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

Cases2 cases

1 to 2 of 2

  1. Symptoms

    At 02:58 UTC on 31 March 2025, the sessionstore service in both Wikimedia data centres began returning 500 errors and edits failed. MediaWikiEditFailures (session loss) fired as critical at 03:03, and SessionStoreErrorRateHigh paged at 03:04.

    Trigger

    A rise in session writes, made up of session overwrites at a high rate, filled the storage of the sessionstore Cassandra nodes. The review says the rollout of SUL3 correlates strongly with it.

    Root cause
    Component
    Contributing factor
    Detection

    MediaWikiEditFailures (session loss) fired as critical at 03:03 UTC, and SessionStoreErrorRateHigh, a high 5xx rate alert, paged the batphone at 03:04. Users also reported the problem in task T390512.

    Remediation
    • Wiped the sessionstore storage, removing all sessions, and restarted Cassandra
    Action items
    • Page when the disk utilisation trend becomes unreasonable
    • Increase sessionstore storage capacity
    • Add namespacing to sessionstore
    • Add observability of the sessionstore workload
    • Identify the cause of the high rate of storage growth in sessionstore Cassandra
    • Consider an alert, without paging, on the Cassandra error rate
    • Consider paging or alerting when Cassandra nodes enter a down state
    Lessons

    The storage growth before the node failures made their timing predictable, so an alert on high storage utilisation well in advance would have given a chance to act before users were affected, and an alert on Cassandra node failures would have told responders more than an HTTP error rate alert. A cluster seen as heavily over-provisioned can still grow quickly and unsustainably under an unusual workload.

  2. Symptoms

    On 29 July 2021, data collection and alerting in New Relic's US region became unusable for many customers for several hours. It began with one unresponsive Kafka broker in a single cell of NRDB, New Relic's telemetry data platform, and over the following hours Kafka brokers in more and more cells failed as their disks filled up.

    Trigger

    Responders used an incident response tool to extend Kafka data retention for the degraded cell so that its backlog would not be lost. The retention increase was larger than usual, and the tool applied it to all cells of the same type, not only the affected one.

    Root cause
    Component
    Contributing factor
    Detection

    Engineers saw a Kafka broker in one cell become unresponsive on the morning of 29 July. Later a monitoring alert warned that disk space was running low, but it fired together with unrelated warnings from several other systems and was missed.

    Remediation
    • Restarted the unresponsive Kafka broker by hand, while the automated restart was also running
    • Resolved the disk space problem on the Kafka brokers, after which service recovered slowly
    Lessons

    Cell isolation is the strongest protection against a widespread disruption, and emergency tools have to respect it just as normal operations do. Emergency response tools must be safe to use in chaotic situations without losing their ability to work. Engineers' attention is limited, so incident response processes and alerts need regular review to direct it at the most important signal.

Check your cluster for this

These 2 cases involve Database and Message broker. 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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