Incident Library
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  • Root cause
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Cases3 cases

1 to 3 of 3

  1. Symptoms

    From 20:31 UTC on July 9, 2026, DigitalOcean reported a problem with Kubernetes deployments in its NYC1 region. Application workloads could see intermittent DNS failures and NodeNotReady events.

    Root cause
    Component
    Contributing factor
    Lessons

    Cluster DNS is sensitive to latency, and CoreDNS on shared-CPU nodes can time out intermittently. DigitalOcean's advice is to place CoreDNS on dedicated-CPU node pools and to run enough CoreDNS replicas.

  2. Symptoms

    CI jobs failed now and then because a hostname could not be resolved. The failures came from tensorstore, appeared on several different instances and did not repeat consistently. The error read: "./tensorstore/util/result.h:420: Status not ok: status(): UNAVAILABLE: CURL error Could not resolve hostname: Could not resolve host: company-bucket.s3.amazonaws.com".

    Trigger

    An administrative pod running with host networking called sudo in a loop. Each sudo call looked up the node's own hostname, and with ndots:5 and four search domains every lookup became five queries, for both A and AAAA records.

    Root cause
    Component
    Contributing factor
    Detection

    Reports of flaky CI jobs that could not resolve an S3 bucket hostname, followed by i/o timeout errors in the CoreDNS logs.

    Remediation
    • added 'Defaults !fqdn' in /etc/sudoers.d/00-no-fqdn (mode 440) to the container image so sudo stopped looking up the hostname
    Lessons

    Traffic from CoreDNS to the VPC DNS resolver is limited to 1024 packets per second per interface, and drops show up only as UDP timeouts; the linklocal_allowance_exceeded counter in ethtool shows them. Names that are not fully qualified are multiplied by the search domains under ndots:5, and AAAA lookups double them again. sudo looks up the host's own name on every call unless 'Defaults !fqdn' is set.

  3. Symptoms

    For about six months, applications on Omio's Google Kubernetes Engine clusters stalled at random: they got stuck, stopped answering health check requests or lost network connections, and nothing the team looked at explained why.

    Trigger

    Multi-threaded workloads running with CPU limits on nodes whose kernel did not yet have the fix for a known CFS quota bug that causes unnecessary throttling.

    Root cause
    Component
    Contributing factor
    Detection

    Months of random stalls and failed health checks led the team to read the cgroup cpu.stat throttling counters inside the pods, which showed far more throttling than the limits should allow.

    Remediation
    • removed CPU limits until the kernel with the CFS bug fix was deployed across all clusters
    Action items
    • Deploy the kernel with the CFS quota bug fix across all clusters
    • Monitor utilisation, saturation and error metrics, API latency and error rates to confirm the change behaves as expected
    Lessons

    A CPU limit is a time quota per 100 ms period, not a share of cores, so a multi-threaded container can be stopped for most of each period long before it uses the cores it was given, and a kernel bug can make that worse. Throttling is invisible in standard Kubernetes metrics and has to be read from the cgroup counters. Removing limits trades away protection against a container that takes a whole node, which is only acceptable when runtimes are tuned.

Check your cluster for this

These 3 cases involve CoreDNS and Container CPU 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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