(upbeat music)
>> Hey, welcome back everyone to KubeCon's coverage
and CloudNativeCon with theCUBE.
I'm John Furrier, your host, with David Nicholson,
CUBE analyst, Cloud analyst, co-host.
We've got two great guests. CUBE alumni,
Jerry Chen, needs no introduction.
Partner at Greylock ventures, has been on theCUBE
many times, almost like an analyst here.
It's great to see you,
>> (laughs) Thanks!
(David) Kind of like a guest analyst.
And Martin Mao, who is the CEO
and co-founder of Chronosphere. Just closed
a whopping $200 million series C round
business is booming. Great to see you. Thanks for coming on.
(Martin) - Thank you.
(David) - Hey, first of all, congratulations
on the business translations.
>> Congratulations
>> Thank you. Thank you so much.
>> Who would have known that observability and
distributed tracing would be a big deal.
Jerry, you predicted that in 2013.
>> I- I- I think we predicted jointly cloud
was going to be big deal with 2013, right?
And I think the rise of cloud creates all these markets
behind it, right. This, you know,
I always say you got to ride a wave bigger than you.
And, and so this ride on cloud and scale
is the macro wave and you know, Martin and Rob in
Chronosphere they're just drafted behind that wave.
Bigger scale high carnality more data, more apps.
I mean, that's, that's where the pucks gone.
>> Yeah. Martin, all kidding aside. You know,
we joke about this because we've had conversations where the
philosophy of you pick the trend is your friend that you
know, is going to be happening.
So you can kind of see the big waves coming,
but you've got to stay true to it.
And one of the things that we talked about is what's the
next Amazon impact going to look like?
And we're watching the rise of Amazon. You know,
if this continues a new way to do things is going to be upon
us. Okay, you got DevOps now, Cloud Native,
but observability became really a key part of that.
It's like almost the, I call it the network
management of the cloud. It's like in a new way,
you guys have been very successful.
There's a lot of solutions out there. What's different?
(Martin) - Yeah. I'd say for courtesy, there's
really three big differences. The first thing is
that we're a platform. So we're still on
observability platform. And by that,
I mean, we solve the problem end to end.
If you think about observability and monitoring,
you want to know when something's wrong,
you want to be able to see how bad it is,
And then you want to better figure out what the root cause
is. Often, there are solutions that do a part of that,
that that problem might solve a part of the problem really
well for a platform that does the whole thing.
End to end that's that's really the first thing.
Second thing is we're really built for not just the cloud,
but cloud native environments.
So microservices architecture on container based
infrastructure. And that is something that we,
we have saw coming maybe 2017, 2018. But luckily for us,
we were already solving this problem at Uber.
That's where myself, my co-founder were back in 2014, 2015.
So we already had the sort of perfect technology to solve
this problem ahead of where the,
the trend was going in the industry and therefore a
purpose-built solution for this type of environment,
a lot more effective than a lot of the existing ones.
(John) - It's interesting, Jerry, you know,
that you invest in companies that have their problem,
that they have to solve themselves as the new thing,
versus someone says, Hey, there's a market.
Let's build a solution for something. I don't really know.
Well, that's kind of what's going on here, right?
>> It's the reason why we love founders
like Martin or Rob that come out with these hyper scale
comes with Uber. Like we say, they've seen the future.
You know, like they were at Uber,
they looked at the existing solutions out there trying to
scale Promethease or you know, data dogs and the vendors.
And it didn't work. It fell over.
It was too expensive. And so Martin and Rob saw the future,
like this is where the world's going.
We're going to solve it. They built M3,
it became Chronosphere. And um, so I don't take
any credit for that. You know,
I just look fine folks that can see the future.
And that was Rob and Martin.
(John) - But they were solving their problem.
No one else had anything. There's no general purpose
software that managed servers you could buy,
you guys were cutting your teeth into solving the pain you
had at Uber. When did you guys figure out
like, oh, well this is pretty big.
(Martin) - Probably about 2017, 2018 with a
rise in popularity of Kubernetes.
That's when we knew, oh wait, the whole world is
shifting to this. It's not, no longer relegated
to just Uber and the big tech giants of the world.
And that's when we really knew, okay,
the whole, the whole whole world is shifting here.
And again, it's sheer blind luck that we
already have the ideal solution for this
particular environment. It wasn't planned.
