Jeremy Burton on Observe’s Series B and Strategic Growth

This is Techstrong tv. Hey everyone. Welcome back here to Techstrong tv.

Our next guest this morning is Jeremy Burton. Jeremy's the CEO of a company called Observe. And we're gonna find out all about observe and what they've been up to here in a second.

But first, Jeremy, welcome to Tech Drunk tv. Pleasure to have you Invite. My pleasure.

So, you know, Jeremy, I always like to start off with who's the person on camera with me? 'cause most of our audience, they don't know you. They, they may, they probably don't know observer.

A lot of people aren't gonna know observers yet. But let's start with you. Give us a little bit of your story.

Well, I'm, I'm not, not a native, uh, uh, certainly not a Native American. I'm actually not from America at all, originally from the uk. Um, I moved out here in The mid nineties.

I couldn't tell from your French accent, you knows, but go ahead. Yeah. I moved out of the mid nineties, uh, which seems like forever ago, uh, to work for a guy called Mark Benioff, who you might know.

Mm-Hmm. I've heard of book back in the day when, when he was at Oracle. And, um, I had a great run at Oracle in the, in the mid to late nineties.

And I've always really worked at sort of larger tech companies, Oracle and Veritas, Symantec. And before observe I was actually at, uh, EMC, I ran all the product teams there, and then we were acquired by Dell. And Sure.

I stuck around working for Michael for a couple of years after that. And, uh, but always wanted to do a startup, right. I, I was always a little bit inspired by Michael's story at Dell actually, him starting to company Radius team Outta of his dorm room.

Mm-Hmm. You know, building what he's built today. And that was sort of one of my pardoning words to Michael, which is, look, I want to try and do what you did.

I wanna build my own thing. So I joined observe with almost nobody here. And that was five and a years ago.

Really. That's great. Um, what a great story too.

You know, and it's, it's interesting. Sw I'm a startup guy. I, I didn't always do this.

I, I've done four or five venture backed startups over my life and, um, generally you get that startup thing in your blood, you know what I mean? And you go from one to the next to the next. And then you might get to, you know, do a gig at a big company to get some of that big company kind of experience and seasoning.

And you go back to startups, a lot of people who have the big company experience you do would find a startup restraining, right. Because you can't, you don't have, you're not a big company, you're a startup. Right.

But was by definition. But I'm, I'm glad to see you made the switch and came over to the dark side here and, but I, I couldn't think of a better old place to be. Um, Yeah, totally giant.

I mean, it's, it's so scary, but scary, exciting, scary. If that, if that makes sense, Abs. It's, it's like every day is an adventure.

And I look, so this is not a venture backed company here, tech Strong. I, I did it myself. And first one I've done without other people's money and a long, long, long, long time.

But every day I love coming in because it's, it's fun and it, you know, we're not big media company, but I, I love what I do. Yeah. But listen, anyway.

Yeah, absolutely. Jeremy, let's talk about observe. You said it's about five and a half years old.

Kinda what, what's the mission there? What do you guys do? Yeah, the thing that, um, I, I was inspired by a couple of things, really.

The, the, the sort of the, the problem we're trying to solve and then, and then the approach that the founders had taken. And, but the space, I've, I've always been on the product side of things and, and certainly back when I was at Oracle, I, I, I really helped people build applications on top of Oracle. So I've always been into application development.

And what struck me is that today, actually, the way people build applications today, distributed applications is very, very different and can be quite complicated, especially when things go wrong. And, um, the idea that, you know, you are, you are pushing new code into production every day, uh, leads you to seeing things in production every day that you've never seen before. Things, things go wrong in weird ways that you've never seen before because you have new code and everybody says, oh yeah, I don't test in production.

But really we do. And the reason is, with mobile apps, you can't reproduce the production environment in text. And so everybody to a certain extent is testing in production.

Um, and so observability, the idea is that can we collect all the telemetry data, all the digital exhaust fumes that come from the application and the infrastructure and make sense of them such that when something goes wrong, you can pinpoint, oh, the problem is here. And, and so that to me just seemed like a no brainer that everybody was gonna need, because today, at least most businesses, whether they're they're born in the cloud or whether they're sort of a, a traditional business, that that's becoming digital, um, that they're conducting business directly to their customers through mobile apps, websites, and that, that, that, that digital experience is a proxy for the business. So if, if, if bad things are happening, you've gotta get to the bottom of that pretty quickly.

