build pipeline we're putting tools out there that are helping the user go through the experience, and from a engineering standpoint, that we're collaborating, that there's a feedback loop as people are using the product we want it to be a frictionless experience when they meet us out in the field or they come to our website, and that part's important as a registering for the product, as they come in, as they start to use the product and making sure we all have access to that data it helps sales better do their job, engineering build a better product, and marketing better really hook, hook the user in. >> So marketing helps sustain that journey, but also, also being, ensuring that sales is getting the appropriate information and insight on what customers are doing, but it's much more, it's multi-nodal today, I mean people talk about multi-channel all the time, talk a bit about how you anticipate the engagement model changing as more personas get involved, as technology gets more deeply embedded into the risk profile changes, and very importantly, especially for a company like MongoDB, as the number of use cases explodes. >> Yes, yeah I mean it's a good point, we are, from a marketing standpoint we're going directed developers who wanna do self serve with our MongoDB Atlas product, all the way to the CIO and CTO, who are trying to digitally transform their businesses, and that's, they're all different channels, it's not just email, it's social, it's your website, it's how you interact with them in the field, it's supporting your sales team, it's our developers that are out there working in the field and building the product. So you're right, at MongoDB we have 28 technologies in our Martec stack, and we've sunset seven, so we've experimented with 35, and the reason is because there's a lot of work around website, making a better experience, there's work around social media, how we design what we put out there, what we're doing in the field, making sure every experience, every form you fill out is is really optimized for that customer experience. >> Yeah, it's creating some sort of value with customers, not a distraction, not an annoyance. But if you think about it, another CMO once said, here on theCUBE, that they kinda summarize some of the new role marketing, is that marketing is creating the community, and marking is sustaining the community, where a community really is defined as people who are doing something in common. So your customers are trying to imply this technology that has enormous flexibility, I'm gonna ask you to explain a little bit about that in a second, we're not gonna get too deep, to a lot of new use cases, and that's what your users are trying to do bringing those together so they can share insights share experience, improve the quality tool, speed the process, the rate at which it all happens, there's gotta be a central feature of the marketing mission at MongoDB, is that right? >> Yes, definitely, I mean we're very focused on the developer, their experience, winning their hearts and minds, and creating advocates, people and developers that come and use the product and love it and build upon it and have, you know, things that they've learned that they wanna share, we have a pretty detailed documentation for new folks, we have a MongoDB university where we've had over 800 thousand developers take courses, it's definitely a highly engaged group that wants to innovate, and they wanna use the hottest technology, they don't wanna be on Legacy. You know, Legacy databases came out 40 years ago, the likes of Oracle, right, that was designed before cloud before mobile, before the volume and variety of data that we have today, and so if you want to build new apps you have to do it in a new, modern way, and MongoDB is a real alternative to those Legacy databases. >> Yeah, so one of the things I think is especially important as we think about some of this stuff, ultimately is, you said you wanna build that, the developer community, and make sure that engagement's strong while at the same time, obviously, sustaining relationships with other personas who are gonna write the checks, probably through your sales organization. >> Yes, yes. >> What is the role of diffusing knowledge through a service, I mean do you have a university or do ya, how does content get designed and instrumented at MongoDB to catalyze that community activity? >> Yes, I mean content's very important, all the way from our developer advocates at relations are building content to educate developers, to help them learn about the product, use the product, and then for the C level execs that are trying to transform their businesses, they're trying to learn about microservices, blockchain, there's a lot of content, and we see it like HubSpot really educated the marketing community around inbound marketing, we're doing a lot of work to educate and work with developers and create that digital watering hole so they can learn what they need to build their next app. >> Especially on the idea of complex, rich, natural data. >> Yes that's right, we believe that MongoDB is the natural way and the best way to work with data, and you can put it where you want intelligently as well as the freedom to run it anywere, our MongoDB Atlas runs on all three major clouds, with AWS GCP and Azure, and that ability to migrate, we're on 54 different regions, so really anywhere in the world you want to have your app running, we've got it set up for you. >> So MongoDB as a database company is trying to reduce the limitations of how well database can handle more complex data, the engineering is using an opensource approach trying to ensure that there's a high quality offering associated with that promise, >> Sure. >> You're deploying it on a lot of different platforms, cloud, not cloud, so that people don't face fundamental infrastructure complaints as to try to get advantage of that, that creates an enormous number of opportunities for someone to come in and try it, the whole try by motion, or land and expand as people like to talk about. How is MongoDB refining that notion of land and expand through its marketing mission? >> Sure, I mean well certainly we're making it frictionless for you to sign up, self serve, you can go put a credit card in, we've got a free tier where you can quickly experiment, try it out, as your application grows and becomes mission critical we've got the tools that you need to maintain it, we've got security and all the features you would need to run a modern application, and we're, we've set it in a way where no matter where you are in the world or who you wanna collaborate with, it's easy for you, it's very frictionless for the developer, it's a natural way to develop, and you're not, you know, you're not worried about the operational overload that comes with relational or Legacy databases. >> So we've talked a little bit about how MongoDB is working with developers, let's pivot a little bit and talk about how MongoDB worked with potential investors. I've been fascinated by the role that marketing plays within IPOs, you've got finance with a very very well defined role, sales typically has a very well defined role, but marketing's trying to straddle that fine line between driving new volume, but being very careful about what you say and how you say it to keep people feeling confident and comfortable from a financial standpoint. You got, you joined MongoDB three years ago. >> Yes, yes three years ago. >> You had an IPO about halfway in your tenure. >> Yes. >> Tell us a little bit about that. >> Sure, I mean, October 2017 the company went public it was a very exciting time, certainly the first time that I had been with the company and taken them public, I was fortunate enough, our CEO Dev Ittycheria had done it multiple times as a leader and as a board member, and so he brought a lot of knowledge around that, and as a marketer you're thinking how do you stay within the guidelines but make sure everyone's aware of what you're doing, certainly if you've been doing it in the past you can keep doing, you know, if you're not hyping the market, you can keep doing what you've been doing you can keep running your events you can talk about the product, the day of is a really big day to get in front of media, I was really impressed by what the team did to align media interviews I think we had 24 different interviews in one day, and we had over 50 or 60 stories break within the next week or so. So that was exciting just, you know, that timing, 'cause you can't line those up too soon, you've gotta make sure everything's a go, and, you know, it really worked out and now we're just excited about the future of the market, 60 billion dollar market by 2020 according to IDC, so we've got a massive opportunity in front of us, so what can we do, certainly from a marketing standpoint, what do I need to be doing to get on that and work through that. >> So MongoDB is a growth company, you know, good solid set of employees, tell us a little bit about how marketing's role is gonna change in the next couple years, as MongoDB tries to grab more of this 60 billion dollar opportunity. >> Yeah, I mean we definitely have a strong vision around where we're going with our products and solutions as a database