Incident Library
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Cases2 cases

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  1. Symptoms

    On 12 May 2025 at 20:15 EEST a Freshdesk ticket reported that users' servers on the Earthscope hub were taking more than 15 minutes to start and that their kernels were being killed. It happened during a workshop and also affected other instructors using the hub; a second report said a short course of about 30 users was having major problems.

    Trigger

    A workshop with about 30 users on a profile option that guaranteed 8 GB of memory and set no memory limit on 32 GB nodes.

    Root cause
    Component
    Contributing factor
    Detection

    A Freshdesk support ticket from the community at 20:15 EEST, brought to the team's attention in the #support-freshdesk Slack channel at 20:49.

    Remediation
    • ran a helm rollout and hub redeploy, which partly improved server starts
    • made the 'medium' profile available and raised its memory guarantee to reduce overcommitment
    • pre-warmed the cluster with 15 nodes for the 30-user workshop
    • set explicit memory limits, with the guarantee equal to the limit, on the community's small-node profile options (https://github.com/2i2c-org/infrastructure/pull/6047)
    Action items
    • Write an incident report
    • Hold an internal retrospective about the incident (https://github.com/2i2c-org/meta/issues/2194)
    Lessons

    A memory guarantee without a limit lets a user server grow into memory that other pods on the same node were counting on, and on a shared node that ends with users' pods evicting each other. Setting the guarantee equal to the limit removes the overcommitment. For a known workshop, pre-warming enough nodes ahead of time keeps server start times short.

  2. Symptoms

    The hub pod of the prod JupyterHub on the leap cluster (leap.2i2c.org) restarted unexpectedly during a large node scale-up, and a user opened a support ticket. The ingress-nginx and proxy pods kept running.

    Trigger

    A user's dask-gateway workload added about 100 dask-worker nodes within a minute, and Prometheus started scraping the metrics exporters on about 200 nodes.

    Root cause
    Component
    Contributing factor
    Detection

    A user support ticket (2i2c Freshdesk ticket 414) about the leap hub; the engineer then looked at Grafana and the cluster's nodes and events.

    Action items
    • Configure CPU and memory requests for the hub and proxy pods (#2127; at least 100m CPU was proposed)
    • Make the Grafana OOMKiller dashboard work (#2213)
    • Move LEAP cloud infrastructure to shared nodes (#2209)
    • Update resource requests and limits, mainly for ingress-nginx and Prometheus (#2324)
    • Decide whether Prometheus should scrape dask worker pods (#2366)
    Lessons

    Prometheus load grows with the number of nodes, so a burst of autoscaled nodes can push a nearly full core node over the edge and evict the pods that matter most. Core pods that request 10m of CPU get a tenth of the CPU share of busy neighbours that request 100m. Kubernetes events expire after an hour, so evidence of OOM kills needs a dashboard that keeps it.

Check your cluster for this

These 2 cases involve Node pool and Container memory limit. 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.

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