Transcript
A (0:00)
Observability emerged from the need to understand complex software systems and involves tracking metrics, logs and traces so engineers can detect and diagnose problems before they affect users. However, modern applications often encompass hundreds of services, containers and dependencies, generating more observability data than dashboards and alerts alone can effectively surface. New Relic is a leading observability platform with a history that spans the full arc of modern software operations. Today, they are working to apply AI to move observability beyond passive monitoring toward active intelligence where systems can surface what matters, reduce alert noise, and ultimately take autonomous action before problems reach engineers or users. Nick Benders is the Chief Technology Strategist at New Relic, where he has worked for 16 years. In this episode, Nick joins Lee Acheson to discuss the evolution of observability from dashboards and alerts to AI driven intelligence, how LLMs and statistical tools work together to surface meaningful signals from massive data sets, the emerging challenge of observing AI systems themselves, and what the rise of AI means for the future of software engineering as a profession. This episode is hosted by Lee Acheson. Lee Acheson is a software architect, author and thought leader on cloud computing and application modernization. His best selling book, Architecting for Scale is an essential resource for technical teams looking to maintain high availability and manage risk in their cloud environments. Lee is the host of his podcast Modern Digital Business, produced for people looking to build and grow their Digital Business. Listen DB FM, follow Lee@softwarearchitectureinsights.com and see all his content@leeacheson.com.
B (2:08)
AI and Observability how exactly do they work together? My guest today is Nick Benders. Nick is the Chief Technology Strategist for New Relic, one of the major observability platforms that is now focused on AI. And Nick is also a personal friend of mine. So Nick, welcome to Software Engineering Daily.
C (2:27)
Thanks Lee. It's great to be here.
B (2:29)
Now, you and I go back a long time from New Relic days. Early in the New Relic days. Matter of fact, we've just spent a little bit of time talking about some of those earlier days. But can you catch listeners up on what you've been doing since those early days in New Relic and what your role as Chief Technology Strategist really involves?
C (2:48)
Absolutely. So when I think about New Relic's journey and really in some ways the industry's journey, back when we started at New Relic, we were very much solidly in this instrumentation era. Like the thing that we sat down at our desks and tried to figure out every day was how can we instrument more of the systems that matter to people? Oh, well, we started with Ruby. How do we get Java, how do we get Net, how do we get Python? How do we get into the browser or onto mobile apps or add a new library? And pretty soon we were instrumented so many things that there was more data than we could deal with. And so it moved from this instrumentation era into this data platform era. And for new Relic, that shift was around 2013, 2014, when we introduced NRDB. NRDB gave people a way to ask questions of a system that you didn't know you needed to ask. So all the data goes into it and. And then after the fact, you're like, oh, where are my slow queries coming from? Oh, well, that's mostly a test system. Exclude that test system. Where are the rest of the slow queries coming from? Can you break that out by country? And so this type of like interactive questioning system that powers dashboards, it powers like just kind of a interactive data explorer, it powers alerts. There's all these things you can do with a data platform, but that was over 10 years ago now. And what we've seen is the ability to have all the data and to put it all into place so you can ask any question is no longer enough because you have so much data, you don't even know what to ask from it. And so instead of just being about the ability to ask something or to make a dashboard out of anything, you need a tool that tells you what are the questions you want to ask. It tells you what are the things you want to look at. And so that's that shift from the data platform era into this intelligence era. And intelligence everybody jumps on. Immediately you're like, oh, it's AI. I'm like, yes, AI is a piece of intelligence, but it's also about product design. It's about the way that we use something, having those built in opinions, those flows. Because when somebody sits down at a tool, they don't want to just see a prompt and say, oh, I can dashboard anything. Great. They want answers, they want to know what's important in their system. And so that's that intelligent shift. That's the era we're in now. I'm going to talk about this a little bit later. But also, the intelligence era won't last forever. And it may already be bringing to a close as we need to move into an action era as an industry and for New Relic. And so New Relic's journey since those early days has been getting into each of these Kind of pioneering it, figuring out what has to be done, and then asking the question of what has to be done next. As the chief technology strategist, that's where I come in, is I've been with the company now for 16 years, just working with every piece of the system. And I've been using observability tools for 30 years now. And back from when we used to call it monitoring was just ping.