It wasn't what we were planning for
back then. But yeah, get everything sort of lined up.
(john) - It makes a lot of difference.
When you walk into customers, say we had this problem,
I can empathize with you. Not just say we got solved.
>> Exactly.
>> Jerry, how do they compete in the cloud?
We always talk about how Amazon and Azure want to eat up
anything that they see that might, you know,
something on AWS, this castle in the cloud opportunity here.
>> Castle in the cloud. I mean, you know,
we talked last time about how to fight the
big three, Amazon Azure and, and Google.
And I think for sure they have basic offerings, right?
You know, Google launched Stackdriver years ago,
they've done basic rebrief offering, basic modern
offerings. I think you have like basic, simple needs.
It's a great way to get started,
but customers don't want kind of a piecemeal solution all
the time. They want a full product.
Like Datadog shows a better user experience,
but full product is going to, you know,
the better mousetrap the world beat a path to your door.
So first you can build a better
product versus these point solutions.
Number two is at some scale and some level of complexity,
those guys cannot handle like the demanding users that
Chronosphere is handling right now, right?
The door dash, the world. And finally you don't
want the Fox guarding the hen house.
You know, you don't want to see like Amazon monitoring,
you can't depend on Amazon service monitoring your Amazon
apps or Google service monitoring, Google apps,
having something that is independent and multi-cloud
that can do all things Martin said, you know, see a triage,
and fix your issues is kind of what you want.
And that's where the market's killing.
So I do believe the cloud guys will have an offering the
space, but in our castle and cloud research, we saw that,
yeah, there's a plenty of startups being funded.
There's plenty of opportunity.
And the scoreboard between Splunk Datadog and all these
other companies that there's a huge amount of market and
value to be created in this space.
(David) - So at, at, at the time when you, you know,
necessity is the mother of invention, you're at Uber,
you have a practical problem to solve. And you,
you look around you and you see that you're not the only
entity out there that has this problem.
Where are we in that wave?
So not everyone is at, cloud-scale not everyone
has adopted completely Kubernetes
and cloud Native for everything.
Are we just at the beginning of this wave?
How far from the beach are we?
(Martin) - We think we're just at the beginning
of this wave right now. And if you think
about most enterprises today, they're still using,
and they're not even or perhaps in the cloud at all right.
Are you still using perhaps APM solutions on,
on premise? So if you look at that wave, we're just at
the beginning of it. But when we talked
to a lot of these companies and you ask
them for their three year vision,
Kubernetes is a huge piece of that because everyone wants to
be multi-cloud everyone to be hybrid eventually.
And that's going to be the enabler of that.
So we're just in the beginning now,
but it seems like an inevitable wave that is coming.
(David) - So obviously people evaluated that
exactly the way you're evaluating that.
>> Right
Thus the funding,
>> Right
Because no one makes that kind of investment without
thinking that there is a multiplier on that over time.
So that's pretty, that's a pretty exciting place to be.
(Martin) - Yeah. I think to your point, a lot of companies
are running into that situation right now,
and they're looking at existing solutions there. For us,
it was necessity because there wasn't anything out there.
Now that there is a lot of companies
are not using their sort of precious engineering
resources to build their own, they would prefer
to buy a solution because this is
something that we can offer to all the companies.
And it's not necessarily a business differentiating
technology for the businesses themselves too.
(John) - So you guys have distributed tracing
in the observability platform. That's the news.
And you mentioned, you've got this, a good bid.
You do some good business.
Is scale the big differentiator for
you guys? Or is it the functionality?
Because it sounds like with clients like
door dash, and it looks a lot like Uber,
they're doing a lot of stuff too.
I'm sure everyone Instacart, other people doing the
same kind of thing. That scale,
massive amount of consumer data coming in on the edge.
(Martin) - Yeah
Is that the, the differentiation or do you work
for the old one, you know, main street enterprise?
(Martin) - That is a good part of the differentiation
and for our product thus far before we had
a distributor tracing for monitoring and metric data,
that was the main differentiation is the sheer volume of
data that gets produced so much higher.
I'm really excited about distributor tracing because that's
actually not just a scale problem. It's,
it's a space that everybody can see the potential
distributor tracing yet. No one has really
realized that potential. So our offering
right now is fairly unique. It does things that
no other vendors out there can do.
