~/panel

Panel: Improving and Managing Kubernetes at Scale

slides:none on file

Multiple companies report concrete limits and fixes: control plane and etcd benchmarking shows storage and API server as bottlenecks; an 8k nodes -> 40k pods: 5m to 30s experiment cuts launch time by suppressing pod events; deployment models include public shared pools and dedicated clusters with API gateway frontends; runtime tweaks include virtual kubelet, sidecar controllers, injected API servers (virtual clusters), CPU sets and two‑level scheduling for collocation; largest fleets claim >6,000 nodes; >100k containers per cluster and require staged upgrades with week‑long baking.

AI-written summary · about

  1. 0:00Start
  2. 18:06Testing against Api Server
  3. 21:59What Is the Biggest Pain Point You Guys Face When Adopting Kubernetes and What Is the Status of each of the Companies
  4. 26:45How Do We Use Kubernetes Extension Points To Fit in an Already Rich Infrastructure Ecosystem
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