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Episode 8: SaltStack – Event-Driven Automation with Thomas Hatch

Thomas Hatch is the Co-Founder and CTO of SaltStack, an event-driven automation platform that delivers threat-aware security compliance, fast and scalable control of any cloud, and configuration management for heterogeneous application environments and data center infrastructure. In this episode, Thomas describes how SaltStack has built tools and point solutions to monetize a very flexible open source platform for orchestration and configuration.

Transcript

Michael Schwartz: Welcome to Open Source Underdogs, the podcast where we talk to the people who make open source companies get up and go.

Today my guest is Thomas Hatch, CTO and Co-Founder of SaltStack.

The SaltStack automation platform delivers threat-aware security compliance, fast and scalable control of any cloud and configuration management for heterogeneous application environments and data center infrastructure.

This is one of their first remote interviews, and I forgot to get hellos and goodbyes, so we’re just going to dive right in with the first question. Here we go.

Origin

Tom, can you share with our listeners the journey that led you to start SaltStack, and why using the open source development methodology was important to you?

Thomas Hatch: To be honest, when I started writing Salt, my aspirations weren’t quite as high as they are now. I started writing Salt in my basement to pretty much solve a problem.

I’ve written a lot of other pieces of software that were proprietary owned, and owned by companies that I work for, but always as an internal tool, and I was kind of sick of having to rewrite it.

And so I thought, “Well, I’ll just write it this time and make it open source and clear it with this company that I’m going to make it open source.” And after about ten months or so, people were using it. So I started looking at it saying, “I should try and make a business out of this.”

I mean, like you were saying about business models, it started off that journey, that journey of trying to figure out what are the optimal ways to be profitable, with an open source software platform.

Initial Struggles

Michael Schwartz: How do you survive those first two years?

Thomas Hatch: Well, back in 2011, I mean, that’s when I started writing the project to my basement, I still had a job, and at that point, it was me, spending my nights writing Salt, and my employer didn’t mind because they were using Salt internally, but it also made it a great test bed.

That company went out of business not because of their infrastructure, but went out of business at the end of 2011.Yeah, I mean, I still remember, I was in my basement, and I get the “Hey, we are out of the business” phone call.

And I went upstairs, and I tell my wife, “Hey, do you think I should make a business with this Salt thing, people are starting to use it?”

And she looked at me and said, “Don’t you dare do anything but start a business! I don’t want to listen to you moan for the rest of our lives together about how you missed your big chance.”

So, then, we had a fair amount of money in savings and we pretty much burnt through that, through 2012, and we were honestly running pretty low on cash when we got our first seed money in the door, but yeah, I mean, that was basically it, that and a few consulting jobs.

Initial Community

Michael Schwartz: That’s amazing! Congratulations. What was the community like in, let’s say 2013, when you raised that seed funding, like how large was the community at that point?

Thomas Hatch: We had received contributions from maybe 400 people, community had grown pretty quickly through 2012. We had quite a few pretty large users. So some of the flagship users that we still have we’ve gained back then, like LinkedIn for instance.

Open Core

Michael Schwartz: I was watching the 2016 keynote that’s on YouTube, and in that keynote you mentioned you’re not a fan of open core. Have your thoughts changed at all on this topic?

Thomas Hatch: Well, I’d like to say that my thoughts have evolved a lot over the years. In the early days, my thinking was, “Let’s just make a ton of open source software and figure it out.”

But at the same time, I did want to avoid an open core issue because when you go with open core, it stifles the innovation that can happen inside of your community.

I really wanted to avoid stifling innovation, but at the same time, we ran into a problem which is pretty typical I think of a lot of open source software companies is that, we’re out there and we’re selling services and support, but once we solve the problem for our customer, they don’t really need us anymore.

I mean, we go back to the early, early years, and that was a lot of what we’re running into. So we decided to start working on an Enterprise product. I specifically architected the Enterprise product so that it was a separate piece of software.

The actual definition of open core is hotly-debated, I definitely argued that we are not open core, but every now and then someone comes out of the woodwork and accuses us of being such.

The way that I look at it is that open core means that you have one piece of software that is augmented with proprietary software directly in that codebase. What I wanted to do is create a separate piece of software that could sit above Salt and value.

One of the things that I find challenging with that was that, right off the bat, developing proprietary software is very different from developing open source software.

And I think that that’s one of the major problems that a lot of open source companies run into.

They say, “Okay, we’ve been really successful, making a piece of open source software that people love, and we can make a proprietary one, but the way that software was developed is so dramatically different from open software.”

So we struggled a lot admittedly early on in making that piece of proprietary software. And then we hit another wall that, again, in retrospect, I think it’s a common wall for people to hit from business and monetization perspective, especially with add-on software.

It was that the proprietary software that we had just ended up, mostly at the beginning it just expressed what we already did with open source software.

So we found it was really hard to create differentiation. It was especially difficult to create that differentiation because Salt does a lot of things. I mean, it’s an incredibly powerful platform. So, then, we struggled with that.

A lot of where my head is at today, it’s actually along the lines of what I like to refer to as “peripheral engagement.”

So when we come back and we look at our core users of Salt, their needs are typically your devops professionals, SRE professionals, people who are very technical and low-level in being able to use the automation platform.

But then the power that we found from a sales perspective and a monetization perspective is to make sure that our Enterprise products are geared towards the needs, not of that core team as much, but more towards the groups that are slightly peripheral to that core team.

And it helps that core team, and then they are able then to expose the power of what they’ve built with Salt to these other teams.

So, right now, a lot of our success has come through our Enterprise software, exposing the functionality of Salt over to, say a NOC environment, or your IT maintenance teams, which makes just that day-to-day maintenance significantly easier.

And then we’re also in the process now, because we’ve seen some success there, we’re in the process now of creating a new security, a SecOps piece. And we’re really excited that’s going to come out, our Enterprise software first quarter of next year. And we’ve already got a lot of companies lining up to purchase this in their infrastructure.

And, again, it turned into the situation where we’ve got a powerful, open source foundation that is widely used.

That open source foundation needs to cover certain use cases that are broad in nature and are platform in nature.

And open source communities are really good at developing those, but we find over and over again that there are certain areas of software development, where open source communities, to be frank, don’t seem to be quite – I mean, I’m going to get burned for saying this, for saying anything disparaging about the effectiveness of open source communities and software development – but there are certain areas where open source communities seem to have difficulty building software that gets wide, mainstream traction despite the quality of the software that comes out.

And those are areas where open source through the years just hasn’t been able to penetrate.

One of my favorite examples there is the “year-of-the-open-source-desktop.” I mean, I’m running KTE, sure, of course, but Linux desktop hasn’t penetrated the masses whereas the Kernel has.

So you end up being able to kind of step back and say, “There are things that an open source community express as well if we can build the targeted solutions, that solve business problems that aren’t going to be solved as easily in a pure open source environment, then that is a way to market, and the way to augment your position.

Open V. Commercial

Michael Schwartz: How do you decide which software to make commercial?

Thomas Hatch: So early on, it was kind of, “Well, where does it belong?” You’ve got an Enterprise platform, if it belongs in the Enterprise platform, it’s commercial. Otherwise, it goes in the Open.

At this point, it’s shifted a little bit. I mean, that’s still part of that philosophy, but it’s shifted in, proprietary is that which is tied to the solution that is being expressed in the proprietary software.

Actually, that core answer still really holds true. If that functionality belongs on the Salt agent, it’s got to be open source. If that functionality belongs on the master, it’s generally going to be open source. If hat functionality belongs in the Enterprise piece, it’s going to be proprietary.

Resource Allocation

Michael Schwartz: So how do you prioritize, with regard to like resource allocation, everyone’s resource-constrained, you know, you can’t develop everything you’d like to develop, but how do you decide how much to invest in a Commercial versus the open source?

Thomas Hatch: A lot of that has to do with really just hitting our goals. We have that blogmenting who’s working on what quite a bit.

We’ve got a few people who stay Open all the time, and we’ve got a number of people that stay Enterprise all the time, and we’ve got a few people that kind of bleed between teams.

It’s basically, Hey, we’ve got to get X, Y, Z then to meet our protocols of the Open, and we’re a little ahead on the Enterprise side. Then, we’ll shift him over and vice-versa.

It really depends on, frankly, sprint-by-sprint basis on where those needs are. It’s just this constant balancing.

Commercial & Open Source?

Michael Schwartz: Do Commercial features ever move into open source?

Thomas Hatch: Oh, definitely. It’s one of the interesting things too.

As I come back and look at it, occasionally there’s some component libraries that we make for the Enterprise piece that we move into the Open.

One of the things about having a separate codebase like we do, for the Enterprise platform, is that things that belong in that Enterprise platform, again, by their nature are more likely to stay proprietary, but in the places where there is some lead over.

So occasionally we’ll end up writing something that – actually, let me just kind of walk you through a life cycle of this.

So Salt’s pluggable, crazy pluggable, and so we’ll write plugins that are going to be running on the minion that need to be deployed by the Enterprise products. So they can, you know, do its work.

And, oftentimes, those plug-ins are very specific. So we don’t hide the code, but we don’t add them directly into the Open source product because their functionality is directly tied to the use case that’s being expressed in our Enterprise product.

But occasionally, those plug-ins are of such a value that they are generic, in which case, we end up putting them in the Open and the proprietary software at the same time, so that the proprietary software can then send those plug-ins out, really as a back port, to older versions, until our entire customer base migrated to a version where that’s just baked in.

It’s not always this philosophy of, “I’m going to make a piece of proprietary software, and it’s got a timeline until it becomes Open.”

That is something that I think that we’ll probably be adopting as some of our proprietary software matures a little bit, and its install base matures. And we’re able to continually make the right business cases and the right alignment.

But yeah, that’s one of those things we feel that we need to walk into, as opposed to trying to pursue the future too much, too early on.

Is New Model Working?

Michael Schwartz: You mentioned before what I call the open source dilemma, which is, customers only buy support when they need help.

You’ve moved towards a licensed strategy, where certain features are licensed, and certain features are open – how do you feel about commercial adoption so far since moving to that strategy? Has it met your expectations?

Thomas Hatch: It has certainly improved. It has certainly met some of my expectations.

I mean, entering into that strategy, there were still things that I was skeptical about.
A lot of my goal for a long time inside of the company, we need to express a certain amount of functionality from our proprietary software, to be able to just get to the point, where we can start expressing these targeted solutions that I was talking about.

As we built out the targeted solutions more, the sales improved significantly. It’s been really interesting to watch because those solutions that are built out in an Enterprise software, that augment the automation platform that we have in the Open, does start to drive sales, and does start to drive a business model that is much more sustainable as we grow.

As opposed to, I mean, we still run into a number of open source companies that struggle making that sustainability kerf, they still need to have a significant amount of their business consumed by professional services.

Customer Segments

Michael Schwartz: Do you segment your customers at all?

Thomas Hatch: Oh, definitely. Usually we segment them along solution verticals.

Instead of looking at them from industry perspective, and there’s certain industry overlap relative to solutions, we look at the very much so as to what are the problems that they’re trying to solve.

And we’ve got customers that are solving IoT problems, that, you know, if our automation said, ‘customer’, you would probably think, “Well, I wouldn’t think that they’d be the kind of customer that would be solving the IoT problem.”

And vice versa. I mean, when we come back, when we look at one of our customers is a major cruise line, and they use Salt to manage devices on cruise ships. So we categorize them as an IoT customer.

Other customers will do things like as this typical network automation or application deployment, all those generally automation platform use cases that you run into.

So, yeah, that’s mostly how we separate them.

Customer Interaction

Michael Schwartz: How do you interact with customers?

Thomas Hatch: We’ve got numerous tiers that we can sell, everything from allowing somebody to get us on the phone within a few minutes, all the way down to, they’re going to open up a ticket, we promise to get back to them in the next, say, 72 hours. All depending on which tier of support they want to buy with their licenses.

You look at what you offer, then you look at what people use, and it doesn’t always line up quite as nicely as you hope when you create set offerings.

Customer Size

Michael Schwartz: Is your business skewed more towards large or small transactions?

Thomas Hatch: Our software, by its nature, it tends to be more applicable to larger, more complex problems, from a platform perspective.

From a solution perspective, it’s a lot easier for us to sell into those smaller and mid-market size companies.

And then, again, I completely agree there, I mean, that is your sustainable revenue.

But, yeah, that has been something that’s been interesting, because earlier on, the vast majority of our revenue came from really large installations.

Or they would come back and say, “We just have to have a relationship with you, guys.” We are using Salt to manage hundreds of thousands of systems and, yeah, we just have to have a relationship. Even if they would go months, and not talk to us or reach out to us, we’re reaching out to just say, “Hey, is everything okay?”

That still turned out to be a significant chant, again, early on. But, yeah, as we’ve evolved and as we’ve been able to embrace these solution expressions in a cleaner way from our proprietary software, that has attracted more of the smaller and mid-market customers.

How Has Offering Evolved?

Michael Schwartz: That sounds like your offering has changed. What’s working well, or what hasn’t worked well, or what do you think is missing?

Thomas Hatch: Oh, I mean, what I think is missing is, you know, just more software. Always trying to get more products, build them to be more robust, but yeah, I mean, like you expressed, it’s a journey, so a lot of my assumptions about things have changed over the years.

A lot of my assumptions about the role and mechanism of how development happen, that’s changed.

Again, if we look back at the customer base, how that’s changed, we still have a lot of strength and really big customers.

We’re used by quite a few major banks, insurance companies, big tech companies, but yeah, the things have changed for the better, I think, more recently over the last year, so that improved traction in the mid-market.

And our change, I would say is very much so towards our ability to begin to shift from a pure platform support sale to say, “You’ve got a really complicated platform.”

“Our Enterprise piece can help you manage it.” to being able to say, “You’ve got a target of pain point, and the entirety of the software that we deliver can help you solve that pain point.”

When we talk in terms of pain points directly, that is more directly applicable to those smaller and mid-market companies, whereas the big platform play makes more sense to the larger ones.

Reducing Revenue Lumpiness

Michael Schwartz: Can you imagine serving the smaller pain points is more scalable, in terms of building the revenue?

Thomas Hatch: Definitely. I mean, as you are probably aware, you get the big guys and it’s up and flow.

You have two months that are fantastic, and then you hold your breath for another month and a half until the next giant deal comes in, but once we’ve got more of those pain point solutions in, they’re significantly easier to support, they are significantly easier to sell, you get a more consistent sales cadence, our revenue still looks a little lumpy, but it’s not lumpy in a bad way, like it was two or three years ago.

It’s lumpy in a way of saying, “Hey, there’s frosting on the top of this cake.”

Channels

Michael Schwartz: Have you worked much with channel partners?

Thomas Hatch: Oh, I think channels are very, very useful. They can be tricky.

In the early days, we started with professional services channels. And we did, we struggled a lot to get those going. But more recently, the picture and painting is that our model has evolved a lot for the last few years and it continues to evolve.

And as it’s continued to evolve to be more solution-oriented and less supporting a complex platform-oriented as far as that mixture, then channel partners have started to be much more lucrative for us.

It’s a lot easier for a channel partner to execute a sale that has a more simplified delivery, as opposed to going in and dealing with that whole complex platform sale.

Resources

Michael Schwartz: Where do you feel like you’re the most constrained, resource-constrained?

Thomas Hatch: I don’t know, everywhere? That is admittedly a very challenging question. I definitely feel resource-constrained in engineering, both on the Open and Enterprise side.

Probably the place where I feel like I’ve heard the most resource-wise over the years honestly has been marketing.

I think that’s one of the things that we struggled more with, and I think we’re struggling more, going back again to that platform versus solution thing.

As we’ve rolled out our solutions, it’s been a lot easier to market, as opposed to platform play. It’s hard to market, “Hey, we can do anything, tell us what your problem is?”

Underdog?

Michael Schwartz: Do you think SaltStack’s an Underdog?

Thomas Hatch: We get pigeonholed by the market in certain places, and so we have a very powerful configuration management platform. So the market likes to put us with Puppet, and Chef, and Ansible.

When our customers come back to us, they say, “Yes, we use your config management, but not in the same way that the other guys use it.”

So it’s hard to categorize this as an underdog because I think we’re an underdog in the sense of the market things we belong there, but that’s not where we want to be, as much as – I mean, don’t get me wrong, config is very important and I would still argue that we’ve got the best config platform, but so much of our focus is around automating tasks that are outside of that classical config management use case.

I don’t see us as much of like an application, deployment and management company, which is what you see a lot more from the config management players.

I see it’s more of an infrastructure maintenance and building company, and then, event-driven company, and a security out of remediation company.

And in those areas, I don’t feel as much like we are an underdog. When we go in, from command and control, and an execution position, we don’t really have a lot of competition there.

We’ll get compared to some of the other open source players, and we just say, “Yeah, but they don’t do X, Y, and Z.”

