Today on Modern Digital Business, I’m starting a new series on the podcast—the series is called ModernOps. I’ll be hosting this series along with a good friend of mine, Beth Long, who is the Head of Product at Jeli.io, an incident analysis company.

This will be our first of a series of episodes. In this first episode, we will be talking about how the experience using the cloud varies for large companies vs small companies.

Today on Modern Digital Business.

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Transcript
Lee:

Today and modern digital business.

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I'm starting a new series on the podcast.

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The series is called ModernOps.

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I'll be hosting this series along with a good friend of mine, Beth

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Long, who is the head of product at jeli.io, an incident analysis company.

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This will be our first of a series of episodes.

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In this first episode, we will be talking about how the experience

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of using the cloud varies for large companies versus small companies.

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Are you ready?

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Let's go.

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My co-host for this series is Beth Long.

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Beth is head of product at jeli.io, an incident analysis and management

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platform that combines comprehensive data from multiple sources to help identify

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problems and proactive solutions.

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Beth and I worked together a New Relic where Beth was heavily involved in a

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product operational management of a highly scaled and fast-growing application.

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Beth has a strong background in IT operations.

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Given my cloud and IT management expertise and her IT operations expertise, Beth

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and I joined together to create the series of episodes we called ModernOps.

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middle of the pandemic, but we never published it, until now.

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In this first episode, Beth and I are talking about AWS and how

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using their offerings and services changes based on whether you're

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a small company or a larger, more established company or an enterprise.

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I hope you enjoy.

Beth:

So what made me think about this in initially is that when

Beth:

I worked at New Relic, I was on the build and deploy tools team.

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We worked somewhat directly with AWS.

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There were things that, that we owned and managed and got pulled into, but also

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watched a lot of other teams that, that owned a lot more surface area in AWS.

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I got interested in thinking about two, two different aspects of this question.

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One is.

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How organizations that are operating at different scales, think about

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actually using the, the AWS offerings and, and the sorts of things that

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they're going to be drawn to.

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And then also some of the, some of the organizational constraints

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that can influence the decision about how to use AWS services.

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So in the first category, thinking about things like: if you are already

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in a data center and you're looking at moving into the cloud, you're

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going to have a progression that you're gonna be moving through.

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And if you have a lot of services, you're going to need to make a jump to

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a more fully featured cloud environment.

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Whereas if you're a very small organization and you're spinning

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up brand new services, you can try things out incrementally, and there's

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a much different path into the cloud.

Beth:

And that's one thing that intrigues me.

Beth:

And I know you've talked about cloud transformation a fair bit.

Lee:

Yeah.

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And that's actually a good point.

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One of the things I actually did a course for O'Reilly on is

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planning for a cloud migration.

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And one of the things I talk about in there is the critical mass, right?

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You know how much you need a certain amount to move to the cloud at once

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yet you don't wanna move anything until you've tested something.

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And so how do you make that transition?

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And, and actually one of the things I found when I did some research and talking

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to do different customers about this is a lot of companies that when they first

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started using the cloud, they didn't do it with a project and with a critical mass,

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what they did is they had, team Y off in the corner, the nomad team that always

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did things a little bit cockeyed anyway.

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They went off and they decided to try something new in the cloud and just did it

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and tried it and had some success or some failures and, and management kind of turns

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a, a blind eye to those teams because they always do good stuff and see what happens.

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And sometimes what happens is they are the ones that create enough of a

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critical mass that makes it acceptable.

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And, and often they're the group that turns into the Cloud Center of Excellence.

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They won't call it that necessarily, but that's really what it is.

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That the group that, Hey, you we're, we now decided that we're gonna bring

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all of our applications to the cloud and everyone go talk to those guys.

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They know how to do it.

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It's not necessarily the best formula for success.

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But a lot of the larger companies will end up doing things that way.

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So in many ways, it's like the startup model where it's like a, let's just

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test it out and see what happens.

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And we can make some mistakes, not a problem, but not every company does that.

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They, the companies need that maverick team for that model to work.

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And in a lot of company cultures there isn't that maverick mentality.

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and for those companies, like you say, it's then a matter of, okay,

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you have to do a leap of faith and a leap of faith is something, those

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sorts of companies just really aren't familiar with and how to make happen.

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So that's always a challenge.

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So how so in a company like jeli.io where, you know, you

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didn't have the migration, right?

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You just all into the cloud from the very beginning.

Beth:

Right

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was it different than that?

Beth:

Yeah.

Beth:

So with Jeli.io, first of all, there's the, the matter of just there's the,

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the factors of both size and timing, the fact that we were starting to

Beth:build our services out in:Beth:

It was already established and we could just, just walk right into it.

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But yeah, the, with jelly, the decision process was like, We're very small.

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We don't have a team, a big team of infrastructure engineers to

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even run things them, themselves.

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And so AWS, let us go much faster because, obviously, we were able,

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able to just walk up and provision something with a click of a button.

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And so it was a matter of, okay, what's the smallest footprint that we can have

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just because we're, we're bootstrapping our entire product and how can we, what's

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sort of the most tried and true off the shelf thing that we can build in AWS.

