Most teams scale Kubernetes by thinking about pods and nodes. At Render, Brian Stack ran into a different dimension: hundreds of thousands of namespaces per cluster, multiplied across DaemonSets that list-watch every namespace.
Brian explains how Render traced the issue through Calico and Vector, worked with upstream maintainers, and turned memory profiling into operational wins: lower node costs, lighter API-server load, and faster rollouts.
In this interview:
Why namespaces can become a hidden scaling bottleneck
How DaemonSets multiply memory and control-plane pressure
How profiling, staging clusters, and upstream collaboration freed 7 TiB
Why pushing from an 80% fix to a complete fix can make teams faster
Podden och tillhörande omslagsbild på den här sidan tillhör
KubeFM. Innehållet i podden är skapat av KubeFM och inte av,
eller tillsammans med, Poddtoppen.
