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

Cases13 cases

12 to 13 of 13

  1. Symptoms

    Customers of the Zalando Fashion Store got a high rate of errors on all web product pages and outfit pages for more than an hour. The errors came from the main data aggregation layer service, which runs in one of Zalando's Kubernetes clusters.

    Trigger

    Calls from the aggregation layer to a single, not very important downstream service started timing out. The aggregation layer returned 404s for them, clients retried, and the resulting spike in requests became a spike in DNS queries to CoreDNS.

    Root cause
    Component
    Contributing factor
    Detection

    The on-call engineer for the aggregation layer phoned the on-call Kubernetes engineer. Automatic paging did not happen because the cluster's monitoring and alerting ran inside the cluster and failed along with DNS. The Kubernetes engineer then saw that the CoreDNS pods were being OOM-killed.

    Remediation
    • Raised the CoreDNS memory requests and limits by hand from 100Mi to 2000Mi
    Action items
    • Introduce a more resilient DNS setup: CoreDNS fronted by dnsmasq on every node
    • Improve high-level alerting from outside the clusters, so that a cluster problem is known before or at the same time as applications are affected
    • Improve incident response processes and tooling so that any on-call engineer can escalate directly to other teams when automatic paging fails, for example through a chat bot
    Lessons

    The Kubernetes DNS setup was far from resilient enough: a single application could take down DNS for everything in the cluster. The blast radius of one application sending more DNS queries should be limited to one node at most, ideally to single pods. Known Kubernetes DNS problems, such as Linux kernel races in conntrack handling and the ndots 5 problem, were familiar to the team and partly mitigated, but their combined effect on the DNS infrastructure was worse than the team had understood. Monitoring that runs inside the cluster was not robust enough: when the cluster's DNS broke, it could not page anyone, and recovery took longer than it should have.

  2. Symptoms

    Customers were affected, and Zalando's IAM service answered requests with HTTP 404. The talk shows this on slides titled "Customer impact" and "IAM returning 404", followed by a slide on the number of pods in the cluster.

    Trigger

    A CronJob (apiVersion batch/v2alpha1, schedule "*/15 9-19 * * Mon-Fri") whose concurrencyPolicy: Forbid and job history limits sat inside the pod template spec instead of the CronJob spec. The talk shows it right after the slides on the number of pods and the API server being OOM-killed, and the lessons add a quota on the number of pods.

    Root cause
    Component
    Contributing factor
    Remediation
    • fixed the CronJob manifest: moved concurrencyPolicy: Forbid and the job history limits to the CronJob spec, added activeDeadlineSeconds: 120 and changed the schedule to "7 8-18 * * Mon-Fri"
    Action items
    • Make the ingress stay healthy during API server problems
    • Make the ingress keep the last known set of routes
    • Use a ResourceQuota on the number of pods (the example sets pods: "1500")
    Lessons

    An AWS ALB routes traffic to all hosts when all hosts report unhealthy, so the ingress should stay healthy during API server problems. An ingress controller that reads routes from the API server should keep its last known set of routes. Use a quota for the number of pods.

Check your cluster for this

These 13 cases involve Container memory limit 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.

By root cause1

Capacity exhaustion13 cases

  1. IL-0102 CoreDNS pods on a production EKS cluster ran out of memory under a burst of new pods, endpoints and nodes, taking down the Buildkite web UI, APIs and job dispatch
  2. IL-0027 All CoreDNS pods landed on one node, the node ran out of memory, and DNS for the whole service went down
  3. IL-0044 Prometheus OOMKilled in a loop while replaying its write-ahead log after a kube-prometheus-stack upgrade
  4. IL-0110 A Grafana Agent pod's high memory use and crash-looping Hangfire pods drove a Kubernetes node into system OOM and NotReady, twice in one day
    DFDS2024
  5. IL-0168 Simultaneous cluster auto-upgrades overloaded Scaleway's Kubernetes API, and a node authentication retry loop kept Kapsule and Kosmos nodes NotReady in FR-PAR
  6. IL-0169 The Scaleway Kubernetes API in FR-PAR ran out of memory under simultaneous deployments, and because it also handled node authentication, Kapsule and Kosmos nodes went NotReady
  7. IL-0016 Prometheus on the live cluster ran out of memory and was OOMKilled, and the monitoring node it ran on went NotReady
  8. IL-0195 The kube-apiservers of a cluster with more than 200 nodes ran out of memory and crashed one after another under mass LIST requests from Cilium agents
    Palark2023
  9. IL-0206 Consul agents in GitLab.com's GKE pods were repeatedly OOM-killed, so the Rails pods lost database replica discovery and sent every query to the primary
    GitLab2022
  10. IL-0176 Prometheus in a 235-node Kubernetes cluster crash-looped because over two million series exhausted host memory and the kernel OOM killer chose it first, as Burstable QoS gave it oom_score_adj 999
    LINE2020
  11. IL-0026 Kubernetes nodes hit SystemOOM because fluentd-sumologic log shipper pods had no memory limits
  12. IL-0001 Cluster-wide DNS outage after CoreDNS pods were OOM-killed again and again under a burst of DNS queries
  13. IL-0031 Kubernetes API server OOM-killed, leaving the Skipper ingress without routes; the talk points to a misconfigured CronJob manifest