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Cases2 cases

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  1. Symptoms

    At 15:10 (Bucharest time) on 2026-03-31 an alert fired for the prod hub on the berkeley-geojupyter cluster on AWS: "[FIRING:1] At least two servers failed to start in the last 30m cluster=berkeley-geojupyter hub=prod (provider=aws immediate action needed)". It opened PagerDuty incident #2057.

    Trigger

    An upgrade merged on 2026-03-30 bumped the cluster autoscaler version, and the new version was incompatible with Kubernetes 1.33, which the berkeley-geojupyter cluster still ran.

    Root cause
    Component
    Contributing factor
    Detection

    An alert that at least two servers failed to start in the last 30 minutes fired at 15:10 and opened PagerDuty incident #2057. The report notes it was triggered by an automatic health check run, not by users being unable to start servers.

    Remediation
    • upgraded the cluster's Kubernetes version from 1.33 to 1.34
    • downgraded the cluster autoscaler by one patch version to 9.55.0, the version meant for Kubernetes 1.34
    Action items
    • The change in https://github.com/2i2c-org/infrastructure/pull/8008 (the report gives only the link)
    • Use recurrent issues, such as the recurrent-k8s-aws-upgrades workflow, to standardize Kubernetes versions across clusters
    Lessons

    Because the context of the autoscaler bump was fresh, the team went down the right path from the start. The upgrade batches had been designed with only 1.32 clusters in mind, so the one 1.33 cluster was missed and got an incompatible autoscaler. 2i2c notes it was lucky that an automatic health check, not real users, hit the failure first.

  2. Symptoms

    A user of the LIS JupyterHub reported a "backoff after failed scale-up" error, and user servers would not start. An engineer opened incident #36, "LIS hub cannot scale", at 5:40 AM Pacific on 14 November 2022.

    Trigger

    At 10 AM UK time on 14 November 2022, the B zone of Google Cloud's europe-west2 region (London) ran out of resources to allocate. The LIS cluster's nodes were restricted to that zone.

    Root cause
    Component
    Contributing factor
    Detection

    A user reported the "backoff after failed scale-up" error; an engineer opened the incident at 5:40 AM Pacific, about three hours and forty minutes after the zone ran out of resources.

    Remediation
    • edited the node pool in the GCP console to allow node creation in the A and C zones of europe-west2, which were not exhausted
    Action items
    • Either restrict the node pool back to the B zone after the Black Friday event, or move the cluster and the NFS Filestore to the A zone (infrastructure issue #1944)
    • Investigate an enterprise plan that allows a regional NFS, at higher cost (infrastructure issue #1945)
    • Make sure PagerDuty notifications always get through to engineers (team-compass issue #574)
    Lessons

    A node pool pinned to one zone for storage performance cannot scale when the cloud provider runs out of capacity in that zone. The autoscaler's "backoff after failed scale-up" message usually points to quotas, and raising quotas does nothing here; the ZONE_RESOURCE_POOL_EXHAUSTED error in the logs is what identifies a zone without capacity. The review found that one engineer wearing many hats (incident commander, comms and debugging), with pages not reaching the other responders, made the response harder; a team response would have given more support.

Check your cluster for this

These 2 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.

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