Open Standards in Data Observability with MyDecisive’s Ari Zilka

This is Textron tv. Hey everyone. Welcome back here to techron tv.

You know, I've got a actually first time on new company to introduce you to. Very excited. I want to introduce you to Ari Zilka.

Ari is the founder at CEO of a company called My Decisive. Uh, first of all, Ari, welcome to Tech Drunk tv. It's great to have you here.

It's great to be here. I'm super excited. Thank you for your time.

No, thank you. Thank you. We we're here every day.

You wear the warm I'm dragging you in. But anyway, Ari, its, I often like to do with these things. I like to give people a sense, you know, everybody once has the dream of being a founder, of starting their own company, of, you know, reaching the top of the mountain, raising money and exiting, or going public, and it's all very sexy.

But it, the, you know, the day in, day out, minute by minute, hour by hour is, is more like a war. Yeah. Um, and people always say, you know, how did he do it?

How did she do it? Give people a sense, maybe of, of your journey here, how you come to be the founder, CEO of my decisive. Sure.

Happy to. I am here through a long path, almost 30 years, that traverses open source, it traverses data management and it traverses large scale production systems. Um, I think one of my investors put it best, like the, the, the reason I was able to get funding to get where I'm at is that I wa I represent three experience sets.

Right. And I love this was, uh, one of the founders of one of the big VCs on Sound General Road. He's like, I like you, Ari, because you sold other people's software in your past.

So I used to work at like s Sapient, Pricewaterhouse, and do big consulting gig. Dude, Those are big, those are names I haven't heard in them. Big s Sapient.

Yeah. Then I, I sold other people's software. I built my own.

com, founding Chief architect. And, uh, so I built my own and I've run big production systems like Walmart. So, uh, at the time I was at Walmart, it was the number two e-comm site in the world.

Uh, it was, I think it still might be though, or it's gotta be the top five. It might be, It might be. It's, it's definitely top five.

But we were in year 2000 doing a billion page impressions a day. And that's really where I got my focus on data. So we were paying Oracle too much money.

I decided let's go op. I mean, we were mostly open source. I didn't decide, but, you know, I took the open source we were using and started bending it and twisting it to get to crazy scale.

Yeah. And, uh, that led to terracotta, which led me to hang out with the open source gang, which led me to Hortonworks, which led me to try my hand at vc. I was at Coastal Ventures as a partner for a while.

And so how did I get here? Uh, it's good news, bad news. The good news is work hard and you get rewarded.

Right. Do what love you get to do it for in the big time. The bad news is, it's sort of an in the family kind of thing.

Like, uh, I got a couple of jobs through Pure Grit and then ended up in a place where I was inside the family. And people are super helpful to me at this point. But you know what?

That, that's not unique either, either, right, right. Um, it is, it is about network. I mean, I look, we'd like to think we live in this meritocracy where, you know, everyone gets treated equal.

Every idea you send into a VC gets looked at. Mm-Hmm. You know, with due diligence and, and the time it deserves.

The fact of the matter is it's still a lot of who you know. Yeah. And it's not just a Silicon Valley thing, it's a, it's just a world of business thing.

Yeah, it is. And um, you know what I like about it though, because too many, so many people think, oh, founding a startup is something for 20 something or early 30 something euros. Right.

Because, you know, what is it? What is a guy in his forties or fifties? Mm-Hmm Mm-Hmm.

But yet, and I've seen studies on this, founders who are a little more seasoned, who are a little more experienced, who have the kind of resume you have can do a better job. Right. It's not like they, they suffer from a lack of ideas, but they also have a ton of experience.

Yeah. And you know, there was a time where some VCs, I think definitely, I don't want to use the word discriminated, but definitely preferred, you know, younger, first time entrepreneurs. Mm-Hmm.

But I think that's changed. I think people realize Mm-Hmm. Totally Right.

People with experience do it. So I, you know, I wasn't always on this side. I was on the outside of the camera a lot in my life too.

