Modern cloud-native systems are highly dynamic and distributed, which makes it difficult to monitor cloud infrastructure using traditional tools designed for static environments.

This has motivated the development and widespread adoption of dedicated observability platforms.

Prometheus is an open-source observability tool designed for cloud-native environments.

Its strong integration with Kubernetes

and pull-based data collection model have driven its popularization in DevOps. However, a common

challenge with Prometheus is that it struggles with large data volumes and has limited cost

optimization capabilities. This raises the question of how best to handle Prometheus deployments at large

scale. Eric Chabelle works in Devrel at Chronosphere, where he's the director of community and

developer. He also is a CNCF ambassador. Eric joins the show with Kevin Ball to talk about

metrics collection, time series data, managing Prometheus at scale,

tradeoffs between self-hosted versus managed observability, and more.

Kevin Ball, or K. Ball, is the vice president of engineering at Mento and an independent

coach for engineers and engineering leaders. He co-founded and served as CTO for two companies,

founded the San Diego JavaScript meetup,

and organizes the AI inaction discussion group through latent space.

Check out the show notes to follow KBall on Twitter or LinkedIn, or visit his website, kball.

LLC. Eric, welcome to the show.

Hey, thank you very much.

Nice to be here.

I'm excited to get to talk with you.

So let's maybe start out with a little bit of introduction about you and what

brings you here and maybe start touching on Prometheus and Chronosphere. Sure. So my name's Eric Chabelle.

...