Incident Library
Applied filters ComponentNode poolSymptomService outageFactorOverlapping failuresClear allEvery case under the filters, with no sentence; newest first.
Suggested filters Search, and the values found in your words appear here.

Graph

  • Root cause
  • Component
  • Symptom
  • Contributing factor
  • Case

Cases2 cases

1 to 2 of 2

  1. Symptoms

    At 16:40 UTC on 19 April 2024 CoW Protocol's mainnet production environment stopped producing settlements; the outage officially began then.

    Trigger

    During a cluster capacity expansion, the Infrastructure as Code automation updated the AWS VPC CNI plugin, because the CNI version was not hardcoded in the IaC and the IaC library version had recently changed.

    Root cause
    Component
    Contributing factor
    Detection

    The CNI version mismatch was identified as the cause at 17:03 UTC, 23 minutes after settlements stopped.

    Remediation
    • upgraded the Kubernetes cluster
    • set up new node groups with a new version of the networking plugin
    Lessons

    Versions in IaC scripts should be specified explicitly so an automation run cannot update a component such as the CNI plugin unintentionally. Changes in production need change management that is easy to revert.

  2. Symptoms

    On the evening of a long-overdue upgrade of a loveholidays production GKE cluster from 1.10.X to 1.12.5-gke.10, planned to take 2 to 2.5 hours, the master upgrade and the first two 7-node NodePools went smoothly. After that the NodePool upgrades slowed to a crawl. Each node is cordoned, drained and upgraded in turn. Even a 14-node cluster at about 5 minutes per node took over an hour, and with about 100 more nodes to go, some of them taking over 15 minutes to drain, the sequential drains were too slow to finish at a reasonable hour.

    Trigger

    A manual upgrade of the GKE masters and NodePools from 1.10.X to 1.12.5-gke.10, two versions at once, on 19 March 2019; GKE's release notes of 14 March had already said that version was no longer available for new clusters or master upgrades because masters showed elevated error rates, but it could still be selected.

    Root cause
    Component
    Contributing factor
    Detection

    The slow drains, zombie nodes and stuck NodePool were seen by the engineer running the upgrade; the broken Ingress was noticed after the upgrade and explained by Google support; the HPA problem was noticed the next day.

    Remediation
    • drained the remaining NodePool nodes ahead of the upgrade with kubectl drain --ignore-daemonsets --delete-local-data
    • deleted the zombie instances from the managed instance group with gcloud compute instance-groups managed delete-instances
    • cancelled the stuck UPGRADE_NODES operation with gcloud beta container operations cancel
    • used kubectl port-forward in place of the broken internal Ingresses
    • scaled down the older of two active ReplicaSets, or triggered a dummy deployment, to bring the HPA back
    Action items
    • Alert when a HorizontalPodAutoscaler is at 70% and at 100% of its capacity
    • Alert when a deployment has had two active ReplicaSets for 30 minutes and for 60 minutes
    • Re-evaluate termination grace periods that were set to arbitrary large values
    • Read the GKE release notes before every cluster upgrade
    • Use auto-upgrade in non-production environments, and manual cluster upgrades with automatic node upgrades in production
    • Keep environments as identical as possible, including resource names
    Lessons

    Read the release notes before upgrading: the target version had been withdrawn five days earlier. Drain time depends on pod configuration, so emptyDir volumes, long grace periods and missing disruption budgets turn a NodePool upgrade into hours. Pre-production only catches problems like the ingress bug if it matches production down to resource names. Auto-upgrades in non-production surface problems early, and a mix of manual cluster upgrades and automatic node upgrades in production keeps clusters current without much effort.

Check your cluster for this

These 2 cases involve Node pool and Cluster autoscaler. kubegap audits a Kubernetes cluster for gaps like these, read-only, from Claude Code or Codex; its checks cite public reports like the ones in this library.

By root cause2