platform, we're doing a lot of work with partners, we've got some great stuff going on with SA- SIs like Accenture and Infosys and Wipro who have modern, you know, they're modernizing the tech stack and working with really large companies, and we're part of that offering, so we'll be working heavily with that. We're very close with the cloud vendors, with AWS and Microsoft Azure and GCP, so a lot of good work going around that and we'll continue to grow our cloud offering itself, Atlas, MongoDB Atlas, it's only been around two years, it's already 14% of our business now has grown 400% over the last year, and so we're excited to see-- >> Congratulations! That's not bad. (laughing) >> Thank you, yeah, thank you. That's a, you know, really exciting part of the business and so much moving to the cloud it's the right place to be, I feel like we've done a great job really, you know, looking at where we need to be and then highlighting that in the markets. >> So last question Meagen would be Mongo is carving out an interesting spot for itself within the marketplace and as you focus on customers, customers are increasingly dictating how the market's gonna evolve, it's an interesting dynamic, especially that community approach, but there's always efforts to pull it back, especially from some of the entrenched database competitors. How are you guys trying to both keep the focus in what the customer needs, drive them to this modernization while at the same time acknowledging, recognizing, that they can't change everything on day one, that you have to coexist? >> Yeah, so, I mean MongoDB is doing a lot of work around migrations, making it very easy and frictionless. If you're gonna move to the cloud, this is the perfect time to move off Legacy databases, and we see it with our customers, they're struggling with 40 year old technology they need a more modern approach, they want a single view of their data, they're dealing with so much of it, and it's the right time when they move to the cloud. So we're making sure our product is on all the major clouds, which it is, and all the regions, that we've got the tools that they need, and that that process is really simple. >> Alright, Meagen Eisenberg, CMO of MongoDB, thank you very much for being on theCUBE. >> Thank you for having me. >> It's been a great conversation, and once again, you will see additional CUBE Conversations, until next time I'm Peter Burris, thank you very much for watching. (intense orchestral music)

>> Announcer: Live from Las Vegas, it's theCUBE, covering ServiceNow Knowledge 2018. Brought to you by ServiceNow. >> Welcome back everyone to theCUBE's live coverage of ServiceNow Knowledge18. We are wrapping up day one of coverage. I'm Rebecca Knight, your host, along with my co-host, Dave Vellante. We're joined by Bipin Paracha. He is the co-founder and principal consultant of IntegRhythm. Thanks so much for coming on the show, Bipin. >> Thank you for having us. >> So let's just lay the scene for our viewers. Tell our viewers a little bit about what IntegRhythm does. >> So IntegRhythm started as a management advisory firm. We were teaching clients how to transform, fell in love with ServiceNow platform back in 2012, and since then, we love leaving behind working systems that drive outcomes for our clients. So we do a lot of transformative process organization, shared service transformations, things that leave behind business value for our clients. >> So a combination of tip of the spear consulting, and also implementation, is that correct or? >> So we change the tip of the spear, we kind of have tip of the spear in the implementation phase. So it is kind of baked into our methodology on how we drive outcomes for our clients. >> Dave: Oh, okay. >> So we don't charge our clients extra for consulting because we believe we get paid when we drive outcomes. >> Outcome-based incentives. >> Bipin: Yep, exactly. >> So your growth has been phenomenal, really, in recent years. So what's the magic? What are you doing? How has it been achievable? >> So one of the fundamental things that you've heard all along here, but what we also believe, is customer success. If you drive value for your customers, if you drive great value, they come back. Lot of people say that. Lot of people believe that. But we were fortunate enough to latch on to the comet's tail with ServiceNow early on. We were one of the few early partners. We saw the platform is amazing. It can do terrific things. And we've been able to drive the platform to do things for our customers, and that's helped propel our growth. As long as we stay true to that mission, we are keeping to grow. >> I want to ask you a question as a practitioner, somebody who really knows this space. ServiceNow obviously great for mid to large-size companies, trying to do anything related to a service request, customer service management, obviously ITSM, change management, problem management, et cetera, et cetera, et cetera. What's it not good at? It's not for small business. It's not CRM. It's not an HR app. So what's the profile of a company that you typically work with? >> So it is great for small businesses. We are a small business. We own ServiceNow. >> Dave: Really? We run our business on ServiceNow. >> Dave: Get out of here. >> For the right profile of a customer, it is beautiful. >> How many employees are you? >> We have 70 today. >> Dave: 70? >> 70. >> Dave: Oh, you really are a small business. >> And we are pretty small, but we still run our business on ServiceNow. It does more things than any other project management tool. It does more things than any other content management tool. We use CSM, we use PPM, we use everything. It drives value. >> Dave: Do you run your CRM at ServiceNow? >> We integrate with CRM. >> Dave: Okay. >> So we use the same CRM that ServiceNow uses, Hubspot. Our marketing, our website. >> Which is really marketing, I mean, ServiceNow is your backend CRM platform essentially. >> Yep. So our single view of our customer is ServiceNow. Anytime anybody touches us across a project, across an incident, across, we see them in ServiceNow. >> Wow, that's, I didn't realize that. I mean, is that common that a company of your size? >> It's actually not, so one of the big leg-ups we have is we are an implementation company, we are passionate, so we kind of get the free implementation. So our team goes gangbusters. >> Yeah, you're ServiceNow alpha geeks. You guys are really deep into this stuff. >> Yeah, they love what they're doing. We have to kind of slow them down sometimes. We got customers to deal with, go focus on customers. >> You are a passionate evangelist for ServiceNow. >> Oh yeah. >> What are you learning here at Knowledge? And this is not your first Knowledge, not your first rodeo. But are you talking with other customers and learning how they're using it, the platform? And then also being able to come back and take those best practices home? >> So we are a business, right, end of the day. So we get our clients here to ServiceNow, and when clients talk to the product company, product team, they learn a lot. When the product team talks with the clients, they learn a lot. But when clients talk to clients, magic happens. We've been a partner for other technologies, I won't name them, but ServiceNow is truly a customer-driven organization. I have never in my 20 plus years of experience run into a passionate customer base. Sometimes customers know how to sell ServiceNow better than ServiceNow themselves. So get a bunch of customers together, we win. >> In the early days when we started covering ServiceNow you would hear stories about making custom mods, making modifications, how that slowed people down, going into subsequent releases. I hear more often now, no custom mods, we avoid custom mods. What are you seeing? What are you preaching in the marketplace? >> So ServiceNow today is different from ServiceNow five years ago. >> Yeah, for sure. >> So we strongly believe you can go live out of the box. We actually had two presentations, a 2.5 billion dollar company, top 20 exporter in the U.S. Took them live in ServiceNow with zero customizations. Straight out of the box. Schooler, American Greetings, CSM out of the box. Our story is you're buying a Ferrari. Drive it around the block. Use what you use, and then figure out how you transform the organization. When you're buying ServiceNow, you get best practices. ServiceNow's already baked in industry best practices. If you are doing something, figure out where you're special, and pay attention to where you're special. >> When you think back to those customers five years ago that did a lot of custom modifications, how do you help them get off that technical debt? >> So we have a couple of programs that we run. So we've done back in the box for a couple of our accounts. Stand up a new ServiceNow instance, build up from scratch, migrate. Sounds easy, but we've done it a few times, so we know we can, we do. The other thing is, you can move in a phased approach. So HR has come up with a scoped app. It was two years. Move off the custom HR into scoped app. GRC, move into the scoped app. So you can migrate in phases. We've had like six major conversations today around how you roll back the stuff. So what customers built six years ago, ServiceNow delivers out of the box. >> Rebecca: Bipin, thanks so much for coming on theCUBE. It's been a pleasure having you. >> So thanks for having me here. It was fun hanging out. >> Dave: You're welcome. Good to meet you. >> The party is getting started, so, I think we've got to join them. It's our time now, exactly. >> Bipin: Alright, thank you. >> Yes, thank you, thank you. We will come back tomorrow with more from ServiceNow Knowledge18. I'm Rebecca Knight for Dave Vellante. We'll see you back here tomorrow. (upbeat music)