So the nature of our offering is so different, and the approach that we’re taking to managing infrastructure has so many differences in it that I generally get pretty frustrated when somebody comes and they say, “Well, you know, I use Ansible instead of Salt because of X,Y,Z.” And I’m like, “I don’t care.” Most of my customers are using also Puppet, Chef, or Ansible.” For many of them, they’re using Salt to orchestrate and manage those tools.

It’s frustrating along those lines, because we’re kind of still pigeonholed in that area when we really shouldn’t be.

And one of the things that I am excited about is that some of these products that we’re working right now, I feel like they’re really going to help us break out of that better and expose our functionality better, and the reasons why what we do isn’t just, you know, a copy of Puppet.

Salt In 5 Years?

Michael Schwartz: Where do you see SaltStack in 5 years?

Thomas Hatch: Especially with the newer security offerings that we’re producing an offering now, as well as the expansion of a number of other solutions, our sale’s on a positive trajectory, moving us towards going public.

And, I mean, again, we’re still many years away from that. I’ll avoid making some public statement. Ten years, I sure hope we make it there in ten years.

That’s definitely the track that we’re on from a macro business perspective. Yeah, figuring out what the revenue models look like is something that I feel is increasingly part of our past. And our future is more of executing along those models and growing out the pieces that we’ve learned to work really well.

Going Public?

Michael Schwartz: Do you think that going public would assure the continuance of the open source mission, in a way that another exit strategy would not?

Thomas Hatch: So I should probably temper my earlier statement, I believe very strongly that you should manage a company towards building the company in such a way that it would be viable as a publicly traded company, and that you’re gearing your company towards growth and stability.

I certainly agree that taking a company public is not necessarily always the best option any more. The markets are much more complicated than they used to be.

I also want to, you know, caveat that by saying I believe that managing a company in such a way to go public, and managing it responsibly, is probably one of the best ways to, either be acquired by another company, or private equity, or whatever.

The right tact that I would take would be that I am managing towards the goal of making SaltStack into a company that can be viable in the public market. But I’m not going to close myself off to potential opportunities.

Final Advice

Michael Schwartz: What are the biggest challenges facing the founders of open source software companies?

Thomas Hatch: The open source business model is viable. I certainly don’t want to say anything to disparage that, but being able to build internal culture, and a management mindset, that deals with open source, and profits from open source, and functions in a stable and responsible way with respect to open source, is in and of itself one of the big challenges that you’re going to face.

It’s one thing to make a piece of open source software and get people to use it. It’s another thing to realize that you now have to build another thing on top of that open source.

Two, your sale cycle and your marketing cycle, these are going to be complicated. You’re not selling candy, so you’ve got to work hard to make sure that your sales teams and your marketing teams, and a lot of these people that are more token and dollar-driven are able to see the benefit that they are receiving from the open source.

Otherwise, you’re bringing these people from other areas and they can eat you alive, and end up sending you down bad paths. And that’s another one of those things that I see all the time.

The other thing to warn against is the extreme on the other end. It’s really easy from an open source developer perspective, and I was very much this way, to get caught up in the virtue of Open Source and the idealism of Open Source.

I certainly believe in the idealism of open source, but my views have changed from what I feel was used to be more of a blind trust in open source into more of views that are along the lines of saying that I understand how open source is important and viable inside of a complex economy, instead of just looking at it and saying, “If I build it, they will come.”

Credits

Michael Schwartz: Well, that’s it for episode 7. Thanks to Tom for answering all my tough questions.

Transcription and episode audio can be found on opensourceunderdogs.com

Special thanks to the Linux Journal for co-sponsoring this podcast to the All Things Open conference for helping us publicize the launch.

Music from Broke For Free, by Chris Zabriskie and Lee Rosevere.

Production assistance from Natalie Lowe. Operational Support from William Lowe.

Thanks to the staff of SaltStack for scheduling support.

Next week, we are joined by Matt Mullenweg, Founder and CEO of Automatic, the company behind WordPress which needs no introduction.

Until then thanks for tuning in.

Episode 7: MongoDB – Cross-Platform Document DB with Eliot Horowitz

Eliot Horowitz is the Co-Founder and CTO of MongoDB. MongoDB is the fastest-growing database ecosystem, with over 30 million downloads, thousands of customers, and over 1,000 technology and service partners. In this episode, Eliot describes how Mongo uses a combination of cloud services and licensing to drive growth of their business.

Transcript

Michael Schwartz: Welcome to Open Source Underdogs, the podcast where we interview founders of amazing open source software companies, and ask questions to help us lay people understand what makes the business tick.

Today I’m in Manhattan, with great views south of Times Square, chatting with Eliot Horowitz, Founder and CTO of MongoDB Inc.

MongoDB is a leading NoSQL database platform and has been downloaded over 40 million times, making it easily one of the most popular new persistence layers for modern web and mobile applications.

Eliot, thank you for joining us today, we’re excited to have you on the show.

Eliot Horowitz: Thanks for having me.

Origin

Michael Schwartz: Can you tell us about the origin story of MongoDB?

Eliot Horowitz: So we started building MongoDB about 11 years ago, and the origin story of Mongo really dovetales entirely well with sort of my background and software.

Every time before starting MongoDB that we got stuck on a really hard problem on some project, it almost always came back to database problems. Either the database wasn’t scalable enough, it wasn’t fast enough, the data model didn’t quite work.

And between Dwight Merriman, who is the other Co-Founder and I, in the decade before we started Mongo, we counted that we probably built about 12 custom databases to work around problems – whether there was a DoubleClick or ShopWiki, always working around databases just to get things done.

And so when we started MongoDB, our goal really was to build a database that we wanted.

And originally were thinking about trying to build, we had some other ideas for some projects and applications we wanted to build, and we very quickly realized that we were going to run into database problems.

And as we started designing the database we would want for that application, pretty quickly realized that we were way more interested in actually building the database than the application, and just started you know, alright well let’s build the database.

And so we started building the database about 11 years ago. Shipped the first version about 18 months later. Been on the journey ever since.

When To Start Company?

Michael Schwartz: That’s awesome. Was there an existing community before you started the company? Or, do you have any thoughts about when’s the right the right time, if you have a great open source project, to start to think about monetizing or making it a business?

Eliot Horowitz: So for Mongo, we started at the same time. It was the two of us and we just started writing the software.

And we did as a company, and it wasn’t actually entirely obvious to us on day one whether it should be open source or not. Frankly, because we really hadn’t thought about it very much.

You know, for the first year we were really just focused on building on building a software. And then once we were ready to start trying to see if people were interested in it, was very obvious to us at that point that no one was really going to be that interested in a proprietary database in 2009.

And so the obvious decision at that point was to make it open source, and then we started building a community around it. So, the other way, I don’t have a lot of particular experience the other way, you know, starting taking a project and then trying to commercialize it.

But the way that we did it, I really kind of enjoy, right. You have an idea, you think the idea really should be open source, so you start building a product you make it open source, and you work on building a community, and a group of people who are really excited about it.

And it was great even early on, you know before we were trying to monetize it. You know, we would hire a lot of people from the community, we’d get contributions, we look through them.

The ones who continuously delivered great contributions became some of our first engineers, some of them are still here today.

Why Are People Excited About The Mission?

Michael Schwartz: Why do you think people were excited about the mission of MongoDB?

Eliot Horowitz: So I don’t think our experience with databases was particularly unique. I don’t think there are many developers who are in love with their database.

You know, the number of developers who have said who have to fight with their databases, whether it’s because of the data model or to solve other problems. And so I think a database that really tried to directly address the three main problems really pretty interesting.

The three problems we had, really are very standard. Right, so those problems are the document model, or problems of the data model, right.

So we saw that with the document model. Whereas the document model is just a much more intuitive data model for most data.

People when they’re thinking about data, when they’re thinking about business objects that they’re writing with code, they don’t tend to want to break them down into tables and rows, they tend to want to store them as as they are in their code; as they are in the real world.

And that resonates with a lot of people because that’s how people think. People think in terms of structures. And if you look at every API in the modern world, they’re almost all in a JSON over HTTP, and why is that?

Well, the same reasons right, JSON is a pretty good format for representing data. And then you can take that JSON and store it directly in Mongo – that becomes pretty powerful.

You tie that with a query language that lets you actually index and query those JSON documents, you got something pretty compelling.

Then you take that and you add on distributed systems, so you solve a lot of the problems around high availability, and scalability that people have, and let you solve other really interesting problems like putting data in different places.

And then you take those two really great attributes, make it open source, make it accessible to run anywhere on any kind of platform, whether it’s in the cloud or in a private data center.

You know, it’s a pretty compelling product for most developers.

Customers

Michael Schwartz: Who are the customers who said – okay, this is great open source but we actually want to do business with this company, too?

Eliot Horowitz: So there’s a lot of history there as well.

So you start off early on, the people who decided to engage with us commercially, it was largely just around support.

Right, it was larger companies who were really interested in using Mongo, but was a very new technology and they basically were not going to put it into production without a support contract.

That was you know, eight, nine years ago. Things have evolved quite a bit since then.

So now we have a few different kinds of focus areas, I would say, and you can break it down roughly into two major camps.

One is sort of the Enterprises were largely still on premise, who are sort of deploying our Enterprise version which has sort of advanced security features and management features. That sort of one big cohort.

And the other big cohort is the people who are in the cloud, who are using our fully managed service that is MongoDB Atlas, who really want a fully-manned and turnkey database sort of experience in the cloud, so they can come in either with an API of the UI, and manage things really easily.

Deploy clusters, manage clusters, and have all that taken care of by us so they don’t have to worry about database infrastructure and can just build applications.

Customer Interaction

Michael Schwartz: You guys must have tons of customers, and it must be a challenge having relationships with all those customers. How do you interact with the different types of customers?

Eliot Horowitz: We have a large sales team and a large customer success team. But, I mean it’s really, our sales team has grown tremendously in the last five, six years, we’ve got a really great support team.

So that, you know, one of the things we really pride ourselves on is having a great customer support, so whenever anyone calls they can get you help really quickly.

A great customer success team to make sure that customers are happy, that they’re building the things that they need, that were making sure that we’re going in the right direction for them. That if there are any challenges that they’re having that we can address them quickly. I mean those teams are all in all scaling pretty aggressively.

Michael Schwartz: Are there any lower price points where maybe it’s hard to interact directly, where you’re looking to other types of relationships with people, more automated, online ways to sort of scale?i

Eliot Horowitz: In our Atlas product, right, the Atlas product goes anywhere from is a free tier to tiers that are $10 a month or $25 a month, but you know you’re not really having a direct personal relationships with everyone of your users because there’s way too many.

And that’s where we do a lot of automated systems – we’ve got online support forums. We use chat, we use a lot of chat software; usually back by real people, but there’s actually chat software to make that easier.

But a lot of what we’re focused on in the managed service space is how do we make the product really let people help themselves. You know, how do we do better and give you better, help you understand what you should do to help your database go faster.

So for example, index advisors. So we’ve got an index advisor, they’ll tell you – hey we’ve noticed that these queries are running slowly, maybe you should go ahead and add this index. And really trying to let users be incredibly successful without a lot of help.

Community Misunderstanding

Michael Schwartz: Is there any way you wish the community understood MongoDB better?

Eliot Horowitz: There’s a few particularly interesting challenges with Mongo.

One is that the data model is just such a different thing than what a lot of people are used to. And people really need to take the time early on, especially when they’re adopting it quickly, to make sure they really understand the right way to model data with Mongo, and not just to use the relational models they’re used to. That sort of a pretty big one.

The other big one is and I think a lot of early open source projects, or just even companies have this problem where people think you haven’t added a feature in the first 5 years after they’ve asked for it, that you’re never going to do it.

And it’s like no, it’s actually on the list, is actually really important and like maybe you know 7 years after you asked for it it’s going to come.

We had one a couple years ago or so, where someone said – hey this ticket has been open for eight years, so you’re never going to do it, right? And then a year later we did, and they’re like, wow, I really thought you were never going to do this.

It’s like, no, we’re just just taking our time.

And especially in the database space – databases are pretty big, complex pieces of software, and so some of these things just just take time.

Value Prop

Michael Schwartz: The value proposition for MongoDB – is that different from the Enterprise customers to, let’s say the smaller customers? Or how do you think about the value proposition?

Eliot Horowitz: Of the other core database? Or of the commercial offering?

Michael Schwartz: I guess of the commercial offering.

Eliot Horowitz: So the commercial offering is really, very different on the different sides.

So the Enterprise’s who are again largely, on-premises – it really comes down to a few different pieces. So one is support. The second is management.

So we provide, we have a lot of commercial management tools: For monitoring, backing up, automating clusters, for doing rolling deploys, for doing back up’s from production into staging.

All sorts of things around management, we have an integration with Kubernetes, in that space as well.

And we also have a lot of features in the security space. So things like, if you want encryption at rest, or field level auditing, or database level auditing of every single type of operation, those sorts of things are also in the Enterprise edition.

So that’s sort of a one way we differentiate on the Enterprise side. And then on the cloud side – it’s really about the managed service.

It’s really about if you want a fully managed service where you can just have a turn-key thing and say – I want a database. And okay hold on, if something goes wrong we’re going to fix it.
If there’s a hardware problem, we take care of it.

If you want to scale up, you just press two buttons in the UI and you’ve got more capacity. And if you want to move data centers, switch data centers, move cloud providers, add another cloud provider – It all becomes incredibly easy UI changes or API changes, and you don’t have to manage that infrastructure. Security’s managed, all the stuff is fully managed for you, in a really simple solution.

And then that tier, we also have extra security features as well, if you want even more security in a fully hosted environment.

Competition

Michael Schwartz: So two different segments really, Enterprise and Cloud, and two different value propositions. There’s a lot of databases out there even, JSON databases, what do you think makes Mongo unique?

Eliot Horowitz: So I think there’s a lot of databases that let you store JSON, which I think is very different than a JSON database.

And to me, really being a database that works well with documents, really comes down to having a really great query language that makes it really easy to work with documents.

And so it’s very easy to store JSON, right. You can easily just go store JSON in a BLOB field in any relational database, and you can do that for the last 20 years. But that’s not that helpful.

What you really want to be able to do is store a document in its natural form, right – so if you have a user, being able to store a user with a list of addresses, where each address is a document, and maybe you have tags on them, you can have like: Type work, or type home, or type of previous, and you have city, state, ZIP on every single one of those.

But then being able to actually index on that efficiently, and then query on that efficiently. So you can index on address.city, or address.city, address.state, right. You can actually like multiple types of multikey indexes. And then be able to sort and query on those things, and then be able to actual analytics on those things.

So you can say – okay I want to find the average age of people live in New York. Which means you have be able to look through the documents, figure out which documents are New York and then compute it, do some summations on those. And then do other sort of interesting things.

And so it really makes, one of the main things that makes Mongo different than everything else in stores, that lets you store JSON, is we’ve got a very powerful query language that lets you do all sorts of queries, with a very powerful indexes, that are very similar to indexes that people would see in a relational database.

So from a semantic standpoint they work almost the same.

But now you’ve got a very rich query language that lets you go inside of a document, aggregate things, analyze things, do real-time analytics on that data.

In addition, we let you do things like update documents in really interesting ways, So you can update as many fields as you want in a big document.

Let’s say you got an array of line items in an order.

You can actually go ahead and say update every line item, and update the price, multiplying it by you know point eight to give a discount, but only when this predicate on this line item is false. So you can say – take this order, find all the line items in that order that haven’t yet shipped, and give them a thank-you that user a 20% discount because the items are late.

Right, you can really use a query language to go in and understand and work with the documents in a way that you really can’t do with any other sort of database that lets you store JSON. And then you go ahead and take that, and put the distributed systems piece on top of it.

Which is the piece that lets you have a really high availability, both inside of a data center or across data centers. It gives you full elasticity so you can go from one shard to a thousand shards so you can store almost as much data as you want, and almost as many transactions per second as you want.

And then that also has other cool features like workload isolation, so you can actually have one Mongo cluster that serves both your transactional workloads and and your analytical workloads at the same cluster, because you can put different workloads on different machines.

And you could also use some of our more advanced features, which are these Global Clusters, so you can have different data that lives in different places.

So you can have some data that lives in the US, and some data lives in Europe, and some data that lives in Australia – all in one logical cluster.

But the physical data stays where you need it to, either to comply with laws where you have to say certain data can’t leave certain areas. Or just for latency reasons, right, so you want users in Australia to be close to their data so they can have a really great user experience.

License

Michael Schwartz: So on the Enterprise product – just maybe some brief thoughts about licensing.

Eliot Horowitz: So we made the interesting choice way-back-when of choosing the AGPL. Which is definitely not the most common open source license. And the reasons why we did that, you know there’s many of them, and now it’s definitely been a good thing for us.

One of the most obvious ways that open source companies want to, and should try and monetize, is by in a running a managed service. It’s an obviously great way for an open source company to make money.