So pretty inspired about that. And then the approach the founders took, um, I've been, I've been on the board of Snowflake since 2015 and obviously loved Snowflake and the approach to revolutionizing the world of databases and the idea of observe is why don't we put all of this telemetry data, all these digital exhaustions, why don't we put 'em in Snowflake, put them in one big database? Because if you've got the data in one place, it's much easier to answer questions and make sense of it.

And it, it struck me that all of the other vendors in the space have got discreet databases for logs and discrete databases for tracers and discrete databases for time series. And our approach was like, well, look, if we put the data in one place and we see a spike in CPU utilization, we can go see the spans and the application for that spike, and then we can go see the logs for it. And so it would be much easier to investigate, which is really what observability is all about.

I agree. I agree. Um, so let me, let me play the dumb reporter here.

Explain to me the difference between just putting it all in a single database versus a data lake. Right? A data lake is the cool term Yeah.

That you hear bandied about, but my thought was a data lake means I have multiple databases that I can access. It's part of this lake. Yeah, it's a great question actually.

The, the, the, the amazing thing about Snowflake is it really was the first database that would use as its underlying storage. Um, initially AWS S3. Now obviously they're on Azure and, and, and g ccp.

So, so Snowflake, the only storage it uses is, is, is a bulb saw on, on AWS obviously S3. So in my mind, at at least, yeah, like I use the word like database and data lake interchangeably. I think where the data, the telemetry to get data gets done when we ingest it is into S3, which is the data lake.

And then Snowflake picks it up for that and, and think of Snowflake essentially as that query engine over and above the data in that data lake. Um, and then what, what observe does the magic of observe is we obviously, we look at the data in the lake. We, we, we structure the data, we relay the data, and we make it faster and easier to navigate and to query, because this data in its raw form is, it's all machine generated.

It's impossible for humans to understand. And, and it takes a long time to query it because it's complicated and there's a lot of it. And so we, yeah, we, we sort of transform it, make sense of it, and then we use the Snowflake query engine to answer questions for the user Bringing order to chaos.

Yeah. A big part of that, there's a lot of chaos in, 'cause the, the, the, the, the, the ultimate truth of what an application is doing is, is in the telemetry data at a mix. It's in the logs, right.

Or it's in the spans and it's sort of unfettered machine generated data. So, you know, it's the truth. The problem is, is it's not that understandable.

And so we try and make sense of it for humans so we can get to the bottom of problems. Got it. Good stuff.

Um, Jeremy, you guys recently announced a really healthy, especially in today's world, this ain't Covid times anymore, $125 million series B. And I gotta tell you, that's probably the biggest series B I've seen in a year or 18 months, maybe more, right? Because that we're just not seeing big numbers like that anymore.

So first of all, congratulations. Thank you. Second of all, how'd you do it?

Well, it, it, it helps to have good numbers, right? Mm-Hmm. We, we, We, when the clock back go, go into our last fiscal year, which we closed at the end of January, um, we were a little bit concerned because yeah, if you cast your mind back to the end of 2022, um, there, there were sort of profits of doom on the economy.

Everybody thought the economy was gonna go into a recession. Um, obviously the tech world was been turned on its head because, um, you know, a lot of companies had been funded by cheap money. Yeah.

Interest rates to rising money supply was tighter. And, and we as a company, we did not have the market fit with that product, right? We hadn't found that groove, uh, that we could repeatedly sell the products, uh, into.

And so we were a little bit worried and we, we went through a process, uh, that took about nine months of just completely redoing the UX of the product. Um, I had a great head of engineering from Stripe, a guy called Chi Gen, uh mm-Hmm. And he was the VP of payments, uh, VP of engineering for, for payments at Stripe.

Yep. And he was like, Hey, the back end of the product's great, the front end, we gotta redo it. And you know, Stripe obviously have got a lot of good attention to detail on developer experience, right?

That that's sort of that thing. And so as we rewrote the UX and we started to roll it out, we, we started to find that market fit and we saw the breakout in the numbers. And so, you know, our, our revenue, uh, pretty much tripled year over year.

Um, a RR and then, yeah, the, the, the net revenue retention, which is usually a sign of how sticky, how much people like the product. If I bought a double last year, then this year, if I buy like $2 70 cents, then you know, your net revenue retention will be 170%. And, and so we, which is around about where ours is, 130% is sort market leading.

