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

Cases3 cases

1 to 3 of 3

  1. Symptoms

    A bug report said that some reservation notifications in the AutoReserve restaurant reservation service never arrived. Of the several kinds of notification sent as a reservation progresses, only one kind sometimes arrived and sometimes did not.

    Root cause
    Component
    Contributing factor
    Detection

    A bug report from AutoReserve said that some reservation notifications were not arriving.

    Remediation
    • Scaled the Memorystore for Redis instance from 8 GiB to 16 GiB, which did not stop the write rejections
    • Upgraded Redis from 3.2 to 7.2, which removed the fragmentation and stopped the write rejections
    • Moved the notification sent status from Redis to the relational database
    Action items
    • Consider enabling active defrag if physical memory use rises above 1.3 times logical memory use
    Lessons

    The logs and the instance page metrics did not show the cause; it took looking inside Redis with INFO memory to see physical memory far above logical memory. A cache is a place for values that can be rebuilt if lost and whose writes may fail, so the sent status, which had to persist and be decided once under concurrent processing, belonged in the relational database.

  2. Symptoms

    From 21:08 on 28 May 2025, about 60 indices of Wikimedia's OpenSearch clusters for CirrusSearch were in red, unwritable state. At 21:27 CirrusStreamingUpdaterFlinkJobUnstable alerts began to fire because the search update pipeline could not write to those indices.

    Trigger

    A Puppet patch that removed cluster access for the hosts elastic/cirrussearch10[53-67] while some of them still held primary shards.

    Root cause
    Component
    Contributing factor
    Detection

    CirrusStreamingUpdaterFlinkJobUnstable alerts fired from 21:27; the review records the detection as human, by the engineer who started troubleshooting the next morning, and many other alerts were suppressed for maintenance.

    Remediation
    • Deleted the red indices, which brought the cluster back to green
    • Restored the broken indices
    Action items
    • Re-enable the snapshot repositories in production CirrusSearch
    • Create an operations-focused OpenSearch dashboard
    • Verify or fix the Logstash pipeline for Search Platform-owned OpenSearch clusters
    Lessons

    Banning nodes before removing them is a best-effort action and did not work as expected. A large operation such as decommissioning many servers at once had no maintenance plan or runbook, and the snapshots, dashboards and logging that recovery needed were not available or not documented well enough.

  3. Symptoms

    On 10 July 2019 the Stripe API failed a substantial majority of requests twice, from 16:35 to 17:02 UTC and from 21:14 to 22:47 UTC. In the first period automated monitoring detected within a minute that a database cluster had failed to elect a new primary.

    Trigger

    The primary node of a database cluster failed at 16:35 UTC while one shard had several stalled nodes. The second period was set off by rolling the election protocol back to the previous minor version at 20:42 UTC.

    Root cause
    Component
    Contributing factor
    Detection

    Automated monitoring detected the failed election within a minute, and the team was alerted at 16:36 UTC. The second period was announced at 21:14 UTC by automated alerts that some shards in the cluster were unavailable.

    Remediation
    • Restarted all nodes of the database cluster, which forced a successful primary election
    • Updated the production configuration and restarted the database cluster's nodes
    • Ramped traffic back up, putting services for user-initiated API requests first
    Action items
    • Alert when nodes stop reporting their replication lag
    • Alert when a shard enters a state that could trigger the election fault
    • Work with the database maintainers on a fix for the underlying fault
    • Add circuit breaking on failed operations to particular database clusters
    • Use fault isolation to contain the impact of a single failed shard
    • Limit the resources used by clients that keep retrying failed requests
    • Add procedures and tooling that make rapid configuration changes during incident response safer
Check your cluster for this

These 3 cases involve In-memory cache and Database. 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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