I think most consumers of this kind of technology would prefer to consume it as a service these days.

So from a user standpoint it works great as well, but having open source is also great because they have some of that freedom if something does go wrong.

The challenge with that of course, is that you got cloud providers who can take that same open source software and make it a competing service. And so one of the great things with us is the AGPL makes that a lot trickier for these cloud providers.

So I think our choice of license definitely has helped us tremendously over last few years.

Pricing

Michael Schwartz: Quick question about, I guess pricing – what was your feelings about the experience of trying to figure out what’s the right price?

Eliot Horowitz: I definitely say it’s not easy. Early on, I think we definitely probably undercharged significantly. Because we were like, hey this is open source, we’re trying to get people to pay for an open source thing, that’s kind of weird.

And so we were definitely sort of undervaluing the software we were providing, and the value of we were providing. In the cloud was a lot easier because they’re better comparisons.

So for the managed service it has been a lot easier to price that, and we’ve had much fewer issues there trying to figure out what the right price is.

Evolution Of Product

Michael Schwartz: Is what you’re selling today in the Enterprise space roughly like what you were selling when you got started?

Eliot Horowitz: In broad strokes, yes. If you think about it, the very first Enterprise things we were selling was just support.

Then we started adding in some Enterprise security features, then we started adding in management. Then added a lot more management at a lot more Enterprise security features.

More recently we started to expand that portfolio even more – we’ve got some new products in the charting space, in the BI, in the analytics space, that are also in that suite.

So we started building out that product suite a little bit further and put more products inside of that suite. So the biggest change the really probably been in the analytics space, and we’re putting some tools for Enterprises who have business analysts into that suite as well.

Channel

Michael Schwartz: Changing tracks a little bit. What are some of your thoughts about like building channels and distribution?

Eliot Horowitz: So early on, all of our go-to-market was really focused around just developer you know, developer advocacy.

We really didn’t know what we were doing for marketing or sales standpoint; we were just you know, a few people. So really, what we were doing is we were going to meetups and talking about why developers should use MongoDB, and going to hackathons, and talking to our friends.

And pretty quickly what happened was the people who were really excited about Mongo started talking themselves at conferences, and things of that nature. It was really just a grassroots developer adoption strategy.

I use the word strategy strongly, that’s that’s all we knew. As we started getting bigger, we started hiring a sales team, doing direct sales, and going through those kinds of motions, and a marketing team that’s doing all sorts of other things. We also started doing our own events.

Because there is so much interest in learning about how to use MongoDB and what other people were doing. We started doing MongoDB events relatively early in our in our company’s history, have always been very successful for us.

Partnerships

Michael Schwartz: Are there any strategic alliances you’ve found that have been really helpful for you to build a company?

Eliot Horowitz: I would say there’s not one particular one. Obviously we have a lot of partnerships you know.

These days we do a lot of partnering with all the different cloud providers: Amazon, Google, and Microsoft, We partners with other technology companies who embed MongoDB in their products, or there’s a lot of synergy between what we do.

We partner with a lot of the consulting companies who are trying to get some of their clients to use more MongoDB to be more effective in what they do. So it’s a little bit of everything.

Definitely hasn’t been one partnership that you know, been way more worth than others.

Resources

Michael Schwartz: Do you ever feel like your company’s been constrained by resources?

Eliot Horowitz: I think it would be hard for anyone to say resources are never an issue. But I think we’ve been pretty lucky in our ability to sort of have a fair amount of capital even early on, to grow pretty quickly.

I’d say you know, where we could have grown faster, it largely is around understanding where we fit into the ecosystem and strategy, moving faster.

But frankly we’ve been able to move pretty fast and we’ve had a pretty good flow of resources even from the beginning.

Advice

Michael Schwartz: What do you think are some of the biggest challenges facing the founders of new open source startups today?

Eliot Horowitz: I think the biggest challenge is understanding the right monetization strategy.

Alright – getting people excited to develop it, to use it, I think that’s actually, you know, people like open source, people get open source. You’ve got a great adoption life cycle, I think that makes a lot of sense.

The challenge really is trying to understand what things you want to make free versus what things you want to make paid.

And then around the service side – which I think the cloud service is by far one of the best strategies – is how to do that in a way, and do that in a way that is sort of both easy for your users to use and also has enough sort of, protection so you’re not fighting with the cloud providers on day one.

Hosting

Michael Schwartz: It seems like having a hosted cloud offering, it’s a great way to monetize, but it’s also challenging because it requires a certain amount of capital and established operating procedures and policies.

If that weren’t an option, what other recommendations would you have about how to how to monetize?

Eliot Horowitz: Well I would definitely try pretty hard to go to the cloud services route.

I think on the capital side – because you can actually leverage cloud providers as well – so you can actually keep your initial capital needs pretty low.

But you do need to like, you know, learn how to operate the software as opposed to just running and writing the software.

Although I would also argue that your experience in running the software yourself, on behalf of your users, is going to make the software way better. You’re going to find all the little pitfalls, when you’re on the hook for issues, there’s going to be less issues, and managing it’s going to be easier anyway.

So I think that’s actually, I’d push people pretty hard to go that route.

If you’re not going that route, definitely the most successful ones are, I don’t know if I love the phrase but the open core model, where you’ve got some core that is open source, and then you have some features that are commercial around it.

But I think the hosted service route seems to be the direction most people want to go in.

Stability

Michael Schwartz: Do you think that the software needs to achieve a certain level of stability before you can really build a business around it?

Eliot Horowitz: It certainly has got to achieve a certain, enough stability that people are willing to use it in production.

If people aren’t willing to use in production, I think it’d be pretty hard to build the business around it, right. It’s got to be compelling enough that people want to use it and then good enough that people are willing to put it in important applications in production.

Upgrade

Michael Schwartz: Not just stability, but ease of upgrade?

Eliot Horowitz: We’ve spent an enormous amount of time making sure that it’s relatively easy to upgrade versions of Mongo.

We’ve been around long enough now that there are people who run relatively older versions, but we work very hard to make sure our users stay in the latest version, to make upgrades as seamless as possible – and we spend an enormous amount of time on it. But it pays itself back as it lets us move faster as well.

But we do spend a huge amount of time on that. We’ve got a huge amount of our testing infrastructure dedicated to understanding how the software can get upgrade from one version to the next, and then downgraded if there’s a problem. We try to automate all of that.

It’s such a huge problem if your users aren’t upgrading, or if it’s too hard to upgrade.

Underdog?

Michael Schwartz: We name this podcast Open Source Underdogs. Mongo’s been so successful, but – do you still consider yourself an underdog?

Eliot Horowitz: Sort of analogous to the question of “do you still consider yourself a startup or not”; and I think the answer is in some ways yes, in some ways no.

Obviously we are a public company now, we’ve got a lot of money, we’re over a thousand people. So the company’s pretty big.

On the other hand the people were competing with in the space, you know whether it’s Oracle, or Amazon, or Google, or Microsoft, are definitely considerably bigger than we are.

So are we a underdog?

Yes and no. Like we’re still small compared to them, but was also a pretty well-established company, and have a lot of good things going for us.

10 Years?

Michael Schwartz: Where do you see Mongo in 10 years?

Eliot Horowitz: The database space, the good thing about it is that it’s a pretty long-term space.

So if you look at our roadmap the number of things we want to add over the next 10 years – whether it’s in the core database, or the areas that we’re working around in the database, are enormous.

And the nice thing about what we’re trying to do here, and even if you look at some of the new products like MongoDB Stitch, everything we’re doing is really about making it easier for developers to work with data. Almost an infinite amount of things you can do there.

And the core database, you’ve got a ton of stuff, and then we’re doing things like Stitch, which is all about bringing a lot of those database features to where developers are today.

So for example – making it easier to use databases directly from mobile applications are web applications. Or making it easy to embed charts in a mobile applications, so you’ve got data sitting in a database and you expose a dashboard inside of an application, where someone can only see a subset of the data.

How do you make that easier?

So in ten years? You know, what I hope we’re doing is continuing to make it even easier for developers to make use of data.

At that point I’d love for most developers to be using MongoDB to store a lot of their data, and to be getting a ton of value out of it. Both on a transactional like, hey I’m using this every second for my application, and on the back end to say okay, how do I get insights from this data and do interesting things.

You know, I still think there are people out there who know they have to use a database, but they don’t want to because they’re scared of them and they’re kind of annoying.

And you know, our goal will be every developer just wants to use MongoDB because it makes their lives easier. And lets them focus on building great applications, and makes the data management, takes that out of the way.

Personal Advice

Michael Schwartz: Do you have any advice, on a personal level, for entrepreneurs for starting a company with open source?

Eliot Horowitz: I think the most important thing, whether it’s open source or not open source, frankly – is for you to get incredibly close to your users.

For many years after we started, I spent an enormous amount of time just working with users, whether they’re paying customers are not. On forums, on IRC.

I used to do these things where I’d just hang in the coffee shop and have people who would come and say, hey I’m going to be here for the next two hours, if you’re having trouble, you know, let me help.

And it was great both to help our early users be successful, but it was almost more valuable for me because I really understood what users were trying to do. I understood what their pain points were. Not just the obvious pain points, but the subtle pain points that made it go from a – ok this is an interesting product to now, okay, I actually really like this product.

And so, especially a technical person starting a technical project, there is nothing more valuable than really getting incredibly close to your users.

And I would push most of those people starting those projects to, don’t think about it as the first five or ten users, but you know how can you host the first 50 users, or 500 users, or first 5000 users.

And push yourself there more than other places. Because it’ll pay itself off very quickly.

Michael Schwartz: I know I got a lot of information out of this interview. So Eliot, thank you so much for sharing your your experience and your thoughts on open source. And best of luck with with MongoDB.

Eliot Horowitz: Thanks, you too.

Transcription and episode audio can be found on opensourceunderdogs.com.

Special thanks to the Linux Journal for co-sponsoring this podcast, to The All Things Open Conference for helping us publicize the launch.

Music from Broke for Free, by Chris Zabriskie and Lee Rosevere.

Production assistance from Natalie Lowe. Operational support from William Lowe.

Thanks for the staff of MongoDB – especially to the audio technicians who recorded this episode.

Next week we are joined by Tom Hatch, Founder and CEO of saltstack, one of the leading orchestration automation platforms.

Until then, thanks for listening.

Episode 6: Automattic – Web Dev & Publishing with Matt Mullenweg

Matt Mullenweg is Co-Founder of WordPress, the most popular open source blogging and content management platform in the world. In 2005 he founded Automattic, the company behind WordPress.com, WooCommerce, Jetpack, and more. In this episode, Matt describes how they built a thriving business around WordPress.

Transcription coming soon!

Episode 5: Cloudera – Machine Learning & Big Data with Mike Olson

Mike Olson Co-Founded Cloudera in 2008 and served as CEO until 2013, when he took on his current role of Chief Strategy Officer (CSO). Cloudera delivers enterprise tools that leverage the open source Apache Hadoop platform for big data analytics. In this episode, Mike describes how Cloudera contributes to the open source community while also holding back enough proprietary IP to build one of the most successful open source software businesses of all time.

Transcript

Introduction

Michael Schwartz: Welcome to Open Source Underdogs, the podcast where we dig into the business models of the best open source software companies in the world.

Today I’m excited to be with Mike Olson, Founder and Chief Strategy Officer at Cloudera.

Cloudera provides Enterprise tools for data engineering, data warehousing, machine learning, and analytics that leverage the open source Apache Hadoop platform.

Mike Olson, thank you so much for joining the podcast today.

Mike Olson: Michael thanks for coming by, I’m excited to talk.

How Did Cloudera Get Started?

Michael Schwartz: How did Cloudera get started?

Mike Olson: The company’s ten years and a few months old at this point. We started in 2008, early summer.

The conviction that I had, along with my three co-founders Amr Awadallah, Christophe Bisciglia, and Jeff Hammerbacher. The conviction we all had was that big data was going to be a big deal.

So if you looked at Yahoo, and Google, and Facebook and others, they were collecting and analyzing data at enormous scale – much bigger than banks or hospitals were doing at the time. And they had invented a collection of new tools to do that.

So Apache Hadoop was sort of the foundational project of this ecosystem. We all believed that banks, hospitals, insurance companies would want to get lots of data and then analyze it in powerful new ways. And this wonderful open source Hadoop project was ideally designed for that.

So our idea was let’s bring those capabilities to traditional Enterprises.

Now I had had a long career in database technology, I had worked for Informix, and Oracle, and a bunch of other database startups you never heard of. I had a long career in open source, so I had worked at Berkeley Unix, on Postgres, Berkeley DB.

So I understood the big Enterprise data consumption behavior, and I kind of got open source. I didn’t know anything about Hadoop.

I had no code running in there, I had not developed it. But I understood what it did, how it worked. And my co-founders had all been actively involved in its development and its use at Facebook, Yahoo, Google.

So together I think we were uniquely positioned at that time to start the business and to try to bring this web technology to traditional Enterprises.

Cloudera Customers

Michael Schwartz: Who’s using Cloudera’s product today?

Mike Olson: Let me talk about what we’ve built for the market, because it’s been heavily influenced by our target customer; and that’ll give me a chance to explain then, who we chose, why and so on.

When we started the company, all we had was Apache Hadoop. That is two open source components, a file system DTFS, and distributed processing engine, MapReduce.

Those two things together were what Google invented for big data processing and what took over the consumer internet. Fast forward ten years, we have 26 different open source projects in the bundle now.

In general all of the new stuff has swiped the fundamental design ideas of Hadoop. Scale out, so deploy and run on a whole bunch of servers, and bring the processing to the data. So MapReduce let you plow through huge amounts of data by every server basically running out tiny little plow-through job on its own, and then you combine the results at the end.

Well, there are other processing engines available now, there is Apache Impala for high-performance distributed SQL analysis. There’s Apache Spark for stream processing, and for marshalling like model training in machine learning. There’s the SlrCloud Lucene search engine that does document search and so on.

So, a whole bunch of scale-out projects now can collaborate on the data on that cluster, on those servers. So you don’t need to make multiple copies of the day, you can do lots of different processing at massive scale by taking advantage of all of the CPUs that you have attached to the storage.

So, platform’s gotten a lot more interesting and handles way more analytic work less than ever before. We’ve built a collection of services that compliment that core open source offering.

Data governance, compliance, living up to regulatory regimes in these big industries like healthcare and financial services, we built tools on the platform that let administrators, and chief information officers, and the privacy team be sure that the rules are getting followed and policies were enforced.

We’ve got high performance security and encryption services, deploy, and manage this infrastructure at massive scale – if you’ve got a thousand computers running a mission-critical job how do you ensure that the jobs going to finish on time, and so on.

So we’ve built a collection of large Enterprise-focused software compliments to that open source platform. The data storage, the processing, and so on, all of that is in the open source and were substantial contributors to that ecosystem, and we benefit from the great workout that ecosystem.

And then we build a product that adds some proprietary IP. That is not, that is differentiated and not nearly as easy for a competitor to pick up and use against us, as the open source would otherwise be. So we maintain some differentiated IP and some reasons for customers to buy from us.

We chose those capabilities: Regulatory support, operations at massive scale, compliance, and so on, security, because we aim to sell to large Enterprises.

Banks and hospitals and insurance companies have lots of data, complex businesses with lots of opportunities to do analysis, so they’re good customers, and crassly they got a lot of money.

So we designed our product strategy, and we did a lot of really innovative stuff expressly to go after, kind of that same large Enterprise buyer that I had been servicing for my entire career as a relational database industry player.

Competition

Michael Schwartz: There must be a lot of competition in this market. How do you differentiate Cloudera from some of the other offerings that are out there?

Mike Olson: In 2008 when we started the company nobody had heard of Hadoop.

It was just, you know, it was some nerd technology, if you were an engineer at Yahoo you were up to date. But the industry at large hadn’t heard of it.

The meme of Big Data didn’t even exist yet, so those words weren’t being used to apply to any kind of business problem.

That changed in a hurry. So many competitors have entered the market, lots of folks have recognized the value of Big Data. A number of companies have even stepped in and joined us in delivering solutions that build on the Apache Hadoop ecosystem.

Look, I think there’s a bunch of reasons we’re good, we’re deeply involved in the open source community in order to take advantage of and help drive that benefit, we’ve got to do that. But our differentiation, how we set ourselves apart, is really based on how we been thinking about the customer.

So large Enterprises need the security governance compliance and regulatory support we’ve got. We genuinely believe that, given the decade that we’ve been building the product and the expertise we got, we’re differentiated there.

In addition however, our large Enterprise clients have data centers, and we think they’re going to have data center for a long time, so they want to be able to run stuff on premises.

They need to be able to take advantage of the public cloud, so spin jobs up on Google or on Amazon or on Microsoft Azure. And then, they’d like to be able to move those workloads around among those places – on prem, the various public cloud providers, as business requirements demand.