And so we feel like we got the product last year, like into the, the strike term, lemme put it that way. And so that showed up in a RR, it showed up in the NRR, it showed up in the, in the, in the, in the A CV. And so I think when you're raising money, um, obviously demonstrate in that you've reached market fit, demonstrate in that the product is starting to break out.

Um, and, and, and that, hey, if we keep going, potentially we can double a triple again next year. I think that that's what investors like. Well, congratulations, man, that, that's a really impressive number.

As I mentioned, one of the things I want to talk about with that though is, uh, a new investor, um, snowflake themselves. Now hearing you're on the board there, that probably didn't hurt. But, but the fact that, you know, you're, you're using Snowflake extensively in your product as, you know, as part of that backended, the database, if you will, for the product.

Um, I mean, I could see why it, it's a smart move for them. Yeah. I, I think as well, I mean, you mentioned earlier, look, the venture environment is very, very difficult, right?

I think it's maybe starting to turn the corner, but as I mentioned earlier, there are a lot of companies that have been funded at big valuations that, that need ongoing funding and money supply is not what it used to be. And so what you're finding is that the traditional venture crowd are sort of sitting on the hands, right? And so the strategic investors, and we have a, a couple of those on our cap table, capital One, and, uh, snowflake, they, they obviously become very interesting because they, they tend to take a, a, a longer term view, right?

And, and they, they tend not to have a huge portfolio of companies that, that some of these traditional venture firms have. So Snowflake, I I was delighted not, not just because, you know, I'm a, I'm a huge fan of the company, but we're doing a lot of work with the Snowflake sales team right now. They, they've probably got a big presence with a lot of enterprise accounts, uh, to date, um, observe.

We've largely sold to sort of small to medium sized companies, SaaS companies, companies that look like ourselves. Um, but, but again, last year we, we had a couple of enterprise accounts that we won, and we want to do more of that. And so Snowflake investing it, it sends a good message to the Snowflake sales team, like, Hey, these guys are doing so good.

They're On the home teams, We believe. Yeah. And as you, I'm sure, you know, enterprise sales teams can be, uh, quiet, you know, emotional.

And so if you've got some good positive news, you get the positive emotion, uh, when, you know, when we engage with them. So I, I would delight to do Snowflake as a, as a partner. Yeah, no, I, I could see Right.

Things in your future with that, right? Mm-Hmm. com days.

I, I worked, I helped put together a company. We went public, we were in early, what they called a SP we're actually a big, we were, we were hosting hosting Oracle apps in the nineties before there's a cloud, before there's multier, you know, multi-tenent, all that stuff. Yeah.

But we were also Dell host. I, I did, I was the biz dev corp dev guy. I did a deal with Dell, where we were Dell host and, you know, working with Michael.

And at that time, the whole Dell server unit was fairly new, right? Mm-Hmm. They had just really broke in, had pure PCs into servers, and there was good and bad.

There were two sides to the coin. One side to the coin was, look, nobody sold stuff like Dell did, right? My sales team selling the product, Dell's team selling the product, their add-ons added an extra 35% to the, to the bottom line versus what we could sell it for.

Um, on the other hand though, it prevented us from doing deals at the time with Sun. And this before Dell owned DMC, right? And, and I had EMC and IBM storage kinda deals.

And I, it was, I'll tell you sometime over beer or something, we used to, depending who was coming to our data centers on any given day, we would switch out the machines that were in front, right? From Spark Machines to Dell Service to IBMs, the hps. It was, it was nuts.

But, so there is a little bit of that lock-in, if you will, where people say, well, I'm not a Snowflake customer. And, and these guys are, you know, they're in with Snowflake. How do you combat that?

Yeah. The, I think the good news is that our traditional buyer, they, they typically don't know Snowflake, and they, they never see it. It, um, maybe the best analogy I can give you, back in the day when people bought SAP, they didn't really know Oracle was under the cupboards.

You know, the, the CFO had no idea. And I think it's the same with observe. Like we, we sell to a head of DevOps or SRE and all the, they, they use Observe and, and yeah, the, the person behind the curtain storing the date with Snowflake, but they never really interact with Snowflake directly.

