Exploring AI’s Role in Incident Management with Rootly’s Sylvain Kalache

Hey everyone. Alan Shimmel. We're back here live at Platform Con Day in New York City.

Of course, this is just the in-person day of a week long virtual event that's going on. com. I forgot how many speakers and sessions there are, but there's a lot, and I encourage you to do so.

Let me introduce you to our next guest. His name is Sylvan Chy. Yes.

You got this right. A neighbor of mine from Fort Lauderdale. We're both up here in New York.

Um, Sivan, welcome to Tech Drunk tv. It's nice to have you on here. Thank You, Ann.

Um, not everyone watching this is gonna know who you are. Tell them a little bit about yourself. Yeah, So I, um, I'm a former software engineer, was an SRE for nearly 10 years.

Um, then I was an entrepreneur, got an education training software engineer, and now I'm, uh, heading the Rootly AI Labs. Um, so for this, we don't know, ROOTLY is an incident management and on-call platform. So we competition to PagerDuty, uh Okay.

Which, you know, I think you probably heard of. So we help businesses to manage their incident and we're used by, um, you know, small companies and large businesses like Nvidia, Figma, Cisco, LinkedIn, and so on. Right.

So we, we help, uh, a large, uh, large company, um, and the operation team to make sure that their incidents are, um, handled smoothly. And my role, uh, truly, uh, is to lead this AI labs. And the AI lab is a community led initiative where we, uh, work with team of fellows.

So, um, we have people who are tech leader in the industry. We have as the head of platform engineering at Venmo, the former head of AI at Twilio and research students. And we work with these folks to really understand what can AI bring to the world of readability and it's applied ai.

So we build prototypes, open source tools, we run, um, research and we write report and we share all of this open source, um, on our GitHub with the community. So really the goal of this lab is like, how do you use AI for SRE or platform people? Excellent.

So this time probably is a good audience for you. Yes, It is. It is.

Um, you mentioned you were on a, uh, a panel this morning. Yeah, So we were on the panel with um, Google Sort work, um, and uh, Nvidia. And the goal was really to discuss, um, what's, uh, what's hyped with AI and what's reality applied to platform engineering.

Right. Like, uh, I think we hear a lot from, uh, the executive and CEOs from uh, uh, model providers who are selling a GI or fully autonomous system. I think we all agree that we're not there.

And, um, I think especially for practitioner, which I think today is a lot of practitioner, they really want to understand what's true, what's maybe not there yet, and how can they really apply this in the, in their day to day job. Yeah. I sivan I think one of the big problems, especially for practitioners is every day it seems there's a new news story that some big tech company is doing a layoff and they're laying people off 'cause they're replacing them with ai.

Yeah. I think as we sit here today, very few people are actually being replaced with ai. Sorry.

I think what it really is is that these companies overhired Yeah. During c and before. Correct.

And they need to cut back. They have too many people. And rather than just saying that they kind of blame it on ai.

Yeah. And so AI gets this thing of, oh, it's taking people's jobs. Yeah, Yeah, yeah, yeah.

You know, New York State is now setting up a tracker, jobs lost to ai, you know, and, and, and so you talk about separating reality from a hype. Yeah. To me that's a big, a big issue here.

Now, I'm not saying that AI may replace people's jobs someday. I'm not saying that AI can help us or cannot help us. Uh, to me today, AI is more of a co-pilot than a pilot.

Mm-hmm. Does that make sense? Yeah, it does.

And, and so I wonder now on the other hand, I'm talking to you, you run an AI lab. Yeah. What do you see?

What do you think? Yeah, so, you know, I think there are different type of AI labs. Uh, if you look at, you know, the large stakes who are building these, uh, models, you know, these are like more like research, uh, researcher and PhD and people who are like building all these LMS at ru we are really taking, um, a different stand where it's like really applied ai.

So we use this tool to see how we can empower current practitioner, augment themselves, do their job better and uh, faster. And yeah, I agree with you. It's like any tech new technology or tools, eventually it may replace some jobs, but maybe it's for the good.

You know, like let's say before electricity, we had people going in the street and lighting the candle, uh, you know, for, for Street Lightning. Like we don't use this anymore, but maybe that's a good thing. Um, so for instance, um, shortly we are really focusing on incident management, right?

That's, uh, what we are about. And what we found is that you can really use the AI to help, uh, operation team to spend less time on managing incident because that's not something you want to do. Right?

Um, so I would share two main use cases where we saw, um, uh, you know, how this technology can help. One of them is incident, uh, triage and filtering, right? You have all this alerts coming from a lot of tools and you don't human to be looking at this, right?

So here LLMs can do a great job at like helping to filter and cut through the nose. And the second thing is, uh, root cause analysis. So when you have an incident and you need to understand what's happening, what's wrong, a human may take 10 to 20 minutes to like gather all the graph, look at GitHub to see what were the last commit, maybe go on Slack and see what conversations they were perhaps on the project.

With LLM, you can reduce this by like 80 to 90%. So instead of spending 10 to 20 minutes investigating an incident, it can be done in like one to two minutes. And that's a huge, that's that's a factor of 10, right?

It is. And and I think that is, at least in the interim, that 10 x is the goal. It is 10 ai, 10 x you.

Yes. And we've been speaking about the 10 x engineer for A long time. A long time.

It's finally coming. Absolutely. Absolutely.

So, and it's finally coming through. You know what we didn't mention Rootly. What's the website?

com. com. Yeah.

And, uh, the, the platform helps you. Basically, we sit at the center of your incident response, um, uh, efforts. So you connect all your monitoring and logging, logging tools, uh, to our platform.

So your data and Sentry. And, and we, we help help your RE team to orchestrate a response to that. So we will create for you, um, a team or a Slack channel, uh, spun up a Google meet or Zoom room so people can, uh, share.

And then we embedded, um, a bunch of features that will help you to, uh, do the job faster. For instance, we have a bot that will listen to the conversation on Slack and audio, you know, and then if someone join an incident, you have a bot that you can ask, Hey, what's happening? Can you gimme an update?

Um, once an incident is solved, you have to write a postmortem or incident report. No one's likes to do this, so we automated this for you. Um, so yeah, it's like a very, like, basically when something breaks, SREs, go to Rotten.

I love it. Ban. It was a quick 15 minutes.

It Was quick. Indeed. Thank, Thank you for telling us this.

Maybe we'll get together in person in Lauderdale, come into our studio. Yeah, I'm down. All righty.

Thank you. We're live at Platform Calm. We've got a lot more coming your way.

Stay tuned. We'll be back in a moment.