StorPool software defined storage

Hey, everyone, this is Alan Shimel. com. And my guest in this DevOps chat is Boyon Krasnoff Storpool.

And I know it's not perfect, but the best I could do with your name. I apologize for our audience. Sorry if it.

Did you say your name for our audience? Yes. My name is Boyan Krasnoff.

But in kind of four English speakers, most people say Boyon Krasnoff like with the stresses of the wrong places. But it's perfectly okay. And I think as long as they don't call you late for dinner, as we say here, I said, well, you have your company's store pool.

Yes. And what's your position with Storpool? I'm one of the co-founders, one of the three founders of the company in my role as a co-founder from the very beginning has been kind of the glow between technology and business and the product person in the company.

The chief of product, Storpool. Sure. And the other two co-founders, respectively, think are focused on technology development.

And the other co-founder, strictly business, who is our CEO. And one has to do that. Okay.

Someone has to do the business. Yes, I have. Excuse me before we jump in.

Boyon to what Storpool is about and what you guys do. Why don't we talk a little bit about your own personal journey, how did you come to Storpool or what's your background? Yeah.

All right. So back in the 90s, I used to do like competitive programing. So I came from a fairly early age.

I got very interested in informatics or like computer science. Right. And from that, later on, I went to networking and ISB's.

Later on, I had a startup around something called packet processing and nowadays a software defined networking. And from that, like at the later stages of that start up before we folded up, we found this gem of an idea of software defined storage before it was called software defined storage. So we didn't know it was called software defined storage.

The term wasn't coined yet, but that's like in 2011. And from that, we found it store Porzel like it got with the other founders on in did it like a whiteboard exercise of what an ideal storage system would look like. And that became the architecture of all products afterwards.

And we've been building on that for the last. Years. Right.

Eight years now. Yeah. And along the way, we got.

Yeah, so they live in a few places, not just in Bulgaria. I've lived in Iceland, in the UK and Malaysia and a few others. And so instore, Paul.

You know, we started with the idea, implemented it, got it to force production use something like five, six years ago. Right. And since then, we've been expanding it in a very kind of real business, organic way, meaning pretty high growth.

But at the same time, very customer oriented. So. So it's very like the things we build into the product are things that our customers demands.

Right. It's not like a, you know, completely green field. Yeah.

And he has some data. We do stuff that matters for our customers. Right.

So, boy, I'm listening to your story. I'm reminded of my own. You know, I got into technology in the mid 90s.

With when the Web first started coming, it was starting to get commercial and we were we were storing Web sites. It wasn't called hosting. I thought I was a virtual real estate person because what would you know, I needed more land.

I put it another hard drive in. Right. And and by about 1997, people started calling that web hosting.

And we sold the company in 1998 when wind up doing a Pope IPO and that old thing. But, you know, at the end of the day, what we were doing is we were just we were storing people's Web sites. I was selling virtual real estate, renting virtual real estate out.

And it turns out a similar thing. You before there was a thing called storage software, defined storage. You recognized that there was a need in the market for people to do to be able to store stuff without the expense of.

I mean, you know, back I don't remember in those days buying EMC boxes. And some of the sun in IBM was the IBM shak, I forget. But all of these huge sand.

Remember, you remember the dates, millions, millions of dollars in Zan's and all of that. And then it was like a flip, like a switch flipped. People started saying, wait a second, we could do this in software for a lot less money with a lot more advantages.

Yeah, it sounds like store poll happen to be right there at the right time when this was coming together. Yeah. So kind of the reason we started it was a few conversations with actually hosting companies actually goes into place and some banks books started with hosting companies.

And at that time there was this big movement in hosting. Everyone wanted to be the next digital Osano.. Right.

Everyone wanted to have like a public cloud service with virtual machines and be like Amazon is the location. And they were like architects in these companies that were trying to figure out how to do it and they couldn't. And the one piece that was missing was software defined storage.

It was like that they couldn't make the business model work with standart some from HP or IBM or EMC. And we had to find a solution that worked for them, which runs all standard, sort of. It's like it's it's not appropriate.

Workbox. Understood. Understood.

So, I mean, what time is 2012? Now, here we are, 2020. Software defined storage is a much better understood term.

I think it's gone mainstream, if you will. Right. People still use that.

So how you know, as you sit here today, how I as store for. Changed in in these years, I would. What is some of the new innovations and use cases that you guys are seeing that you know and you've you've had to build or change technology for.

Yeah. So first, there is in the last few years, there is this realization in terms of our kind of positioning and product. T.

organization where the system, I mean, receives another form and fulfills that. Right. T.

workflow or an organization in which there is a lot of kind of dynamism and automation. Right. So there are systems talking to systems and or people talking to people.

And we've been very good about from the very beginning. But now we realize that more and more and alongside without our kind of fairly new use cases for us are. So we come from automated environments in which there are virtual machines and newer use cases for us, or same kind of automated environments in which there are containers and pods on the cabinets.

And also fairly recently, automation environments. Which provision bare metal or physical servers. Now, if you think of people that have like idle hundreds of servers which sit sit idle and they can dynamically provision these resources to be part of their application, Coaster's signed in some way and a product turns out to be pretty good for both of these newer use cases.

And the other thing that's happening in terms of our positioning and the other direction where the company is going is we are because of our longer history and the product is more proven. It has been more proven over time. We are managing to attract larger customers.

So there is this focus on larger icon organizations which have bigger pain, pain points and bigger problems to solve. So sort of this direction in the development of the product and the company ship shape. One of the things we've seen here, DevOps, Starcom and Container Journal, is all people recognizing that it's about the data.

