Observability
topic on 7 shows · 14 statements across 11 episodes
the Y Combinator Startup Podcast
In Depth
Latent Space
Lenny's Podcast
the Neon Show
No Priors
the MAD Podcast
14 statements about Observability, every show
Pomel: Legacy monitoring was siloed for Ops, leaving developers blind to production
“It was not called observability. It was called monitoring. And it was very job specific and very reactive. So, you know, for network monitoring, you'd have a product for, you know you'd have something that the ops team would use, but the developers would never…”
Sanyal: Enterprises Will Not Deploy Action-Taking Agents Without Observability
“No one's going to put an agentic system, especially if they do actions and tasks, they're not going to do it without any kind of observability.”
Sanyal: AI observability faces a trilemma of cost, latency, and quality
“Observability is a bit of a different ballgame because it has a different set of challenges. It's an infrastructural problem and latency and cost and quality. Those are the three things, and they are a bit of opposing forces with each other. It's like this tri…”
Bubna: System Observability Is Becoming More Important Than Reading Code
“You still need humans to go interpret what's going on and you know, make judgment calls and whatnot. And that's, I feel like maybe more important now than looking at the code itself.”
Bubna: AI agents struggle to reason through logs and observability
“I think the things that sometimes agents struggle with without right guidance and a skill is how to use the rest of our observability. Like, how to, something is failing, like, How do you look at the logs and then update the right thing? It's sort of reasoning…”
Bhatawdekar: Gen AI Systems Require Observability Feedback Loops for Evals
“So when you're building Gen AI systems, you really want that feedback loop of observability that helps you build better evals, that helps you ship better AI.”
AI observability logs average 50KB per row compared to 900B traditionally
“Every span in brain trust land, which is like a row of something that you'd log in brain trust, the average size is
50 kilobytes.
In traditional observability, it's 900 bytes.”
Colvin: Gen AI observability will merge into general-purpose observability platforms
“Web observability stopped being a thing, not because the web stopped being a thing, but because all observability had to do web. If you were talking to people in 2010 or 2012, they would have talked about cloud observability. Now that's not a term because all …”
Goyal: AI observability exists to collect datasets for evaluations and fine-tuning
“In AI, the whole point of observability is to collect data into data sets that you can use to do evals, and then again, eventually fine tune models or, you know, more advanced things.”
Pomel: Within five years, security will inevitably attach to observability
“We have a thesis that security, like, five years from now will be will be, or rather, let me rephrase it will be a no-brainer that you have to attach your security to your observability, because that is what gets deployed everywhere in your application, in you…”
Pomel: Observability log volumes grow much faster than customer revenue
“The biggest challenge with observability is that any application can generate any arbitrary large amount of logs. And so the data volumes grow much faster then our customers revenue”
GitLab is expanding its platform into observability and service management
“And we are currently working on expanding into observability and service management, but it is truly an amazing experience.”
Rauch: Observability is mandatory from v0.1 for AI applications
“It's like letting you provide a great quality of service, but in the AI realm, it's just so mandatory. Like your V 0.1 already needs that critical feedback loop.”
Pomel: Infrastructure, APM, and log monitoring will merge into one category
“An example of that being observability is emerging as one big super category that really encompasses what used to be infrastructure monitoring, application performance monitoring, and log management. And we still sell those three as different skews today. But …”