I've started several venture backed companies. I co-founded Right On. Um, and I've been interviewing and talking to entrepreneurs for a long time.

Everyone I know who started a company, Ari thinks that in some small way, their company's gonna make the world better. Mm-Hmm. Make someone's life better.

And they're passionate. They're passionate about what they're doing. What's the passion Behind my decisive?

Oh, wow. I love that question. So look, I have it defined my decisive, let me define it quickly.

Go ahead. Good. Yeah.

Super geeky terminology. It's composable observability in, in why in essence, observability just went through an inflection point. New Relic, Datadog, Dynatrace, big public companies, one of them went private recently.

Customers are paying millions of dollars a year each for this technology, this for this value prop, uh, observability. If you look at the debate about its definition, it's very much defining, uh, a state of a system, a quality of a system. I can observe without knowing the source code, without editing the system.

And that's very passive to me. I want to flip to active. Why do I wanna flip to active?

Now I can answer your question. So if, uh, I wanna flip to active, because data matters. Okay.

And specifically Oracle Cybase, these guy Postgres, these guy Ingress, these guys grew up taking control and making real easy, low cost, commoditized use of business, state sales orders, customer orders, inventory, state, they know financial transactions. They record the, the state of the money and the, the people and the processes. Then came Hadoop, big data.

I was part of that movement. We were basically taking this log data that Splunk made supervi popular. We were turning it into understanding value.

Right now, you have two pillars of data. You have the business processes in Oracle. You have the user behavior in big data in Hadoop, in data lakes.

And it tells you Ari's worth more than so and so, because he will tend to buy more and more and more from you. That analytic couldn't be done in Oracle. So here comes Hadoop.

There's a third pillar of data, and New Relic and Datadog missed it. That third pillar of data is telemetry data. It's the behavior of your systems.

So you've got your processes, you've got your users, and you've got your systems. And all you can do with observability vendors is push all this data to them and then chart it. You can chart very basic things about it.

Composable observability equals your ability to take over the data flow and turn it into answers for you. Like, is this piece of software secure as it's releasing to production? Is this system in the correct region in the cloud?

Or should I move it closer to my users? Where are my users? What is the latency right now?

If I move it, do I improve things? Should I scale up? Should I run bigger instances, smaller instances?

Can I run at 60% CPU or should I try 90% CPU? That would be a 30% savings. Composable, observability equals the, uh, equals the human ability to take over telemetry data, treat it as the third pillar of business, your system's behavior, and let it answer questions for you that no other data can answer for you.

So why am I passionate? Because I'm staring at an opportunity to create the next Oracle. I Love it.

Think, don't think small. Thank you. Don't think small.

Thank you. Now, but something a little different about your vision is it's a lot more open source based or open source friendly than let's say, uh, Oracle. It's even though Oracle, you know, let's not even get into their record on source.

Um, and, and that's an interesting thing. You know, you said that observability hit an inflection point and it did. But to me, you know, I look at some of the companies with the New Relic, uh, you know, all the, the companies you were mentioning, and though they may not have started as big open source advocates, the fact of the matter is Datadog, all of 'em, when you look under the hood, they're all using a lot.

They're based on a lot of open source. Yeah. I'm Gonna assume that my decisive is too, but you're just more open about it, right?

No pun intended. Um, you know, OpenTelemetry, Prometheus, all of these kind of mega projects that are just wow, you know, going bonkers. Yeah.

Um, is the main thrust of, of my decisive to help like pre-release to make software better at release? Or is it more sort of a traditional, let's say New Relic? com 10 years ago, right?

New Relic, AppDynamics, these were a PM application, you know, uh, uh, management, right? Yeah. Yeah.

We don't call them that anymore. Now they're all observability. But to me, there's that sort of observability, sort of the right side of the deployment line.

And then there's observability to the left side. To the left side. Yep.

What do you, where, where's my decisive? Like We are, we are focused right now on the right side. Um, mm-Hmm.