It's not. The technology needs to make us be able to access the data DLC data to use the data, but it's about the data. But the other thing is, you know, we have this thing called data ops.

I don't know if you heard the term. It kind of rides on top of DevOps or at least in our world because we're DevOps Starcom. We see it in conjunction with really the power we see is that a lot of organizations that are adopting DevOps, adopting automation and continuous type of delivery are also adopting data ops and automation around data data storage.

Data analysis. And so I'm wondering if it's store pool, if you're seeing this connection between DevOps and NDU using product and data and how they're using it. So the way we plug into the whole DevOps ecosystem is the infrastructure layer.

So if you think of applications being built as application or also known as big business logic, layer on top and then in the middle, you have some form of block form, which could be, you know, a database application, server room times, things like that. And then at the bottom, you have infrastructure where our product plugs into the school system is the infrastructure layer. So things like, for example.

Things like a Kafka or I could do coaster or things like that. They said maybe you can think of them in the middle in the platform. They are great.

And if you deploy a circle coaster, you could deploy that on top of or servers, but you could also deploy that on top of a real storage system like poll. And there are some advantages to doing that. Right.

And the way we plug into that is through deployment, automation and dynamic provisioning said. So you could, you know, scale your in your data lake or whatever you want to call it. Without having to physically touch.

Right. And in order to do that, you need automation and the infrastructure there. Not just the platform and application.

We plug into that infrastructure automation. Absolutely. Very good.

You know what, Boyon, I didn't. I apologize. We should've said this upfront from people want to get information about Storpool just go to the website.

You know, the Web site's pretty good. I think we've we've spent a lot of time with s t o r p o o l. I guess.

Exactly. OK. Now the offering is it a kind of a SAS model or is it you just buy this software.

Like how, how, how, what's the sort of go to market if you will. Yeah. So it is a software omni model, meaning that for most of our customers we don't ship cargo.

Right. Right. Because software defined storage.

Yeah. That, that there are there are very few exceptions where someone would come close and they would say, you know, you guys go software. But I would also like to buy like the servers from you.

Because it gives me a bit more assurances to, you know, what I'm getting. Right. And we can sort of that use case to.

But it's kind of the retro use case. And so what we provide is software and the services you need around us to run that software. So things like monitoring and say deploying it abrading, it's like all the support and services you need that on that that software is installed on our in our customers infrastructure means on their servers, in their data center.

It's most kind of typical use cases would be like private cloud environments, which maybe in like proper design take center or they may be you know, they're, most of them. So this has got help, but the whole floor looks like the team that builds and operates infrastructure for it, for the psyche large our children ization that they need to build the infrastructure that consists of computer networking and storage. Right.

That they will get different storage vendors and ours. T. automation kind of environment.

We'll say they select our products. They will buy servers from their preferred server vendor or they would compete different servers, vendors in in a process. These servers will be installed in a data center and connected to their network and they will get the license for the Storpool software, as well as supporting services from us.

So are deploying it's training them, upgrading, etc.. Right. And this is how the model works.

We in this space, we compete with different types of folks. It's not just software defined storage. There is also kind of the traditional sun or fossil Evander's.

Right. And increasingly so. Also, even those are quite popular, by the way, in this area in private cloud infrastructure.

Right. T.. So that's one of our strong advantages there.

Understood. Excellent. All right.

Well, I and I think we're running out of time here. We give the web in. I told you, the time goes quick.

Once we start talking about technology and the companies, the time goes quick. You know, we can have you on. But we could do some other feature on DevOps about it.

Is there anything we miss that you want to touch on? Just six I like talking points here. So there is this for example, there is this concept of persistence and persistence, storage versus a shared one.

So, yeah. So what we're doing in Cuba, Natus and Polzin containers, right. Is what we provide persistent volumes for containers.

Right. And it's if you think about it, it's it's nothing new. So so the same kind of thing was needed for virtual machines before that.

So you had the choice of virtual machine with local storage or let's give that virtual machine a a virtual disk, which would survive if a particular physical host died. Right. And that that would be called persistent storage.

And the same thing is now happening in containers. You know, it used to be containers or stateless and you don't need assistance. And over time, people have realized that it's some level in your stock.

You need persistence and actually every every service, you need some form of assistance. It's kind of extremely rare that you would have a completely stateless service which wouldn't need assistance. Right.

So what we did there was we implemented a quality CSA driver that provides assistance storage for and response systems. Volumes. Right.

And these are used. So what are they used for? They're used for things like transactional databases.

So, you know, my skill, PostgreSQL, and they're also used in these. Batch processing applications, you know, where yours take a large amount of data in your transform it and outputs a concise index of the data that you can then curity and you can think of one parse that outputs the, you know, does a little calculation and produces an index and need assistance to store the index. And another other parts that's.

Cure is the index, and that may need very low maintenance and that's very performance oriented. The second part, the first part is like more of a batch processing. It's OK if it takes a long, long time.

But the second part of the public process, this online cure, is usually very performance and maintenance sensitive and, you know. So that's that's where we play quite well. Excellent.

All right, Boyon, we're going to end this this discussion, but maybe we'll have you back on. We can continue. And then you're going to get this whole the whole data space is really heating up and everything around it.

As, again, as I mentioned, people are recognizing that it really is about the data. All of the technology we built around it is about data. And so we need to to kind of focus there.

But anyway, Boyon Krasnoff, Storpool has been our guest here. This is Alan Shimel. You've just listened to another DevOps chat.