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

Cases11 cases

11 to 11 of 11

  1. 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    Read the release notes before upgrading: the target version had been withdrawn five days earlier.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 11 cases involve Cluster autoscaler and Node pool. 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 cause6

Faulty deployment2 cases

  1. IL-0166 A compute host update removed the credential parser used to decode StackScripts, so new Linodes and every new LKE and LKE-E node failed to boot and autoscaling and node recycling failed in all regions
    Linode2026
  2. IL-0020 During an EKS 1.30 upgrade the descheduler tried to reschedule every pod on the cordoned nodes at once and production workloads went down

Breaking change in an upgrade1 case

Organisation
  1. IL-0097 A cluster autoscaler version bump was incompatible with the one cluster still on Kubernetes 1.33, so no scale-up events fired and new nodes were not created
    2i2c2026

Certificate or credential expiry1 case

Contributing factor
Organisation
  1. IL-0156 Revoking old certificates after a rotation left a certificate key mismatch between API endpoints and the cluster controller, and LKE cluster management and autoscaling in Atlanta returned 5xx errors
    Linode2025

Capacity exhaustion2 cases

Organisation
  1. IL-0006 VPC subnets ran out of IP addresses because the AWS VPC CNI kept IPs on full nodes, and WARM_IP_TARGET changes then blocked pod starts after every pod deletion
    Neon2025
  2. IL-0015 A GKE cluster's /16 pod address range ran out at 256 nodes, leaving new pods Pending and node scale-ups failing

Software defect2 cases

  1. IL-0157 After a release, new nodes could not join Linode Kubernetes Engine clusters with IP ACL enabled, so autoscaling failed on about 20 to 25 clusters
    Linode2025
  2. IL-0024 Expensive cache-backed API calls and uncancelled database requests overloaded MongoDB and took the Hugging Face Hub down three times

Cloud provider outage3 cases

  1. IL-0096 A GKE node pool pinned to the europe-west2-b zone could not scale for 6.5 hours because Google ran out of resources in that zone (ZONE_RESOURCE_POOL_EXHAUSTED)
    2i2c2022
  2. IL-0205 The GKE cluster autoscaler could not add nodes to GitLab.com's production cluster because Google Cloud ran out of SSD persistent disks in us-east1
    GitLab2021
  3. IL-0014 A GKE upgrade to a withdrawn version stalled on slow drains and a stuck node pool, then broke an ingress and confused the HPA