We support support this sort of, hybrid on-prem and cloud, and also multi-cloud, you can move among the cloud vendors capability, so that our customers get all that security, governance, compliance, regulatory support, and aren’t locked into a single cloud provider.

There are outstanding offerings that are single cloud only, so you know Amazon’s got a rich collection of great data services, and we integrate with and complement those.

But the promise we make our CIO customers is, you can deploy with confidence on any of those venues because if you decide later to move, your applications don’t change, you don’t, you haven’t coded to any sort of built-in proprietary, native cloud API’s. You’re building on the open source ecosystem of Hadoop, and your app will move easily.

Customer Interaction

Michael Schwartz: Are there any grades of interaction, maybe for smaller customers or the community?

Mike Olson: So of the 26 open source projects that we distribute, some were ingested from the open source community, created outside of Cloudera entirely – so Apache Spark’s a great example. Now we’re major contributors in the Spark ecosystem as well, but that was created at Berkeley and then released through the Apache Software Foundation.

One of the two original founders of the Hadoop project, Doug Cutting, actually works at Cloudera so you know, that predated the company, but obviously we were engaged in that from the very earliest days.

And we’ve created open source projects. So a great example is Apache Impala, our distributed query processing engine. Or Apache Kudu, an IoT-based storage engine that were conceived and originally developed here, and released through the Apache Software Foundation to the open source community, and we’ve built communities around that.

We benefit from the great work of the global open source development community. We earn our credibility by contributing to that community as well, so both of those are important.

We don’t really engage commercially with say, small companies with small data problems. Remember, we’re aimed at these large organizations and regulated industries with complex business.

So we really sell to very, very large Enterprises and we focus on those problems, and our interactions with those customers is aimed at basically that kind of buyer.

So we don’t really do much with open source consumption of the platform, although a great deal of it goes on.

We’re concentrating on monetizing and easing the adoption of the open source tech by those big guys.

What Goes In Open Source?

Michael Schwartz: How do you decide how much to invest in the open source projects versus your commercial project?

Mike Olson: This is going to sound glib, actually a whole bunch of thought has gone into it. But very briefly if it’s about data storage, data analysis, data processing – CIO’s don’t want to be locked in.

They don’t want a single vendor proprietary solution.

I mean, I spent a bunch of my career working for great big database vendors and we taught CIO’s that single vendor proprietary lock-in was a mistake. So everybody’s learned, they don’t want me to be able to turn off their data access, they don’t want me to be able to shut down their analytic workload.

So if it’s data storage, data process, data analysis really it needs to be in the open source.

If it’s addressing the unique requirements of a large Enterprise, like if you need to be able to answer the demands of regulators, or if law enforcement shows up and you’ve got to do a data lineage work.

Well, look man, that’s fair game. Because first of all the open source community isn’t going to spend a lot of time on that kind of problem. And 2nd it’s expensive and difficult to develop those solutions, and so I should legitimately be able to be paid for those.

And so in general we’ve got a philosophy on needs to be open source and what can be closed source, proprietary IP.

Channels

Michael Schwartz: Have you developed channel partners, or do you rely on the open source to be a distribution Channel?

Mike Olson: We’ve got good channel relationships with some of the big systems vendors.

So you know Dell is a fantastic partner, HP’s a fantastic partner, even Oracle and Teradata offer appliances that bundle the Cloudera platform and they’ll sell through their sales force to their customer base our IP on those appliances.

The global systems integrators are likewise a really good channel for us they turn up a bunch of opportunity.

The bulk of our revenue is from direct sales.

So we’ve got a substantial global sales force with concentrations in AMEA, in Asia-Pacific, and then the Americas and leaders identified there. And we have a bunch of direct sellers and technical folks in the field that engage with our large Enterprise customers.

Initial Sales Strategy

Michael Schwartz: When you were first getting started was it really hard to figure out how to manage the long sales cycle of a large Enterprise? How did it go in the early days?

Mike Olson: Bear in mind that had been the market that I sold two for my entire career, so I knew what to expect in terms of sale cycle. And I was an engineer to begin with right, but in middle-late 90s I stopped being an engineer and became or more and more field-focused.

Anyway, I was used to the buying cycle of that community. I’ll say that we got lucky in a weird way.

So you remember 2008 was the Global Financial Market meltdown. It had a really important knock-on effect, it was everybody was really afraid of what was going to happen further in the economy.

So large Enterprises were looking for ways to shed expense, and if they had to do innovative stuff to do it in novel and much less expensive ways.

So you know, it used to be that you could legitimately go charge somebody $40,000 to manage a terabyte of data. You know there’s a lot of terabytes of data in the world these days, and at 40,000 bucks a terabyte, there’s a huge penalty for having data.

Well this platform was designed to make lots of data cheap, to a cheap to accumulate, and then operate on. So the market crashed, a bunch of CIOs got very cost-conscious, and here we were with this open source foundation and a new way of building scale-out, distributed systems that was vastly cheaper than what came before.

Look I mean, the market crash was a disaster for a bunch of reasons but it was a little bit lucky for us. We tried to stay rigorously focused on what we thought customers needed and that varies by time.

You know the needs of customers today are very different from what they were a decade ago, because everybody gets open source now, right. Everybody gets big data.

We’ve evolved our product strategy along with the maturing market. And I’d, maybe it’s vain, I’d claim we helped to mature the market as we went.

Red Hat IoT Partnership

Michael Schwartz: One of the new trends is IoT. To expand a little bit on the partnership angle, we were reading about a partnership with Red Hat.

Do you see that as the new direction, that better solutions are needed?

Mike Olson: I actually do and unsurprisingly that’s why we got involved in, that’s why I’m so excited about the work we’re doing with Red Hat.

I’d take a step back, IoT as a broad secular trend, is a huge boon to those of us in the big data industry. Right, I mean that data got to come from somewhere.

It’s nice if we just put sensors all over the place, if we were able to ingest you know, stock trader market data at very fine grain, and then we can store huge amounts of it. So the more things there are on the internet making data, the better off that the big data platform is going to be. So, very excited about it on that basis.

If you know much about the Hadoop architecture, it’s kind of this big back-end, where data lands and then you analyze it. What we hadn’t done, what we don’t build, is the end-to-end architecture.

So how do you rely on to get data off of the sensor, or off of the device? What happens to it as it runs the network? Is their analysis and aggregation of data in flight?

Well it turns out the folks at Red Hat and a number of other industry partners, were thinking about those capabilities and taking advantage of their infrastructure software, to deliver some interesting services there.

If we can make our analytic platform a good destination for that data, and then train models using machine learning techniques to spot anomalous activity in those sensors in real-time – well that’s awesome, right?

So the combination of these technologies, really the partnership around IoT data, enables applications that we couldn’t have enabled on our own.

And then obviously, you know Red Hat’s been a fantastic partner in Enterprise software for for open source, forever and ever.

Other Partnerships

Michael Schwartz: Are there other partners that you think have been helpful?

Mike Olson: So in the IoT space in particular, Eurotech and the Eurotech Everyware family, is an important part of that partnership. Looking more broadly than just at that IoT activity though, like any platform software company we rely on a rich ecosystem of other companies in order to succeed.

So you squint your eyes, you’re allowed to think of a Cloudera Enterprise as a database. It’s just not a 1980s database it’s a 2018 database; lots more data with lots more powerful analytic capabilities. But you need the application that runs on that database.

I want to predict which customers will churn out of my mobile service. I want to spot fraudulent transactions in data flows. I want to guess which patient at my hospital is likeliest to be readmitted based on past behavior.

We don’t build that app but we have a collection of systems integrator partners, and independent software vendors that do build those applications. And they’re absolutely essential to our success, right – nobody buys the platform, everybody buys the application, but the platform has to be there to build the application on.

License Strategy

Michael Schwartz: One of the popular licensing strategies in open source is open core. Do you have some thoughts on that strategy, or maybe licensing in general?

Mike Olson: Couple things. So first of all – this is just a super fraught emotional area. People have very strongly held views. I’m pretty pragmatic. I deeply believe in the strategic value of open source.

You get this global community of really smart folks, anyone who cares enough about a problem can join the community and concentrate on solving that problem; and because they care a lot about it, they’re probably going to be better at it then someone you choose randomly.

So open source innovates in ways that proprietary software can’t because you can harness the whole planet, and you get to take advantage of distributed expertise. I love it.

The challenges of purely open source products is able to be picked up, and given away by any vendor who wants to do that.

So you can think of a mega vendor grabbing a collection of open source IP, pricing it at zero and then monetizing that by selling proprietary database that connects to it, or a whole bunch of expensive services or… if you invest a lot an open source development you run the risk of being commoditized when someone else takes that IP. And drives its cost way down, so you wind up competing with them.

Our decision to complement our open source platform with proprietary IP is not intended to lock customers in, its intended to lock competitors out.

I want to have some reason that customers will come to talk to me and not go talk to one of those big bad commoditizing vendors. And that’s why we build our product, that’s why we have the IP strategy that we do.

We’ll always have proprietary IP that complements the open core, the open source.

What that is will evolve over time as our business involves. And the open source ecosystem will also evolve over time.

People are going to innovate a new ways, maybe some stuff that used to only be able to get one way you’ll be able to get four or five different ways. But I believe it’s a good sustainable long-term model. Certainly it’s served as well in the decade since we started the business.

Tools?

Michael Schwartz: Would it be oversimplifying to say that the strategy is to build proprietary tools around the open source?

Mike Olson: It’s a fair view. I mean if, if I use those terms in front of my marketing guys, they’d say but we build way more than tools, we build a platform. Fair enough, right.

But complementary code aimed at the specific requirements of large Enterprises, that compliments all the power, flexibility, scale of the open source ecosystem.

Closing Advice

Michael Schwartz: So if you are an entrepreneur who wanted to use open source as part of your business?

Mike Olson: I’d say first of all, you know, 20 years ago… Oh heck, man. Yeah 20 years ago, 30 years ago, when I was working on Postgres, when I was working on Berkeley DB, there was this question you know, what is the open source business model?

I think that question is poorly formed. A business model is actually complex construct. Open source is a really important component of strategic thinking.

It’s a great distributed development model, it’s a genius low-cost distribution model – anybody can download your software at very low cost on very low friction.

And those have a bunch of advantages, right. You need to think about how you’re going to get paid. So what is it that people will give you money for, and it can’t just be because you’re good at what you do, because sooner or later somebody else is going to get good at that too, and competition is going to be tough to maintain attractive margins.

So you need to be thoughtful about the unique value that you’re adding. You need to think about who the customer is, and what they require, and why they will uniquely buy from you.

The particulars of the license that you choose matter a lot.

The GPL is coercive in a way that a lot of people like but that freaks out, for example, a lot of cloud vendors. They won’t pick up GPL’d code because they’re concerned about getting infected with the GPL requirements on code that they developed. The Apache license I think is actually a great license and has some good IP protection around patents, but is much more permissive.

So you want to think about what the license requires relative to what you’re going to deliver to your customers, and why they’re going to buy, and how that’s going to stay defensible. I think there’s a lot of really good thinking on this.

Clearly Red Hat is world-class at building an open source business, but it’s much more than – what should I do with open source? You want to think about who you’re going to sell to, why they’re going to buy, and why you’ll be able to preserve differentiation, and your advantage long-term in that market.

Michael Schwartz: Wise words from Mike Olson. Thank you so much for sharing your thoughts with us.

Mike Olson: Thank you Michael, I really enjoyed it. Thank you for coming by.

Michael Schwartz: That’s it for episode five. Transcription and episode audio can be found on opensourceunderdogs.com.

Special thanks to the Linux Journal for co-sponsoring this podcast to the All Things Open conference for helping us publicize the launch.

Music from Broke for Free, by Chris Zabriskie and Lee Rosevere.

Production assistance from Natalie Lowe. Operational support from William Lowe. Thanks for the staff of Cloudera for schedule juggling.

Next week we’re leaving the Bay Area and we’re off to the Big Apple, where we’ll visit with Eliot Horowitz, one of the founders of MongoDB.

Thanks for tuning in.

Episode 3: MariaDB – Open Source RDBMS with Michael Howard

Michael Howard is the CEO of MariaDB, one of the fastest growing open source database platforms in the world. MariaDB powers applications at companies like Google, Wikipedia, Verizon, Deutsche Bank, Telefónica and more. In this episode, Michael describes how the “Business Source License” enables MariaDB to monetize software and reap the benefits of an open source community and development methodology.

Transcript

Introduction

Michael Schwartz: Welcome to Open Source Underdogs, the podcast where we bring you the wisdom of open source business leaders.

Today my guest is Michael Howard, the CEO of MariaDB Corporation, the company behind the fastest-growing open source database in the world.

MariaDB is used by more than 12 million developers worldwide and is the database of choice to power applications at companies like HP, ServiceNow, and Wikipedia.

Michael, thank you for taking the time to join us today.

Michael Howard: You’re welcome.

Michael Schwartz: Why don’t we start the podcast with just a brief introduction of how you happen to join MariaDB and maybe a little history about MariaDB.

MariaDB History

Michael Howard: So MySQL was named after Monty Widenius’s daughter.

Her name was My, something like that in Finnish or Swedish. And Maria is his second daughter. So that’s the naming convention here, it is through Monty’s daughters. And as a result of course, the group of engineers that build MySQL and MariaDB are very attached to their family.

And when MySQL was initially bought by Sun, and then ultimately segwayed through to Oracle, there was a rift in the family. And in about 2009 there was a fork of the MySQL project and that fork became MariaDB.

And then some years later in 2013 MariaDB amalgamated, or put together, all the different aspects of the programming group the foundation, a support organization called SkySQL and in late 2013 that’s the MariaDB Corporation as you know it now.

Michael Schwartz: How did Michael Howard end up joining MariaDB?

Michael Howard: Michael Howard in the late, all through the 90s and late 90s was a disbeliever of MySQL and anything open source.

So that’s the origin of my story, in that, I could never imagine a group of programmers building a general-purpose database that would be able to tolerate an accommodate and support the primary functions of a business.

And I truly believed that the only way that that could be done is assembling very straightforward proprietary approach and let’s say it, my PhD thesis of that came when I joined Oracle in the 90s, and that’s what I believed.

But then as the world changed, and this is after 2000, you could see that the world was dividing. There were a couple of important signs of that and that was the Hadoop or HTFS world coming to play. It was the NoSQL databases coming into play starting with the caching layer.

And my view changed along with that new ark of software. So I knew the guys at MySQL and MariaDB for many years, didn’t think that they could bring themselves forward into true OLTP enterprise fortitude workloads.

But the world has changed. And I changed with it.

Michael Schwartz: OLTP – Online Transaction Processing?

Michael Howard: Yeah, you got it. Should have said that, but yes.

Customers

Michael Schwartz: So tell me a little bit about today. Who are the customers of MariaDB?

Michael Howard: Almost every company in the world now is touching MariaDB in some kind of way, in that we have displaced MySQL as the viable default relational database in all the Linux distributions. So even mom-and-pop shops that use Linux automatically have access to MariaDB, we have an addition that goes in those Linux distributions.

Somewhere between 12 and 60 million customers are touching MariaDB today through this unique distribution. And this is by the way one of the unique things about open source, that your ability to propagate and touch people across the world is enormous.

But that’s how it’s happening with the Linux distributions, and so to with the clouds in that, since it’s a default mechanism in Linux suddenly becomes a default mechanism in many clouds.

So we span from small shops that you’ve never heard of to the Fortune 10. You could look at things like AT&T, Verizon, Barclays, New York Mellon Bank, Development Bank of Singapore, Alibaba, ServiceNow, I mean it just goes from the most consequential companies in the world, even running airports. It’s quite remarkable.

80/20 Rule For Customers

Michael Schwartz: Just to drill down a little bit. Is there an 80/20 rule? Who are the most important customers in terms of Revenue?

Michael Howard: That’s a matter of opinion, how you do the 80/20 on that.

Because one of the problems that, let’s say the Hadoop family has via Cloudera or Hortonworks, is that Hadoop has become kind of part of the 1%, not big part of the 99%. And for me coming from proprietary areas you don’t want to relegate a company like MariaDB to the top 1% or 10%.

Therefore saying that your top 10% or biggest customers are the most important because here we want, and I’m going to use the word extremely, an extremely well-rounded business model.

So for example, in our world about 40% of our transactions on a quarterly basis comes from mom-and-pop shops. They don’t really think too hard about databases, but they kind of go with what’s easy for them to include as part of their environment. Then there’s another 40 odd percent where they’re making more strategic decisions but it’s still appended to a mentality of, for example replacing MySQL.

And then if we use those percentages there, there’s another 10 to 15% which is big time, and literally replacing out the likes of DB2, SQL server or Oracle itself.

And so I guess you could apply the 80/20 rule in each of those categories, or sale segmentations. But you couldn’t come up with an 80/20 rule across the board.

