Incident Library
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  • Root cause
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Cases2 cases

1 to 2 of 2

  1. Symptoms

    From 10:32 UTC on 6 August 2024, Wasabi's S3 service and user services failed in every region: users had trouble logging into the Web Console and requests to Wasabi regions returned errors.

    Trigger

    At 10:32 UTC on 6 August, Wasabi's queueing service reached full capacity, and that made the database cache unresponsive.

    Root cause
    Component
    Contributing factor
    –
    Remediation
    • Restarted the primary database to clear stale connections and cleared the queueing service's queue at the same time, which did not fully restore the database
    • Promoted the secondary database instance to primary, after which S3 was fully operational at 11:20 UTC
    • Restarted the database again between 13:17 and 13:23 UTC to fully incorporate the queueing service library
    • Promoted the original primary database back to production on 7 August, which stopped the user service timeouts
    • Recreated and redeployed the automation cluster that the automation service could not see, which fully restored S3
  2. Symptoms

    Shortly after incident.io moved its infrastructure fully into Google Cloud, the application saw a larger-than-normal number of Postgres connection timeouts, and new database connections per second were in the hundreds, spiking up and down. At the same time, the memcached instance used for transient data and faster API responses had sporadic connection timeouts.

    Trigger

    After the move to Google Cloud, the application opened hundreds of new Postgres connections per second, and an accidental database join made it send thousands of duplicate calls to an external third party in parallel.

    Root cause
    Component
    Contributing factor
    Detection

    An incident was declared when the number of Postgres connection timeouts rose above normal. The remaining cache timeouts were traced through the logs of the Kubernetes node that served an affected request, the request's trace and the node's metrics.

    Remediation
    • Doubled the maximum Postgres connection lifespan from 15m to 30m
    • Made the Postgres connection pools static so they always keep N connections open
    • Raised the memcache client's MaxIdleConns from 2 to 20
    • Moved temporarily from Google's hosted memcached to a memcached inside the Kubernetes cluster
    • Shipped the fix for the accidental database join that made thousands of duplicate external calls
    Action items
    • Set more sensible concurrency limits for outbound network calls
    Lessons

    Network timeouts are not always local to one request or pod: when they appear, the whole activity of the node, including other pods on it, needs to be checked. Staying within a provider's rate limits does not keep outbound calls from affecting a node, so outbound network calls need more sensible concurrency limits.

Check your cluster for this

These 2 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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