>> Announcer: Live from the Moscone Center. It's theCUBE! Covering AWS Summit San Francisco 2018. Brought to you by Amazon Web Services. (upbeat techno music) >> Hey, welcome back, everyone. We're live here in San Francisco. This is theCUBE's exclusive coverage of AWS Amazon Web Services Summit 2018 with my co-host Stu Miniman. We have two great guests. Hot startup from SingleFx, the CEO, Karthik Rau, and the CTO, Arijit Mukherji. Welcome to theCUBE. Good to see you again. >> Karthik: Yeah, great to see you again. Thanks for having us. >> So, we've been following you guys. You've been out five years. Two years in stealth, three years ago you launched on theCUBE. >> Karthik: Right here on theCUBE. >> We see you at AWS and VMware. Cloud's changed a lot. So, let's get an update. Karthik, take a minute to explain where you guys are at now company-wise, employees, traction momentum, product. Where are you guys at now? >> Karthik: Yeah, absolutely. So, SignalFx, first of all, let me tell you what we do. SignalFx is a realtime streaming operational intelligence solution. Basically, what that means is we collect monitoring data, operational data across the entire cloud environment, from the infrastructure all the way up to the applications. And we apply realtime analytics on that data to help people be a lot more proactive in their monitoring of these distributed environments. We launched the company in 2015. We come ... I'll let Arijit talk about our origins. We came out of Facebook. And we had a lot of experience building this to Facebook. In the past three years, we've been building up our company aggressively. We've now got hundreds of customers including several large Fortune 500 accounts, large web scale accounts like Acquia and HubSpot and Yelp and KAYAK. And we're over 100 employees now, about 120 employees. And yeah, doing great. >> So, Werner Vogels, the CTO, laid out on stage plus a great Matt Wood conversation about machine learning but the real thing that Werner laid out was the old way, the web server, multi-tier architecture stack kind of thing going on there to a more cloud DevOps horizontally scalable where sets of servers that could be spawned in parallel creates a new kind of operating model but also creates challenges around what to instrument. You know, as we would joke, someone left the lights on, implying EC2s been running. And all these kinds of things are going on. And you mentioned some of the Facebook kind of challenges. People were building their own scale. What have you guys learned and how does that apply today's modern infrastructure? What are some of the threshold challenges that companies are facing when they say, one, already there or I want to get there? How do you guys look at the main issues? >> Karthik: Do you want to take that? >> Yeah, so monitoring modern environments and infrastructure is actually quite a challenge. There's obviously a few things going around. One, as you mentioned, is the variety, the sheer variety of things. No longer just the three-tier architecture I have cloud services. I have containers. I have lambdas. I have my own applications. I have the cloud infrastructure itself that all needs to be monitored. And things are also becoming far more numerous. So, there's just many more of everything, right? And so, making sense of that space is becoming a big challenge. And our company was founded on the idea that monitoring is becoming an analytics problem. So, it's no longer about looking at individual servers or applications instances. It's more about making sense holistically over what's going on and being able to combine different types of data from different systems together to provide you with that high level view and that's the kind of functionality that we at SignalFx have been trying to provide. >> What are some of the data flows volumes look like. Cause I've heard multiple people talk about either Facebook or in open compute environments where there's just so much data coming in from the instrumentation that no human could actually get their arms around it. And you need to supplement it with machine learning and intelligence. I mean, is that something that you're seeing? What are some of the -- >> Yes, so actually what we see is different prospects or customers will be in different stages of a spectrum where maybe they were in a stage one where they're sort of using traditional architectures and then moving to these more modern systems. And as they get more modernized themselves, their use cases or the ways they wanted to do monitoring also gets more advanced. And so, we see the whole spectrum of it, as you mentioned. And so, understanding analytically how what we're is doing is great. But then you also want to take the human out of things as much as possible, right? >> Yeah. >> And make things more automated. And you want to look at the data and how things are behaving to learn from existing patterns to find outlines. So, that's really a very interesting challenge. And what I look at what we can do as a company going forward, like all the technological stuff that we can invest in, it's quite interesting. >> Yeah, Karthik, take us inside your customers. How does this modern monitoring, how does it change their business? How does it impact things like feedback loops and DevOps and everything that customers are having to deal in this kind of ever changing environment? >> Yeah, well I'll give you an example. There's a Fortune 500 company. They do product launches. And this is one of our customers and their product launches drive so much traffic that they do 80% of their business in the first two minutes of a product launch. And this is not at all uncommon in today's economy. And they're leveraging a lot of modern technologies, container architectures, serverless function architectures to spin up a bunch of capacity during these launches. And they were effectively flying blind most of the time. Because most of the traditional systems management monitoring solutions are not designed, A, to handle that volume. But, B, to handle the instant discovery requirements of if you're going to do 80% of your business in the first two minutes. So, the challenge is you're always playing defense. You're reacting to issues. And you're mostly flying blind. By leveraging SignalFx, they're getting realtime visibility, realtime discovery of these components as they're coming up. We're the only solution that can do that. So, literally within seconds of spinning up all of these containers, they're getting live streams into their dashboards, and live analytics, and live alerts. And what that's enabled them to do is be a lot more aggressive and effectively doing a lot more of these launches. So, that's driving their business and it's helping them drive their digital strategy forward. >> And microservices is really enabling you guys to be more relevant. Because truly the signal from the noise is where all these services reporting to? >> Karthik: Yeah. >> You talk about container madness. >> Karthik: There are two fundamental problems. So, one there's an architecture shift. And that's driving massive amounts of volume. You have physical machines that will live for three years in a data center. Divide it up into VMs, 10, 20 VMs per server. That'll maybe live for a few months. To now every process running in it's own container that might live for a few minutes. So, you have a massive exponential explosion in the number of components. But that's not the only problem. I was part of an architectural shift at VMware for a number of years. We weren't just affecting an architecture change. What's happening now is there's a cultural change and a process change that's happening as well. Because with containers, your development team can push changes directly out into a production environment. And what you're finding is you're going from sequential product development to parallel product development and a massive exponential increase in the number of code pushes. The only way you can operationalize that is you have to have realtime visibility in everything that's happening. Otherwise, the left arm doesn't know what the right arm is doing. >> John: And you need prescriptive and predictive analytics. >> Exactly. And you need predictive analytics to identify there's something unusual here. It's not a problem yet. But this is highly unusual and maybe it's your canary release. We need to do a code push. So, you want to roll it back. So, having that level of predictiveness becomes absolutely critical. >> Yeah, you mentioned realtime. We used to argue what really is realtime. And it was usually well in time to react to what the customer needs. What does realtime mean to your