When I did my tour of duty in the observability space, I pushed really hard for shifting left, um, and giving clear visibility into the software lifecycle. And in fact, there are notions of grading teams like this team service is an A, that team service is a B. So that teams with an A Grade can move through software lifecycle automatically, and teams with a B grade have to have like human approval processes for releases and can only release at a certain rate so that they don't destabilize too much.

Uh, I'd like the left, uh, side of the equation. It's very powerful. Uh, but, you know, to, to answer why are we focused on the right, why are we going back after, as you pointed out, a PM observability?

Do it yet again. Why once more into the fray. Um, the answer is in the question you asked, right?

These guys, they were a PM. It was all about a language agent that quickly and very lightweight, sent a bunch of telemetry somewhere else, and then loaded it up on a graph. Now we have all this open source power open telemetry Prometheus.

People are assembling an alternative to vended observability by hand. Every single company is doing it. And they're jumping down a path of copycatting, of ended solutions.

So let me get things to graphs. I met with a company, and graphs is not the end game, man. We're in the world of ai.

We're in the generation of ai. You shouldn't be staring at a graph. You shouldn't be getting paged at night and being told, you know, you're slow.

You should be waking up in the morning reading the news from your system, telling you that it took a couple of autoscale and migration events and restart events to keep your system up or to prepare it for the next day. That requires much more mastery than these vented solutions are prepared to, to offer. They, they've made a mistake they built 16 years ago towards a charting and graphing and a human-centric incident response use case.

And that mistake has buried them down in the, in the muck of alerts and human paging and Slack interfaces. And they cannot now pivot to control and add value to the enterprise around OpenTelemetry and Prometheus. So I, I am basically saying open source has given me a foundation, a platform on which I intend to build this composable observability at my decisive.

You can have it for free. Why am I open source or open core? I have to be because no one knows that this is necessary.

Yet, once you hear it from me, uh, your audience hears it from me, they'll go, oh, I would love to join security feeds or vulnerability feeds onto my production deployment flow and say, whoa, yellow alert, this application has unsecure libraries in it. Are you sure you want this container image to go into your registry? True or false?

Yes or no Human, uh, interaction required just at this step that, that composition, I built a product that does that. I built a security product two years ago that took 20 people a year to build on one of these vendors platforms. That's ridiculous.

It's ridiculous. If it takes me a year as an expert industry internal player with five years experience and mastery of my platform and total control of the data, how are you as an end user supposed to crack open this black box platform and build it for yourself? It's impossible.

That's why this stuff turns into shelfware. Yeah. No one's starting these projects.

They're looking at the, the open source and saying, wow, that's a huge hurdle compared to New Relic or Datadog. And yet the open source unlocks the power in the data. And so all I'm doing is saying, I, as my decisive will create an open platform.

Everyone will be able to get access to the data, whether it comes from New Relic, OpenTelemetry, Datadog, Dynatrace, Splunk, I don't care. I'm gonna open up the data and then you're gonna be able to prepare it to and tailor it to your use case to your need. And I will of course, build tailored solutions on top of it.

That's how I'll make money. Absolutely. Well, the, the fact of the matter is, when you go under the coverage, even the New Relic now, and, and there you duck, they're using SoCo telemetry and and so forth.

They're just putting their front ends on it. Yeah. And because at, at, and that's the beauty of open source, right?

Like this foundational model of open source where it's not controlled by any one vendor, right. Which is a little different than maybe it was in the early two thousands. Um, you know, everybody gets that foundation, that base.

And then what you do, what you build on top of that, that's where you distinguish yourself. Yeah. But everyone can get the Prometheus feeds.

Right. And what and why if Prometheus is so widespread, why do I need to get another agent To Exactly, Exactly. To, to use that.