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And so as we started to mature, We would expand what we were doing

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in AWS, but we had, uh, a lot more optionality in what we were building

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because we were able to select from this wide set of managed services.

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And we knew that with just two or three engineers, We could still consider,

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for example, we're not deploying on Kubernetes yet, but we can talk about

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it because we don't have to have full expertise on this entire technology.

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We need to have enough expertise to manage the managed service.

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So AWS lets you limit your expertise in certain areas.

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And still allow you to move forward.

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Yeah.

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And I can relate to that too.

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And even a smaller company standpoint.

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SaaS then, but the SaaS application for managing boy scout websites.

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And I built that application and actually turned it into a full ended up, building

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it into a corporation and had real revenue, taxes and all that sort of stuff.

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It ended up being a, a pretty, pretty big thing, not enough that I could do full

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time, but it was, it was a big thing.

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But over the course of many years, that grew up into that.

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But when I first started, it was like, it was a server that was in my home

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that was connected to my home internet, that I had to do an upgrade on to

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make sure I had enough bandwidth and hope they didn't yell at me too much.

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That's the way it started.

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And I had to do, I had to know a whole lot about a whole lot of things

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just to get that up and running.

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There's just no choice.

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And then this whole idea of being able.

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Buy a server or rent a server from some managed provider that would sell

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me one server was a fantastic idea.

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And once I could afford that one server, this would all be great.

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It was, you know, a very small setting, but you know, then when the cloud started,

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it was like, oh, this solves everything.

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This makes everything so much better.

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And that's one of the reasons I got very interested in AWS and

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ultimately went to work at AWS.

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The, the whole idea that all of those things that were hard for me to do that

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took all this time and energy to do.

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And I was before that, I was at another startup that also had the same problem.

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They said they had the server rack in the back room and hoped it didn't have a power

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outage because I wasn't that good of a battery backup and all that sort of stuff.

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And, and imagine how much easier that would have been if the cloud

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was prevalent then and how to do that startup, then you jump forward then to.

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to nowadays in the types of situation that for instance like Jeli.io is in,

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and it's so much easier because you don't have to worry about any of that.

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You say, I need one of these and these and click buttons to get

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them and pay for them, et cetera.

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I, I'm also working with some other startups now and in my current role

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that are in the same situation where it's like, they're trying to decide what

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they want their operations budget to be.

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And imagine being able to say that sentence, they want to, they're gonna

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figure out, decide how large they want their startup operations budget to

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be, but they essentially can do that.

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They they're making the trade outs of what type of footprint they wanna

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have for their first deployment versus how much they wanna invest in.

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And then they can relatively easily, because it's just a sheer matter of

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changing a slider of how many servers in each area and all that sort of stuff.

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That's a whole lot different situation than it used to be and makes it

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a whole lot easier for companies like, like Jeli.io to get going.

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Now, how does that differ then from New Relic now there's New Relic as a startup,

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which was pre-cloud and then there's New Relic as it currently is, which involves

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both cloud and non-cloud offerings.

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And I'd love to get your perspective on both sides of that.

Beth:

That's such a great question.

Beth:

And as you've been talking, it it's occurred to me that when I, when we first

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started talking, we were comparing the scale of the organization, but then what

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I really was honing in on had less to do with scale and more to do with age

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and the age of the services themselves.

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And you mentioned a few minutes ago, you're with AWS, you're

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essentially outsourcing expertise.

Lee:

Right

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The fact that when you've got a mature set of services, they're

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intimately coupled with the kinds of infrastructure that they're built on.

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And so moving that is, is into a different kind of infrastructure

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ecosystem is, can be very challenging.

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One of the things that I worked through in.

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So when did you start with New Relic?

Beth:started in very beginning of:Lee:

17.

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So you were there, three...

Beth:

Three and a half.

Beth:

Almost four years.

Beth:

Yeah.

Beth:

Okay.

Lee:

I was there about three years before that, so I was there

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a little bit over seven years.

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So yeah, when I started there, I was like employee number 98 or something like that.

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Yeah.

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the, the Portland office.

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Was lunchroom, a couple of offices and everyone, just, everyone sat around the

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lunch, the one lunch table for lunch every day, I've heard the stories.

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That was what the culture was.

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It was a great sounds.

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Great.

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I loved the early new Relic culture.

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It was a fantastic culture.

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Yeah.

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And so it was very much smaller sort of company.

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but back then it was, the cloud wasn't even a vocabulary item, even

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though the cloud obviously was big.

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I was, I moved to New Relic after leaving AWS and spending three, four

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years at AWS and doing lots of things.

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So it wasn't, the cloud didn't exist or wasn't established, but it wasn't part

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of, of the vocabulary of New Relic.

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New Relic was all about.

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We need.

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We're a heavy infrastructure centric company because data intake is

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everything and there's no way anybody could satisfy those needs for us.

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Other than ourselves, we need custom database servers that could handle the

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load to handle all of this data intake.