customers? Architecturally, is there something you do different to kind of understand what that means? >> Arijit: Yeah, so we actually fundamentally took a very different approach when we build a product. Where, typically, monitoring our metrics, monitoring was done with what we call a store and create or a batch-like architecture where you store all the data points that are coming in, then you create from it to any other use cases. While what we build at SignalFx is a fully end-to-end streaming architecture which is realtime. And what we mean by realtime is like two to three seconds between a data point coming through us and it's firing an alert or showing up in your chart. So, that's the kind of realtime. And it requires us to do lots of innovations up and down the stack. And we've built a lot of IP. We've got now patterns. And more are coming because the approach we took was quite novel. Different from-- >> John: You guys got a great management team. And looking at what you guys have done. I've been impressed with you guys. I want to just ask, Karthik, you mentioned about all these parallel processes that are going on. Totally agree. The process change, operationalizing an all new cultural way to create software manage the data. I mean, it really is the perfect storm for innovation. But also, it could literally screw people up. So, I got to ask you, who are you targeting for your customer? Who is the person that you talk to? Assuming it's kind of DevOps, so it's more like a cloud architect. Who do you target? Who do you sell to? Who's the buyer? Who uses your service? >> Karthik: Well, we see ... Every enterprise we see following a very similar journey. So, the first stage is, typically, you're just getting familiar with cloud. And you're probably just lifting and shifting enterprise workloads into the cloud. Probably experimenting with big data on the cloud. You're not yet doing microservices or containers or DevOps. And for them, we're still selling largely to classic IT. There just trying to get better visibility into their digital environment, you know, they're cloud environment. But then, what ends up happening is they very quickly get to what we call basically chaos. It's stage two. And it has a lot of parallels to shadow IT. What happened with SAS, where you have hundreds of different SAS tools is happening all over again with cloud but you've got hundreds or thousands of different operational tools. Different ways of doing monitoring, logging, security. And every team is doing it's own thing. And so, that's a big problem for enterprises who are trying to build best practices across their broader team. In that place, we're typically selling to departments because they don't have a centralize strategy yet. But what we find is the organizations at maturity have figured out that it's important to have certain centralized core services. And that doesn't mean they're forced on the end users. But they provide best practices around monitoring, logging, and such. And just make it easy for them to use those solutions. So, that's almost a new IT organization. It's platform engineering -- >> John: Is that a cloud architect? >> Platform engineering team, infrastructure engineering team, and they are effectively building best practices around the new stack not the traditional stack. >> So, you are or aren't targeting department level? Are you are? >> We sell to departments. But we also sell to the teams that are standardizing across the entire organization. >> So, cloud architects, for instance? >> Depends on the stage of the cloud journey. >> Or company. >> And the company, exactly. >> From an architectural standpoint, you talked that there's virtualization, there's containers, now serverless. How do you even figure out what to monitor in serverless? How fast is that changing? And how is that impacting your road map? >> So, serverless brings a very interesting challenge because they are very, very ephemeral. Like they're ephemeral in some sense. So, we realize there are two things. One is serverless, there's a reason why things are moving faster. It's because you want to be able to move faster. But then you also need to be able to monitor faster. It's no good monitoring serverless at five minutes later, for example. So, one of the things we invested in was how to get metrics, etc. and telemetry from these serverless environments in a very fast fashion. And that's something that we've done. The second thing we are doing that really works for this environment is afterall it's not about how many times a serverless function ran, it's about the value that it's providing the application that's running on it. And by focusing on a platform that let's you send these application metrics in great detail and then be able to monitor and analyze them, I think really amplifies the value in some sense. So, those are the two ... >> John: And talk about the ecosystems. One of the things I want to ask you guys because we've been seeing a collision between a lot of the different clouds. Clients want multicloud. Well, obviously, we're here at Amazon. They believe they should be the only cloud. But I think most customers would look at either legacy systems with some instrumentation and operational data to edge of the network, for instance. I mean, look at the edge of the network. That's just an extension of the data center depending on how you look at it. So, how do you guys view that kind of direction where customer says, "Hey, you know, I got a cloud architect. We're on Amazon. Of course, we have some old Microsoft stuff. So, we've got Azure going up there. We're kicking the tires on Google. And I got this whole IoT Edge project. SignalFx, instrument that for me. (laughs) Is that what you do? Or how do you deal with that? How would you deal with that kind of conversation? >> Well, I think most enterprises, the larger companies we see looking at multiple clouds. And they have different workloads running in different clouds, depending on the needs and what they're looking to do. So, the nice thing about a solution like SignalFx is we span all of these different architectures. And what we find is that most of the larger companies want to separate their business process solutions from their runtime architectures. Because they want to have a solution like SignalFx that it doesn't matter who you're using. If you choose to have your analytics intensive workloads in Google Cloud and your eCommerce workloads in Amazon, but you only want one system that will page someone in the middle of the night if there's a problem, then you have SignalFx to do that. And then you have your choice of runtime environments depending on what your developers need or what the business demands. We provide a lot of that glue across the different environments. >> Do you see that as the preferred architecture with most customers? Cause that makes a lot of sense. I mean, whether you're doing other data services, it kind of makes sense to separate out. Is that consistent? >> To have different applications >> Yeah. >> In different clouds? It depends. I mean, I think we see some people who are more comfortable running on a single cloud vendor and they make the decision based on what a portfolio of platforms and service features that are available. And they really like those, and they say it's easy to just go with one. But more often, we find people wanting to at least have some percentage running in a different cloud vendor. >> John: All right, final question. What's the secret sauce for the company? Tell us about the secret sauce. >> Arijit: I think-- >> We got the patents. I heard patents. You don't have to show all this exactly. But what is the secret DNA of the tech? What's the magic? >> I think it's our very unique architecture. It's entirely different from what you have. It's streaming and it focuses on scale, on timeliness, as well as on analytics capability. I think that unique combination is very special for us. And that, in a way, sort of allows us to address very, very different use cases, including this hybrid environments and what not, in a very effective way. So, it's a very, very powerful platform that can be used for many use cases. >> All right, so that was John's final question. Karthik, I've got one last one for you. What's it like being a CEO of a software company in the cloud era today compared to what it's been earlier in our career? >> Well, it's moving very, very quickly, right? I mean, technology always move very quickly. But I think compared to when I was at VMware in the mid 2000s, it just feels like every 18 months there's a new technology wave. You know, when we started our company five years ago, that was the first year that AWS eclipsed a billion dollars in sales and Dagra hadn't even launched. It launched a month after we started the company. And then serverless came. And now function architecture is all there. So, there's just so much change happening, and it's happening so quickly, it forces vendors like us to really be on the cutting edge and forward looking and making sure that you're keeping an eye out for what's coming cause the markets are moving way faster, I think, then they were 15 years ago. >> John: Well, Karthik, thanks so much. We appreciate you guys coming on, SignalFx. I'll give you the final word on the interview. Take a minute to share something with the audience that they might not know about SignalFx that they should know about. >> Well, I think what people may not realize is how realtime we can actually get. I think most people are used to doing all their monitoring and observation, and they think of realtime in the order of minutes, or if you can get stuff every 30 seconds. We really are the only realtime solution. That's why we say real realtime. We're on the order of seconds. You can build really, really sophisticated analytics and get visibility like you can't anywhere else. So, it's real, realtime. >> And that's soon to be table stakes. TheCUBE is realtime. We're live right here, on theCUBE here, in San Francisco at Amazon Web Services, AWS Summit 2018. We've been covering all the Amazon re:Invents since it started, of course. I'm John Furrier with Stu Miniman. Back with more live coverage after this short break. (upbeat techno music) (gentle instrumental music)

