Incident Library
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Cases3 cases

1 to 3 of 3

  1. Symptoms

    Services on the production Amazon EKS cluster behind the idus marketplace threw intermittent errors whose cause was hard to pin down. Calls to external services such as RDS and Redis failed now and then, and whenever DNS traffic spiked, domain lookups answered slowly or failed outright.

    Trigger

    All CoreDNS pods were scheduled onto the same node, and that node's memory usage spiked until it ran out of memory.

    Root cause
    Component
    Contributing factor
    Detection

    The write-up does not say how the full outage was noticed. The earlier DNS trouble showed up as intermittent service errors, and investigating failed calls to RDS and Redis led to DNS resolution failures.

    Remediation
    • deployed NodeLocal DNSCache as a DaemonSet in front of CoreDNS
    • added a PodDisruptionBudget (maxUnavailable 1) and topologySpreadConstraints across zones for CoreDNS
    • lowered ndots from 5 to 2 with dnsConfig in the Deployments
    Lessons

    The CoreDNS setup that EKS creates by default (two pods) can be enough for a small or development cluster but becomes a bottleneck in a large production cluster, and DNS is a single point of failure that needs high availability and room to scale. Tuning the CoreDNS cache and buffer size only relieved the symptoms; the real load came from the extra queries that ndots:5 generates for external names. A CoreDNS pod without a memory limit can share a node's fate with everything else on it.

  2. Symptoms

    Request latency from the Temporal Server History service, the service that starts workflow executions and records their progress, was higher and less steady than it should be on a self-hosted Kubernetes deployment. The CPU dashboard showed the history pods using less than 60 percent of their CPU, yet the same pods were being throttled.

    Trigger

    Normal load on History pods that had a CPU limit of 2 cores on 8-core nodes, with the Go runtime's GOMAXPROCS left at its default of one per node core.

    Root cause
    Component
    Contributing factor
    Detection

    A Prometheus query for CPU throttling showed the history pods throttled although their CPU usage read under 60 percent.

    Remediation
    • set the GOMAXPROCS environment variable to 2 to match the 2-core CPU limit
    Action items
    • Set GOMAXPROCS automatically from the Kubernetes CPU limit, from Temporal release 1.21.0
    Lessons

    A CPU usage graph averaged over 15 seconds or more can sit far below 100 percent while a container is being throttled, so throttling needs its own metric. A Go program in a container should have GOMAXPROCS matched to its CPU limit, or to its CPU request when it has no limit. The author recommends not using CPU limits at all.

  3. Symptoms

    On May 10 the latency graphs of several services showed a few spikes of up to about one second, then latency climbed to five seconds and then to 20 seconds, and it stayed there for a long time. The same pattern appeared on many services, not just one.

    Trigger

    Several services sent a high volume of external DNS queries, all of which went through kube-dns.

    Root cause
    Component
    Contributing factor
    Detection

    Latency graphs of several services showed the rise; engineers then looked at load per kube-dns pod.

    Lessons

    By default a pod discovers DNS through the kube-dns cluster IP and uses the ClusterFirst policy, so even external lookups go through kube-dns. If a pod does not need cluster DNS, set its dnsPolicy to Default or None. Check the DNS policy early and often. iptables picks backends at random and is not a load balancer, so pods behind a cluster IP, kube-dns included, can carry very different loads.

Check your cluster for this

These 3 cases involve Client-side DNS resolver and cache and CoreDNS. 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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