And we're really excited about that because we think that
that fundamentally solves the problem
differently, not just at a larger scale.
(John) - Why I got you here because you're an expert.
What is distributed tracing?
(Martin) - Yeah, it's a great question.
So really, if you look at distributor tracing,
it captures the details of a particular request.
So a particular customer interaction with your business and
it captures how that request flows through your complex
architecture, right? So you have every detail
of that at every step of the way.
And you can imagine this data is extremely rich and
extremely useful to figure out what the
underlying root causes of, of issues are.
The problem with that is it's very robust
it's a lot of data gets produced.
A ton of data gets produced, every interaction,
every request. So one of the main issues
in this space is that people can't
afford cost effectively to store all of this data. Right?
So one of the main differentiators for our product is we
made it cost efficient enough to store everything.
And when you have all the data, you have far better
analytics and you have far clear antics
(John) - Machine learning is better.
Everything's better with data.
(Martin) - Exactly, yeah
What's the blind spot out there for customers that
cybersecurity is always looking for corners and threats.
Some people say, it's not what you don't
It's what you don't see that kills you.
That's, that's a tracing issue.
That's a data problem. How do you see that evolving
in your customer base or clients trying to
get a handle of the visibility into the data?
(Martin) - Yeah I think right now, again, it's,
it's very early in this space that people are just getting
started here and you're completely correct where, you know,
you need that visibility. And again,
this is why it's such a differentiator to have all the data.
If you can imagine with only 10% of the data or 1% of data,
how can you actually detect any of these particular issues?
Right. So data is key to solving that problem.
(john) - Oh, well, great to have you guys
on expert and congratulations on the funding.
Jerry, Good to see you take a minute to give
a plug for the company. What do you guys do?
And actually close around the funding,
told you a million dollars. Congratulations.
What are you looking for for hiring?
What are your milestones? What's on your plan plan.
>> Yeah. So with the spanning, it's really to,
to continue to grow the company, right?
So we're sort of hiring, as I told you earlier, we are,
we grew our revenue this year by,
by 10X in the 10 months of this year, thus far.
So our team hasn't really grown in 10X. So, so we,
we need to keep up with that grid.
So hiring across the board on engineering side,
on the go to market side, and I just continue to meet that.
(John) - And you have a headquarters,
you're virtual, if you don't mind,
>> We're all completely distributed now.
We're mostly in the US, I have a bunch of folks in
Seattle and in New York, however,
we're going completely remote.
So hiring anywhere in the US anywhere in Europe at all.
>> Jerry, while I got you here,
what's your investment thesis.
Now you've got castles in the cloud, by the way,
if you haven't seen the research from Greylock,
Jerry and the team called castles in the cloud,
you can Google it. What's your thesis now?
What are you investing in?
>> You know it is.
It is hard to always predict the next wave. I mean,
my job is to find the right founders,
but I'd say the three core areas are still the same. One is
this cloud disruption to Martin's point we're
so early days the wave, I say, number two,
there's vertical apps, different SAS applications
be finance, healthcare construction, all are changing.
I think healthcare, especially the past
couple of years through COVID,
we've seen that's a market that needs
to be digitized. And finally, FinTech,
we talked about this before everything
becomes a payments company, right?
And that's why Stripe is such a huge juggernaut. You know,
I don't think the world's all Stripe,
but the insurance, payments, you know
stuff and crypto or whatever. I think fintech
still has a lot of, a lot of market to grow.
(John)- Making things easier as a good formula right now.
If you can reduce complexity, it
makes up as easy in every market.
You're going to, seems to be the formula.
>> What's the line, "the next great thing is making
today's crappy thing better". Right? So the next,
the next page shows making this cube crappy thing. Yeah.
>> We're getting better we're working every day
we're on our 11th season or year
we're calling things seasons now,
episodes and season for streaming.
>> I can't wait for all the seasons to
drop on Netflix, and just binge watch them all.
>> theCUBE plus and NFT's for our early videos.
They'll be worth something because they get not that good,
Jerry of course. You're great.
(Jerry) - Thank you, Thanks guys, Thanks for having us
>> Thanks for coming on.
A CUBE coverage here in a physical event, 2021
CloudNativeCon + CubeCon I'm John Furrier
and Dave Nicholson. Thanks for watching.