Konrad Kowalski (rootsher)Principal Platform & Reliability Architect110100111001101100101111111100011100000110000101

Kubernetes

posts (9)

  1. CPU in Kubernetes from the kernel up12/12

    Anatomy of a CPU problem: from an understated request to p99 latency

    One incident end to end: a 500m request, no limit, no throttling, and p99 climbing from 35 to 180 ms. The whole path of the mechanism.

  2. CPU in Kubernetes from the kernel up11/12

    Noisy neighbor and CPU overcommit: when one Pod breaks another

    Overcommit works until bursts become correlated. An understated request is not only about placement - it is a weaker position under contention.

  3. CPU in Kubernetes from the kernel up10/12

    How to debug CPU in Kubernetes without guessing

    Usage, throttling, contention and pressure are four different phenomena. A single CPU chart settles none of them - you need an order of operations.

  4. CPU in Kubernetes from the kernel up8/12

    Why 1 CPU does not mean one core

    CPU time and CPU placement are two different mechanisms. A limit says how much you may consume; affinity and cpuset say where a task may execute.

  5. CPU in Kubernetes from the kernel up7/12

    Requests, Limits and QoS: how Kubernetes classifies Pods

    A QoS class is the result of how requests and limits are configured, not a separate CPU allocation mechanism. Guaranteed is not a dedicated core.

  6. CPU in Kubernetes from the kernel up6/12

    PSI: how Linux measures real CPU pressure

    Utilisation says how much CPU a workload got. PSI measures the time it lost because it wanted to execute and had nothing to execute on.

  7. CPU in Kubernetes from the kernel up4/12

    CPU Limits and throttling: what a CPU limit really does

    A limit does not pin a container to a core. It gives it a CPU-time budget accounted per period, and once that runs out the kernel throttles it.

  8. CPU in Kubernetes from the kernel up3/12

    CPU Requests in Kubernetes: what they really are

    A request is a declaration of demand, not a ceiling. It feeds placement in kube-scheduler and CPU weight on the kernel side.

  9. series · 12 parts

    CPU in Kubernetes from the kernel up

    A CPU model built bottom-up: from runnable tasks and the scheduler, through cgroups, requests and limits, to throttling, contention, PSI and diagnostics.