And so what, and, and then, so that's one that, that is 95% of our customers and then 5% are, are, are like very aware of Snowflake, and they tend to be the larger enterprises. And the, the nice thing that we've done in that model is we've said, and, and this is part of the, the Snowflake partnership, is, is look, um, in that, in that environment, the customer's got a choice they can deploy on our multi-tenant SaaS environment, in which case they'll never see Snowflake, or we can pint observe at the, at their Snowflake tenant. And so the, the thing that they like, and I think the Snowflake sales team like, is all of the snowflake that the Snowflake sales team has sold into their accounts, we can burn down the credit sold using Observe because we use the Snowflake credits that they've sold in, and they're not using the Snowflake credits on our multi-tenant SaaS environment.

Right? So that, that tends to be the focus of the go to market with the Snowflake sales scene, enterprise accounts, and then what Snowflake would call connected apps. Meaning we're gonna connect, observe, um, to, to the, the customer, snowflake tenant.

And I think importantly for the Snowflake sales team, we're gonna use up all the credits that they've sold in which they're getting paid on, which I mean, obviously they love that. Love it. Jeremy, we don't have a lot of time, but there's one more area I wanted to hit on, if you don't mind.

Yeah. You know, I'm just back, I was out in, well, I'm back now about two weeks, but I was out in Paris at CubeCon. Well, then I hopped around Europe a little bit, but I was in Paris with Q Con and of course, observability, right?

Open Telemetry is the second biggest project at CNCF. So much of what we see around observability seems to be a lot of vendors building on top of Prometheus Open telemetry, open source projects that are really good at gathering data. And then, um, these companies then try to do the analysis and add the value by how they analyze and, you know, how they slice and dice that data.

I didn't hear you mention open source here or any of those projects. Are you guys on a different path or is that part of the underlying infrastructure as well? Yeah, Uh, yes and no.

So, uh, open Telemetry we're big fans of, um, the nice thing about Open Telemetry is the data comes to you structured. Mm-Hmm. So once you've ingested the data, it's in a nice structured format.

Um, there's less transformation for us to do. And therefore it's, it's easy to query. The, the reality is though, that that is probably 1% or less than 1% of the world's telemetry data.

Um, and certainly when you get to the high end, it, it's, it's all logs and metrics and the logs of, uh, uh, are somewhat unstructured or the nitty semi-structured JSO. Um, and so what we, when we set out to build observe, actually we, we were going down at the time, the open tracing path, actually pre Uhhuh Open Telemetry. Sure.

And then we, we talked to a bunch of prospects and we couldn't find anyone who was using it. And so we're like, okay, why, why don't we do this? Why don't we be very permissive with, uh, respect to the, the data we can ingest, but then let's build out the visualizations and the workflows for log analytics and for monitoring first, and then let's do the tracing last.

'cause we, we just felt it wasn't ready for prime time. Right. And, and anyway, wind the clock forward, and I'm really pleased we took that approach because we can sort of go to the customer and say, look, give us what you've got.

If, if, I know you might want, if you go in Open, open Telemetry, great. But let me guess, you've got years of unstructured loads. Yes.

Okay, well give us that. We'll help you do a better job of that. We'll save you a bit of money, and then look, as the open telemetry comes online, we we can take that too.

There's just, there's actually less work for us to do when that's ingested. And, and we do rely on open source collectors. We made a decision in the company to, to not put intellectual property into agents.

We were gonna use open source agents, telegraph, fluent bit open telemetry collector. But we're, but we're not an open source product per se. We're not like Elastic or Grafana.

And I think there will be a chunk of the market that goes that direction, but I think there's also a chunk of the market who doesn't wanna buy a bag of rocks and assemble it themselves. They want an outcome that they, they want to spend their time on the analytics not assembling the open source stack. And, and, and that's where we come in.

I'm gonna have to remember that one. A bag of rocks and put it together yourself. I love it.

Hey Jeremy, we're gonna find out of time. You know, one thing we didn't tell people though, for people wanting to get more information on observe, what's the website? Yeah.

com, um, the Observe Inc. On the end of observe is, is important. Um-Huh.

And by way, you can send up for a free trial within 30 seconds, you can take a look at the product. Fantastic. Thank you so much for coming on here today.

We hope to hear more about Observe Soon. Again, congratulations on this series B We is a great story. I'm looking forward to seeing how it, it continues to evolve.

All right. Thanks Jon. All right.

Jeremy Burton, CEO of Observe here on Textron tv. We're gonna take a break. We'll be back with more in a moment.