Incident Library
Applied filters Root causeFaulty deploymentSymptomCluster or node provisioning stallDomainKubernetesClear 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

    From about 19:15 UTC on 12 March 2026, customers in the Osaka data center (JP-OSA) could not create Linode Kubernetes Engine for Enterprise (LKE-E) clusters. Cluster creation stalled indefinitely.

    Trigger

    A phased rollout of the LKE software release reached the Osaka data center.

    Root cause
    Component
    Contributing factor
    –
    Detection

    The problem began at about 19:15 UTC, and the first status post, about five and a half hours later at 00:45 UTC on 13 March, said the team was investigating an emerging issue with deploying new LKE Enterprise clusters in Osaka.

    Remediation
    • deployed a software fix to mitigate the impact
    Action items
    • Investigate the root cause further and take preventive actions
    Lessons

    The problem followed a phased rollout of an LKE software release in the Osaka data center. There, cluster creation and administrative tasks stalled for more than six hours, and the first status post came about five and a half hours after the start.

  2. Symptoms

    On 5 October 2023 in us-central1, newly created VMs waited a long time before their networking worked, and VMs that had been live migrated lost connectivity for a long time after the migration. Networking telemetry showed cross-region packet loss to and from us-central1 from 03:08 US/Pacific. Health check state of VMs reached load balancers late.

    Trigger

    A management plane behaviour change, meant to decouple the processing of API updates to Instance Groups and Network Endpoint Groups used as load balancer backends, was deployed in us-central1 after rolling out to several other regions without incident.

    Root cause
    Component
    Contributing factor
    Detection

    Engineers were alerted to slowness in the virtual network control plane in us-central1 at 21:45 US/Pacific on 4 October, before the packet loss started, and to controller failures from memory exhaustion at 02:11 on 5 October. Networking telemetry showed cross-region packet loss from 03:08.

    Remediation
    • Increased the memory allocated to the virtual network router controllers
    • Rolled back the management plane change in us-central1
    • Restarted by hand the routers that were still not accepting updates
    Action items
    • Alert proactively on memory risks and unexpected memory increases
    • Refactor the deployment configuration so engineers can reallocate memory much faster
    • Re-evaluate existing practices and add safety mechanisms for API reconciliation
    • Make management plane changes more visible across teams so the changes can be correlated faster
    • Adjust the deployment footprint so a regional API change is less likely to exhaust memory across the region at once
    • Optimise memory use in the traffic routers and their controllers
Check your cluster for this

These 2 cases involve Cloud load balancer and Managed Kubernetes control plane and provider API. 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 cause1