So there is sale segmentation, if you look at our documentation for example, it’s free. So anybody who doesn’t have a support contract can use a magnificent amount of content. But if someone has a production application and they need some sort of identification that’s a different level of interaction with the company.

We can’t talk to all customers, it’s impossible. It’s a challenge that cannot be overcome by people. If you look at it from let’s say, a business perspective like margins and productivity per person, there has to be more automation.

There has to be more automation in terms of buying contracts or buying things through eCommerce.

We even have to have easier ways where people can instantiate and test out new features instead of going it on their own, so we’ll do some things in the cloud to facilitate that.

So there’s many levels of interaction that must take place. But I think what we need to do to improve, really big time, I mean we have some major steps to make to be able to handle the numbers that we’re talking about, and we’re not doing that right now.

You know you look at some of the big players like Amazon or Netflix or whatever, they are doing it. So that’s the funny thing we’re a small company, under 200 people but we have the same level of interactions as the cloud platforms do.

Because, and sometimes even more, because MariaDB is on all those clouds. It’s a fixture there, so it kind of gets multiplied many times.

Revenues

Michael Schwartz: What are the most important revenue streams? Is it license? Is it support?

Michael Howard: Well for me coming from the proprietary world and the SaaS cloud, I’m very formalistic about this.

So the most important from a just formalistic point of view is ARR, Annual Recurring Revenue, on a quarterly basis the amount of new annual contract revenue.

Things like TCV which is equivalent to bookings are less important to me, more important for let’s say my CFO who wants to make sure we have a certain amount of cash in our bank accounts.

So the most important thing is ARR, that’s the first level. Second level is what does that ARR constitute.

And again coming from where I came from, where the multipliers on services and manpower support is not as powerful, not as valuable to, let’s say listing the product at NASDAQ or having some big liquidity event in the future, the most potent value is product; license on product.

And that becomes a very interesting and almost somewhat contradictory or paradoxical conversation when it regards open source. So our subscriptions are the most important part, and those subscriptions come with many facets.

It comes with technology that cannot be procured or accessed in a general sense by just the Community Edition.

We save some stuff that’s private. It may or may not be licensed under something that we came up with which we believe in, very much not only for MariaDB, but for open source entrepreneurs world over, and that’s something called the business source license, which we should probably talk about.

So you have technology. You have things that are not necessarily available through the Community Edition. You have legal protections, I named one, in some cases limited indemnification issues come up in especially regulated industries for production applications.

Then of course you have the typical element which is, a typical element of open source which is support.

So that’s how we make money. Our revenue come solely from our subscriptions which has a spectrum of things in it to make it valuable.

Open Source Dilemma

Michael Schwartz: There’s a saying called the open source dilemma where customers only renew support contracts when they need help, when they have problems. How do you get customers to renew and retain them to get that revenue to be actually recurring?

Michael Howard: Right, there’s a… It’s an interesting topic because the good and the bad of open source is that it compels the engineer or the firm to build new things. So for example, in our latest release we have temporal processing, inversion tables, very sophisticated ways of supporting governance applications.

This is a very very, it’s a multi-dimensional data object, being able to be joined with a million other multidimensional data objects, the math is extraordinary; be able to do that in an optimized way.

When you put out features like that and you continually do so, you will compel, behoove, motivate very easily customers to continue with their contracts. So the virtuous cycle is inherent in your ability to innovate.

Channel

Michael Schwartz: Changing topics a little bit. Are there Partners who help you get MariaDB out there, or that you rely on for success? What is the channel?

Michael Howard: We do have channel partners but it’s not as mature as, let’s say older firms.

I think we’re just at the very beginning of it. And channel partners can come from an enormous number of different areas, for example it could be a cloud vendor that is actually a channel partner, right. Being able to serve a certain constituency, as you put it, through their Cloud. It could be your typical channel partner that has some kind of ecosystem, could be that.

The one that comes to mind, just kind of new, both I think for the world and for us is you take something like ServiceNow, where they’re serving 40% of the Fortune 2000. And many of those companies don’t even know that MariaDB is the engine behind every single workflow that is going on in those companies, which is quite extraordinary.

But in some cases they need to have on-prem support from us and so suddenly you have the world of cloud interacting with the world of on-premise and that becomes a channel play that you would have never envisioned before.

Value Prop

Michael Schwartz: Why do people use MariaDB?

Michael Howard: I’ll give you an example.

Let’s say you’re a big company and have a huge server farm, and you want to start looking into ARM as your chip bases. You’re not going to be able to use a process space database on an ARM chip, it just won’t be economical.

Maria happens to be thread-based and the pooling resources for threads on ARM is as good as typical non-ARM chips.

So it could be that you are trying to have more compact space for your server farms, less real estate, less use of electricity, less heat. It could be that you realize after 20 years that you’re paying 60 times more than you should for basic SQL standards.

It could be that the basic philosophy of the company that you’re using is so out of touch with what a modern system is that you want to move forward with your own stack.

There’s an extraordinary number of reasons.

I mean the the primary one is that when you go into MariaDB you’re not only partnering with one of the best engineering firms in the world. You’re partnering with other great engineering firms in the world that are contributing to the MariaDB kernel. And you know that MariaDB will never be out of touch because of the extraordinary open source community that is contributing to it and there is no equivalent.

At Oracle everything goes through Larry; he is the Editor in Chief of Oracle.

Here you have a much more diverse set of curators.

MariaDB Foundation

Michael Schwartz: One of the things I wanted to ask you about was the MariaDB Foundation. It’s the ideal of a lot of Open Source projects.

Maybe you could talk a little bit about how that came about and what their role is.

Michael Howard: So the way I look at the foundation is they are the steward of the project’s repository. And they are the ones that teach people how to contribute to that repository.

Allowing freedom and equality for creativity, innovation through code, persisted in repository that is formalized under the foundation. And they’re advocacy to developers to help with that, their outreach to Linux distros. That’s the kernel of what they do.

Michael Schwartz: Where’s the line between the company and the foundation in terms of a decisions?

Michael Howard: Well I mean, there are simple lines, I’ll start with the simple ones.

They don’t do any support, you can’t go to the foundation and say I have a problem with something or bug, they won’t, they don’t have anything to do with that. That’s where the corporation comes in.

If there is a hot patch that needs to be applied because of a security issue, they’re not, they don’t act in that manner, they don’t respond that way; the corporation can.

Obviously you can’t get any legal privileges through the foundation. Let’s say you have a big idea that you want to put into the project, but it’s maybe a little bit over your head to really do it in the right way. You know just because there’s an open repository doesn’t mean that you can willy-nilly put something in there that’s mediocre.

But there are certain projects, I’ll give you an example: The Development Bank of Singapore wanted MariaDB to have a PL/SQL Oracle compatibility layer. That’s an extraordinary difficult project and could never be done themselves. And that’s when you enlist, for example, our engineers in the corporation.

Foundation Feelings

Michael Schwartz: So not to put you on the spot..

Michael Howard: You have so many times already!

Michael Schwartz: But nonprofits always involve politics and so how do you feel about how has it gone?

Michael Howard: I think it has pros and cons. I don’t think it’s a clean deal by any means.

I think that when you have independent entities they each have their own egos and they each have their own aspirations to spread their own wings. You know it’s just like when two people are discussing a subject, each one of them kind of wants to have their opinion supersede the other.

So it’s part of humanity to have that innate conflict but also innate need to work together.

Business Source License

Michael Schwartz: You mentioned license before, and I didn’t want to make this podcast a deep dive on license because you could probably do a podcast by itself just on the licensing part. But you did mention the business source license.

Maybe you could talk a little bit about what is the business source license and how does it relate to the other licenses perhaps at some of the other products or offerings come under?

Michael Howard: I’m going to start in a strange fashion on this narrative and that is: When I announced business source license I should’ve had a set of security guards from the open source community. I wasn’t sure what might happen to me.

Because it was disagreeable to them in some emotional ways in that, there are a lot of people out there that are pure open source zealots, and it’s an ideology like any political or kind of religion that can get the best of certain people.

But I felt that the company needed to be able to have as much financial resources as possible to make our products great.

And since we were stepping into the enterprise zone, which meant that we had to simulate or actually replicate many things that SQL Server via Microsoft or Oracle through Oracle does for their customers. And financial resources are extremely important to do that. And database features as you know, it’s not like a SaaS application.

Sometimes it takes many years to build one feature and those people are dedicated, like the version tables in the temporal processing that I mentioned, that was a very difficult feature, it took us years.

So how do you reconcile the world of free and the world of financial resources? How does an entrepreneur like yourself go to a VC and expect any funding if there is no business model. And at the same time if your whole company pivots off open source, again how do you do this?

After some deep thought the business source license seemed to be the best balance that I could find.

And what it is, is essentially very simply postponed open source. You get one of our products that uses the business source license, and for a certain set of time that particular version you pay for.

But at a certain point in time let’s say 36 months later it becomes open source. You can self support, you can do anything you want to it, and you’re not dependent on the corporation.

So it’s just trying to bootstrap product so it can meet the expectations, especially when these expectations have been built over 20 years with many billions of dollars.

Michael Schwartz: Sort of like a patent that expires, maybe.

Michael Howard: Yeah. That expires, that’s a good one.

Except I guess the deviation would be that even though the patent in this case is on for that amount of time, you can look at the code, it’s completely transparent just like open source.

Go to repository, our repository, it’s on GitHub, look at branch, you see it, you can contribute to it, you can do all those things. There’s even certain times when the license says you can use it for free, you know that kind of thing.

But, if you going to into like a production mode, and this is the case with a MaxScale, our database proxy. If you have many nodes that you’re serving with this proxy – you got to pay for it at some point. But that version will under the file name go GPL at a specific date.

License Enforcement

Michael Schwartz: What are your thoughts on enforcement? Is it on the honor system?

Michael Howard: So, right now it’s honor system. I think we’ll have to do some kind of home calls at some point and identifiers.

So there are times when certain customers try to take advantage. Where they’ll buy let’s say one or two copies of the paid version, but really the problem is emanating from thousands of free things that they’re using.

So right now it’s the honor system. There’s been some transgressions that I’ve seen. And of course the bigger the company you go to the less transgressions there happens to be. It’s more in the lower end where I see abuse.

Advice To Startups

Michael Schwartz: Any advice for entrepreneurs who are starting, who want to use open source as part of their business?

Michael Howard: So my advice is: It depends on what part of the stack you are.

So if you are in infrastructure you have no choice but to be somewhat commodity based or open source based. I don’t really believe that security for example has to be open source.

I see, you know I have a little security background. So listening to you, there was no reason to make, let’s say FireEye, open source. Just no reason, no one would expect it.

I think it’s interesting that you guys have gone in that area a little bit but the key management systems that I work with I never expect them to be open source.

On the SaaS level, you know you have one interesting juxtaposition between SugarCRM in Salesforce right. Has Sugar really gotten major benefit from its open source disposition?

You know I think what’s happened is the proprietary vendors have milked the industry so badly, that the time came when that practice had to stop. And MariaDB is sort of a symbol of that arrest.

Michael Schwartz: If you’re an entrepreneur, you’re saying if it’s infrastructure you should go open source.

Infrastructure & Open Source

Michael Howard: You don’t have a choice anymore.

Michael Schwartz: You have to, okay, that’s interesting.

Michael Howard: You really don’t. I mean you know, you have Intel maybe coming up with a chipset that’s not open source or their 3D XPoint, you know, that’s not open source.

But if you look at, you know let’s say a no more commodity-based analogs to that; they’re going to end up winning. I mean Intel will lose again because they’re charging too much.

So infrastructure I don’t think there’s a choice.

Funding

Michael Schwartz: Any thoughts about how do you stay true to the open source mission that maybe has helped build the culture around the company, and still fund the company, or build a business?

Michael Howard: Well, I think you see with very few exceptions VC’s funding open source companies. I think the market has already made that decision.

I mean there’s just no comparison between the funding percentages for open source versus lets say closed. There’s just no comparison. So I think the decision has already been made.

So then the question is if you have an idea at store at a storage software level, let’s say, or a container, you have no choice to be open source.

So then there are two things that come to mind. One is, you have to employ something like business source license and that’s the only way you’re going to get funded when you are presenting to a venture capitalist.

You have to have some way of bootstrapping your company with some revenue, a support meal ticket just does not make sense from a margin perspective, or the multipliers that VC’s are expecting in a liquidity event. So it’s dead on arrival if you go that way.

So it’s very simple you can’t just go open source, you have to have a business model behind it that makes sense. There’s only a couple ways you can do that.

Michael Schwartz: Thank you so much Michael for sharing your wisdom and best of luck to MariaDB.

Michael Howard: And to you too at Gluu.

Michael Schwartz: Thank you.

Michael Howard: Alright, bye.

Michael Schwartz: That’s it for episode 3. Transcription and episode audio can be found on opensourceunderdogs.com

Special thanks to the Linux Journal for co-sponsoring this podcast, to The All Things Open Conference for helping us publicize the launch.

Music from Broke for Free, by Chris Zabriskie and Lee Rosevere.

Production assistance from Natalie Lowe. operational support from William Lowe. Thanks for the Staff of MariaDB for logistical support.

Next week we’ll talk to one of the youngest startups in our series – Ian Tien, CEO and Founder of Mattermost, one of the leading chat and communication platforms.

Until then, thanks for listening.

Episode 2: Netgate – Secure Networking Software with Jamie Thompson

Jamie Thompson is the President of Netgate, the company behind the popular open source firewall project, pfSense. Both Jamie and her husband Jim, who is also featured on this episode, have spent the last 15+ years making secure, high-performance network connectivity tools available to the masses. In this episode, Jamie and Jim discuss bootstrapping their company and Netgate’s unique business model that involves monetizing hardware that implements their open source software.

Transcript

Michael Schwartz: Welcome back to open source underdogs, the podcast where we interview leaders from successful open source software companies and bring their stories to you.

Today my guests are Jamie and Jim Thompson, founders of Netgate, the company behind the popular open source firewall project pfSense which is over 1 million installations.

Jamie could you start by telling us a little about Netgate and your journey founding it?

Founder Story

Jaimie Thompson: Sure. Netgate is a open source network security company, both contribute to and utilize open source software and create products from those projects.

About me personally, I’m too old. I’m from Oklahoma originally. I was peak woman, there was a peak year for women in computer science and that was the year I graduated with a degree in computer science. And that was 1984, a long time ago. And I have a master’s degree in applied cognition and neuroscience which is essentially experimental psychology.

Worked as a software engineer. Early my career switched over to doing more of the sales engineering, worked for Sun Microsystems. I’ve worked for here in Austin a company called Tivoli Systems, which was ultimately went public in the 90s and got bought by IBM.

And I guess we started Netgate in about 2002 and I’ve been doing it ever since.

Jim Thompson: So Netgate was originally the name of a firewall that we’d done.

The first time we had an open source company called SmallWorks here in Austin that started with open-source I think my first open-source contribution was a port of new E-Maxx to a convex supercomputer in like 1987.

And there I went to Sun and that’s where I and Jamie met. Building out their worldwide network and got pretty involved in network security, that point I download the first set of proxies. Around 1989 or so I did that, because we had a need internally.

Once we started hooking up all the sales offices and remote facilities to this internal WAN and everybody wanted access to what we now know as the internet. It was really more ARPANET then. So I built a proxy so that people could get out and go fetch the latest version of the X11 system or something like that.

And that sort of, I saw that and saw people use it and sort of identified a need for actually agreeing to build a packet filter for the Sun Systems that was sort of the origination of the original Netgate packet filter or firewall.

Jamie Thompson: So when we started, Jim came up with this packet filtering firewall back in the early 1990s. And it was also open source but in kind of a different way – when you bought it from us, we gave you the source code so that you could analyze it and make sure that there weren’t any backdoors and you couldn’t sell it further on.

But you could certainly take it and analyze it internally, and in fact one of our early customers was Wells Fargo Bank. So we’ve kind of been dealing with network security and firewalls and took a detour through wireless for a decade. And have always been interested in and involved in network security and how do you create both privacy and security, both for companies and for individuals.

Customers

Michael Schwartz: Who are the customers of Netgate today?

Jamie Thompson: Well it’s really interesting, the software is very lightweight on providing any sort of feedback for us. It is open source, you can download it off the internet and run it.

You don’t have to sign up for anything, we don’t create any not paywall, but there’s no registration wall, to get the software. So we don’t always know who it is unless they are either asking us questions, either on the forum or in support or if they need some professional services or they want a private port or something like that.

So we’re we actually are learning more and more about who the customer base is at this time, but we have everything from individuals who are running it in their home labs, and then those people sometimes will take it into their companies.

And we also have a lot of government entities who run it. And then there’s actually in entire governments that run it, not the United States government but portions of it actually do, yeah. So it is used both inside the US and then other government entities around the world. Lots of individual, yeah, lots of S&B. There are some service providers who also use it.