>> Narrator: From the Silicon Angle Media office, in Boston, Massachusets. It's The Cube. Now here's you host, Stu Miniman. >> Hi, I'm Stu Miniman and we're coming to you from the Boston area studio here of The Cube. Excited to talk about some of my favorite topics. Talking about the culture, innovation, and really transformation in what's happening in data center. Digital transformation is on everybody's mind. Specifically happy to welcome Mike Grandinetti who is the Chief Marketing and Corporate Strategy Officer with Reduxio. Mike, thanks so much for joining us. >> Stu, thank you so much for having me. Great to be out here with you today. >> Alright, so you're a local guy? >> Mike: Yeah. >> We're glad that you could join us here. Before we jump into the company tells a little about your background, what you worked on, what brought you to Reduxio. >> In a nutshell I guess my background is all about innovation. I've sort of eat, breathe and slept innovation for the last 25 years of my career. So I started off as an engineer in Silicon Valley with HP back when Bill and Dave were still around. At a time when it was America's most admired company. Was a remarkable sort of introduction to what is possible. Went back, got my MBA, did several years at McKinzie doing corporate strategy consulting. Mostly around innovation related projects. And then I moved up here to Boston to be a part of the first of what is now eight consecutive enterprise venture capital backed start ups. And I've been lucky enough that two of those went public on the NASDAQ. The prior seven have all been acquired by companies like AT&T and Oracle. And now Reduxio is my eighth start up. We're really having a great time building this business. >> Great, we're definitely going to big into some of the innovations of Redux I O. >> Yes. >> So the name kind of tells itself. We've seen a few companies with the I O at the end. We've talked so much that when we've talked about kind of 2018 data is at the center of everything. Really what is driving business. So for an audience that hasn't run across Reduxio kind of give us the why and the what. >> Yeah, and so to your point, data's driving everything. Mark Andressen famously said software's eating the world. I think if we were to update that it's data is eating the world. And so I think you and I have had this discussion off camera. Whether it's fair or not, I think it's true. And it needs to be stated that the amount of innovation that has occurred in the storage industry over the last 20 years, has been disappointing at best. The solutions that have evolved have evolved in an extremely fragmented way. They are over, way too complex. They're way too expensive. And because it's a collection of piece parts, you've got to manage multiple screens, multiple learning curves. And a lot of things fall through the cracks. So when you go and look at some of the research data from a wide range of analysts, what you hear from them is there's this extraordinary lack of confidence that even though I've spend a ton of money, invested a lot of staff time and attention to building out this infrastructure, very lacking in confidence that I'm actually going to get that data back when I need it. So it's the old adage, it's time to fix it. So this is exactly what the founders of Reduxio saw. They were looking at this evolutionary path and saying people are just making it worse. So they did what many people would condsider to be radical. They threw out the entire playbook of what storage architecture has been and they took a clean sheet of paper, design centric approach. What are the use cases? Where are we in the world with regard to technology? And how do we design and experience for storage admin or BD admin or a person in the dev center that doesn't require a PhD in storage? And so that's kind of what the premise was. >> Yeah, so many things there that there are to dig into. Absolutely. I live, I worked for one of the storage companies for a decade. Absolutely complexity is how we would describe it. And what companies are looking for today, is they need simplicity. They need to focus on the business. Turing dials and worrying about do I have enough capacity? Do I have enough performance? Do I have enough of those things, is not what drives the business. >> Mike: Exactly. >> They need to focus on their applications. The bit flip we saw in big data, and we can argue whether or not big data was hype or whatever we had there, but it was oh my gosh I'm getting all this data to oh my gosh I have all of this data and therefore I can do more things, I can find more value. >> Mike: Absolutely. >> I worry a little bit when I hear things like oh, the storage admin. >> Yeah. >> The storage admin's job before was how to I triage and kind of deal with those issues? Many solutions now you look at the wave of hyper convergence. Let's push that to a cloud architect or the virtualization layer. How do we start with a clean slate and get out of the storage business and get into the data business? >> Mike: I love it. So I'm going to bring you back ten years to one of the most remarkable product introductions that has ever been conducted on this planet. It was the introduction of the iPhone. And if you recall in those first five minutes that Steve Jobs took the stage in a way that only Steve Jobs could. He went onto tease the audience by saying that we are going to be introducing three products today. And then over the next minute or two became clear that it wasn't three products, it was one very innovative product at the time. The iPhone. What they basically did is they integrated these three previously disparate pieces of technology. Certainly the mobile phone but also a music player and an internet navigator. Behind this gorgeous revolutionary user interface. So what we've tried to do is take a page out of the Job's iPhone innovation. We're integrating. And Forrester Research has written an incredible report about this and others, IDC and others, have consistently supported it. Chris Malore from the Register has written about this at length as well. Reduxio is integrating primary and secondary storage along with built in data protection. So those previously siloed capabilities are now one. We're also, like Jobs did, when you looked at the old style smart phone, the BlackBerry and the Trio and the- ya know all of those things that had all of those keyboards, is we've created a user interface using game designers so when our customers go home at night and they log into Reduxio, their little kids will say, hey dad what game are you playing? And dad will say, I'm not playing a game. I'm actually working on Reduxio. And so what that's done for us I think is it's allowed us to be able to drop a Reduxio system into any number of use cases with someone who may not have the luxury of being deep in storage. And literally get time to value that they put production workloads on the system that day. >> It's interesting, another piece that I'll draw from your analogy is when you talk about how did Apple take all of those pieces. And it's kind of certain technologies moving along. But there's one specific technology that really helped drive that adoption. And it's Flash. >> Mike: Yes. >> And the consumer adoption of Flash ten years ago drove the wave that we've seen in enterprise storage. >> Right. >> So help connect the dots for us, because we look at- I remember a decade ago primary to secondary storage oh I'll give you a big eleven refrigerator size cabinet and you can do both. >> Mike: Right, sure. >> But I put expensive stuff here, I put cheap stuff here. I used the software to put it together. I'm assuming I can consolidate it down and I think Flash has something to do with it. >> Yeah, and so it's a multi tiered system. The array itself. It's an appliance. And obviously most of the value is in the software. There's a management platform that allows us to peer deep into the data. But everything is time stamped and indexed. So we have a global view of the data. And you can tier it, the most hot data very mission critical, business app data, goes to Flash. Secondary data can go to spinning disk or now we can archive to the cloud. Specifically any S3 target, Amazon or any S3 