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

Sponsor

This episode is sponsored by LearnKube — get started on your Kubernetes journey through comprehensive online, in-person or remote training.

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