It’s also integrated into some other products, so you’ll see people who’re providing some sort of service and they use our software either for the transport or for a firewalling, that sort of thing.

Product

Michael Schwartz: Is there software that people can buy? Or do individuals just download the open source?

Jamie Thompson: Well both. They actually can download it for free or we also take that software and we package it onto hardware.

So Netgate utilizes the project and creates a product from it. And then the product is packaged either with hardware or in the cloud and we sell support and services around that. So really how we’re…

Jim Thompson: Some part of that is system integration. You know, product test and release testing. that kind of thing. We test primarily on the things we sell.

So there is a lot of system integration or ports to get on new hardware, so we expend the effort to get on some of them and make that experience. You know really clean and easy. But then we have to maintain that going forward.

So we test and release in part just on what we sell, we make a generic version available to anyone. But the actual, if you will, hard work of making sure that things really work has to be done on some hardware platform.

This we have to focus on, we sell or cloud platforms, virtualization, that kind of thing.

Support Services

Michael Schwartz: Do you sell support services?

Jamie Thompson: Not everyone who purchases hardware from us gets a support contract or needs professional services, a lot of people already know how to use the software. It’s straightforward enough that they don’t need any extra work.

So like a lot of other companies out there, we can’t sustain the project on just support and services.

Jim Thompson: There are both large and small customers on the forum. US Army Cyber School we discovered on Reddit. Literally, one day. They were already a customer and they are user of pfSense. We didn’t know it because we have no way of testing them.

So again, it’s sort of across the entire range of customer types or segments of the market, if you will. We only know and work with people who have approached us.

Now, we know the approximate attach rate for people that we sell to versus how many instances of pfSense are turning up in the world. We can’t measure on a very granular, non-granular or scale that we see, more and more IP addresses if you will, looking for updates, or downloading additional functionality via packages, that kind of thing.

So we can see in approximation of the size of the installed base on any given month, and we know who we sold. And you know that ratio is about 1 and 20.

OEM

Michael Schwartz: Are there some companies who are OEMing the product?

Jamie Thompson: Well, there are companies that have taken it – it is open source, and so they can integrate that into their own product or in the cloud.

We have versions of the software available on the public Cloud so they can utilize it and in their businesses or integrated as part of their own software as a service product offering.

Partners

Michael Schwartz: How about channels? Do you mostly sell direct, or do you have any integration partners who help you reach customers?

Jamie Thompson: We have both a set of hardware resellers. So there are people who wanted to be involved with pfSense and especially in other countries, or in other languages we don’t have the ability to speak with them directly, we have ported the, it’s not call port it’s a…

Jim Thompson: Endemic translations.

Jamie Thompson: Yeah we’ve done a bunch of language translations, do you remember how many?

Jim Thompson: It’s approximately 30.

Jamie Thompson: Yeah I was thinking 30 as well. So the software runs in these other languages and obviously we can’t speak all those languages, no one here is that good.

So we have in-country partners who can either sell support service, and we have both people who are doing straight reselling, we have people who are MSP’s or MSSP’s. We have people who are buying it direct and then daily lease it. So there’s all kinds of different models.

We also, in terms of channels on the cloud, we do support some of the cloud service providers. People who do the integrations to basically create an entire stack. So if you wanted to move your application or the set of applications to have as a company into the cloud you could do that and the cloud service providers, their partners would help you migrate all of your data and put together your infrastructure and help you monitor and manage it.

And our best partners right now are in Europe. Some of them again are MSP’s or MSSP’s and some of them are just selling direct or helping people integrate.

Value Prop

Michael Schwartz: What’s the value proposition of Netgate?

Jim Thompson: We are the developers of pfSense primarily. There are community contributions that you can actually go out and look at like the list of Git commits. And you filter out the ones that you know staff here have done. It’s you know 90% plus Netgate.

And so since we’re the developer a lot of people feel safer when they’re dealing with the people who actually make software, you know, why wouldn’t we give the best possible experience on things we sell.

Jamie Thompson: We employ a lot of engineers, we have people who have commitments for FreeBSD. We have people who are just fantastically gifted both in hardware and software. We couldn’t do it without the engineering team, they’re just fantastic.

And it’s, you know the kind of thing you can’t get from a community because it’s hard to prioritize that open source development over what you’re doing in order to be able to be paid so that you can eat, and have a house, and all those good things.

So we actually do employ a huge team of Engineers to work on this open source product. And do the testing and the architecture and we run the infrastructure and…

Jim Thompson: You’d be amazed at how low-level we have to go to fix some issues. You’re talking about, you know, peak of second timing on NMMC bus, or we run into in situations where Ethernet PHYs don’t have the right choke on them, and so you can see more power in the PHY than you otherwise would. And we’ve had to actually go back and debug designs we didn’t do.

So there are there literally three people on staff who are EE’s, know them and engaged with EE on a day-to-day basis. The 4th who knows enough about it he could, he used to design medical devices. So we have a depth here, the technical depth that some people would find astonishing.

Use Of Open Source

Michael Schwartz: Has open source served as the main distribution channel for Netgate?

Jim Thompson: Well principally it’s a licensing structure. It’s almost all open source licenses are based on copyright, the original, the ability of the original author for assigning to control that copyright or leverage it.

The original, if you will, of the GPL turned copyright on its head that’s why some people call it copyleft. They use copyright to enforce the fact that you can control the copying. It’s an interesting hack if you own the legal system.

We have benefited enormously as has, you know, RedHat and a slew of other companies you can name from, if you will, marketing via these you know user groups. They’re in control of their own conversation, there’s no marketing conversation in the room. There’s all this experimentation if you will, 10000 flowers.

Try the successful ones are successful, and the unsuccessful ones you never heard about. So yeah we’ve engaged that too, and the fact that the the software is open source and free has been quite a bit of the actual marketing.

People discovered it and use for their own purposes and introduce to people who we were never gonna here from unless they approach us directly. It spread largely through that if you will, word of mouth or word of forum, association of use pfSense, it’s great.

You can still see that going on today. There are hundreds and thousands of people I will never meet who are using software we create.

Activities

Michael Schwartz: What is the primary activity of Netgate?

Jamie Thompson: Software development is the primary activity. If you say what are you as a company? We would say that we’re a software company.

But in order to leverage that software, in order to be able to actually continue to develop that software we do need an income stream, we need a revenue stream. And since we are self-funded, we don’t have VC, we’ve had to do that by selling hardware and services and renting it in the cloud.

So just like any any other company would do, I’d say that our number 2 activity actually is probably hardware development, which is kind of weird.

We have hardware, we work with some of the ODM’s and OEM’s on hardware designs and so we’ll go to them and say well we need, an Intel box that has 4+ next, you know i350 and two i210’s, don’t want those i211’s.

So like Jim said earlier, we have a lot of hardware depth that you wouldn’t expect for a software company. And that really isn’t normal, I think that, you know, if you look back we’re kind of more of a throwback to the kinds of companies that you had in the 80s where you would, you would develop both the hardware and software together and sell tell the system.

So that’s what we’re doing, we’re selling appliances and we’re providing both the software and the hardware that it runs the best on.

Jim Thompson: Vertically integrated.

Jamie Thompson: Yes, oh there you go.

How Did You Figure Out How To Vertically Integrate And Self-Fund?

Michael Schwartz: Normally I would think a hardware company needs a lot of capital. How did you figure out how to vertically integrate and self-fund?

Jim Thompson: A lot of credit card debt.

Jamie Thompson: Yes there’s been a lot of credit card debt, that’s true. When we started down this path with the hardware we were taking components that were available, and we were basically integrating those components and we were doing it on a pretty small scale.

And as we were able to convince people that we knew what we were doing in terms of both the software and the hardware and the integration. And we just had some really good solid products out there. That, actually, stuff that we sold 8 years ago is still on the field running today. And we basically just slowly grew and slowly grew.

Then we would reach kind of the limit of that hardware or of the supplier. We had one supplier, so we were doing 500 a month and we’re like okay we need to go 600 a month. Well we can’t do that, we can’t manufacture that much.

Okay we have to go off and find a different manufacturing and we’ve slowly gotten to the point where it’s just been a pretty much continuous ramp to the point now where we can go to some of the larger people in China or Taiwan or wherever they happen to be. And say, okay we will sign up to this many systems over this period of time and …

Jim Thompson: We can write large PO’s and back them with financial strength of what we built together over the past decade.

But has taken reinvesting almost everything we made to continue to make the business grow. So we live, sleep, and breathe Netgate… While raising a child!

What’s Next For Netgate?

Jamie Thompson: Kind of more interesting thing is that over time we’re looking at the software which actually started with Manual Casper, manu wall back in the day. And we’ve improved the software, we’ve ported it as FreeBSD has changed, we gone along with that.

One of the big things that we’ve just done is we’ve all ported to PHP 7.2. So we were running with the older version of PHP and the current person that’ll be coming out here shortly we’ve had to to update to 7.2 because of course you know software end-of-life’s, over period of time it goes to a no-support model.

One of the interesting things we did about three and a half years ago, four years ago, is we sat down, we said you know – if we were going to rewrite this what would we do? Because the questions that were being asked and the requests we were getting from the customer base who talk to us are like you know, it’s easy to do one firewall.

It’s easy for me to sit down in my home lab and control the firewall for my house. But at work I’ve got 50 of these things and I have to go control them individually just have a GUI, rather than a GUI, do you have an API? Can we use rest RESTCONF for NETCONF, or basically as architectures have changed and people’s thinking about management has changed.

We saw that there really wasn’t a way for us to change that software because of the way that was originally architected. If would be really difficult to put an API in. So while we’re also moving pfSense along we’re also thinking in the back of our heads what do we need to be doing differently.

We have actually some new software and it’s also based on open source, it’s Linux-based. It’s called TNSR.

And TNSR is really the result of a lot of architecture discussions within the engineering group and looking out to see what other people are doing now in terms of managing their networks and providing security for their networks.

So now you’re looking at orchestration and automation. A lot of people are are looking at well how does this run with Kubernetes how does this run with containers.

How I manage 50 of these things at once, and so not only are we working with pfSense but we’re also working with TNSR is really, well it’s available today in the cloud, but it’s really trying to kind of solve the next generation of problems around network security.

Why TNSR Was Needed

Jim Thompson: In those environments computers and the networks they run on have disappeared inside a machine, there is no box, there’s just one box, it’s the big box that you don’t even know it or see it.

It’s on a cloud provider somewhere, so on Amazon or Google cloud or Azure or something, and you never see it, and you never see the networks around. You just have the sort of remote ability to control via an API so there’s no there’s no blinking lights, there’s nothing left to touch.

And so that ends up being very different environment, these Kubernetes environments have messaging rates sometimes that are you know hundred thousand messages a second you have to be able to tell what’s happening.

So TNSR, which Jamie started talking about, is sort of an answer to what’s starting to occur in-network.
How Much Profit Gets Re-Invested In R&D?

Michael Schwartz: How much profit gets reinvested in R&D?

Jamie Thompson: All of it, basically. Yeah.

So, basically as we’ve grown the company and have been able to add more people, or we’re really lucky and in the respect that we took whatever we had, and said okay, what’s the next thing that we can do to make ourselves be more useful to our customer base or to be more useful to enterprise.

One year we added 24/7 support. And suddenly, oh okay, you guys are real because you do 24/7 support now.

But we’re no more real the next day then we were the day before. It’s just suddenly people felt more comfortable because they can get a hold of us and they can we can help him walk through their problems. And of course no firewall problem ever occurs at noon on Monday it’s always midnight on Friday.

So going to the 24/7 support model was huge for us, starting a partner program, a worldwide program, to help support people in-country and in-language with our partners was another huge bump for us because we’re now able to actually answer the questions that people had in a way that was more comfortable for them.

As things have changed out if to focus more on the cloud and to focus on this automation and orchestration.

Non-Integrator Partnerships

Michael Schwartz: What are some of the non-integrator partnerships?

Jamie Thompson: We didn’t see a way for us to take the software that we had and move it forward so we started looking around.

We have supported the BSD Foundation in the past. We’ve also now joined Linux Foundation and we’re big contributors with LFN, with Fido. We also support Clixon. So, not only we are supporting the software that we have written, we’re also supporting groups and other software projects where we’re either contributing with monetary contribution or code.

So you actually if you got look at at Fido, you’ll see that we are in the top five maybe even top three contributors for VPP which is the vector packet processing, that LFN is doing.

So we’re trying to help contribute to the ecosystem not only the code that we’re writing and that we’re putting forward, but helping, trying to help move networking and security long a little bit further in ways that we couldn’t do on our own.

But we can we can contribute to it, we can help.

Jim Thompson: In the same way that we have a community for pfSense were part of other communities around some of these constituent technologies. There’s even marketing on that side as well, the Linux Foundation markets LFN.

Fido’s BPP is a big part of that. So we know we show up at conferences and occasionally talk and participate in various mailing lists, you know online conference calls about where should we go next and that kind of thing. So all that tend to count for contribution.

Making the technology move along even though that technology ends up in potentially competitors product system.

Like I said, in the same way we have a community of people that we support. We’re also constituents in a community of some of these technologies that we take advantage of.

VC Money Risks

Michael Schwartz: You’ve avoided raising venture capital, why?

Jim Thompson: As with almost any decision there are pros and cons to that particular decision. The money is what people tend to focus on, how do I get this thing bootstrapped to get enough people working on it while I have something.

I’ve been the CTO of two companies, that combined I helped raise over a quarter billion dollars of venture capital, over seven or eight rounds. One of those companies was in product and one of those companies was in services.

My best advice is while things are going according to plan, the venture capitalist are here to help. They will open the Rolodex and they’ll introduce you to additional partners, give you some legitimacy into accounts that potentially you didn’t, you couldn’t enter.

If you can’t execute on the plan that you told him about, that’s when things can take a turn.

Jamie Thompson: That’s when they change the plan. Sometimes.

Jim Thompson: You know, VC’s are financial engineers. They’re there to optimize return for their fund.

And so the best advice I have for anyone who’s looking at this is to go out and really understand what VC is and how it can help. And what the VC’s goals are versus what your goals are. And if you can find a way to line those it can be great.

If those goals aren’t aligned then it’s just money and there are potential other places to make that happen.

Jamie Thompson: If it’s something you can articulate and something that is a physical product you can always go Kickstarter, or crowdfund, or there’s all kinds of other ways to do it.

But like Jim said I mean we’ve both been involved in companies that have been VC-backed and we’ve seen them sling the company around to try to meet whatever their goals are.

And so that’s actually one of the things that we’ve talked about occasionally, is okay are we at the point now where we can’t continue to bootstrap it ourselves, are we at the point where we should take some money and so we can do some additional marketing.

And we were real hesitant on that. Trying to decide.

How do we move forward and how do we maintain the spirit and the feeling of the company. How do we maintain our open source roots because we were all very focused on security and privacy and we believe that everybody should be able to have security and privacy if they want.

But if a VC makes it, if a VC says okay well now you have to get everybody to register, well you know we’ve got people who don’t want to do that.

Startup Advice

Michael Schwartz: Any advice for entrepreneurs starting an open source software business?

Jamie Thompson: It’s harder than it looks. It can be fun, it can be difficult.

But if you have what they call today grit, if you have that ability to stick with your idea and keep going but yet, if someone is able to influence you and you change your mind help steer you in a new direction, that’s great.

But it really, it’s on you and you find, they would say find your passion, but find a thing that’s really interesting to you and stick with it.

Jim Thompson: Businesses survive at the will of their customers. Solving customer problems and providing value to the customer is literally why you have a business. Because without that nobody is sending money your way unless they feel bad for you.

As an entrepreneur you have to be willing to engage with and talk to your customers and prospects. You have to be willing to take the call that says your code is broken, fix it now. You have to be able to hear rejection when somebody chooses another solution and get up the next morning and go back to work.

These things all sounds trite but a lot of people the computer field are into the computer field because they like working with computers, not other people. They have friends but population at large can be scary to approach because what if they say no.

The best thing you can do for yourself as a business or as an entrepreneur is to be willing to interact with the people who think your product is interesting. And they would like to find a way to use it and they have potentially other ideas about how it could be used and you have to be willing to listen.

If the number of bright people on a given body of people is, I think as Bill Joy famously said, is the log of the number of people in a group, so the number of smart people in a group is log of number of people in a group, and he didn’t say what the base was, but it’s this diminishing returns, a larger group you have the fewer smarter people you have per out of basis.

But these ideas occur everywhere. And open source is really one of the answers to the question of how do we adopt other people’s ideas. Somebody can have an idea and they can develop an open source project and it flourishes or it doesn’t. If it flourishes it was a great idea, incorporate that into their technology stack.

It’s the same thing with customers, some customers will help you focus your products in ways that you weren’t going to think of. And so that ability to be open to hear both positive and negative messages about the thing you’re doing with your life or that part of your life is really critical.