target. But what I think makes it very relevant is we've illuminated the notion of snapshotting. So we've built something that we call the time OS or the time operating system. And it's a time machine for your data. What happens is rather than incur that incredible burden of having to schedule snapshots, that only requires you at another incredible heroic effort to bring the data back, you have continuous data protection. I can go back at any point in time and literally with a very graphical screen point and say I want to bring data back from two seconds ago. And one of our best examples of that is we had a customer who had been attacked, has suffered from a ransomware attack. They went down for a week, they went down hard for a week. And they came and found Reduxio. They got attacked again. And the second time around they lost only two minutes of data. And the recovery time was 20 minutes. So this is what we enable you to do. By being able to give you access to wherever you're data may be, anywhere in the world, you can- we're approaching near zero RPO and RTO. >> Mike, there's been a number of companies that come and said data protection's been broken. We've been hearing that for a while. I think right down the road from us, like Tiffeo, company that looked at data management. Companies like Cohesity and Rubric, have quite a bit of buzz. Give us a little compare, contrast how Redxio looks at it verses some of those other- >> Yeah, and I'd say again, for anybody watching I think the Forrester Research Report outlines Reduxio, Cohesity and Rubric, right? And of course Cohesity and Rubric are doing an extraordinary job. They're scaling rapidly. They've got world class in Silicon Valley money in the company. They've got a world class client base. I think the primary difference is that we are bringing that third component. We're integrating primary storage along with secondary storage in data protection. Both of them are focusing just on the secondary and the data protection. We take issue architecturally with the fact that you've got to make additional copies. We take issue with the fact that the way they're approaching this actually they're in some ways exacerbating the problem because they're creating more data. But at the same time, they're also, for a given amount of capability two to three times the cost. So what we're hearing from a lot of our customers and our vars that sell both is they're walking into a lot of more, let's call them price sensitive accounts. Where they don't believe that the incremental value of what Cohesity or Rubric is offering is easily justifiable. There's going to be some pretty extreme use cases to justify a $300,000 initial investment as you go into the data center. >> Another piece, when I talk to companies today, one of the biggest challenges they have is really figuring out what their strategy is and how that fits. You talked about tiering and how the cloud fits into it, but how does Reduxio fit in that overall cloud strategy for companies today? >> Again, it's very early in our product evolution and so with version three which we announced back in late June, we allow companies to archive to the cloud. But do instantaneous recovery from the cloud. So we have two capabilities. One is called no migrate. So there's no longer a need to migrate data. So you were at the Amazon invent show and you saw the snowmobile get rolled out. And the reason that Amazon rolled that snowmobile and at first I thought it was a joke, is because it takes an incredible amount of time and effort to move data from one data center to the next. Reduxio has this no migrate capability where if I need to move data from that data center, I set that data in motion. And I don't know if you're a Trekkie or not, but you remember the teleporter? In version three we've created a teleporter. You can move that data from the cloud and although it may take a long time for that data to actually get to its target, you can start working on that app as if that data had already been migrated. When we run usability tests, and I remember one of them very specifically. And I know that you speak a little bit of Hebrew. I speak zero Hebrew. But I can remember watching one of our Israeli customers seeing this happen and this visceral reaction, like oh my god, I can't believe they did that. So we're trying to bring that end to end ease of use experience to managing and protecting your data wherever it may be. Bringing it back with almost zero RPOs, zero RTO. >> Mike, one of the questions, I've been talking to a number of CMOs lately, and just you've worked for a number of start ups. Today, digital transformations on the mind, what's the changing role of the CMO today? What have you seen the last five to ten years that's different and exciting? >> It's a great question. And I'd say that, and again, I did my first start up in 1991. So I can't begin to tell you how much high tech marketing has changed. But everything changed with social, digital and inbound marketing. It used to be that the sales team was responsible for filling the funnel. It is very clear that is an incredibly non scalable unproductive effort. And so we now are all about acquiring high quality prospects. We're a hub spot shop. We're a highly automated shop. And we are very biased toward digital and social. Is doesn't mean that we're not going to events and things like that but we feel that the way that we're going to scale this business, especially when we compete against big guys like Dell EMC and HP and others, there's no way that we can go person to person. So I'm not a very big fan of cold calling. I'm not a very big fan of going to trade shows. And collecting business cards in fish bowls and giving away tee shirts. We really believe that our customers are too busy, the know what they need when they need it. They've built a fortress around themselves. They're getting hammered. Just like I'm a CMO. And I must get 150 LinkedIn inmails and emails a day telling me about the next great lead management service. I can't even imagine what our customers are putting up with. So our job is to find relevant personas with highly relevant content at the moment that that is relevant to them. And there's many ways to do that, but this is really what we have to do with the data. >> So, Mike, at the beginning of the conversation we talked a little bit about innovation. >> Mike: Yes. >> Those of us that have been in a while, they're too many peers of mine that I think if you say the word innovation they roll their eyes. You have the great opportunity, you're working with master students around the globe, talk to us the people coming out of those programs. What does innovation mean today? What are they looking for, from a career standpoint? >> It's a great question. I think you and I could probably go for the next three hours on this subject so we'll have to be careful. >> We'll make sure to post on the website the expanded audio. >> Okay, but I mean innovation is such an overused word. And most companies really can't spell it and they can't spell it because their culture doesn't allow for it. So first and foremost, I think any innovative company or any innovative team starts with a culture that is all about trying to manage at the bleeding edge of best practices and really understand what's current. I have the blessing of being both the Chief Marketing and Corporate Strategy Officer of Reduxio and a global professor of innovation entrepreneurship at the Hult International School of Business. I teach between 1,200 and 1,500 students a year. I teach them courses in entrepreneurship, in innovation, in digital marketing. And I run hackathons on campus. We do a lot of events that give me an insight into who's passionate about innovation. And it's one thing to think innovation is interesting, because you can get a good job. It's another thing to actually have the comfort level of living in a world of ambiguity and high velocity. So a lot of it is, I'm looking for students that really want to sort of push the envelope. And they exhibit that in the classroom, they exhibit that in hackathons. They exhibit that in some of the internships that we take. They exhibit it by getting certified on HubSpot. Without me telling them to. Getting certified on Idio without me telling them to. Going to conferences. Learning. And then me learning from them. Because nobody can know everything. It's just so much new stuff going on right now. I've now got a team of 11 people and nine of them were my former students. I had a chance to observe them in action over 18 months and they're world class. And they have that innovation gene in their DNA. We're really at a point where I'm learning from them everyday. It's a very symbiotic relationship. >> Mike, for closing comments, I want to give you the opportunity, people find out more about Reduxio. What should we be looking for in 2018? >> Yeah, and so again, the one thing is will say is we are now at 200 distinct customers. We have in a very short period of time, and you know, when you sell into the data center people don't have a real sense of humor. It's pretty important that the stuff works. So the first thing I would say is we've gotten to that point now where we've got a lot of very significant customer references across websites and a lot of peer review sites. So we're now, so 2018 is building on that foundation. I think what you're going to see from us is couple of very radically innovative new projects. One a software only project. That will allow us to drive an inflection point in growth. By making available some of our core capabilities to anybody. Whether they own a Reduxio system or not. We really want to go big now. We've validated the architecture. We've got some great early indications from the market that this stuff works as advertised. Our customers are telling us we're simplifying their lives, we're making them more productive. And 2018 is about to really kick this thing into high gear. >> Stu: Mike Grandinetti, pleasure chatting with you. Thanks so much for sharing. And thank you for watching The Cube. >> Mike: Great. (upbeat music)

