Videos

Jon: I'm here with Dimitri Vlachos, CMO from Devo. Welcome, Dimitri.

Dimitri: Thank you, Jon.

Jon: So, very exciting. You're the first speaker in our 2019 SOAPA series, and I'm also excited, because you're the first company that's sort of born in the cloud security analytics and SOAPA. So, tell me about that. Why are you dedicated to cloud? What does that give you? What does that bring to the customers?

Dimitri: Sure. So, first off, very excited to be here. In terms of why cloud first, we're finding most applications, everything people are building moving forward is toward the cloud. Now, overall, is cloud still a smaller percentage of IT spend overall? Yes, but the growth of it is really exponential. And, we're finding that people want their analytics and their data to reside close to where their data actually begins, to the applications, to the infrastructure.

And so, we not only believe that it's cloud first, it's also multi-cloud. The ability to have an analytics and data layer that can sit in, you know...it can be in the public cloud in AWS, in Azure, in GCP. It can also sit in a private cloud. But the ability to have all of that data sit where it needs to, whether that's for regulatory reasons, whether it's for performance and cost reasons, because moving data in and out of clouds is very expensive...

That's why, you know, we went from a multi-cloud perspective to solve this problem, as well as just the ability to provision and spin up very quickly. You know, that's why we went cloud first.

Jon: Okay, and from my perspective, using the cloud as your analytics layer and your data layer gives you the ability to throw a lot of processing at security analytics, a lot of storage at security analytics. Am I right there or... Is that an advantage?

Dimitri: Absolutely, I think it allows us to...in a very dynamic fashion is we add new types of analysis. Not have to worry about what processing power do you need. We control that. We understand what's needed and we're able to really align those together very quickly.

Jon: Okay, now you know from our talks that SOAPA is sort of a bottom-up architecture, starts with what we call a distributed data management layer. So, talk about data management and the data pipelining using the cloud infrastructure.

Dimitri: So, for us, there's a couple of major pieces. One, there's where does your data reside? We talked a little about that in the first. Second for us is, when the data comes in...we looked historically at the way a lot of companies or solutions solve this. When data would come in, you would actually change that data to be optimized, you know, for your platform.

Jon: Yeah, index it, normalize it.

Dimitri: And so, we've taken a very different approach of when it comes in, we basically store it raw. So, we're not altering it. You know, we are able to, on the fly, analyze it and put views on top that are very specific to the data type, but we store it raw always. And, that's a huge advantage, because what we have found is people don't know the questions they want to ask of their data when they're first collecting it, right?

Jon: Very true.

Dimitri: And, that might change over time as their needs change, the data changes. So, the more interpretation and processing you have to do on ingest really hampers your ability to react in real time. It also tends to lock you into what you're able to analyze. So, we've, you know, we have customers who are holding years of data and what they want to do with that data definitely changes very quickly as new users come on, as new use cases, they understand the datasets better.

So, our ability to have the full data raw the whole time is a huge advantage that people really focus on.

Jon: You know, I was going to ask you about retention rates, because again, you have all this storage capacity. Are your customers collecting more data, storing more data, retaining more data than you've seen in the past in your career?

Dimitri: Absolutely, and I think there's two aspects to it. I think there's... We really look at... To solve the type of analytic and security-scale problems that you know, we're talking about and the architecture talks about, you can't just look at real-time data and you can't just look at historical, you know, batch data. You need both.

And so, the ability for people to look back years, you know? We have some customers that need to store data for years. On average, our customers will probably do a year or more, but the ability to not have that be off the shelf where they have to do a lot of work to bring it back or have different indexes to look at that data. They can seamlessly access data from a year ago as if they were accessing data that's coming in streaming live today.

That's a huge aspect that people really find beneficial and a key part of how they need to move forward with security.

Jon: Okay. One more quick question on data, and that is storing data in the cloud, is there a data privacy issue for your customers?

Dimitri: So, privacy certainly is an important piece. You know, there's a couple aspects. We talked a little about location, right? I need it to reside in-country, so the ability to have...that's one piece. The second piece is being able to encrypt it both in-flight all the way down to storage, so that's another. We also allow people to put their own keys in, where we can't interpret the data.

So, it's your data. It's under your control, your encryption keys. We can't actually see the data. And so, we're a multi-tenant platform as well, so our data is isolated by customer all the way down to the storage level. So, those are some of the really important things from the actual data level. And then, we have also, of course, a rich set of controls for who can access that data, even within the same organization.

Jon: We're just getting started here. Do you mind hanging around for part two of our video?

Dimitri: No, that'd be great. That'd be great.

Jon: All right, thanks so much.

Dimitri: Sure.