Michael Schwartz: Jamie and Jim, thank you so much for sharing your insights and best of luck with Netgate.

Jamie Thompson: Thanks for having us.

Jim Thompson: Thank you.

Credits

Michael Schwartz: That’s it for episode 2. Transcription and episode audio can be found on opensourceunderdogs.com.

Special thanks to the Linux kernel for co-sponsoring this podcast, to the all things open conference for helping us publicize the launch.

Music from Broke for Free, Chris Zabriskie and Lee Rosevere.

Production assistance from Natalie Lowe. Operational support from William Lowe. Thanks for the staff of Netgate for logistical support.

Next week we’ll talk to one of the superstars of open source business, Michael Howard CEO of Maria DB. Until then, thanks for listening.

Episode 1: Anaconda – Python Data Science Platform with Peter Wang

Peter Wang is the Co-Founder and CTO at Anaconda, Inc. Anaconda is the world’s most popular Python data science platform and is the industry standard for data scientists. In this episode, Peter discusses Anaconda’s fast growing business, and how they use enterprise tools to monetize their open source software.

Transcript

Founder Story

Michael Schwartz: For our introductory episode of Open Source Underdogs I’m sitting here with Peter Wang, CTO of Anaconda, a distribution of Python math libraries used by data scientist all over the world.

Peter could you start by telling us about your background and how Anaconda got started?

Peter Wang: My background is actually in physics and I end up going to software after college because I really like coding. And I sort of found my way to doing consulting using the Python scientific DAC if you will, that was kind of in the early and mid-2000s and as I did more work in that area I realize that there were significant commercial adoption opportunities for Python.

But the scientific stack was you know, it was still coming together at the time, right, there is some significant gaps and difficulties and how to use it. Then once I saw the Big Data wave starting to hit I recognized that enterprise data analytics would be something that Python be very good at, and people already starting to self service and use Python for.

But there were gaps, and so we started actually as Continuum analytics in order to promote the use of Python for data science and data analytics beyond just scientific computing that we want to do some innovative projects to fill some gaps and holes, things like that. And then also to build a enduring and sustaining open source software company.

Customers

Michael Schwartz: Who are the customers of Anaconda?

Peter Wang: Our customers are large medium sized companies that buy our enterprise software, so that is a machine learning and AI enablement platform. It’s a very different pile of bits the that most people in the open source world who download free Anaconda are used to thinking about and so that’s you know the Enterprise customers buy that in order to support their data scientists that are using Anaconda internally in their businesses.

Value Prop

Michael Schwartz: What’s the value proposition of Anaconda?

Peter Wang: When you look at what data scientists need to do there’s a lot of data they need access to, there’s a lot of compute they need to run their stuff on. They need to do a lot of different things that actually traditional Enterprise IT is not very well equipped to support them in.

So our Enterprise platform comes in, and gives IT an easy way to provide a governed and secure computer environment for data scientists. They can collaborate, build models, build notebooks, build interactive dashboards, gives data scientist an easy way to also deploy those in a production way.

Now in businesses lot of data science can put toys together, they can’t it for them to then throw it over the fence to get IT to make something that actually runs for other people’s business to use, that can take a very long time.

So the Enterprise platform eases the deployment, it gives IT a way to manage and to govern the kind of data science it’s done, gives data scientists access to packages and software internally inside the enterprise firewall. And then for people who have only lived in the open source world that may sound really strange but lot of people they live in corporate environments that are very logged down, they can’t get access to software.

So with Anaconda Enterprise we provide a way for IT to feel good about there being a vendor to provide the software and the data scientists are happy because they get the latest and greatest versions of all the packages they want.

Challenges Of Open Source

Michael Schwartz: What have been some of the challenges of using open source as part of the business model?

Peter Wang: So one of the things is that we both use open source in building our Enterprise product, we also, what Enterprise product does is makes open source available for people to use, right, so there’s things like machine learning libraries like scikit-learn that we don’t write and we provide. So there’s challenges associated with simply providing open source to Enterprise users.

Then there’s additional challenges of just using open source software in our proprietary enterprise software, right, there’s sort of two sets of challenges. With the former, with the distribution open source software I would say that most businesses are actually starting to understand that open source software is a key part of the software development stack.

For machine learning and AI applications in particular, it’s an integral part of it, you can’t do without using open source software, so Enterprise IT is starting a clue into the fact.

The challenges run into are that even though they are clued into this, there’s still procurement and legal and security and governance questionnaires that come down to us that sometimes you’re just like WTF, you look at this like you know like there’s no way we would make reps and warranties on a piece open source software that has global contributors, right, or yeah we have customers asking for unlimited indemnity of something or the other.

It’s like we don’t even write half of the software, it’s your users internally that want to use it. You know, we’re just making this available for you.

So there’s like some of those kinds of, I would say disconnects and impedance mismatches between enterprise expectations.

The biggest challenge I would say is that enterprises, they think of data analytics providers and vendors like SaaS or someone like that, that comes in with a big giant piece of shrink wrap, very expensive shrink wrap software.

That’s all just that vendors bits and so they’re used interacting with vendors in that way. So when we come in and we say we’re a vendor that’s an enablement platform, we have our pile of bits, we indemnify and support and provide you warranties, but then part of that is we provide fluid rapid access to a ton of additional capability in the open source ecosystem.

They really have a hard time, it’s really legal oftentimes that has the challenge of separating, you know, the bits that the vendor wrote and the bits that the vendor’s providing access to. They have a really hard time disambiguating those two sometimes.

Anaconda Platform

Michael Schwartz: Can you talk a little bit more about what makes or what defines a platform and what does that mean exactly to you?

Peter Wang: So for me a platform is something that, it’s like a market right and so it facilitates an interaction between providers of value and consumers or users of value and it makes it from an M times N problem to a smaller like M plus N kind of problem.

So in our case, we have you know, there’s hundreds and hundreds of developers of open source libraries that want people to use their software, and that you know there’s a lot of capability there. And then there’s thousands, tens of thousands, millions of people inside businesses that want to use the software. But they don’t know which software they should use, they don’t know what software is secure to run, what versions are the most up-to-date, things like that.

Our platform essentially is a bridge between the open source innovation space and development around these machine learning libraries to the Enterprise, very governed environments, in which the software needs to run.

So creating a place where people can bring their goods so to speak, so in this case software packages and capabilities, notebooks, it could be datasets, whatever. And then where the consumers of those things can come and actually pick what they want, that’s what makes it a platform.

So we ourselves of course we built quite a bit of functionality into the platform but really letting this additional generated activity happen inside it.

It’s not merely, oh here’s a big pile of software and then we have some extension points so that people to plug-in things, it’s not a plug-in ecosystem.

It really is a platform that provides people with this bridge that lets people go both ways.

Cloud Offering

Michael Schwartz: On your website I noticed Anaconda.Org mentions a cloud offering. Is that a direction that you think is is promising? Or is the main focus the enterprise software suite?

Peter Wang: I’ve always been very interested in data science in the cloud.

Actually one of our first offerings as a company in 2012 was a cloud-based on demand and notebook computation system called Wakari. And then we eventually shut it down because it was a very hard way to make money at the time and it takes a lot of capital to actually get a software-as-a-service company going.

And so right now Anaconda Cloud as it exists is mostly a place for people to host packages and notebooks and to share those with people but we don’t actually execute those notebooks on people’s behalf.

In the future I cannot make any promises about our long term product roadmap, but I do feel like cloud-based execution of notebooks and of models, things like that, it’s a natural need that emerges and you know we may do something in that space.

What’s Next

Michael Schwartz: What are the most promising areas that you’re investing in or looking to innovate in, in the future?

Peter Wang: Well, you know, the space moves so quickly and it’s evolving quite a bit so we really are looking at I think for most Enterprise software companies would be, because of a very short time windows, or innovation sort of new, de novo innovation work.

We’re mostly right now investing in the existing projects that we have. We’re also investing, there’s a new project we just released for data access, to really solve that data reproducibility and data sharing problem; lightweight data catalog and data access library called intake that we are very excited about.

But moving forward we will be looking at doing, you know more things with regard to model management and helping people share models in a more reproducible and seamless way. And you know beyond that it really depends on how the business evolves.

Revenues

Michael Schwartz: So of those different areas where you could generate revenue, which one is generating the most revenue as a percentage? Is it license?

Peter Wang: We’re primarily, the vast majority of our revenue comes from software licenses.

That’s wasn’t always the case, we actually made a pretty dramatic change over the last year. Flipped almost completely 180° around from being mostly consulting with some small amount of, relatively small amount of software revenue to the other way around. Where it’s mostly software revenue and a much smaller amount of consulting, training, services, things like that.

License Model

Michael Schwartz: Can you share any details about how you went about licensing?

Peter Wang: We start as a company to support and promote the growth of Python for data science.

So we’re something that’s very much of a community, right, it’s not like Travis and I sat down and said: Oh, aha, we have this genius idea for some crazy new cool technology, we build it and then we’ve vend it.

It’s, we’re of this community, we built more innovations to help, amplify the the efforts of the community, we’re always of the Python data science community. So, the ethos of that community is to license everything permissibly so MIT, BSD licensed, LGPL sometimes.

And so it wasn’t really feasible to do any kind of open core business model around that. Some communities, R as different right, the R Data Science community, R is all GPL based. And so classically there have been two companies, one got acquired by Microsoft, that were heavily doing work in R around open core model.

In the Python world I don’t feel like the community has an appetite for open core business models. And so we very quickly came to understand either A) we have to sell something directly to the community so our users and they’re our customers.

Or, we figure out some kind of enterprise software that we sell, that is a proxy need, fills the proxy need or as a proxy to the open source of free stuff that we give away.

So the business model we converged on was essentially that. We give away this stuff you know, you give away burgers and you sell the Coca-Cola or something like that, right.

It’s not, you get a free burger but if you want two patties, or if you want the burger with cheese then you pay extra, right. That’s not the model we have, so Anaconda, all the work I do are around Anaconda and the packages the distribution of the testing with all that stuff give away for free.

We will give it away for free forever, because we know that when businesses start using this stuff more, and more, and more, it will drive proximate need for for other kinds of things. And the first significant proxy need that showed up was the need for a management platform or some way of managing and governing the use of open source data science packages inside the business then it became managing the collaboration around Jupiter notebooks and things like that.

And now lately it’s evolved much more into deploying models and looking how models are running, you know, the actual models in production is a much larger part of what’s driving business pain and so those are prominent, all three of those things I mentioned the repository package governance, the collaboration and then the management of models of production.

All three of them are core components of our platform offering in our Enterprise product.

Tools

Michael Schwartz: Would it be fair to describe that as tools around the open source?

Peter Wang: I don’t think it’s tools as much as it’s, I mean the nature of the software itself is to provide an infrastructure for you know spinning up servers, deploying things. It’s not, they’re not really tools as such.

I mean actually the end user experience, when they’re sitting there, like if you’re a business user, as a customer that’s bought Anaconda Enterprise, you’re using the browser login to our Enterprise platform and you get the the Jupiter notebook experience there.

You can also use Anaconda as you always used it on your laptop or something, and the Conda package manager will connect your internal package repository. So it’s not like you’re getting extra tools, you have the same tools you’ve always had from an actual data science day-to-day perspective.

But using them in an Enterprise environment is much easier for you now.

Marketing

Michael Schwartz: Maybe switching gears a little bit to the marketing side. Does Anaconda just sell itself? Because the community has a strong underlying, you know science Python community? Or what are some of the channels that you use to get the software out there?

Peter Wang: Well, so the enterprise software – so very few things in the world sell themselves. And the reason is two-fold, one if there’s not much demand for what you’re doing, then you have to go and tell everyone about what you’re doing.

If there is a lot of demands what you’re doing you’re going to competitors that race in and provide messaging around why their product is better than yours, right.

So in both cases if there is or there isn’t a demand and you’ve got to be doing some kind of selling.

Now for us the the machine learning platform, data science platform, that term is now a term of trade, right, in the business so we have people at the CIO level, CTO level, that are like, okay we need a data science platform, right. They know what that is, they know it’s something they need to do to support their data scientist.

Now it does help us that those data scientist will tend to already be Anaconda users, we do have access to their mail list and social media and whatever else. We have a pretty visible, pretty well-known as a brand, so the brand everything is top-notch. We’re known for our investments, interaction with the open source community.

So all of that stuff helps us in the actual sales process. But in the end of the day we do have to do marketing, we do have to inform people about what the features are, why they would buy.

It’s like any other piece of software you’re trying to sell, there’s real activity you have to do there.

Sales

Michael Schwartz: So without going into actual prices, but maybe just around pricing philosophy – were you able to quickly figure out what your price should be? Have you changed a lot over time?

Peter Wang: It’s changed a lot of over time. Depending on who you’re selling to, it really, you know, we’ve always been in the enterprise sales sort of mode, for our support training, things like that, as well for our products.

So from the beginning we had this understanding that enterprise sales is a different kind of animal than you know consumer sales, setting prices and all those things.

There’s a whole process to sales and sales strategy, and neither my co-founder nor I would claim to be experts in that, although we have some perspective and some background in it. So it’s important to actually work with sales people who kind of know what they were doing. And we’ve been evolving overtime, we’ve been learning overtime, how that whole thing works.

Partnerships

Michael Schwartz: Maybe we can talk a little bit about partnerships. Do you have a strong partner network or who are the partners that you’ve built up over time that you think have been important to you, getting out there and getting to market?

Peter Wang: So Partnerships, we’ve always worked with some other companies, but in terms of actually driving to sales success, that’s been a fairly target activity over only the last couple of years. Because using partners as a channel – their sales people have to know how to sell your product, right.

They have to know how to close a deal and include your product in the pricing so you have to have really, really clear definition of what is the product, how to talk about it as an integrated part of the partner offering, all those different things. And I would say that’s again, that’s something we’ve only been doing relatively recently.

Prior to that our partnerships really consisted of technology partnerships and sort of marketing and exposure kinds of things.

I mean the data science field itself is also relatively new, at least in terms of enterprise adoption of this stuff. So we actually partner with, there’s sort of two classes of folks: One of them are hardware vendors, actually. So Intel and Nvidia Microsoft, the cloud vendors like Microsoft, Google, Amazon all that.

But the hardware vendors AMD, Intel, Nvidia and gosh I probably could use some others there, IBM obviously, they have hardware. So with those we are partnered on technology as well as some go-to-market activities.

So we have a compiler called Numba that have distributing computing system Dask. Those are very, very exciting for these hardware partners because they want to showcase their chips running at scale, they want to showcase the kind of performance wins.

Now if they require end-users to have to write extremely low-level code in order to get those wins it’s a non-starter, right. So the idea, it’s not just performance but it’s performance as accessible.

So using our tools and technologies they can get your average data scientist with not some like C++ optimization nerd. Your average data scientist can use some of our libraries and then be running these things you know and really showcase their performance.

That’s some harder partnerships, then the cloud partnerships as well as some others. They’re really around the data science tools, around notebooks or visualization. Some cases they’ve been with our enterprise platform as well so it really depends.

So like with Microsoft for instance, we are partnered multiple ways.

So our Anaconda distribution is installed on Azure, it’s available as the Python runtime inside sequel server itself which is pretty cool. It’s something you can install as part of the default Visual Studio installer if you say I’m data scientist, and you select that profile, it will install Anaconda for you. So that’s a really cool partnership.

And then on the flip side of it, we’ve included the VS code editor inside the Anaconda distribution installer so that that’s one of the editors and ID’s that’s available for end-user.

So there’s multiple aspects of Microsoft relationship, but those are probably the most significant ones. But these partnerships are very exciting for us, they’re still in the early stages, you know, right now we would love to see driving more revenue through those.

We are investing in those relationships because we believe we will be able to drive a lot more revenue through them.

Ecosystem Partnerships

Michael Schwartz: What about non-, let’s say business partnerships, any organizations, or foundations, or other communities that you found that had been really useful for you to promote the product?

Peter Wang: Oh yeah, well so we primarily stay in the data science space, right, in the Python ecosystem.

We’ve been growing our inclusion of the R ecosystem as well because many data scientist use both Python and R. And so we’re trying to find better ways to play nicely and be a good participant in that ecosystem.

But on the Python side we’re actually I would say pretty unique in that we started the company in January of 2012 and then by March we started the effort to create a non-profit to support and sustain several open source projects in the Python ecosystem.

That nonprofit is called NumFOCUS and that’s been a really good partnership of ours.

When I started the PyData sort of global community sort of effort, we attached that essentially to NumFOCUS as well. So now NumFOCUS runs as a center point of coordination for PyData meetups, PyData conferences all around the world.

It’s really grown, just really blown up. So that’s a constant and really great partnership with that foundation. That’s, I would say probably the primary one at this point.