(upbeat music) >> This is theCUBE from Silicon ANGLE Media. I'm Paul Gillin. The cloud is all the rage these days, but as companies move to the cloud, and some of them seeking simplicity, what they find is they actually get complexity. Because they want to balance their resources, they want to hedge their bets, they don't want to get locked in, so they end up doing business with multiple cloud providers, and often with an on premise cloud as well. That creates cost complexity, and that's what Cloud Health Technologies is addressing. My guest is Tom Axbey, he's the new CEO of Cloud Health Technologies, a Boston based company, recently raised $46 million, they have software that helps companies understand their cloud costs and of course, to reduce them as well. So, Tom, just a couple weeks on the job, welcome to theCUBE. >> Right, thank you Paul, nice to be here. >> I'm sure you could tell better what Cloud Health does, than I can, so why don't you give your description. >> Actually, I mean you just did a very good set up for me. I mean Cloud Health is the de facto standard, cloud service management software. And as you quite rightly pointed out, One of the complexities now, is have a multi-cloud or hybrid cloud environment. So people aren't making a single vendor bet. That of course, increases, as you mentioned, the complexity and the costs controls, the governance, security, even more, and that's what we do. We manage all that complexity and give our customers a single pane of glass to help manage and optimize their cloud experience. >> When do customers typically come to you? Are they in a crisis, or are they coming to you earlier in the process, to avoid that crisis? >> You know, it's all over the map. It depends on their cloud maturity. So, customers, we've got, who are early customers, who were literally born in the cloud. So you think of services such as AirBnB and Pinterest, and Yelp!, you know, those services are cloud based right from the get go. What they've done is experienced tremendous growth, on global basis by offering these services, managing huge data sets, in the public cloud. But, they also had the expertise, because they were going through that right from the beginning. As soon as that scale becomes unmanageable, as it does, and that complexity becomes greater in a multi-cloud environment, they bring us in. It's just that their technical acumen was a little bit more advanced than say someone in the enterprise, who's been managing data centers and they want to migrate to the cloud. But they find that their expertise is in the data center world, and their expectations are, I want the same governance and management that I had in my data center, as I move to the cloud. So you're really embarking on the beginning of their cloud journey. Then sort of the third set of our customers are MSPs. So these are actually cloud service providers, who are basically offering their customers, and they're the trusted source for their customers, all the aggregated services that are available for them, and their experience. Mainly small-medium businesses and mid-market businesses will go through the MSPs, but they're customers for us too. >> Talk about complexity, what are some of the unique characteristics of the cloud environment that create complexity that perhaps customers don't always anticipate? >> Well the first thing is, is the pace of innovation in the cloud is at light speed. You've got these cloud vendors, Amazon, Microsoft, Google, and now you got IBM, you got Oracle, and many other ones, Alibaba, and AsiaPac, they're all increasing their service offerings at a rapid pace of innovation. Just keeping up to speed with the domain expertise is very very complex. Then, when you migrate to the cloud, you're migrating services, critical business services, and just like any other environment, computing environment, whether it's distributed computing or client server, you got to manage those complexities, so your business services and applications can run smoothly. As you know from certainly your experience, there's an inordinate amount of moving parts, and even more so in the cloud. Now, you multiply that by a multi-cloud or a cloud, or a hybrid cloud experience, and certainly, being able to aggregate that data, becomes a business critical task. >> We hear a lot about multi-cloud and customers trying to hedge their bets, is that a major force in the industry right now? Do you see companies actively trying to diversify the number of providers that they work with? >> We do, yeah, absolutely, and obviously, the larger the company, and the larger their cloud spend, the more likely they are to do that. So their not reliant on one cloud provider, and also they're experiencing different paces of innovation from the cloud providers, who are jockeying for that innovation right now. We're really focused on as well is the hybrid cloud. It could be a multi-cloud environment, but it also could be their private data center they're managing, or both. So yeah, we do see a huge trend in that. >> When customers come to you for the first time, and you do an initial analysis, what are typically some of the areas where you find the greatest inefficiencies, the greatest opportunities to save costs? >> Sure, I think it depends again on where they are in their cloud journey. They may be moving to the cloud, or thinking about it, and they want is some kind of visibility because they're so used to having tight controls, visibility, and budgets within their data center, because that environment is so mature to them, and the cloud is like the wild west to them. They're going to get these monthly bills, or they got to commit to certain workloads, or resources, without really understanding what their usage patterns are going to be. So we may come in and help with the migration, capacity planning, and certainly their forecasting abilities. The more mature they are, they want to start allocating costs, maybe by department, or by geographic regions, so they're getting more and more sophisticated in terms of their cost breakdown and their usage patterns and when those usage patterns happen. But also, as they control their costs, one of the ways they can do that is to buy future visibility, if you will, into those resources or compute power from the cloud providers. Being able to figure that out from a histotical and perspective billing standpoint, can be incredibly valuable to the customers. >> So what kinds of data do you provide for them? >> Well we provide essentially a window of aggregated roll-up of any particular service that they could have. So it could be their financial data in terms of their usage information, which resources or compute loads are working, also as they've deployed stovepipe data vendors for performance management or configuration management, security management, all of that comes into play as well, so we can roll up that aggregated data source. So they got a single pane of glass into sort of their entire environment. That could be at the VP level, who's running a multi-cloud environment, it could be at the financial level, where they're looking for cost controls, or could be the DevOps level where they're looking for anomalies or performance issues, or bottlenecks, or capacity planning, so at every level, we're trying to provide visibility into sort of the function and task that our customers have. >> Of course cloud vendors aren't interested in having their customers be multi-cloud, they want them to be single cloud, how cooperative do you find the vendors are in working with you to enable your customers to hedge their bets? >> I mean I think that they're very helpful, I mean number one, we've got deep relationships with all the cloud providers because we've been doing this a long time. Also, what we're doing is, we're hastening and accelerating our customers movement to the cloud by offering them the same visibility and governance and tools that they had in their data, or private data center world. So they actually embrace it, and they know it's going to be a multi-cloud environment, especially for the larger customers, and so, absolutely, we're helping that. >> Are customers beginning to look to broker their experiences, their costs, to move workloads sort of flexibly between different cloud providers, based, perhaps on even short term savings? >> They can do, yeah, absolutely. But again, short term