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The vocabulary of the cloud wasn't part of the vocabulary of New Relic

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at the time, it just wasn't there.

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Everything had to be, you know, tuned and, and the, we didn't

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have stock database drivers.

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We didn't have stock servers.

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We tuned them.

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We went to the servers in Chicago.

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We made sure they were tuned exactly the way we wanted to and connected the

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network exactly the way we wanted to.

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We felt that level of control over the hardware was critical to get

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the performance out of the, the hardware investment that we had

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in order to make things happen.

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And I remember having conversations with Lew very early on back when

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well, when insights was first starting to become a possibility for

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a product wasn't the product yet.

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But, and I, and one of the concerns he had was he didn't know how to size it.

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He didn't know how many servers to need.

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And I started talking to him about dynamic allocation and how to build out

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in the cloud and make all this happen.

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And he's, he was really intrigued by that, but it hadn't even entered his

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vocabulary to consider until then.

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And then they did, he did some calculations and did some.

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That and his, the conclusion was no, we can't make that

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work for performance reasons.

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It's just not gonna be there.

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And later on, of course it changed his mind on that, but it's

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interesting that the mindset there was just so non-cloud at all it,

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because everything had to be tuned.

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And so the data center was everything.

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The data center was value and that the data center was an asset to the company.

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And that was the mindset.

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I don't think there's very many companies now and I certainly would bet

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that Jeli.io is one of these companies that would ever say a statement

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that the data center is an asset.

Beth:

Exactly.

Beth:

And you're bringing up some of the things that, that, that are real

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differences that aren't necessarily about the age of your services and whether

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they're already on legacy hardware.

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One of the, obviously one of the huge differences between Jeli.io and a

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company like New Relic is the scale of not just the services, but the

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scale of, uh, the data that's that's flowing in is certainly New Relic's

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data ingestion is just staggering,

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astronomical

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it's astronomical, but then also a more mature organization.

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It's not just about the services being services and

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infrastructure being more mature.

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It's about the expectations and the, even the sales cycle.

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So new Relic's scale of data ingestion and the maturity of the expectations of

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the customer mean that when you're quote unquote outsourcing expertise to the

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cloud, I think one of the differences is, what we're building at jelly.

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We really can trust AWS.

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They're providing us with the level of control that we

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need over our infrastructure.

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At a place like New Relic, you need to develop a whole new

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expertise, which is how to manage all as, as deep down as you can.

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What's happening on your cloud infrastructure, which is a new kind

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of expertise, versus managing your own racks and machines in the data center.

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And so you have to develop this new set of expectations and tools and controls

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because when something goes wrong, you need to be able to troubleshoot

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in a whole new way in the cloud.

Lee:

Right.

Lee:

Right.

Beth:

So I think that is a big difference.

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And one thing that bigger organizations are thinking about whereas an organization

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like Jeli.io, we really can just for the scale of what we're currently doing

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and for the, the kinds of work that we need, our cloud services to provide us,

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we can just trust that a little bit more blindly, as opposed to New Relic, where

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you're dealing as you're talking about when you've got, uh, you're moving a bunch

Beth:

of data into containerized databases that are hosted in the cloud as part of your

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interim, your interim solution to getting fully into AWS managed data stores.

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There's a lot there that you need.

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You need extra expertise in house to be able to deal with that.

Beth:

When things go awry, when the performance problems crop up.

Lee:

And not to, you know, discount the Jeli.io customer

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versus the New Relic customer,.

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But when.

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You have a glitch that causes a problem.

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When you have five customers or 10 customers, it's very different than

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you when you have 5,000 or 10,000,

Beth:

exactly

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customers.

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And, and when those customers pay you large checks, you know,

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it's a very different situation.

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And so it's very scary to make any sort of operational change

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at any sort of complexity in an organization like New Relic.

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But it's a lot easier to do it in an organization like Jeli.io

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or Muskrat Software, which is the name of my scout manage company or

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any of those sorts of, of places.

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It's Hey, let's try this blam.

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You can do that and get away with it because the expectation is acceptable.

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That if there is a problem, the risk, the risk reward ratio is very different.

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The, the risk is very low, relatively speaking.

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What can go wrong is.

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Is is bad, but has less impact, but what can go, right and the value is huge.

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With an organization like New Relic.

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It's the exact opposite, tiny little things can cause cost major amounts

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of money, either in the form of real dollars or in lost revenue for lost

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opportunities or lost customers, whatever.

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So the risk is much, much higher and the rewards therefore have to be equally

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better, but often are more incremental and it's harder to see those benefits.

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So by far, it's obviously it's easier to consider a cloud-based

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solution when you're starting from scratch as a small startup.

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I don't think we're telling anybody anything new by saying that.

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I hope you enjoyed modern ops with my co-host Beth Long.

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ModernOps will be a regular series that will appear occasionally

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on Modern Digital Business.

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If you enjoyed this episode, let me know.

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So we can make sure to include more conversations

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like this in future episodes.

Lee:

You can reach me via the links in the show notes, or sign up for more