There’s a lot of community events and things like that, that we do as well just to be good stewards you know, and show up. But those drive a lot of awareness for us.

One of the challenges from a business perspective is, if you say too close, just mingling with your friends, you’re not going to sell much because, in our case our friends are all users of the free stuff, right and they’re not really the people who are signing the procurement checks to go and buy the enterprise software. So yeah, that’s one of the dynamics there.

Keeping Current

Michael Schwartz: How do you stay current on what’s a very hard domain?

Peter Wang: Yeah it’s tough. I mean I don’t… I wouldn’t go so far as to say I am current. I am current on some things and there’s other things that I’m not as current on.

We have just a very, very broad range of technical expertise under one roof here. So we have people working on compilers, people working on distributed computing, people working to visualization.

People who are working on JavaScript front-end things for the enterprise software with people who are working the back-end. So many things – containers and all the back-end coordination orchestration kinds of things.

Our consultants and trainers who go out in the field and talk to customers they get exposure to a wide variety of different kinds of modeling problems, optimization problems, what’s the state-of-the-art in machine learning, in deep learning, all these things.

And I just have the great privilege of being able to talk to all these people and kind of glean from their learning as much as I can. Now I do some deep dives myself on some things, I have more time now than I’ve had in awhile. That’s part of it.

But, most recently I’ve actually spent the last I would say 3 or 4 months really nerding out on, believe it or not, the physics and the anthropology and the human ecology around open source and open source ecosystems, communities, and how we do sustainable open source; how we continue innovation while maintaining stable software.

The nature of software businesses as a whole, especially as it pertains to open source. So these are areas that I’ve been actually thinking about quite a lot and I found that my physics metaphors or my physics intuition has helped me a lot in thinking about the System Dynamics of that human ecology.

Open V. Commercial

Michael Schwartz: What are some of the challenges you think of starting an open source business or, I should say a business that uses open source as part of their model, versus straight commercial software company?

Peter Wang: I have a snarky answer – which is that the challenges that face an open source company are no, really, theoretically, no different than what face in a commercial company.

In practicality they’re different. Because a commercial company one tends to have a fairly reasonable expectation that the investors of the company and their shareholders are the ones that the company’s optimizing for.

If a company does a great job that’s measured very quantifiably in returns to shareholders. That’s the American model of capitalism, that’s what a company does. So if you screw up the company. The only people you’re going to piss off are your shareholders and your investors. Probably your employees too.

But in the open source side, open source software company there’s actually much more explicit or intentional vision that matters.

Most companies, they have a lot of like vision, mission, blah blah blah. For the most part once you get to a certain size employees are all like, yeah this is to make money. Unfortunately, you know, that’s just the reality of it. Now some businesses have highfalutin goals, most don’t actually even attempt to play to those.

But it open source companies the founders and the people who are stakeholders in it, there’s a broader set of stakeholders.

So who you piss off is a much bigger range than just the shareholders and employees. And so I would say that’s the thing – is that failure means different things.

And for open source companies usually – it’s sort of like you split the whole world of living things and prokaryotes and eukaryotes, right. Like in the world of companies, of open source companies, I would say you can cleave it in to those that do open source as a means to an end; and those for whom the open source bodies part of the ends itself.

And how open source embodies an ends – now that itself can vary. For some people there’s a religious belief that all software should be free and by golly, we’re going to build this thing to be free.

And those companies sometimes can struggle because there’s this reluctance to charge for software because you believe software is free, and so they are limited to a particular kind of growth curve because the corporate financing is available to them is of a particular stripe because they’re consulting or services company.

The ways that they can fuel innovation is also limited because they cannot go and sell a product as easily as someone else could.

So those for whom just open source because, it’s open source, those companies who have that ends, you know they’re kind of constraint to one part of the landscape.

Then there’s other companies for whom open source is an ends and a means and part of it is that it embodies some technical vision that the founders cared about. That technical vision is either only achievable through open source or gathered momentum and gathered user base, and a way of doing things, a technical perspective, that is now at this point so steeped – like the open source is part of its DNA – that it would seem like a violation and a rejection of everything that the soul of the company is, to walk away from that. That’s a different kind of ends, right.

And then there’s others like, I think for my perspective we’re little bit of that, but then also, from my perspective there is a fairly opinionated view for us that open source is, it’s a statement that were not going to lock people out by closing the software.

So it’s almost like a statement of – we may fight as a business and compete in a landscape that’s rich and filled with many kinds of competitors but one thing we’re not going to do, is we’re not going to use closing down access to software as a means of either charging rent or fighting dirty, or a way to charge rent so we don’t have to innovate anymore.

So in that sense being open source company means that you are essentially committed, there’s a covenant to your customers, to your users, to the ecosystem, to your employees. There’s a covenant that you are going to innovate, because it’s so much harder to be just a rent seeking monopolist as an open source company just around the software itself.

So, it has a bit farther range than you’ve expected from the answer, but…

Competitors

Michael Schwartz: Actually, you brought up one thing I wanted to ask you. Does Anaconda actually have a lot of competitors?

Peter Wang: There are some things that we do that are unique in the world. So on certain aspects of the technology and some of our product features I would say we are very unique.

Now there are certain other things that we do, in particular the software that we sell that, you know we think we’re the best but there may be other companies who think they’re our competitors, right. And so I think that from that perspective, and certainly it’s up to the customers and not us, to say.

So there are times when customers will you know bank us off on other things and so we definitely have competitors in the enterprise space.

FOSS Development

Michael Schwartz: And you mentioned open source as requiring you to innovate. But has it also helped you to innovate?

Peter Wang: Software is a collaborative creative activity. And then some, for some problems, for some kinds of projects, the kind of open collaboration that open source represents are the most effective way to harness collective intelligence and get something really useful out.

In other cases open source is actually, the open source development methodology if you will, a way of engagement. It’s actually not necessarily the most effective to harnessing innovation.

And the dirty truth is if you look at the way the open source project actually roll. For all you know, all the Kumbaya aside, you know how they actually roll.

The most successful ones are launched by one, two, maybe three person founding team. I mean 3 is pretty rare, usually it’s one or two people, usually one actually, and they like a blaze of glory, they dropped this code in the world. And other people start glomming on and that initial nucleation site around the initial feature set, the collaborative dynamics of that. That really sets the future, like the seals the fate of the project a lot of times.

But usually open source projects they launch when it is a blaze of glory sort of innovative leap from one person’s brain.

And even now like, if you look at there’s a really sad or interesting way of looking at this, like the maintainers of some of the most critical open source projects in Python that are used daily by millions and millions of people that back billions of dollars of commercial infrastructure activity whether it’s power grid whether it’s keeping satellites up, whatever… I could fit all those maintainers in my minivan.

Now one can say, wow witness the amazing leveraging power of open source but you could also look at that say wow that’s really sad, we’re under supporting and investing these projects. So I am a big believer in open source, I don’t want this to sound like I’m like poo-pooing it, I’m a big believer in it but I’m also a realist.

And I think that open source in the early days had a lot more of the, you know, the OSI, FSF kind of days and all that.

I mean a stallman, coming out and planting a stake in the ground and saying we’re doing open source, the commercial Unix people can go you know, they can go pound sand, and we’re doing open source. That was important as a stake in the ground at the time, and over the 90’s as, you know, the Linux folks tried to educate everyone about, hey open source, okay here’s what it is, here’s free software, here’s open source.

Now, there’s a very different dynamic, as businesses are like, yeah we don’t care. Like the golden era of software is over, its services, it’s machine learning enabled services. These are where the top end of the value chain are.

There’s a real squishing compression dynamic on software that’s happening, specifically just on open source software. And if we’re not cognizant of that dynamic, if we don’t step up as fans of open source software who love the collaboration dynamics of the community, if we don’t step up and defend that and say actually, if you’re going to rely on this infrastructure you need to be paying for the maintenance of it and not rely on volunteer labor.

You know I think that’s a conversation that the free software world needs to have with the commercial world.

Venture Capital

Michael Schwartz: We found sometimes that being open source actually is a hindrance to us. Do you ever feel that, like that open source makes your life more difficult?

Peter Wang: Yeah. For venture capital fundraising, open source is a huge liability, absolutely. Because VC’s don’t understand open source. The big ones, I would say.

Like, smaller funds that have maybe a little bit more, that can take a bit more of an opinion, be a bit more of a gambler on business models, things like that. Maybe, certainly there’s angels, you know there are angel funds that they believe in the technology or something like that.

But the but the vast majority of VC’s, they’re there to really pattern match against known business models, known growth curves, you know things like that.

So if your business model is working to charge the software they’re going to ask, well how much value is the software? What do we believe the predictable growth curve looks like for this.

If your business model is we’re going to get users, they don’t care if give away the software, right.

So it’s all about, when you talk to the VC’s, how do you present them with articulation of your long-term value or not long-term value, but the returns you generate on their investment. That’s often the only conversation they really care to have.

So if they’re investing in software and you just giving it all away it literally looks like you’re just giving away their money.

In fact – if you were to say we’re going to take the money, buy iPhones and give it away to everyone, they would at least understand that a little better, because it’s something tangible in an iPhone right, they can say well we’re going to get on the other side of it.

You know, or you’re going to give away anything like MoviePass or whatever, I wanna give away free movie tickets to people and lose money on movie tickets. VC’s are not afraid to lose money, they want understand what that money is buying them. Right.

If it’s buying something else, some other number – eyeballs, or users, or something else, which you can then show how that converts in the long-term revenue, they are happy for you to give away the money.

But if it’s simply we’re funding software development and you’re giving it all the way, and you can’t show conversion that they believe in to revenue then it’s not going to fly.

VC Alignment With FOSS

Michael Schwartz: Were you ever concerned that perhaps the investment would come with strings that would make you to give up some of the mission or culture of open source?

Peter Wang: As we were talking to investors that was certainly one of the concerns.

I mean that with the reason we picked the investors we did was because we felt that they were mission-aligned and that was that’s a real luxury, we were very lucky in that.

And we worked pretty hard of the fundraising thing, especially as first time founders, not knowing what we’re doing. We talked to a lot of people. Probably screwed up a lot of meetings but, we ended up with some folks that actually really understood, not only the commercial potential of investing this, in the space in this company but also the mission, so we’ve been pretty lucky with that.

Again I would say that it’s rare to find that.

Advice

Michael Schwartz: What advice would you give someone who wants to start an open source software business today?

Peter Wang: Ultimately the act of going into business, it’s not separable question from why are you going to business at all, right?

Like if you’re going to start a business it’s because you either A) want to fund some activity; B) you believe you have some unique thing that you can sell to the world or some unique service you can provide to the world.

There’s actually very few, a small set of valid reasons for starting a business, in my view. And attached to each of those reasons, if you do open source as core activity the question you have to ask yourself is, am I doing this as a means to an end or am I doing this, is this one of the main things I’m starting business to do. If it’s the latter which I think is really where the meat of your question is, if someone says I want to do open source software but I also want to make money doing it somehow.

There’s many people who can, by building open source software, use it essentially as a marketing or brand awareness tool and then they can freelance, they can build a very healthy consultancy from getting their name out there and being known. That shouldn’t be downplayed as a valuable thing, and you can build a reasonably good small business around that.

But that’s not going to get you into unicorn billion dollar valuation territory, it just won’t, because to get to that level you have to somehow get to a certain size of revenue.

How do you take down certain amount of revenue, either you produce something like a piece of software that’s extremely valuable that you sell a lot of. Or you have a ton of people doing a lot of work.

Scaling up a consultancy is highly non-trivial, most software geeks who care a lot about technology are not wired to scale-up, a lot of meatware if you will. Once you get to a certain number of headcount you have got to figure out as an entrepreneur and as a technical entrepreneur how to let go of parts of it and let someone else actually help you grow that and that will change the culture and that will probably change part of the mission too.

So if you want to scale the certain revenue sizes you’ve got to do that either the basis of providing a really valuable, scalable service, or software.

I would just say understand the dynamics. Don’t blindly rush in with a whole bunch of optimism and then just curse your fate like, there’s a real dynamic here.

Investors coming in to help put more gas in your gas tank. They want to understand what roads you’re on, how far you’re going to go. If you can’t communicate to investors on the basis that they understand, about what your business model revenue models are, then you have no business asking for them for their money. You know, don’t get mad at them, right.

So, I mean it sucks in a sense that we live in this world where people do not think more about investing capital in socially-aware activities or in a generative sort of effective labor. That’s a broader conversation outside the scope of this interview probably, but that’s a systemic thing which I hope will resolve in 20-30 years time. But at this point of time it’s just the reality of the investment you know field, what it looks like.

Comparables

Michael Schwartz: What were some of the businesses that you looked to as you were looking to scale Anaconda as businesses that you could model after?

Peter Wang: We recognized that actually because we were not doing open core that took a lot of our peer crowd of open source companies off the table, right. So like, MongoDB is an example.

Michael Schwartz: Could you just define open core real quick?

Peter Wang: It’s where the core of the software is open source and then to use, to put more data through it, or to run it on certain kinds of machines with more cores, or to do blah blah blah you know additional features and additional whatever, charge money for it.

Michael Schwartz: So like an enterprise version and a community version.

Peter Wang: Yeah, community version only supports 100 users, enterprise is unlimited. Community version can only run in the cloud, enterprise version can run on prem, like things like that, open core yeah, it’s best way to define it I guess.

Michael Schwartz: I see.

Peter Wang: The core of it is still open source, you know it’s still legit open source.

Dual licensing I think also falls under that. Right, so like you basically, the core is open source GPL and then commercial license. That’s that dual licensing is also something, something that people do.

So you can use it for free for to a non-commercial setting but as soon as you take it in the house in a commercial environment your lawyers and their total like allergy to GPL will cause you to go and give IT a call to go buy the commercial license of the software so you don’t have to risk, you know, virally contaminating your internal software with GPL. Those are the kinds of models, and so we felt like many things in the data analytic space were in that kind of model.

And certainly databases have this a bunch. We didn’t really, we didn’t see those as comparables. And when you look at platform software there’s RedHat. Really not that much else to compare to.

Now we look at some of the Java framework companies that manage to sell, some got acquired by RedHat, some got acquired by Oracle. For the most part I mean once we figured out that we’re just going to sell enterprise software, you know by seats, sometimes by notes to customers.

It actually became pretty straight-forward how to think about the business, so in that case it was really drive a lot of usage of the open source stuff and that’s going to drive a smaller but correlated usage and demand of the enterprise stuff, that was it.

Final Thoughts

Michael Schwartz: What did I miss? Or is there anything else you want to add?

Peter Wang: I would say that right now I sort of just glanced by this comment earlier but I really do think that right now the world of software is in transition, so people who want to start open source based software companies now should think long and hard about what is the value chain for software actually look like.

It may be better just to do a software-as-a-service kind of thing and then you get to own the customer relationship, you own much more the value chain, etc.

Now there’s downsides to that as well but that’s something to think about because I think that the, and Jason talks about software eating the world, and that may be true, but I think less and less of what it eats has really high caloric value right; more more the high calorie stuff is going to other kinds of things.

So I would encourage you think strong about what it means to be a software business in the modern-day, especially as things like Amazon, Google, Microsoft eat the world of cloud services.

The second thing is understand what it is about open source that you love, that’s intrinsic to your mission and figure out, be very, brutally honest with yourself about what of that you want to preserve and what are the right mechanisms for preserving that.

Don’t assume it’s just a money problem don’t assume it’s just, oh if I got out from this like horrible soul-crushing corporate job I could do open source all the time.

There’s always going to be a whole bunch of yak shaving from a business and management perspective no matter what you do. Understand why you’re taking that particular road if you’re gonna take that road.

And the third thing is open source doesn’t exist in vacuum. It exists in a human ecology of users, contributors, competitors, and evolving technology landscape.

You need to understand to think strongly about whether or not the thing you’re building has long-term sustaining ecology value and if it does then it’s worth investing. Otherwise you might want to think about how to pull various other pieces of your ecosystem together to something that’s more valuable as an agglomerate.

Michael Schwartz: Peter Wang, Founder of Anaconda, thank you so much for sharing your wisdom with us. Best of luck.

Peter Wang: Thank you very much, thank you.

Michael Schwartz: Well that’s it for this first edition of open-source underdogs. Special thanks to the Linux Journal for co-sponsoring this podcast.

To the All Things Open conference we’re launching on October 21st.

Music from Broke for Free, Chris Zabriskie and Lee Rosevere.

Production assistance from Natalie Lowe. Operational support from William Lowe. And from the staff at Anaconda.

Next week we’ll talk to Netgate, a rare bootstrapped open source company who’s also based in my hometown of Austin, Texas.

Until then, thanks for listening.

Episode 0: Intro and words from our sponsor, the Linux Journal

In this episode, we introduce the podcast and hear from Doc Searls, Chief Editor at the Linux Journal, the original magazine for the open source community, and one of the sponsors for this podcast.

Transcript coming soon!