You mentioned a AI though, and that's something, you know, I have a lot of friends in the DevOps space especially. I was talking and I was at the dinner the other night with some, the feeling is that, and I think you hit it on, why do I gotta get woken up in the middle of the night? Let me just wake up in the morning and see what, see what it did for me.

You know? Yeah. The feeling is that as this gen ai, you know, continues to evolve, is it a lot of what we're seeing from some of the vendors you mentioned, not, you know, bad mouth, any of them.

They're toast. Yeah. Right?

Yeah. Um, it, it, I mean it's it's, it's a changing world. Yeah.

A very big change in that part of the world. Yes. You agree.

Totally. I I mean one, the, the vendor I came from, we had two AI solutions. One I built one a peer built, and that the peer solution worked in some use cases.

My solution worked in some use cases. The punchline is like, I spoke to a giant telco last month, and they're like, I'm out. I, I tag out on all this AI ops, it's not working for me.

And, and my lesson learned, and what's what's gonna become powerful about my decisive is one size fits all doesn't work. Especially in DevOps, right? You can't say, because this Oracle database over here went down last week at 85% CPU, that you should rebo auto reboot every Oracle database at 85% CPU, your, your business will grind to a halt guaranteed.

Right? And so the action loops need to be programmable. Like should I re autoscale?

Should I upscale? Should I restart? You need to have pluggable logic.

You need to have more than that though. You need to have pluggable algorithms. Like, I want to use a different algorithm for checkout than I use for sign in.

They're totally different services with totally different architectures. And the math is different for them. And the signal set might even be different.

This uses CPU and memory 'cause it's very hot that on those resources, this uses database latency and something else. How is a general purpose vetted solution supposed to build all this flexibility? You need to take control.

You need to take control. AI is where you're gonna get scale. So first op, my decisive gives you control back.

Let me feed these signals to these algorithms for that service. That's impossible today. Impossible.

And the vendors can't get there. 'cause they built a one size fits all architecture, and they, if they start routing fine grain signals to fine grain processing logic, they're dead. They can't scale.

So I push it all back to the customer, give you cloud automation, stand up your own Kubernetes and Prometheus clusters that can make all this decisioning for you. That's where the AI and my company name comes from. My decisive AI is we're gonna let you put all the intelligence back near the, the data where it's low cost, it hasn't left your envelope yet, and you can make high, high grained or fine grained decisions about what to do with each opportunity to your business.

The simplest example is AI ops. Like I will eliminate AI ops over the next 10 years is my prediction by giving people the ability to say, I have an ensemble. I have 20 or 40 algorithms and I have 10,000 services.

And where the AI comes in, is it intelligently maps, which services need what algorithms. So you can trial everything and you get scale of decision support. Like, let me try 20 different algorithms and see which one predicts outages best.

Thank you. My decisive. I'm now staying up more and I have fine grain control over what I'm doing at every piece of my infrastructure.

Got it. I love it. Good stuff.

Hey, you know what? We never get, you mentioned my decisive. It's actually my decisive ai.

We didn't give people a website. Shame on us. Yeah.

Ari, how, how can, how can they get on board here? Absolutely. org, just my decisive one word.

ai, uh, it'll give you documentation, it'll give you direct links to the GitHub repos. Again, it's open core. So you can get to the source code, you could build it, you can manipulate it, and you can, uh, use the free commercial offering as a push button.

Just go like, you give it your AWS access keys. It'll stand up an OpenTelemetry cluster, put you on a console and let you start taking control of your data in under 30 minutes. My decisive.

I Love it. Yeah. There you got it.

Ari, thank you so much. This is your first time on text, on tv. I really hope it won't be the last come back and keep us posted.

Yeah, Yeah. I will. I will.

This was wonderful. Thank you for your time. Thank you.

Ari Zilka, founder and ZCEO of my decisive. ai. You know what, Larry Ellison started like this.

Who knows, Ari, thank you. We'll see. We'll talk again soon.

Thank you. All righty. We're gonna take a break here on Text Trunk tv.

We'll be back in a moment.