Incident Library
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Cases3 cases

1 to 3 of 3

  1. Symptoms

    At 13:42 UTC on 19 May 2025, RebelMouse's monitoring tools reported a higher error rate and degraded performance across services. A routine reroll of the EKS nodes had started 27 minutes earlier, at 13:15 UTC.

    Trigger

    At 13:15 UTC RebelMouse started its regular reroll of EKS nodes to apply security patches. The planned, automatic termination of an EC2 instance terminated one of the CoreDNS pods.

    Root cause
    Component
    Contributing factor
    Detection

    Monitoring tools detected an increased error rate and degraded service performance at 13:42 UTC, and the tech team started investigating at 13:44 UTC.

    Remediation
    • rescheduled the affected CoreDNS pod onto a new EC2 instance
    • scaled up the CoreDNS deployment to more replicas so DNS load was spread evenly across all pods
    Action items
    • Add scale-in protection so CoreDNS pods are not terminated unexpectedly during peak load
    • Review the CoreDNS configuration so that vertical scaling of the pods works
    • Hold regular capacity reviews so the CoreDNS deployment is provisioned for peak load
  2. 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.

  3. Symptoms

    When traffic changed sharply, CoreDNS came under heavy load, and the cluster saw network problems and a sudden rise in latency. The horizontal pod autoscaler then added pods, database connections surged, and the impact spread to the whole service.

    Trigger

    Sharp changes in traffic loaded the small number of CoreDNS pods beyond what they could handle.

    Root cause
    Component
    Contributing factor
    Remediation
    • Set up the Cluster Proportional Autoscaler for CoreDNS with nodesPerReplica and coresPerReplica chosen for the instance types in use
    • Spread CoreDNS with soft topologySpreadConstraints (ScheduleAnyway) instead of anti-affinity so Karpenter could consolidate nodes
    • Added alert thresholds on CoreDNS error rate, panics, request duration and request rate
    • Deployed NodeLocal DNSCache so each node answers DNS from a local cache and forwards misses to the main CoreDNS
    Lessons

    A fixed, small number of CoreDNS pods cannot follow a cluster whose nodes and pods change quickly with traffic, and the damage spreads: DNS latency triggers autoscaling, which in turn floods the database with connections. Simply adding many CoreDNS replicas created a different problem, because with tainted nodes and a maxSkew: 1 spread constraint the pods piled onto a few nodes and blocked Karpenter consolidation. Scaling CoreDNS in proportion to the cluster and putting a DNS cache on every node handled both.

Check your cluster for this

These 3 cases involve CoreDNS and Node pool. 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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