savings are a trade off between long term savings, in terms of how much capacity you're buying, how much visibility you've got into your usage patterns as well. Certainly, that's the world that we're getting into these days, I mean, Amazon does per second billing now. When you think about all that data, it's absolutely, the complexity of it is absolutely mind boggling. >> The cloud world as Forester pointed out in a recent report, is consolidating into basically three big players, and then sort of everybody else. Do you think that's a good trend as far as customers are concerned? >> I think we've seen it over and over again, you see the dominant providers come forth and start taking over a marketplace, but there's always going to be room for other vendors. Now IBM and Oracle certainly are not just going to lay down. People like VMware are getting into the cloud business as well. They're the dominate ones right now, absolutely. I think what's good for the business is the trend itself of people moving all these workloads to the cloud and having more control over it, so that it'd actually be transparent as to who the cloud provider is. >> You certainly had the opportunity to take executive positions in a number of companies, what was it about this opportunity that appealed to you? >> Well, that's a very good question, I'd been at Rave for quite some time, especially in the high tech world, and we had a very successful run there, and we were acquired by a private equity firm. I was looking around and perhaps making a move, and I'd been fascinated by the cloud, and what it was doing, and how transformative it was to business. It was very akin to experiences I've had in my career, selling infrastructure software. I was at IBM, Tivoli for example, I was at MicroMUSE, and they were basically undergoing exactly the same transformation, in client server and distributed computing days. I was also aware of the investors and a couple of board members of Cloud Health, and I recall their very first investment, and it was explained to me by one their investors, this is Tivoli for the cloud. And of course, that resonated with me. I thought, that's brilliant, that's so simple, 'cause you've got exactly the same complexities, and then I tracked the company, had the opportunity to meet the founders, and I saw how they had executed against their vision, I saw the caliber of the team there. So, when an opportunity came up because the CEO and co-founder Dan Phillips was moving into the Chairman role, as my partner now, I jumped at it. >> You say Tivoli for the cloud, is an interesting analogy, of course the difference with Tivoli and cloud, is that Tivoli is on premise. You control the infrastructure, you have access to all the interfaces you need, not necessarily the case with the cloud. What are some of the difficulties that you encounter with getting customers the information that they need from their cloud providers? >> Well certainly the cloud, like I said, the pace of innovation is huge. So you've really got to be up to speed with the latest offerings, and if you look at all those APIs and how they could be changing, new services that they could be coming out with, literally on week by week basis, you've got to keep track of all of those. Then you've got to have a flexible architecture so you can actually easily integrate with those data sources and also understand the necessary workflows to present all that data in a consumable way. So it really is a very fast pace of innovation right now, and I think that's why the analogy of Tivoli for the cloud was a good one because you are aggregating all that data, you're given critical insight into, certainly back then, their network and infrastructure, business services, so the analogy holds true, but I think you're right, the pace of innovation is much quicker. >> Now, talk about how you justify your cost, what kind of deliverables do you promise customers in exchange for what you charge them? >> Fortunately, the deliverables are born out of history. We've got incredible ROIs. As you know, the monthly spend as it increases, as people's cloud experience grows, those costs can spiral quickly. I think that when people talk about the cost, we always talk about the value. What value are you looking for? How are you going to optimize your environment? So the savings we can save just on their billing or utilization, and then there's the governance, and then people want to do departmental charge backs or geo charge backs, and we can help them with that cost allocation. So we tend to talk about value more than cost. >> Where do customers leave money on the table though? Where do you find some of the greatest disconnects between what they could be spending and what they really are spending? >> It all comes down to consumption. If you, just like if you're deciding which mobile phone bill you want to get based on what your projected consumption is going to be, you know, they want to lock you into the biggest one, they're going to show you lots of different values for signing you up for a three year contract. It's the same for a cloud provider. The more you're willing to prepare, the more you can lock in your costs, and of course, as you do that, the risk is, you don't fulfill all of those costs and realize those savings. On the other hand, you maybe growing so exponentially quickly, that you're actually paying more than you would be, than if you just basically consumed a different pricing model. >> In general though, do you find that customers, if they manage their cloud costs wisely, do they, in the final analysis, save money by moving to the cloud versus an on premises architecture? >> Without a doubt. The time to deploy services is so quick. The time to integrate different facets of your business services is so quick. When you think about unlimited throughput, and speed, and storage, on a global basis for your services, it's unprecedented. >> Does your service cover software as a service as well? We do, I mean, we're a SAS company ourselves. So, as you know, many SAS companies are now providing services into the cloud. We could be collecting data from those services too. >> What's the future hold then for Cloud Health? Where do you want to take this company? >> I think that in beginning, I said we're the de facto standard for cloud service management. It's hard to claim you're really the de facto standard. Especially when we're a private company. I think what we want to do is continue to provide value, continue to innovate, continue to have that domain expertise, and when you look across the whole governance spectrum, about all these different systems, all these cloud providers, all these different data sources, it's absolutely immense. I think that always having that single pane of glass so that people can really get the visibility they need to optimize their services, we're going to be a very large company just doing that. >> I understand you have some ambitious growth plans this year in terms of the number of employees and also moving your headquarters. >> We do, I mean, I've only been on board for what, two and a half weeks, and there's already been 10 people hired since I've been there, so that's the pace of hiring right now. I think we'll end the year at about 240 employees, so probably hired about 80 employees, and then we are moving early next year, we're moving Fort Point to Downtown Crossing. So we got to accommodate them all. >> For those of you who are not familiar with Boston, Downtown Crossing is the center of town, and Four Point is the hot new area where GE is building it's new headquarters. In terms of how your business category develops, do you see this as a continuing to be a major independent category, type of services you provide, or do you think cloud vendors will ultimately acquire companies like yours and offer these services on their own? >> I think both is going to happen. I think cloud vendors will acquire companies who do stovepipe, perhaps functionality, for a certain area, but no cloud vendor's going to be able to offer the cross multi-cloud or hybrid cloud experience that we do. I think you're going to see both, but absolutely, the ability to manage multi and hybrid cloud environments is the key. >> It's something I always ask our Boston based guests, what are the advantages of being based in Boston? >> Well the advantage is absolutely huge, especially in this day and age. Boston has got an immense talent pool coming out every single year from universities, and that talent pool now wants to stay in Boston as opposed to move to other places. Because the city has gone through rejuvenation, it's a vibrant city, it's an invested in city, you mentioned GE, there's other companies moving here, it's a great time to be here, you've got many success points in the high tech arena such as HubSpot and Wayfair, and LogMeIn, publicly traded companies offering great opportunities, so I think the pace of innovation here is happening at a tremendous clip, so Boston's a great place to be. >> Glad to hear it, welcome to town. Congratulations on your growth, and much success to you. >> Tom: Great, well thank you very much for having me. >> Cloud complexity, simplified. I'm Pual Gillin, this is theCUBE. (upbeat music)